{ "course": "Database_Systems", "course_id": "CO2013", "schema_version": "material.v1", "slides": [ { "page_index": 0, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_001.png", "page_index": 0, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:39+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology - VNU-HCMC Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vo Thi Ngoc Chau (chauvtn@hcmut.edu.vn) 1 Semester 1 - 2025-2026" }, { "page_index": 1, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_002.png", "page_index": 1, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:41+07:00" }, "raw_text": "Data/Information/Knowledge ??? Dtta" }, { "page_index": 2, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_003.png", "page_index": 2, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:45+07:00" }, "raw_text": "References Text: [1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References: [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd, 2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 6th Edition, McGraw-Hill, 2006. 41 H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. [5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 2nd Edition, McGraw-Hill. [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Object- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007. 3" }, { "page_index": 3, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_004.png", "page_index": 3, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:48+07:00" }, "raw_text": "R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. FUNDAMENTALSOF DATABASE SYSTEMS 7tHEdition ELMASRINAVATHE 4" }, { "page_index": 4, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_005.png", "page_index": 4, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:51+07:00" }, "raw_text": "N6i dung Chuong 1: Töng quan ve he co sδ dü liéu Chuong 2: Mó hinh thuc thé-mi lien két Chuong 3: M hinh dü liéu quan he Chuong 4: Ng0n ngü SQL Chuong 5: Phuong phäp thiét ké co sö dü lieu Chuong 6: Luu trü va quän ly co sδ dü liéu Chuong 7: Bäo mat co sδ dü lieu 5" }, { "page_index": 5, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_006.png", "page_index": 5, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:53+07:00" }, "raw_text": "Content Chapter 1 : An Overview of Database Systems Chapter 2 : The Entity-Relationship Model Chapter 3: The Relational Data Model Chapter 4: The SQL Language Chapter 5: Relational Database Design Chapter 6: Physical Storage and Data Management Chapter 7: Database Security 6" }, { "page_index": 6, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_007.png", "page_index": 6, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:06:58+07:00" }, "raw_text": "Kién thüc - Ky nang dat duoc Giái thich duoc cäc khái niem co ban (dü lieu, m hinh dü lieu 0 co sö dü lieu, he co s dü lieu, m hinh dü lieu quan he, dai s quan hé, sQL, các phuong,thúc thiét ké co s dü lieu, m hinh thuc thé mi iien két, chuan hoá dü liéu, các úng dung co s dü liéu), m ta duoc kién trüc cüa he co s dü lieu va các thanh phän cüa mt he co s° dü liéu. Thiét ké mt co s d liéu dúng m hinh thuc thé mi lién két m hinh dú liéu quan hé va phuong,pháp thiét ké mt co s dü lieu thoá mán các yéu cáu dú liéu cúa mt úng dung co s dú liéu cu thé. Düng ngn ngú SQL vá quán ly co sö dú liéu trén các hé quán 0 tri co sδ dü lieu sän c6 nhu MySQL, Oracle, va MS SQL Server. C6 khá näng phan tich su dánh di gia tinh hüu dung, hieu xác dinh duoc cách tiép can phü hop, hieu quä cho viec thiét ke va quán ly d liéu cho các úng dung trong mt hé thöng thng tin: dua trén xu ly tap tin hay cách tiép can co s dü lieu, cäc m hinh dü liéu va hé quán tri co só dü liéu nao phu hp. 7" }, { "page_index": 7, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_008.png", "page_index": 7, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:02+07:00" }, "raw_text": "Course Learning Outcomes Explain basic concepts (data, data model, database, database system, the relational 0 data model, the relational algebra, SQL, database design methodology, the entity relationship model, data normalization, database application), describe the architecture of a database system and the components of a database system Design a database using the entity relationship model, the relational data model and a database design methodology to meet data requirements of a particular database application Use SQL and manage databases on an existing relational database management system (DBMS) such as MySQL, Oracle, and MS SQL Server 0 Be able to analyze tradeoffs between usability, performance, security and constraints of resource and technology in order to identify an appropriate approach for data design and implementation (file based approach or database approach, relational data model or other data models, approaches for database management systems 8" }, { "page_index": 8, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_009.png", "page_index": 8, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:04+07:00" }, "raw_text": "Assessment Scheme Test/Discussion/Presentation/... : 20% Assignment #1: 15% Assignment #2: 15% o Final Exam: 50% Open-book: You can use any references according to the university's regulations 9" }, { "page_index": 9, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_010.png", "page_index": 9, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:07+07:00" }, "raw_text": "Grading Never copy from the others Never let the others copy from you Never be absent from class if not necessary In-class time less than Z5% is not allowed! Never be absent from examination 10" }, { "page_index": 10, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_011.png", "page_index": 10, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:10+07:00" }, "raw_text": "Requirements You are asked to study each chapter in the related references at home before each session. You are asked to complete the exercises of each chapter in the related references. You should study more references, especially those on the Internet. n You should use supporting tools/software. Data modeling Data management 11" }, { "page_index": 11, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_012.png", "page_index": 11, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:12+07:00" }, "raw_text": "Practice Data modeling tools ERwin Data Modeler, Rational Rose, Oracle SQL Commercial database management systems Oracle, MS SQL Server, IBM DB2, Informix, Versant, Caché, ... Open source database management systems PostgreSQL, MySQL, .. 12" }, { "page_index": 12, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_013.png", "page_index": 12, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:15+07:00" }, "raw_text": "Database Systems ORACLE mongoDB Microsoft SQL S Server neo4j MySQL R HBASE DBMS??? 13" }, { "page_index": 13, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_014.png", "page_index": 13, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:19+07:00" }, "raw_text": "Where to Find References? Database field: 0 Conference proceedings: ACM-SIGMOD, ACM-PODS, VLDB, ICDE EDBT, DASFAA, etc Journals: ACM-TODS, J. ACM, IEEE-TKDE, JIIS, DKE, etc. Data mining and KDD: 0 Conference proceedings: KDD, and others, such as PKDD, PAKDD, etc Journal: Data Mining and Knowledge Discovery, etc. AI and Machine Learning: Conference proceedings: Machine learning, AAAI, IJCAI, etc. Journals: Machine Learning, Artificial Intelligence, etc. Statistics : Conference proceedings: Joint Stat. Meeting, etc. Journals: Annals of statistics, etc Visualization : 0 Conference proceedings: CHI, etc. Journals: IEEE Trans. visualization and computer graphics, etc 14" }, { "page_index": 14, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_015.png", "page_index": 14, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:21+07:00" }, "raw_text": "Where to Find References? Publishers of Interest ACM IEEE Springer Elsevier Others 15" }, { "page_index": 15, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_016.png", "page_index": 15, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:23+07:00" }, "raw_text": "Contact Assoc. Prof. Dr. Vo Thi Ngoc Chau o Email: chauvtn@hcmut.edu.vn Office hours: Monday, 12:00-14:50 By appointment 16" }, { "page_index": 16, "chapter_num": 0, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_0/slide_017.png", "page_index": 16, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:25+07:00" }, "raw_text": " - Database Systems C02013 gues wstin questi answer question uest questy tion question 2 lestion 17" }, { "page_index": 17, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_001.png", "page_index": 17, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:29+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Chapter 1: An Overview of Database Systems Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vö Thi Ngoc Chau (chauvtn@hcmut.edu.vn) Semester 1 - 2022-2023" }, { "page_index": 18, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_002.png", "page_index": 18, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:33+07:00" }, "raw_text": "Main References Text: [1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References: [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd,2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 7th Edition, McGraw-Hill, 2020. [4] H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. 5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 4th Edition, McGraw-Hill, 2018. [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Object- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007. 2" }, { "page_index": 19, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_003.png", "page_index": 19, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:36+07:00" }, "raw_text": "Content Chapter 1: An Overview of Database Systems Chapter 2: The Entity-Relationship Model Chapter 3: The Relational Data Model 0 C Chapter 4: The SQL Language 0 Chapter 5: Relational Database Design Chapter 6: Physical Storage and Data Management 0 1 Chapter 7: Database Security 3" }, { "page_index": 20, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_004.png", "page_index": 20, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:39+07:00" }, "raw_text": "Chapter 1: An overview of database systems 1.1. Concepts 1.2. File processing systems 0 1.4. Data models 1.5. Database management systems 1.6. Database systems 0 1.7. Applications of database systems 4" }, { "page_index": 21, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_005.png", "page_index": 21, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:41+07:00" }, "raw_text": "1.1. Concepts Data/ Information/ Knowledge/ Metadata Data Information Knowledge Metadata > Relative Database 5" }, { "page_index": 22, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_006.png", "page_index": 22, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:44+07:00" }, "raw_text": "Data information, especially facts or numbers, collected for examination and consideration and used to help decision-making, or information in an electronic form that can be stored and processed by a computer Cambridge Advanced Learner's Dictionary an elementary description of things, events, activities, and transactions that are recorded, classified, and stored but not organized to convey any specific meaning R. K. Rainer, C. G. Cegielski, \"Introduction to Information Systems\", 3rd Edition, John Wiley & Sons, Inc, pp. 10, 2004. 6" }, { "page_index": 23, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_007.png", "page_index": 23, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:48+07:00" }, "raw_text": "Data Users Factual data and clinical evidence provided by a clinician or patient Patients Physicians >Benh nhän A: tén, dia chi, thän New knowledge Diagnoses Patient symptoms nhiet, hinh ánh vé bénh nhan, .. Diagnosis interface Knowledge update interface Patient symptoms Diagnoses > Bác si B: gi khäm, ten thuöc, : Inference engine New knowledge Rules Session information Case Knowledge repository base Historic data Kién trüc cüa he h tro chan doán dua trén Web (architecture of a Web-based diagnosis support system) Analysts" }, { "page_index": 24, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_008.png", "page_index": 24, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:50+07:00" }, "raw_text": "Information facts about a situation, person, event, etc Cambridge Advanced Learner's Dictionary data that have been organized so that they have meaning and value to the recipient > the recipient interprets the meaning and draws conclusions and implications from the information R. K. Rainer, C. G. Cegielski, \"Introduction to Information Systems\", 3rd Edition, John Wiley & Sons, Inc, pp. 10, 2004. 8" }, { "page_index": 25, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_009.png", "page_index": 25, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:53+07:00" }, "raw_text": "Information Users Benh nhan A c6 than nhiét 37.5°. Bäc si B chuyen chän doän benh Patients Physicians ye tim mach New knowledge Diagnoses Patient symptoms Mi tuan, trung binh 100 bénh Diagnosis interface Knowledge update interface nhan tuong tác v6i he thöng. Patient symptoms Diagnoses Inference engine New knowledge Rules Session information Case Knowledge repository base Historic data Kién trüc cüa he h tro chan doán dua trén Web (architecture of a Web-based diagnosis support system) Analysts" }, { "page_index": 26, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_010.png", "page_index": 26, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:07:56+07:00" }, "raw_text": "Knowledge Awareness; understanding of or information about a subject which has been obtained by experience or study, and which is either in a person's mind or possessed by people generally Cambridge Advanced Learner's Dictionary data/information that have been organized and accumulated learning, and expertise as they apply to a current business problem R. K. Rainer, C. G. Cegielski, \"Introduction to Information Systems\", 3rd Edition, John Wiley & Sons, Inc, pp. 10, 2004. 10" }, { "page_index": 27, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_011.png", "page_index": 27, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:01+07:00" }, "raw_text": "Knowledge Néu benh nhan c6 than nhiét cao Users trong vong 3 ngay, c6 dau hieu met mói thi bénh nhän dang c6 bénh cüm. Patients Physicians New knowledge Diagnoses Patient symptoms Cho benh cüm nhe, bénh nhän can düng thuöc ... Diagnosis interface Knowledge update interface Patient symptoms Diagnoses Néu thuc duoc düng trong vöng 5 ngay nhung thän nhiét khng Inference engine New knowledge Rules giäm thi bénh nhan cän nhap Session information vien thuc hien cäc xét nghiém ve mau, ... Case Knowledge repository base Historic data Kién trüc cüa he hö tro chan doán dua trén Web (architecture of a Web-based diagnosis support system) Analysts" }, { "page_index": 28, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_012.png", "page_index": 28, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:03+07:00" }, "raw_text": "Metadata Data about data Vi du: thng tin m0 tá ky thuat cüa 1 word document: title, subject, author, manager, company, ... Data: content cüa word document Metadata: data values cua title, subject, author manager, company, .. 12" }, { "page_index": 29, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_013.png", "page_index": 29, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:06+07:00" }, "raw_text": "Database A collection of related data with an implicit meaning Implicit properties A database represents some aspect of the real world, called the miniworld or the universe of discourse (UoD) Changes to the miniworld are reflected in the database A database is a logically coherent collection of data with some inherent meaning. A random assortment of data cannot correctly be referred to as a database. A database is designed, built, and populated with data for a specific purpose. It has an intended group of users and some preconceived applications in which these users are interested. A database can be of any size and of varying complexity" }, { "page_index": 30, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_014.png", "page_index": 30, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:20+07:00" }, "raw_text": "Database EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren,Houston,TX M 30000 333445555 Part of the Franklin T Wbng 333445555 195512-08 638 Voss,Houston,TX M 40000 888665555 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer s Wallace 987654321 1941-06-20 291 Berry,Beaire,TX F 43000 888665555 4 Company Ramesh K Narayan 666884444 1962-09-15 975 FireOak,Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 database Ahmad V Jabbar 987987987 1969-03-29 980 Dalas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1 1988-05-22 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 888665555 1981-06-19 5 Bellaire 5 Sugarland 5 Houston WORKS_ON PROJECT Essn Pno Hours Pname Pnumber Pocation Dnum 123456789 1 32.5 ProductX 1 Bellaire 5 123456789 2 7.5 ProductY 2 Sugarland 666884444 40.0 ProductZ 3 Houston 453453453 1 20.0 Computerization 10 Stafford 4 453453453 2 20.0 Reorganization 20 Houston 1 333445555 2 10.0 Newbenefits 30 Stafford 4 14 I" }, { "page_index": 31, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_015.png", "page_index": 31, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:23+07:00" }, "raw_text": "1.2. File processing systems HR file HR Acc file Accounting CRM file CRM E-com file E-commerce Database 15" }, { "page_index": 32, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_016.png", "page_index": 32, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:25+07:00" }, "raw_text": "1.3. The database approach HR Accounting Employees Customers Products DBMS Sales CRM Accounts Inventory Database E-commerce 16" }, { "page_index": 33, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_017.png", "page_index": 33, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:29+07:00" }, "raw_text": "systems o File Database Specifically define Define and and implement the implement the data files for each repository for user's needs various users' needs Uncontrolled data Controlled data redundancy redundancy No program-data Program-data independence independence Hard maintenance Easy maintenance No overhead cost of Overhead cost of a a DBMS software DBMS software 17" }, { "page_index": 34, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_018.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_018.png", "page_index": 34, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:32+07:00" }, "raw_text": "1.4. Data a models Informally, a data model is a type of data abstraction that is used to provide this conceptual representation. The data model uses logical concepts, such as objects, their properties, and their interrelationships, that may be easier for most users to understand than computer storage concepts. The data model hides storage and implementation details that are not of interest to most database users. 18" }, { "page_index": 35, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_019.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_019.png", "page_index": 35, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:35+07:00" }, "raw_text": "Data model E. F. Codd. Data models in database management, ACM, 1980 A combination of three following components (1). A collection of data structure types (the building blocks of any database that conforms to the model): (2). A collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired; (3). A collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both --- these rules may sometimes be expressed as insert-update- delete rules 19" }, { "page_index": 36, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_020.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_020.png", "page_index": 36, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:39+07:00" }, "raw_text": "Data a model A collection of concepts that can be used to describe the structure of a database the data types, relationships, and constraints that should hold for the data a set of basic operations for specifying retrievals and updates on the database some level of abstraction by hiding details of data storage that are not needed by most database users 20" }, { "page_index": 37, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_021.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_021.png", "page_index": 37, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:42+07:00" }, "raw_text": "Purposes of a data model E. F. Codd. Data models in database management, ACM, 1980 1. As a tool for specifying the kinds of data and data organization that are permissible in a specific database; 2. As a basis for developing a general design methodology for databases; 3. As a basis for coping with evolution of databases so as to have minimal logical impact on existing application programs and terminal activities; 4. As a basis for the development of families of very 1 high level languages for query and data manipulation; 5. As a focus for DBMS architecture; 6. As a vehicle for research into the behavioral properties of alternative organizations of data. 21" }, { "page_index": 38, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_022.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_022.png", "page_index": 38, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:46+07:00" }, "raw_text": "Categories of data a models High-level or conceptual data models provide concepts that are close to the way many users perceive data e.g. entity relationship model Representational or implementation data models provide concepts that may be understood by end users but that are not too far removed from the way data is organized within the computer hide some details of data storage able to be implemented on a computer system in a direct way e.g. relational data model, object-oriented data model Low-level or physical data models provide concepts that describe the details of how data is stored in the computer 22" }, { "page_index": 39, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_023.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_023.png", "page_index": 39, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:49+07:00" }, "raw_text": "1.5. Database management systems a collection of programs that enables users to create and maintain a database a general-purpose software system that constructing, manipulating, and sharing applications 23" }, { "page_index": 40, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_024.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_024.png", "page_index": 40, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:08:54+07:00" }, "raw_text": "Database e management systems Defining a database involves specifying the data types, structures, and constraints for the data to be stored in the database. Constructing the database is the process of storing the data itself on some storage medium that is controlled by the DBMS. Manipulating a database includes such functions as querying the database to retrieve specific data, updating the database to reflect changes in the miniworld, and generating reports from the data. Sharing a database allows multiple users and programs to access the database concurrently. Protection includes both system protection against hardware or software malfunction (or crashes), and security protection against unauthorized or malicious access. A typical large database may have a life cycle of many years, so the DBMS must be able to maintain the database system by allowing the system to evolve as requirements change over time. 24" }, { "page_index": 41, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_025.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_025.png", "page_index": 41, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:02+07:00" }, "raw_text": "DBMS Database User/application administrator transaction DDL components queries, commands updates commands Query Transaction DDL compiler manager compiler metadata, metadata query statistics plan Execution Logging and Concurrency 1 1 engine recovery control 4 1 index.file.and 1 recordrequests 1 1 108 Index/file/rec Lock pagesi ord manager table 1 data, page metadata, - 1 commands indexes 1 Buffer Buffers manager readlwrite pages system component Storage manager in-memory structure [4] H. G. Molina, J. D. Ullman, J. Widom, control/data flow Database Systems: The Complete Book - Storage data flow 2nd Edition, Prentice-Hall, 2009. 25" }, { "page_index": 42, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_026.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_026.png", "page_index": 42, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:05+07:00" }, "raw_text": "of DBMS development History 1960s, navigational DBMSs IBM's IMS with the hierarchical model IDMS with the CODASYL network model, .. 1970s-late 1980s, relational DBMSs with SQL 0 Oracle, MS SQL Server, IBM's DB2 MySQL, ... 1990s, object-oriented DBMSs (object, object-relational) Oracle, PostgreSQL Informix, ... 2000s, NoSQL and NewSQL XML DBMSs: Oracle Berkely DB XML, .. NoSQL DBMSs: MongoDB, Hbase, Cassandra, .. NewSQL DBMSs: ScaleBase, VoltDB, ... 26" }, { "page_index": 43, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_027.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_027.png", "page_index": 43, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:09+07:00" }, "raw_text": "Database management system When not to use Unnecessary overhead costs of using a DBMS High initial investment in hardware, software, and training The generality that a DBMS provides for defining and processing data Overhead for providing security, concurrency control, recovery, and integrity functions The database and applications are simple, well defined, and not expected to change. There are stringent real-time requirements for some programs that may not be met because of DBMS overhead. Multiple-user access to data is not required. 27" }, { "page_index": 44, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_028.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_028.png", "page_index": 44, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:11+07:00" }, "raw_text": "A simplified database system environment Users/Programmers DATABASE SYSTEM ApplicationPrograms/Queries DBMS SOFTWARE Software to Process Queries/Programs Software to Access Stored Data Stored Database Stored Definition Database (Meta-Data) 28" }, { "page_index": 45, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_029.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_029.png", "page_index": 45, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:14+07:00" }, "raw_text": "A simplified database system environment Users/Programmers use DATABASE SYSTEM ApplicationPrograms/Queries II DBMS SOFTWARE Software to Process Queries/Programs DBMS Software to Access Stored Data Database - Stored Database Stored Definition Database (Meta-Data) 29" }, { "page_index": 46, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_030.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_030.png", "page_index": 46, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:18+07:00" }, "raw_text": "1.6. Database systems Database system database + DBMS Database: data modeling Database management system (DBMs) : functionalities File organization & indexing 0 Query processing & optimization 0 Database security 0 Transaction processing & concurrency 0 control Backup & recovery 0 30" }, { "page_index": 47, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_031.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_031.png", "page_index": 47, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:21+07:00" }, "raw_text": "The Three-Schema Architecture End Users External External External Level View View External/Conceptual Mapping Conceptual Level Conceptual Schema Conceptual/Interna Mapping Internal Level Internal Schema Stored Database The three-schema architecture 31" }, { "page_index": 48, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_032.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_032.png", "page_index": 48, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:25+07:00" }, "raw_text": "The Three-Schema Architecture End Users the part of the database that a particular user group is interested in and hides External External the rest of the database External Level View View from that user group External/Conceptual the structure Mapping of the whole database for a Conceptual Level Conceptual Schema community of Conceptual/Internal users Mapping the physical Internal Level Internal Schema storage structure of the database Stored Database The three-schema architecture 32" }, { "page_index": 49, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_033.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_033.png", "page_index": 49, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:29+07:00" }, "raw_text": "The Three-Schema Architecture The three-schema architecture An internal schema describes the physical storage structure of the database A conceptual schema is a high-level description of the whole database External schemas describe the views of different user groups. Data independence 0 Data Independence is the capacity to change the schema at one level of a database system without having to change the schema at the next higher level. Logical data independence & Physical data independence 33" }, { "page_index": 50, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_034.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_034.png", "page_index": 50, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:32+07:00" }, "raw_text": "The e Three-Schema Architecture Data independence 01 Logical data independence: the capacity to change the conceptual schema without having to change externa/ schemas or application programs Physical data independence: the capacity to change the internal schema without having to change the conceptual schema External Schemas External Schemas Conceptual Schema Conceptual Schema Internal Schema Internal Schema Logical Data Independence Physical Data Independence 34" }, { "page_index": 51, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_035.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_035.png", "page_index": 51, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:36+07:00" }, "raw_text": "Characteristics of database systems Self-describing nature of a database system data abstraction Support of multiple views of the data Sharing of data and multiuser transaction processing Controlling redundancy Restricting g unauthorized access Providing persistent storage for program objects 35" }, { "page_index": 52, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_036.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_036.png", "page_index": 52, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:39+07:00" }, "raw_text": "Characteristics of database systems Providing storage structures for efficient query processing Providing backup and recovery Providing multiple user interfaces Representing complex relationships among data Enforcing integrity constraints Permitting inferencing and actions using rules 36" }, { "page_index": 53, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_037.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_037.png", "page_index": 53, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:42+07:00" }, "raw_text": "Characteristics of database systems Potential for enforcing standards Reduced application development time o Flexibility Availability of up-to-date information Economies of scale 37" }, { "page_index": 54, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_038.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_038.png", "page_index": 54, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:44+07:00" }, "raw_text": "Classification of database systems Based on data models (widely-used) Based on kinds of data Based on data storage and organization Based on architectures Based on the number of users 38" }, { "page_index": 55, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_039.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_039.png", "page_index": 55, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:46+07:00" }, "raw_text": "Classification of database systems Based on data models (widely-used) Relational database systems Object-oriented database systems Object relational database systems XML-enabled database systems XML native database systems Graph database systems 39" }, { "page_index": 56, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_040.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_040.png", "page_index": 56, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:49+07:00" }, "raw_text": "Classification of database systems Based on kinds of data 01 Traditional database systems (simple data) Multimedia database systems Spatial database systems Temporal database systems Spatiotemporal database systems Inductive database systems Deductive database systems 40" }, { "page_index": 57, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_041.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_041.png", "page_index": 57, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:51+07:00" }, "raw_text": "Classification of database systems Based on data storage and organization Traditional database systems In-memory database systems Columnar database systems 41" }, { "page_index": 58, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_042.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_042.png", "page_index": 58, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:53+07:00" }, "raw_text": "Classification of database systems Based on architectures Centralized database systems Distributed database systems Parallel database systems 42" }, { "page_index": 59, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_043.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_043.png", "page_index": 59, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:55+07:00" }, "raw_text": "Classification of database systems Based on the number of users Single-user database systems Multi-user database systems 7 The number of users who can use the system concurrently - that is, at the same time 43" }, { "page_index": 60, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_044.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_044.png", "page_index": 60, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:09:59+07:00" }, "raw_text": "1.7.Applications of database systems In any organization, in any application domain where there is a need: A large database A multiuser environment > Providing application flexibility with relational databases > Object-oriented applications and the need for more complex databases > Interchanging data on the Web for e-commerce > Extending database capabilities for new applications 44" }, { "page_index": 61, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_045.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_045.png", "page_index": 61, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:03+07:00" }, "raw_text": "1.7.Applications of database systems Scientific applications that store large amounts of data resulting from scientific experiments in areas such as high-energy physics or the mapping of the human genome. Storage and retrieval of images, from scanned news or personal 0 photographs to satellite photograph images and images from medical procedures such as X-rays or MRI (magnetic resonance imaging). Storage and retrieval of videos, such as movies, or video clips from news or personal digital cameras. Data mining applications that analyze large amounts of data searching for the occurrences of specific patterns or relationships. Spatial applications that store spatial locations of data such as weather information or maps used in geographical information systems. Time series applications that store information such as economic data at regular points in time, for example, daily sales or monthly gross national product figures. NEED: more complex data structures, new data types, new operations and query language constructs, new storage and indexing structures New general/special purpose functionalities added to a database system" }, { "page_index": 62, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_046.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_046.png", "page_index": 62, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:05+07:00" }, "raw_text": "Summary Database system = database + database management system Database Data/ metadata > information/ knowledge Data model (conceptual, logical) Database management system Three-schema architecture & data independence g Functionalities Characteristics, classification, and applications of database systems File processing systems vs. Database systems 46" }, { "page_index": 63, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_047.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_047.png", "page_index": 63, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:08+07:00" }, "raw_text": "Chapter Introduction to 1: Overall 1 Database Systems ques uslin questi answer question wuest quest tion question 47" }, { "page_index": 64, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_048.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_048.png", "page_index": 64, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:10+07:00" }, "raw_text": "Review 1.1. Define the following terms: data, database, data model, DBMS, database system, program-data independence, metadata, transaction-processing application. 1.3. Discuss the main characteristics of the traditional file systems. 1.6. Discuss the capabilities that should be provided by a DBMS. 1.8. What is the difference between controlled and uncontrolled redundancy? 48" }, { "page_index": 65, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_049.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_049.png", "page_index": 65, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:13+07:00" }, "raw_text": "Review 2.2. Discuss the main categories of data models. 2.3. What is the difference between a database schema and a database state? 2.4. Describe the three-schema architecture. Why do we need mappings between schema Ievels? 2.5. What is the difference between logical data independence and physical data independence? 2.10. Discuss some types of database e utilities and tools and their functions. 49" }, { "page_index": 66, "chapter_num": 1, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_050.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_1/slide_050.png", "page_index": 66, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:16+07:00" }, "raw_text": "Next Chapter 2: The Entity-Relationship Model 2.1. Database design process from conceptual modeling 2.2. Conceptual data modeling 0 2.3. The entity-relationship model 0 2.4. The extended entity-relationship 0 mode 50" }, { "page_index": 67, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_001.png", "page_index": 67, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:20+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Chapter 2: The Entity-Relationship Model Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vö Thi Ngoc Chau (chauvtn@hcmut.edu.vn) Semester 1 - 2022-2023" }, { "page_index": 68, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_002.png", "page_index": 68, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:23+07:00" }, "raw_text": "Content Chapter 1 : An Overview of Database Systems Chapter 2: The Entity-Relationship Model 0 Chapter 3: The Relational Data Model Chapter 4: The SQL Language Chapter 5: Relational Database Design 0 Chapter 6: Physical Storage and Data Management 0 Chapter 7 : Database Security 2" }, { "page_index": 69, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_003.png", "page_index": 69, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:25+07:00" }, "raw_text": "Chapter 2: The Entity-Relationship Mode 2.1. Database design process from conceptual modeling 2.2. Conceptual data modeling 2.3. The entity-relationship model 2.4. The extended entity-relationship model 3" }, { "page_index": 70, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_004.png", "page_index": 70, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:30+07:00" }, "raw_text": "Main References Text : 1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References : [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd,2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 7th Edition, McGraw-Hill, 2020. 4] H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. [5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 4th Edition, McGraw-Hill, 2018. [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Object- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007 4" }, { "page_index": 71, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_005.png", "page_index": 71, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:33+07:00" }, "raw_text": "2.1. Database e design process l F conceptual modeling from c The main phases Input? Output? Requirements collection and analysis Database designers Conceptual design The entity-relationship model Logical design (data model mapping) The relational data model Physical design 5" }, { "page_index": 72, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_006.png", "page_index": 72, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:39+07:00" }, "raw_text": "2.1. Database design process conceptual modeling Miniworld from The main phases REQUIREMENTS COLLECTIONAND of database design ANALYSIS Functional Reguirements Data Requirements FUNCTIONALANALYSIS CONCEPTUAL DESIGN High-Level Transaction Conceptual Schema Specification n a high-level data model DBMS-independent LOGICAL DESIGN DBMS-specific DATA MODEL MAPPING Logical (Conceptual) Schema APPLICATIONPROGRAM (In the data model of a specific DBMS DESIGN PHYSICALDESIGN TRANSACTION Internal Schema IMPLEMENTATION Source: [1] ApplicationPrograms 6" }, { "page_index": 73, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_007.png", "page_index": 73, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:42+07:00" }, "raw_text": "2.2. Conceptual Data Modeling a modeling Data Conceptual data model j r The entity-relationship model Representational data model The relational data model Database design Relational database design 7" }, { "page_index": 74, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_008.png", "page_index": 74, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:45+07:00" }, "raw_text": "2.2. Conceptual Data M Modeling Modeling - Cambridge dictionary Model = a representation of something, either as a physical object which is usually smaller than the real object, or as a simple description of the object which might be used in calculations Modeling = constructing a representation of something, either as a physical object which is usually smaller than the real object, or as a simple description of the object which might be used in calculations 8" }, { "page_index": 75, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_009.png", "page_index": 75, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:50+07:00" }, "raw_text": "2.2. Conceptual Data Modeling Data modeling \"formalizing and representing the data structures of reality\" Shoval and Frumermann, 1994, p.28 a representation of the things of significance to an enterprise and the relationships among those things\" Hay, 1996a \"an attempt to capture the essence of things both concrete and abstract\" o Keuffel, 1996 Source: G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007 9 Data modeling - pp. 31-32." }, { "page_index": 76, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_010.png", "page_index": 76, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:53+07:00" }, "raw_text": "2.2. Conceptual Data Modeling Data modeling \"an abstract representation of the data about entities, events, activities, and their associations within an organization\" McFadden, Hoffer et al., 1999 \"The core idea underlying all the definitions is the same: a data model is used for describing entities and their relationships within a core domain.\" Topi and Ramesh, 2002 Source: G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007 10 Data modeling - pp. 31-32." }, { "page_index": 77, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_011.png", "page_index": 77, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:10:56+07:00" }, "raw_text": "2.2. Conceptual Data Modeling Data modeling \"Data modeling is generally viewed as a design activity\" Srinivasan and Te'eni, 1990 an activity that involves the creation of abstractions\" Davydov, 1994 \"the art and science of arranging the structure and relationship of data\" McComb, 2004, p.293 \"data modeling is a design discipline\" Simsion and Witt, 2005, p.7 Source: G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007 11 Data modeling - pp. 31-32." }, { "page_index": 78, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_012.png", "page_index": 78, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:00+07:00" }, "raw_text": "Why is data modeling important? Leverage Make programming simpler and cheaper Poor data organization can be expensive to fix. Conciseness Take more directly to the heart of the business requirements o Data quality Problems with data quality can be traced back to a lack of consistency in : Defining and interpreting data Implementing mechanisms to enforce the definitions > A key role in achieving good data quality by establishing a common understanding of what is to be held in each table and column and how it is to be interpreted 12 G. C. Simsion, G. C. Witt, Data modeling essentials - 3rd edition, Elsevier Inc, 2005, pp. 8-10." }, { "page_index": 79, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_013.png", "page_index": 79, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:03+07:00" }, "raw_text": "2.2. Conceptual Data Modeling A data model (aka semantic data model) Provides concepts close to the way many users perceive data Provides the concepts essential for supporting the application environment at a very high non- system-specific level Used for a conceptual schema of a database from data requirements Example: the entity-relationship model 13" }, { "page_index": 80, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_014.png", "page_index": 80, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:06+07:00" }, "raw_text": "2.2. Conceptual Data Modeling Characteristics of a conceptual data model Expressiveness Distinctions between data, relationships, constraints Simplicity Simple enough for an end user to use and understand -> an easy diagrammatic notation Minimality A small number of basic concepts that are distinct and orthogonal in their meaning Formality Concepts must be formally defined -> state criteria for the validity of a schema in the model Unique interpretation Complete and unambiguous semantics for each modeling construct 14 S. Navathe. Evolution of data modeling for databases. Communications of the ACM 35(9)(1992) 112-123." }, { "page_index": 81, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_015.png", "page_index": 81, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:10+07:00" }, "raw_text": "Representational data a model A data a model (aka implementation/logical data model Provides concepts understood by end-users and able to be used to describe the structure of a database the data types, relationships, and constraints that should hold for the data a set of basic operations for specifying retrievals and updates on the database Hides some details of data storage but able to be implemented on a computer system in a direct way (in some DBMS) Example: the relational data model 15" }, { "page_index": 82, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_016.png", "page_index": 82, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:13+07:00" }, "raw_text": "Database design Design the logical and physical structures of one or more databases to accommodate the information needs of the users in an organization for a defined set of applications The overall database design activity has to undergo a systematic process called the design methodology, whether the target database is managed by an RDBMS, ODBMS, or ORDBMS, ... The result of the design activity is a rigidly (fixedly) 0 defined database schema that cannot easily be modified once the database is implemented. 16" }, { "page_index": 83, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_017.png", "page_index": 83, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:16+07:00" }, "raw_text": "Database design Goals: 0 Satisfy the information content reguirements of the specified users and applications Provide a natural and easy-to-understand structuring of the information Support processing requirements and any performance objectives, such as response time, processing time, and storage space 17" }, { "page_index": 84, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_018.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_018.png", "page_index": 84, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:22+07:00" }, "raw_text": "Database Data content,structure Database and constraints applications design Phase 1:Requirements Data Processing collection requirements requirements Phases of and analysis database design and Phase 2:Conceptual Conceptual Transaction and database Schema design application design implementation design (DBMS-independent) (DBMS-independent for large databases Phase 3:Choice of DBMS Logical Schema Frequencies, Phase 4:Data model and view design mapping performance (logical design) (DBMS-dependent) constraints Phase 5: Physical Internal design Schema design (DBMS-dependent) Phase 6: System DDL statements Transaction implementation SDL statements and application and tuning implementation DDL: data definition language Source: [1] 18 SDL: storage definition language" }, { "page_index": 85, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_019.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_019.png", "page_index": 85, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:24+07:00" }, "raw_text": "Database design Six main phases of the overall database design and implementation process Requirements collection and analysis Conceptual database design Choice of a DBMS Data model mapping (aka logical database design) Physical database design Database system implementation and tuning 19" }, { "page_index": 86, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_020.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_020.png", "page_index": 86, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:29+07:00" }, "raw_text": "Database design Phase 1 : Requirements Collection and Analysis Identify the major application areas and user groups that will use the database or whole work will be affected by the database Study and analyze existing documentation concerning the applications Study the current operating environment and planned use of the information Analyze the types of transactions and their frequencies as well as of the flow of information within the system Study geographic characteristics regarding users, origin of transactions, destination of 0 reports, ... Specify the input and output data for the transactions Collect written responses to sets of questions from the potential database users or user groups Users' priorities and the importance users place on various applications Reguirements from users and applications of the information system that will interact with the database system Time-consuming but crucial to the success of the information system Identify and analyze the expectations of the users and the intended uses of the database in as much detail as possible 20" }, { "page_index": 87, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_021.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_021.png", "page_index": 87, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:33+07:00" }, "raw_text": "Database design Phase 2: Conceptual Database Design Phase 2a: Conceptual Schema Design Examine the data requirements resulting from Phase 1 Produce a conceptual database schema in a DBMs- independent high-level data model Phase 2b: Transaction Design Design the characteristics of known database transactions (applications) in a DBMS-independent way to ensure that the database schema will include all the information reguired by these transactions Identify transactions' input/output and functional behavior Group transactions into three categories: retrieval transactions, update transactions, mixed transactions 21" }, { "page_index": 88, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_022.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_022.png", "page_index": 88, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:36+07:00" }, "raw_text": "Database design Phase 2: Conceptual Database Design 0 Phase 2a: Conceptual Schema Design Goal = a complete understanding of the database structure, meaning (semantics), interrelationships, and constraints Identify: entity types, relationship types, attributes, key attributes, cardinality and participation constraints on relationships, weak entity types, Approaches The centralized (or one-shot) schema design approach The view integration approach 22" }, { "page_index": 89, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_023.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_023.png", "page_index": 89, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:40+07:00" }, "raw_text": "Database design Phase 2a: Conceptual Schema Design The centralized (or one-shot) schema design approach The reguirements of the different applications and user groups from Phase 1 are merged into a single set of requirements before schema design begins. A single schema corresponding to the merged set of requirements is then designed. The database administrator (DBA) is responsible for deciding how to merge the requirements and for designing the conceptual schema for the whole database. Once the conceptual schema is designed and finalized applications can be specified by the DBA. 23" }, { "page_index": 90, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_024.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_024.png", "page_index": 90, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:43+07:00" }, "raw_text": "Database design Phase 2a: Conceptual Schema Design The view integration approach The requirements are not merged A schema (or view) is designed for each user group or application based only on its own requirements. Each user group or application These schemas are merged or integrated into a global conceptual schema for the entire database. The DBA The individual views can be reconstructed as external schemas after view integration. 24" }, { "page_index": 91, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_025.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_025.png", "page_index": 91, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:47+07:00" }, "raw_text": "Database design Phase e 3: Choice of a DBMS Technical factors Suitability & type of the DBMS for the task Storage structures and access paths, the user and programmer interfaces, high-level query languages, development tools, architectural options, ... supported by DBMS DBMS portability among different types of hardware Non-technical factors Cost: software acguisition cost, maintenance cost, hardware acquisition cost, database creation and conversion cost personnel cost, training cost, operating cost Availability of vendor services 25" }, { "page_index": 92, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_026.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_026.png", "page_index": 92, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:51+07:00" }, "raw_text": "Database design Phase 4: Data Model Mapping (Logical Database Design) Create a conceptual schema and external schemas in the data model of the selected DBMS in the three-schema architecture. The result of this phase should be DDL statements in the language of the chosen DBMs that specify the conceptual and external level schemas of the database system. 26" }, { "page_index": 93, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_027.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_027.png", "page_index": 93, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:54+07:00" }, "raw_text": "Database design Phase 5: Physical Database Design Restricted to choosing the most appropriate structures for the database fi/es from among the options offered by that DBMS Choose specific storage structures and access paths for the database files Response time Space utilization Transaction throughput Estimate record size and number of records in each database file Estimate the update and retrieval patterns for the file cumulatively from all the transactions Estimate the file growth, either in the record size because of new attributes or in the number of records 27" }, { "page_index": 94, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_028.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_028.png", "page_index": 94, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:11:59+07:00" }, "raw_text": "Database design Phase 6: Database System Implementation and Tuning Create the database schemas and (empty) database files Responsibility of the DBA in conjunction with the database designers Reformat the data for loading into the new database if needed Load/populate with the data if needed Implement database transactions referring to the conceptual specifications of transaction, then write and test program code with embedded DML commands Responsibility of the application programmers Database tuning continues as long as the database is in existence, as long as performance problems are discovered and while the reguirements keep changing. 28" }, { "page_index": 95, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_029.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_029.png", "page_index": 95, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:05+07:00" }, "raw_text": "Database DATA CONTENT DATABASE ANDSTRUCTURE APPLICATIONS design Phase1:REQUIREMENTS DATA PROCESSING COLLECTION REQUIREMENTS REQUIREMENTS AND ANALYSIS Entity Relationship Model P. P-S. Chen. The Entity- Phase 2CONCEPTUAL CONCEPTUAL TRANSACTIONAND DATABASE SCHEMA DESIGN APPPLICATIONDESIGN Relationship Model - Toward DESIGN (DBMS-independent (DBMS-independent) a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) Phase 3:CHOICE OFDBMS 9-36. Phase 4:DATA MODEL LOGICAL SCHEMA frequencies MAPPING ANDVIEW DESIGN performance (LOGICALDESIGN) (DBMS-dependent) constraints Phase5PHYSlCAL DESIGN INTERNAL SCHEMA DESIGN DBMS-dependent Figure 2.1 Phases of database design and implementation for Phase 6:SYSTEM IMPLEMENTATION DDL statements TRANSACTION AND large databases AND TUNING SDL statements APPLICATION [1], pp. 368 IMPLEMENTATION" }, { "page_index": 96, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_030.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_030.png", "page_index": 96, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:09+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. The entity-relationship model adopts the more natural view that the real world consists of entities, relationships, and their attributes. The model can achieve a high degree of data independence and is based on set theory and relation theory. The entity-relationship model can be used as a basis for a unified view of data. A special diagrammatic technique, the entity-relationship diagram, is introduced as a tool for database design. 30" }, { "page_index": 97, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_031.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_031.png", "page_index": 97, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:12+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. The entity-relationship (ER) modeling concepts Entity types Relationship types Attributes Key attributes Structural constraints 31" }, { "page_index": 98, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_032.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_032.png", "page_index": 98, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:16+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Symbol Meaning Example Employee Entity type Employees Dependents of an Dependent Weak entity type employee Employee works_on works on Relationship type Project Identifying Dependents dependents_of relationship type of dependents_of the weak entity type Employees 32" }, { "page_index": 99, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_033.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_033.png", "page_index": 99, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:20+07:00" }, "raw_text": "Symbol Meaning Example Attribute of an entity Name of an employee Name or relationship Distinct identifier of an EmployeeID Key Attribute employee Partial Key of a Name of a dependent Name Weak Entity Type of an employee Phone numbers of an PhoneNumber Multivalued Attribute employee Street District City Address (Street, Composite Attribute District, City) of an Address employee Age of an employee Age Derived Attribute (derived from attribute \"date of birth\") 33" }, { "page_index": 100, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_034.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_034.png", "page_index": 100, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:24+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Constraints E1 R E2 Total Participation of E, in R 1 N E1 R E2 Cardinality Ratio 1: N for E : E, in R (min, max) Structural Constraint (min, max R E on Participation of Ein R 34" }, { "page_index": 101, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_035.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_035.png", "page_index": 101, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:30+07:00" }, "raw_text": "A sample database application COMPANY The COMPANY database keeps track of a company's employees, departments, and projects. Suppose that after the requirements collection and analysis phase, the database designers provide the following description of the miniworld that will be represented in the database : - The company is organized into departments. Each department has a unique name, a unique number, and a particular employee who manages the department. We keep track of the start date when that employee began managing the department. A department may have several locations. - A department controls a number of projects, each of which has a unique name, a unique number, and a single location. - The database will store each employee's name, Social Security number (SsN address, salary, sex (gender), and birth date. An employee is assigned to one department, but may work on several projects, which are not necessarily controlled by the same department. It is required to keep track of the current number of hours per week that an employee works on each project, as well as the direct supervisor of each employee (who is another employee)- - The database will keep track of the dependents of each employee for insurance purposes, including each dependent's first name, sex, birth date, and relationship to the employee 35" }, { "page_index": 102, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_036.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_036.png", "page_index": 102, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:36+07:00" }, "raw_text": "Fname Minit Lname Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee 1 1 N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 36" }, { "page_index": 103, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_037.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_037.png", "page_index": 103, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:42+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity: a thing/ object in the real world with an independent existence, being distinguishable physical existence (e.g. person, book, or employee) conceptual existence (e.g. company, job, or course) Entity type: a collection (or set) of entities that have the same attributes s (i.e. share the same structure) EMPLOYEE Attribute: a particular property that describes an entity via a value Key attribute: attributes whose values are distinct for each entity in the entity set of an entity type 37" }, { "page_index": 104, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_038.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_038.png", "page_index": 104, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:12:52+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity An entity has a value for each of its attributes. Entity emp/oyee has three attributes: SsN, name, address with the corresponding values: 123456789, `Peter Pan', 1 Missing Path, Dream World'. NULL is a special value to say \"not applicab/e\" or \"unknown\" for an attribute of a particular entity. A value set (domain) specifies the set of values that may be assigned to an attribute for each entity. SNN name address Entity employee: EMPLOYEE 123456789, Peter Pan', 1, Missing Path, Dream World' 38" }, { "page_index": 105, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_039.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_039.png", "page_index": 105, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:00+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity type: a collection (or set) of entities that have the same attributes An entity type describes the schema or intension for a set of entities that share the same structure. Entity set (aka the extension of the entity type) : the collection of entities of a particular entity type Entity Type Name: EMPLOYEE Name, Age, Salary e1 John Smith,55,80k e2 Entity Set: (Extension) (Fred Brown,40,30K) e3 39 (Judy Clark,25,20K" }, { "page_index": 106, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_040.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_040.png", "page_index": 106, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:05+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity type: a collection (or set) of entities that have the same attributes An entity type describes the schema or intension for a set of entities that share the same structure. Entity set (the extension of the entity type) : the collection of entities of an entity type Key attribute: attributes whose values are distinct for each entity in the entity set Key attribute values can be used to identify each entity uniquely. Sometimes several attributes together form a key. For example, attribute SSN is a key attribute of entity type EMPLOYEE SSN EMPLOYEE 40" }, { "page_index": 107, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_041.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_041.png", "page_index": 107, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:11+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity Simple vs. Composite Single-valued vs. Multivalued Stored vs. Derived Complex 41" }, { "page_index": 108, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_042.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_042.png", "page_index": 108, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:21+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity Simple vs. Composite SSN Simple: atomic attributes that are not divisible. Attribute SSN is a simple attribute of entity emp/oyee EMPLOYEE Composite: attributes that can be divided into subparts. The value of a composite attribute is the concatenation of the values of its component simple attributes. Attribute address is a composite attribute of entity emp/oyee because it can be divided into subparts : street_number, street_name, district. street street district number name address EMPLOYEE 42" }, { "page_index": 109, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_043.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_043.png", "page_index": 109, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:28+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity Simple vs. Composite Single-valued vs. Multivalued Single-valued: an attribute has a single value for a particular entity. SSN Attribute SSN is a single-valued attribute of entity EMPLOYEE employee Multivalued: an attribute has different values for a particular entity. A multivalued attribute may have /ower and upper bounds to constrain the number of values allowed for each individual entity. phone_ number Attribute phone_number is a multivalued attribute of EMPLOYEE entity employee 43" }, { "page_index": 110, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_044.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_044.png", "page_index": 110, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:33+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity Simple vs. Composite Single-valued vs. Multivalued Stored vs. Derived Stored: an attribute whose value is recorded from the fact SSN in the real world Attribute Ss is a stored attribute of entity emp/oyee EMPLOYEE Derived: an attribute whose value is computed (derived) from other values in the database DOB Attribute age is a derived attribute of entity emp/oyee age because its value is derived from the value of attribute EMPLOYEE DOB of its corresponding entity emp/oyee. 44" }, { "page_index": 111, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_045.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_045.png", "page_index": 111, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:39+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute: a particular property that describes an entity Simple vs. Composite Single-valued vs. Multivalued Stored vs. Derived Complex Attributes: composite and multivalued attributes that can be nested arbitrarily. {Address_phone( {Phone(Area_code,Phone_number)}, Address(Street address (Number,Street,Apartment_number), City,State,Zip) )} Phone: composite, multivalued Street_address: composite Address: composite Address_phone: composite, multivalued 45" }, { "page_index": 112, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_046.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_046.png", "page_index": 112, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:47+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Attribute Complex Attributes {Address_phone( {Phone(Area_code,Phone_number)}, Address(Street address (Number,Street,Apartment_number), City,State,Zip) )} Phone: composite, multivalued Street address: composite Address: composite Address_phone: composite, multivalued Apartment Number Street number Area. Phone_ Street_ City State Zip code number address Address Phone Address _phone EMPLOYEE 46" }, { "page_index": 113, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_047.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_047.png", "page_index": 113, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:13:56+07:00" }, "raw_text": "Fname Minit Lname List all the entity types and their attributes. Classify their attributes. Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT 1 MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee 1 1 N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 47" }, { "page_index": 114, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_048.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_048.png", "page_index": 114, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:03+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1 E21 . F relationship set-among g entities from these entity types EMPLOYEE WORKS_FOR DEPARTMENT EMPLOYEE r1 d1 r2 d2 N e3 r3 da e4 14 WORKS FOR e6 16 e6 1 r6 11 DEPARTMENT Relationship type WORKS_FOR ER diagram 48 between EMPLOYEE and DEPARTMENT" }, { "page_index": 115, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_049.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_049.png", "page_index": 115, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:11+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1, E2, . F relationship set-among g entities from these entity types Degree of a relationship type: the number of participating entity types For example, degree of relationship type WORKS_FOR is 2. Degree 1: unary, Degree 2: binary, Degree 3: ternary Unary relationship types: recursive (self-referencing) relationships EMPLOYEE Supervisor Supervisee 1 N SUPERVISES 49" }, { "page_index": 116, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_050.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_050.png", "page_index": 116, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:16+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1, E21 . F relationship set-among g entities from these entity types Degree of a relationship type: the number of participating entity types For example, degree of relationship type WORKS_FOR is 2. Degree 1: unary, Degree 2: binary, Degree 3: ternary Unary relationship types: recursive (self-referencing) relationships EMPLOYEE Roles: Supervisor Supervisee Supervisor 1 N SUPERVISES Supervisee 50" }, { "page_index": 117, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_051.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_051.png", "page_index": 117, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:20+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1, E21 . , E,: a set of associations-or a relationship set-among entities from these entity types Degree of a relationship type Structural constraints on relationship types Cardinality ratios: the maximum number of relationship instances an entity can participate in: 1:1, 1:N, N:1, N:M Participation: the minimum number of relationship instances that each entity can participate in, i.e. whether the existence of an entity depends on its being related to another entity via the relationship type. - Total participation (existence dependency) : every entity participates in the relationship type. Partial participation: just some (not every) entities 51" }, { "page_index": 118, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_052.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_052.png", "page_index": 118, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:25+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. EMPLOYEE MANAGES DEPARTMENT e1 EMPLOYEE e20 r1 d e3 1 r2 e4 d2 e5 13 MANAGES d3 e6 1 e7 DEPARTMENT A 1:1 binary relationship type MANAGES ER diagram Not every employee manages one department. -> partial participation Every department has one manager (employee). => total participation 52" }, { "page_index": 119, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_053.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_053.png", "page_index": 119, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:30+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. EMPLOYEE WORKS_FOR DEPARTMENT r1 e d EMPLOYEE r2 e2 d2 e3 N r3 da e4 14 WORKS FOR e5 r5 e6 1 e1 r6 DEPARTMENT 17 A N:1 binary relationship type WORKS_FOR ER diagram Every employee works for one department. => total participation Every department has one to N employees. => total participation 53" }, { "page_index": 120, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_054.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_054.png", "page_index": 120, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:35+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. EMPLOYEE WORKS ON PROJECT e1 r1 P1 e2 r2 P2 EMPLOYEE e3 r3 e4 P3 M 14 P4 WORKS ON r5 N r6 PROJECT 11 An M:N binary relationship type WORKS_ON ER diagram Every employee works on one to N projects. => total participation 54 Every project has one to M employees. => total participation" }, { "page_index": 121, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_055.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_055.png", "page_index": 121, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:38+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1, E21 . . , E,: a set of associations-or a relationship set-among entities from these entity types Degree of a relationship type Structural constraints on relationship types Attribute of a relationship type: Relationship types can also have attributes, similar to those of entity types. HOURS N M EMPLOYEE WORKS ON PROJECT 55" }, { "page_index": 122, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_056.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_056.png", "page_index": 122, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:43+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Relationship type R among n entity types E1, E21 . . , E,: a set of associations-or a relationship set-among entities from these entity types Degree of a relationship type Structural constraints on relationship types Attribute of a relationship type > Put them altogether: Vin Date Ssn 1 N VEHICLE SALES CUSTOMER 1 Sid SALESPERSOA 56" }, { "page_index": 123, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_057.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_057.png", "page_index": 123, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:46+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity type: a collection (or set) of entities that have the same attributes Key attribute: attributes whose values are distinct for each entity in the entity set of an entity type Weak entity type: entity types that do not have key attributes of their own (in UoD) Entities belonging to a weak entity type are identified by being related to specific entities from other entity types in combination with one of their attribute values. identifying or owner entity type, identifying relationship 57" }, { "page_index": 124, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_058.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_058.png", "page_index": 124, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:52+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity type: a col/ection (or set) of entities that have the same attributes Weak entity type: entity types that do not have key attributes of their own (in UoD) Entities belonging to a weak entity type are identified by being related to specific entities from other entity types in combination with one of their attribute values. identifying or owner entity type, identifying relationship A weak entity type always has a total participation constraint (existence dependency) with respect to its identifying relationship. A weak entity type normally has a partial key, which is the attribute that uniquely identifies weak entities that are related to the same owner entity. 58" }, { "page_index": 125, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_059.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_059.png", "page_index": 125, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:14:55+07:00" }, "raw_text": "The Entity-Relationship Model P. P-S. Chen. The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1(1)(March 1976) 9-36. Entity type: a col/ection (or set) of entities that have the same attributes Weak entity type: entity types that do not have key attributes of their own n (in UoD) SSN NAME N 1 DEPENDENTS EMPLOYEE DEPENDENT OF Dependents of an employee have different Names. Every dependent is a dependent of one employee Not every employee has one to N dependents. 59" }, { "page_index": 126, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_060.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_060.png", "page_index": 126, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:02+07:00" }, "raw_text": "Fname Minit Lname Describe all the relationship types and their constraints. Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT 1 MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee 1 1 N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 60" }, { "page_index": 127, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_061.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_061.png", "page_index": 127, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:08+07:00" }, "raw_text": "1 N BANK BRANCHES BANK-BRANCH Code Name Addr Addr BranchNo a. List the entity types and describe their attributes. ACCTS LOANS b. Is there any weak entity N N type? If yes, give its name, partial key, and identifying relationship AcctNo Balance LoanNo Amount C. What constraints do the partial key and the ACCOUNT Type LOAN Type identifying relationship of the weak entity type specify in this diagram? M M d. Describe all the relationship types and A-C L-C specify the (min, max) constraint on each N N participation of an entity SSN Name type in a relationship type. Phone CUSTOMER Addr An ER diagram for a BANK database schema Source: [1] 61" }, { "page_index": 128, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_062.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_062.png", "page_index": 128, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:13+07:00" }, "raw_text": "Design an Entity-Relationship diagram for the CONFERENCE REVIEW database Consider a CONFERENCE REVIEW database in which researchers submit their research papers for consideration. Reviews by reviewers are recorded for use in the paper selection process. The database system primarily supports reviewers who record answers to evaluation questions for each paper they review and make recommendations regarding whether to accept or reject the paper. The data requirements are summarized as follows: - Authors of papers are uniquely identified by email id. First and last names are also recorded. - Each paper is assigned a unique identifier by the system and is described by a title, abstract, and the name of the electronic file containing the paper. - A paper may have multiple authors, but one of the authors is designated as the contact author - Reviewers of papers are uniquely identified by email address. Each reviewer's first name, last name, phone number, affiliation, and topics of interest are also recorded. Each paper is assigned between two and four reviewers. A reviewer rates each paper assigned to him or her on a scale of 1 to 10 in four categories: technical merit, readability, originality, and relevance to the conference. Finally, each reviewer provides an overall recommendation regarding each paper. - Each review contains two types of written comments: one to be seen by the review committee only and the other as feedback to the author(s) . 62" }, { "page_index": 129, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_063.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_063.png", "page_index": 129, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:17+07:00" }, "raw_text": "Enhanced Entity-Relationship Modeling Class/subclass relationships and type inheritance The relationship between a superclass and any one of its subclasses Specialization Define a set of subclasses of an entity type Establish additional specific attributes with each subclass Establish additional specific relationship types between each subclass and other entity types or other subclasses Generalization A reverse process of abstraction in which we suppress the differences among several entity types Identify their common features Generalize them into a single superclass of which the original entity types are special subclasses Union types using categories The union (U) of objects of different entity types 63" }, { "page_index": 130, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_064.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_064.png", "page_index": 130, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:22+07:00" }, "raw_text": "FName MInit LName Name Ssn BirthDate Address EMPLOYEE total specialization partial specialization 7 TypingSpeed TGrade EngType PayScale SECRETARY TECHNICIAN ENGINEER MANAGER Salary HOURLY EMPLOYEE SALARIED_EMPLOYEE MANAGES BELONGS_TO Three specializations of EMPLOYEE. {SECRETARY.TECHNICIAN,ENGINEER} {MANAGER} PROJECT TRADE_UNION (HOURLY_EMPLOYEE,SALARIED_EMPLOYEE] EER diagram notation to represent subclasses and specialization. 64 Source: [1]" }, { "page_index": 131, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_065.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_065.png", "page_index": 131, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:25+07:00" }, "raw_text": "(a) NoOfPassengers NoOfAxies Price Price Tonnage MaxSpeed TRUCK CAR Vehicieid Vehicleld LicensePlateNo LicensePlateNo (b) LicensePlateNo Price Vehicleld Generalization VEHICLE Source: [1] NoOfPassengers NoOfAxles Tonnage MaxSpeed CAR TRUCK" }, { "page_index": 132, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_066.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_066.png", "page_index": 132, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:28+07:00" }, "raw_text": "PartNo Description PART ManufactureDate SupplierName DrawingNo BatchNo ListPrice MANUFACTURED PART PURCHASED PARI Disjoint (d) : the subclasses of the specialization must be disjoint. Overlapping (o): the subclasses are not constrained to be disjoint, their sets of entities may overlap. EER diagram notation for overlapping (nondisjoint) specialization. 66 Source: [1]" }, { "page_index": 133, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_067.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_067.png", "page_index": 133, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:33+07:00" }, "raw_text": "A specialization lattice with multiple inheritance for a UNIVERSITY database Name Sex Address Source: [1] Ssn PERSON Birth_date a. List superclasses subclasses of each Salary Major_dept superclass EMPLOYEE ALUMNUS STUDENT b. List class/subclass Degrees relationships Year Degree Major C. Describe constraints on Percent_time each specialization STAFF FACULTY STUDENT GRADUATE UNDERGRADUATE ASSISTANT STUDENT STUDENT Position Rank Degree_program Class Project Course RESEARCH_ASSISTANT TEACHING_ASSISTANT 67" }, { "page_index": 134, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_068.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_068.png", "page_index": 134, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:39+07:00" }, "raw_text": "Two categories (union types): OWNER and Bname Baddress REGISTERED VEHICLE BANK Source: [1] Driver_license_no Name Address Cname Caddress A category can be total or partial. Ssn PERSON COMPANY A total category holds the union of all entities in its superclasses. OWNER + A double line (=) connecting the Lien_or_regular M category and the circle A partial category can hold a subset OWNS Purchase_date of the union. N License_plate_no + A single line (-) connecting the REGISTERED_VEHICLE category and the circle U Vehicle_id Vehicle_id Cstyle Tonnage What are differences between a Cmake CAR category and a superclass/subclass TRUCK Tmake relationship? Cyear Tyear Cmodel Tmodel 68" }, { "page_index": 135, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_069.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_069.png", "page_index": 135, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:42+07:00" }, "raw_text": "Summary Data modeling : conceptual, logical Database design process: 6 phases Requirements collection and analysis Conceptual database design The entity-relationship model Choice of a DBMS -> a representational data model The relational data model Data model mapping (aka logical database design) Physical database design Database system implementation and tuning 69" }, { "page_index": 136, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_070.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_070.png", "page_index": 136, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:45+07:00" }, "raw_text": "Summary The Entity-Relationship Model Entity - Entity set - Entity type - Weak entity type Relationship - Identifying Relationship - Relationship types Attributes (simple vs. composite, single-valued vs. multivalued, stored vs. derived) Key attributes - Partial keys Structural constraints 70" }, { "page_index": 137, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_071.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_071.png", "page_index": 137, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:47+07:00" }, "raw_text": "Summary Enhanced Entity-Relationship Modeling Subclass, superclass, attribute and relationship inheritance Specialization vs. Generalization Disjointness constraint: disjoint (d), overlapping (o) Completeness (totalness) constraint: total (=), partial (-) Category (Union type) (U) Total (=) Partial (-) 71" }, { "page_index": 138, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_072.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_072.png", "page_index": 138, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:51+07:00" }, "raw_text": "Chapter 2: The Entity-Relationship Model ques wslin questi answel guestion quest quest question 2 estion 72" }, { "page_index": 139, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_073.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_073.png", "page_index": 139, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:54+07:00" }, "raw_text": "Review 2.1. Distinguish entity types and weak entity 0 types, relationships and identifying relationships. 2.2. Give examples to differentiate between 0 simple and composite attributes, between single-valued and multivalued attributes, between stored and derived attributes. attribute, and relationship in conceptual data modeling with the Entity-Relationship model? Give an example to justify your suggestions. 73" }, { "page_index": 140, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_074.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_074.png", "page_index": 140, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:15:59+07:00" }, "raw_text": "Review 2.4. Design an E-R diagram of a university 0 database application. The university database maintains records of its departments, Iecturers, course modules, and students. The requirements are summarised as follows: The university consists of departments. Each department has a unique name and some other descriptive attributes. A department must also have a number of lecturers. One of them is the head of the department. All lecturers have unique identifiers and different names. They must teach one or more modules. A lecturer can only belong to one department. Modules are offered by departments and taught by lecturers They must also be attendéd by some students. Each module has a unique module number. Students must enrol for a number of modules. Each student is given a unique student number. 74" }, { "page_index": 141, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_075.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_075.png", "page_index": 141, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:03+07:00" }, "raw_text": "Review 2.5. Consider the E-R diagram which shows a simplified schema for an airline reservations system. a. List the strong (non-weak) entity types in the ER diagram. b. Is there any weak entity type? If yes, give its name, partial key, and identifying relationship. c. What constraints do the partial key and the identifying relationship of the weak entity type specify in this diagram? d. Describe all the relationship types and specify the (min, max) constraint on each participation of an entity type in a relationship type. Justify your choices. 75" }, { "page_index": 142, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_076.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_076.png", "page_index": 142, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:11+07:00" }, "raw_text": "Airport_code City State Name DEPARTURE Review AIRPORT 1 N Leg_no AIRPORT Scheduled_dep_time Scheduled_arr_time PLIGHT_LEG 2.5. Consider the N M N E-R diagram ARRIVAL CAN AIRPORT Instances LEGS LAND which shows a N Number 1 simplified schema Type_name INSTANCE OF Max_seats Airline FLIGHT Company for an airline N AIRPLANE Arr_time Weekdays TYPE DEPARTS reservations Restrictions FARES N ARRIVES 1 Dep_time system. Amount N TYPE N Code FARE N Airplane_id Total_no_of_seats Noofavail_seats N Date AIRPLANE ASSIGNED LEG INSTANCE Customer_name Cphone Seat_no RESERVATION Notes: N 1 A LEG(segment) is a nonstop portion of a flight SEAT A LEGINSTANCE is a particular occurrence of aLEGon aparticular date. 76" }, { "page_index": 143, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_077.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_077.png", "page_index": 143, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:14+07:00" }, "raw_text": "Review 2.6. Consider the following EER diagram 0 that describes the computer systems at a company. Provide your own attributes and key for each entity type. Supply max cardinality constraints justifying your choice. Write a complete narrative description of what this EER diagram represents. 77" }, { "page_index": 144, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_078.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_078.png", "page_index": 144, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:19+07:00" }, "raw_text": "Review INSTALLED SOLD_WITH SOFTWARE COMPUTER INSTALLED_OS OPERATING SYSTEM LAPTOP DESKTOP OPTIONS COMPONENT MEM_OPTIONS SUPPORTS ACCESSORY MEMORY VIDEO_CARD SOUND_CARD KEYBOARD MOUSE MONITOR 2.6. Consider the following EER diagram that describes the computer systems at a company. 78" }, { "page_index": 145, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_079.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_079.png", "page_index": 145, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:25+07:00" }, "raw_text": "Review 2.7. Design an enhanced entity-relationship diagram for a 0 GRADE BOOK database in which instructors within an academic department record points earned by individual students in their classes. The data requirements are summarized below: Each student is identified by a unique identifier, first and last name, and an email address. Each instructor teaches certain courses each term. Each course is identified by a course number, a section number, and the term in which it is taught. For each course he or she teaches, the instructor specifies the minimum number of points reguired in order to earn letter grades A, B, C, D, and F. For example, 90 points for an A, 80 points for a B, 70 points for a C, etc. Students are enrolled in each course taught by the instructor. Each course has a number of grading components (such as midterm exam, final exam, project, and so forth). Each grading component has a maximum number of points (such as 100 or 50) and a weight (such as 20% or 10%). The weights of all the grading components of a course usually total 100. Finally, the instructor records the points earned by each student in each of the grading components in each of the courses. For example, student 1234 earns 84 points for the midterm exam grading component of the section 2 course CSc2310 in the fall term of 2oo9. The midterm exam grading component may have been defined to have a maximum of 100 points and a weight of 20% of the course grade. 79" }, { "page_index": 146, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_080.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_080.png", "page_index": 146, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:28+07:00" }, "raw_text": "Review 2.9. Some people consider that problems 0 called connection traps may arise with the Entity-Relationship model when designing a conceptual database schema. Two main types of connection traps are called fan traps and chasm traps. What are fan traps and chasm traps? Give examples to illustrate them. Are they really the problems with the Entity-Relationship model? If not, explain your answer and then fix the problems faced In your previously given examples. 82" }, { "page_index": 147, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_081.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_081.png", "page_index": 147, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:32+07:00" }, "raw_text": "Review 2.9. Connection Traps 0 o Fan Trap Where a diagram represents a relationship between entity types, but pathway between certain entity occurrences is ambiguous Usually: two or more 1:N (M:N) relationships fan out from the same entity Trap Chasm Where a diagram suggests the existence of a relationship between entity types, but pathway does not exist between certain entity occurrences Usually : optional participation 83" }, { "page_index": 148, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_082.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_082.png", "page_index": 148, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:37+07:00" }, "raw_text": "Review An Example of a Fan Trap N 1 N Staff Faculty Department Has Operates Staff Has Faculty Operates Department entities relationship entities relationship entities 10978 r1 r4 D0001 Fac01 12345 r2 r5 D0003 Fac02 09872 r3 r6 D0007 At which department does staff number 12345 work? 84" }, { "page_index": 149, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_083.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_083.png", "page_index": 149, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:41+07:00" }, "raw_text": "Review 1 N 1 N Faculty Department Staff Operates Has Faculty Operates Department Has Staff entities relationship entities relationship entities r4 D0001 r1 10978 Fac01 r5 D0003 r2 12345 Fac02 r6 D0007 r3 09872 12345 works at department D0003. 85" }, { "page_index": 150, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_084.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_084.png", "page_index": 150, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:46+07:00" }, "raw_text": "Review An Example of a Fan Trap SSN PNumber Name M N M N EMPLOYEE PROJECT LOCATION works on is_at EMPLOYEE works on PROJECT is_at LOCATION entities relationship entities relationship entities 10978 r1 r4 L0001 01 12345 r2 r5 L0003 02 r3 r6 L0005 09872 r4 r7 L0007 At which location does employee 12345 work? 86" }, { "page_index": 151, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_085.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_085.png", "page_index": 151, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:51+07:00" }, "raw_text": "Review An Example of a Chasm Trap N N Department Staff Project Has Works_on Department Has Staff Works_on Project entities relationship entities relationship entities D0001 r1 10978 r4 P007 D0003 r2 12345 P123 D0007 r3 09872 r5 P978 Which department does project P123 belong to? 87" }, { "page_index": 152, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_086.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_086.png", "page_index": 152, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:55+07:00" }, "raw_text": "Review Restructured to remove the Chasm Trap 1 N 1 N Department Staff Project Has Works on 1 N Controls Department Has Staff Works_on Project entities relationship entities relationship entities D0001 r1 10978 r4 P007 Project P123 D0003 r2 12345 P123 belongs to D0007 r3 09872 r5 P978 department Controls relationship D0003. 88" }, { "page_index": 153, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_087.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_a/slide_087.png", "page_index": 153, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:16:58+07:00" }, "raw_text": "Next Chapter 3: The Relational Data Mode 3.1. Concepts 3.2. Relation schemas. Relations 3.3. Mapping an entity-relationship schema into a relational database schema 3.4. The Relational algebra 89" }, { "page_index": 154, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_001.png", "page_index": 154, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:01+07:00" }, "raw_text": "The (E)ER model N0TES - Semester 2 - 2023-2024 By: Vo Thi Ngoc Chau 1" }, { "page_index": 155, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_002.png", "page_index": 155, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:03+07:00" }, "raw_text": "Key attributes for entity types One or more key attributes? Key attribute: Composite? Multivalued? Derived? How about partial key attributes? 2" }, { "page_index": 156, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_003.png", "page_index": 156, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:06+07:00" }, "raw_text": "Partial keys for weak entity types if there are more than one weak entity in the identifying scope Sex Name Birth date Ssn Relationship N 1 DEPENDENTS EMPLOYEE DEPENDENT _OF Name 1 Winner' 1 FOOTBALL TEAM plays MATCH Score 'Loser' 1 3" }, { "page_index": 157, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_004.png", "page_index": 157, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:08+07:00" }, "raw_text": "Neither key nor partial key attributes for relationship types 4" }, { "page_index": 158, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_005.png", "page_index": 158, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:10+07:00" }, "raw_text": "Derived attributes can never be key/partial key attributes. 5" }, { "page_index": 159, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_006.png", "page_index": 159, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:12+07:00" }, "raw_text": " Model of cars, ships, buildings, . Skills of each employee Topics of each presentation Authors of books Semesters of courses 6" }, { "page_index": 160, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_007.png", "page_index": 160, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:14+07:00" }, "raw_text": "When to decide an entity type instead of a relationship type Registration: students-courses Match: football team-football team Order: customers-products 7" }, { "page_index": 161, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_008.png", "page_index": 161, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:17+07:00" }, "raw_text": "When to decide regular entity types and weak entity types, weak entity types and relationship types Name Cname M N CANDIDATE CCI COMPANY Department Date K Dept_date M N NTERVIEW RESULTS IN JOB OFFER 8" }, { "page_index": 162, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_009.png", "page_index": 162, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:21+07:00" }, "raw_text": "Date Department Dept_date Cname Name N M Is CANDIDATE COMPANY interviewed Name Cname M N CANDIDATE CCI COMPANY Department Date K Dept_date M N NTERVIEW RESULTS IN JOB OFFER 9" }, { "page_index": 163, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_010.png", "page_index": 163, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:26+07:00" }, "raw_text": "Consider n-ary relationship types Sname Proj_name where nz3 M N (b) SUPPLIER SUPPLIES PROJECT M M CAN SUPPLY USES Part_no Sname Quantity Proj_name N N PART M N (a) SUPPLIER SUPPLY PROJECT (c) Part_no K Sname Quantity Proj_name PART N N - 1 SUPPLIER Ss SUPPLY SPJ PROJECT N SP Part_no 1 PART 10" }, { "page_index": 164, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_011.png", "page_index": 164, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:29+07:00" }, "raw_text": "Consider n-ary relationship types where n3 Semester Year TAUGHT DURING M N Lname Sem_year M N NSTRUCTOR OFFERS SEMESTER M N K CAN TEACH OFFERED DURING Cnumber N M COURSE 11" }, { "page_index": 165, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_012.png", "page_index": 165, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:34+07:00" }, "raw_text": "Date When to Time_stamp Time SHIP MOVEMENT Longitude N decide Latitude HISTORY superclass/ Type Tonnage Hull Sname N 1 SHIP TYPE SHIP TYPE Owner subclasses (0*) Start_date End_date N (1,1) SHIP AT HOME PORT PORT VISIT Continent PORT Name (0*) N 1 IN STATE/COUNTRY Name Pname PORT N 1 ON SEA/OCEAN/LAKE 12" }, { "page_index": 166, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_013.png", "page_index": 166, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:36+07:00" }, "raw_text": "When to decide superclass/subclasses and relationship types 13" }, { "page_index": 167, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_014.png", "page_index": 167, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:38+07:00" }, "raw_text": "When to decide superclass/subclasses and union 14" }, { "page_index": 168, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_015.png", "page_index": 168, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:41+07:00" }, "raw_text": "Connection traps Some people consider that problems called connection traps may arise with the Entity-Relationship model when designing a conceptual database schema. Two main types of connection traps are called fan traps and chasm traps. What are fan traps and chasm traps? Give examples to illustrate them. Are they really the problems with the Entity- Relationship model? If not, explain your answer and then fix the problems faced in your previously given examples. 15" }, { "page_index": 169, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_016.png", "page_index": 169, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:45+07:00" }, "raw_text": "Connection traps Trap Fan 0 1 Where a diagram represents a relationship between entity types, but t pathway between certain entity occurrences is ambiguous Usually: two or more 1:N (M:N) relationships fan the same entity out from 1 Chasm Trap O C Where a diagram suggests the existence of a relationship between entity types, but pathway does not exist between certain entity occurrences Usually : optional participation .6" }, { "page_index": 170, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_017.png", "page_index": 170, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:49+07:00" }, "raw_text": "Connection traps An Example of a Fan Trap N N 1 Staff Faculty Department Has Operates Staff Has Faculty Operates Department entities relationship entities relationship entities 10978 r1 r4 D0001 Fac01 12345 r2 r5 D0003 Fac02 09872 r3 r6 D0007 At which department does staff 12345 work? 17" }, { "page_index": 171, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_018.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_018.png", "page_index": 171, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:54+07:00" }, "raw_text": "Connection traps 1 N 1 N Faculty Department Staff Operates Has Faculty Operates Department Has Staff entities relationship entities relationship entities r4 D0001 r1 10978 Fac01 r5 D0003 r2 12345 Fac02 r6 D0007 r3 09872 18 12345 works at department D0003" }, { "page_index": 172, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_019.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_019.png", "page_index": 172, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:17:59+07:00" }, "raw_text": "Connection traps An Example of a Fan Trap PNumber SSN Name M N M N EMPLOYEE PROJECT LOCATION works_on is_at EMPLOYEE works_on PROJECT is_at LOCATION entities relationship entities relationship entities 10978 r1 r4 L0001 01 12345 r2 r5 L0003 02 r3 r6 L0005 09872 r4 r7 L0007 19" }, { "page_index": 173, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_020.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_020.png", "page_index": 173, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:04+07:00" }, "raw_text": "Connection traps An Example of a Chasm Trap N 1 N Department Staff Project Has Works_on Department Has Staff Works_on Project entities relationship entities relationship entities D0001 r1 10978 r4 P007 D0003 r2 12345 P123 D0007 r3 09872 r5 P978 20 Which department does project P123 belong to?" }, { "page_index": 174, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_021.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_021.png", "page_index": 174, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:10+07:00" }, "raw_text": "Connection traps Restructured to remove the Chasm 1 Trap 1 N 1 N Department Staff Project Has Works_on 1 N Controls Department Has Staff Works_on Project entities relationship entities relationship entities D0001 r1 10978 r4 P007 Project P123 D0003 r2 12345 P123 belongs to D0007 r3 09872 r5 P978 department Controls relationship D0003. 21" }, { "page_index": 175, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_022.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_022.png", "page_index": 175, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:13+07:00" }, "raw_text": "Connection traps Hybrid trap: fan trap + chasm trap Cname DCode LabName M N M N Is used LABORATORY COURSE uses DEVICE for Which particular laboratory does a device belong to? 22" }, { "page_index": 176, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_023.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_023.png", "page_index": 176, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:18+07:00" }, "raw_text": "Connection traps Hybrid trap: fan trap + chasm trap SSN PNumber Name 1 M N M N EXPERT PROJECT LOCATION supports is at EXPERT works_on PROJECT is_at LOCATION entities relationship entities relationship entities 10978 r1 r4 L0001 01 12345 r2 r5 L0003 02 09079 r3 r6 L0005 09872 r4 r7 L0007 03 Which particular location does an expert work at? 23" }, { "page_index": 177, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_024.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_024.png", "page_index": 177, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:22+07:00" }, "raw_text": "Address PhoneNumber Cname Contact Cname Address PhoneNumber COMPANY COMPANY Address PhoneNumber Address PhoneNumber Cname Contact Cname COMPANY COMPANY 24" }, { "page_index": 178, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_025.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_025.png", "page_index": 178, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:25+07:00" }, "raw_text": "Number BuildingName Type Code Type Number BuildingName ROOM ROOM Day Year DoB SSN DoB BirthDay BirthYear SSN BirthDetails PERSON PERSON 25" }, { "page_index": 179, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_026.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_026.png", "page_index": 179, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:27+07:00" }, "raw_text": "Room Code Room Code Code Laboratory Study Room Laboratory Study Room 26" }, { "page_index": 180, "chapter_num": 2, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_027.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_2_b/slide_027.png", "page_index": 180, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:30+07:00" }, "raw_text": "Room Code Room Code Code Laboratory Study Room Laboratory Study Room 27" }, { "page_index": 181, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_001.png", "page_index": 181, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:34+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Chapter 3: The Relational Data Model Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vö Thi Ngoc Chau (chauvtn@hcmut.edu.vn) Semester 1 - 2022-2023" }, { "page_index": 182, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_002.png", "page_index": 182, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:37+07:00" }, "raw_text": "Content Chapter 1 : An Overview of Database Systems Chapter 2: The Entity-Relationship Model 0 Chapter 3: The Relational Data Model 0 Chapter 4: The SQL Language Chapter 5: Relational Database Design 0 Chapter 6: Physical Storage and Data Management 0 Chapter 7 : Database Security 2" }, { "page_index": 183, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_003.png", "page_index": 183, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:41+07:00" }, "raw_text": "Chapter 3 : The Relational Data Mode 3.1. Concepts 3.2. Relation schemas. Relations 3.3. Mapping an entity-relationship schema into a relational database schema 3.4. The Relational algebra 3" }, { "page_index": 184, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_004.png", "page_index": 184, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:45+07:00" }, "raw_text": "Main References Text : 1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References : [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd,2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 7th Edition, McGraw-Hill, 2020. 4] H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. [5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 4th Edition, McGraw-Hill, 2018. [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Object- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007 4" }, { "page_index": 185, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_005.png", "page_index": 185, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:53+07:00" }, "raw_text": "Database Data content,structure Database and constraints applications design Phase 1:Requirements Data Processing collection requirements requirements and analysis A representational data model supported Phase 2: Conceptual Conceptual Transaction and database Schema design application design by the chosen DBMS design (DBMS-independent (DBMS-independent) Relational Data Model E. F. Codd. A Relational Phase 3:Choice of DBMS Model of Data for Large Shared Data Banks. Logical Schema Frequencies Phase4:Data model Communications of the and view design performance mapping ACM 13(6)(June, 1970) (DBMS-dependent (logical design) constraints 377-387. Phase 5:Physica Internal design Schema design (DBMS-dependent Phases of database design Phase 6: System DDL statements Transaction and implementation for implementation SDL statements and application and tuning implementation large databases DDL: data definition language 5 Source: [1] SDL: storage definition language" }, { "page_index": 186, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_006.png", "page_index": 186, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:56+07:00" }, "raw_text": "Representational data a model A data a model (aka implementation/logical data model Provides concepts understood by end-users and able to be used to describe the structure of a database the data types, relationships, and constraints that should hold for the data a set of basic operations for specifying retrievals and updates on the database Hides some details of data storage but able to be implemented on a computer system in a direct way (in some DBMS) Example: the relational data model 6" }, { "page_index": 187, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_007.png", "page_index": 187, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:18:59+07:00" }, "raw_text": "Data a model E. F. Codd. Data models in database management, ACM, 1980 A combination of three following components (1): A collection of data structure types (the building blocks of any database that conforms to the model); (2). A collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired; (3): A collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both --- these rules may sometimes be expressed as insert-update- delete rules. 7" }, { "page_index": 188, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_008.png", "page_index": 188, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:03+07:00" }, "raw_text": "Concepts Relational data model 0 Relational database 0 Relation 0 Degree, cardinality o Tuple Attribute 0 Domain 0 (Atomic) Value 0 NULL Operation (Operator) Constraint 0 Inherent model-based (implicit) constraint Schema-based (explicit) constraint Application-based (semantic) constraint 8" }, { "page_index": 189, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_009.png", "page_index": 189, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:08+07:00" }, "raw_text": "Data a model E. F. Codd. Data models in database management, ACM, 1980 A combination of three following components (1): A collection of data structure types (the building blocks of any database that conforms to the model); (2). A collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired; (3): A collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both --- these rules may sometimes be expressed as insert-update- delete rules. 9" }, { "page_index": 190, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_010.png", "page_index": 190, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:12+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. The term re/ation is used here in its accepted mathematical sense. A relational database based on the relational data model is a collection of relations. 0 is a re/ation on these n sets if it is a set of n-tuples each of which has its first element from Sy its second element from S2, and so on. Sj is the jth domain of R, including atomic values. R is said to have degree n. R is said to have cardinality IRl. More concisely, re/ation R is a subset of the 01 Cartesian product SxS,x...xSn. 10" }, { "page_index": 191, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_011.png", "page_index": 191, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:15+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. An n-ary relation R has the following properties (aka inherent model-based (implicit) constraints) : Each row represents an n-tuple of R. The ordering of rows is immaterial (not important) : All rows are distinct. The ordering of columns is significant - it domains on which R is defined. The significance of each column is partially conveyed by labeling it with the name of the corresponding domain, which is called attribute 11" }, { "page_index": 192, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_012.png", "page_index": 192, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:21+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. SH SNAME STATUS CITY Domains Primary key S SNAME STATUS CITY Attributcs SI Smith 20 London Relation S2 Jones 10 Paris Tuples S3 Blake 30 Paris S4 Clark 20 London S5 Adams 30 Athens The supplier relation S. Re/ation schema: S (S#, SNAME, STATUS, CITY Degree (= the number of attributes) : 4 Cardinality (=sD : 5 12" }, { "page_index": 193, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_013.png", "page_index": 193, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:25+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. supply (supplier project quantity part 2 17 1 1 3 5 23 2 3 2 7 5 4 1 1 12 4 A relation of degree 4, cardinality 5 (=supplyl) A relation of degree 4, called supp/y, which reflects the shipments-in-progress of parts from specified suppliers to specified projects in specified quantities. Its attributes are: supplier, part, project, quantity Its relation schema: supply (supplier, part, project, quantity) 13" }, { "page_index": 194, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_014.png", "page_index": 194, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:28+07:00" }, "raw_text": "The Relational Data Model Relation schema c Relation scheme Relation intension R (A1,A2, ...,An) Relation Relation state Relation instance Relation extension of the relation schema r = a set of n-tuples = {t1, t2, ... , tm}" }, { "page_index": 195, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_015.png", "page_index": 195, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:32+07:00" }, "raw_text": "Data a model E. F. Codd. Data models in database management, ACM, 1980 A combination of three following components (1): A collection of data structure types (the building blocks of any database that conforms to the model); (2). A collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired; (3): A collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both --- these rules may sometimes be expressed as insert-update- delete rules. 14" }, { "page_index": 196, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_016.png", "page_index": 196, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:36+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. Basic operations on relations Usual set operations: union, intersection, minus Compatible relations Projection (t) Select certain columns of a relation (striking out the others) Selection (o) Select a subset of the tuples from a relation that satisfy a selection condition Cartesian product (cross product) (x) Combine tuples from two relations in a combinatorial fashion Join (inner/outer theta join, equijoin, natural join) Combine related tuples from two relations into single tuples 15" }, { "page_index": 197, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_017.png", "page_index": 197, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:41+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. R (supplier part) S (part project) 1 1 1 1 2 1 1 2 2 2 2 1 FIG.5. Two joinable relations R*S (supplier part project) 1 1 1 1 1 2 2 1 1 2 1 2 2 2 1 F1G.6. The natural join of R with S (from Figure 5 16" }, { "page_index": 198, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_018.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_018.png", "page_index": 198, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:44+07:00" }, "raw_text": "The Relational Data Model A Complete Set of Relational Algebra Operations : {o,T,U,P,-, x} 0 = select 0 t = project U = union minus s (difference) x = Cartesian product" }, { "page_index": 199, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_019.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_019.png", "page_index": 199, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:47+07:00" }, "raw_text": "Data a model E. F. Codd. Data models in database management, ACM, 1980 A combination of three following components (1): A collection of data structure types (the building blocks of any database that conforms to the model); (2). A collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired; (3): A collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both --- these rules may sometimes be expressed as insert-update- delete rules. 17" }, { "page_index": 200, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_020.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_020.png", "page_index": 200, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:50+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. Schema-based (explicit) constraints Domain constraints Key constraints Constraints on nulls Entity integrity constraints Referential integrity constraints 18" }, { "page_index": 201, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_021.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_021.png", "page_index": 201, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:54+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. Domain constraints Within each tuple, the value of each attribute A must be an atomic value from the domain dom(A) - Key constraints 1. Two distinct tuples in any state of the relation cannot have identical values for (all) the attributes in the key 2. It is a minimal superkey - that is, a superkey from which we cannot remove any attributes and still have the unigueness constraint in condition 1 hold. Superkey of the relation schema R specifies a uniqueness constraint that no two distinct tuples in any state r of R can have the same value for the superkey 19" }, { "page_index": 202, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_022.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_022.png", "page_index": 202, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:19:57+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13(6)(June, 1970) 377-387. Key constraints A relation schema may have more than one key. Candidate keys: primary key and secondary keys Constraints on nulls Specify whether null values are or are not permitted on attributes Entity integrity constraint No primary key value can be null. Referential integrity constraint Specify a referential integrity constraint between R1 and R2 the two relation schemas 20" }, { "page_index": 203, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_023.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_023.png", "page_index": 203, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:20:01+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. Referential integrity constraint A set of attributes FK (foreign key) in relation schema R is a foreign key of R, that references relation R, if it satisfies the following two rules: The attributes in FK have the same domain(s) as the primary key attributes PK of R,; the attributes FK are A value of FK in a tuple t, of the current state r1(R1) either occurs as a value of PK for some tuple t, in the have t1[FK] = t,[PK], and we say that the tuple t1 21" }, { "page_index": 204, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_024.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_024.png", "page_index": 204, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:20:11+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. EMPLOYEE FNAME MINIT LNAME SSN BDATE ADDRESS SEX SALARY SUPERSSN DNO John B Smitn 123456789 1965-01-09 731 Fondren.Houston,Tx M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston.TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jenniter S Wallace 987654321 1941-06-20 291Berry.Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak.Humble,T M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 null 1 Relation Employee Relation schema: EMPLOYEE (FNAME, MINIT, LNAME, SSN BDATE, ADDRESS, SEX, SALARY, SUPERSSN, DNO Attributes = FNAME, MINIT, LNAME, SSN, BDATE, ADDRESS, SEX SALARY, SUPERSSN, DNO Domain of Attribute SEX = {F, M} Domain of SALARY = a set of positive integer numbers Primary key = SSN Check all the implicit and explicit constraints on this relation! Foreign key = SUPERSSN, DNO 22" }, { "page_index": 205, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_025.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_025.png", "page_index": 205, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:20:21+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. EMPLOYEE FNAME MINIT LNAME SSN BDATE ADDRESS SEX SALARY SUPERSSN DNO John B Smith 123456789 1965-01-09 731 Fondren.Houston,Tx M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston.TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291Berry.Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fre Oak.Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 null 1 Relation Employee Relation schema: EMPLOYEE (FNAME, MINIT, LNAME, SSN BDATE, ADDRESS, SEX, SALARY, SUPERSSN, DNO) Examine more application-based (semantic) constraints : Each department has at most 20 employees. Each employee must has a supervisor in the same department. Otherwise, he/ she is the manager of his/ her department. The salary of an employee must not be greater than the salary of the manager of the department that the employee works for. 23" }, { "page_index": 206, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_026.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_026.png", "page_index": 206, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T06:20:24+07:00" }, "raw_text": "The Relational Data Model E. F. Codd. A Relational Model of Data for Large Shared Data Banks Communications of the ACM 13(6)(June, 1970) 377-387. High-level database language on relational databases Structured Query Language (SQL) Data definition language (DDL) Data query language (SELECT) Data manipulation language (INSERT, DELETE UPDATE Versions: SQL-86, SQL-89, SQL-92, SQL-99, SQL-2003, SQL-2008, SQL-2011, SQL-2016, ... 24" }, { "page_index": 207, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_027.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_027.png", "page_index": 207, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:11:23+07:00" }, "raw_text": "Database Data content,structure, Database design and constraints applications Phase 1:Requirements Data Processing collection requirements requirements and analysis Data model Phase 2: Conceptual Conceptual Transaction and mapping from a database Schema design application design design (DBMS-independent) (DBMS-independent) conceptual schema based on Phase 3: Choice the ER model to of DBMS a relational Logical Schema Frequencies, Phase 4 Data model database schema and view design mapping performance based on the (DBMS-dependent (logical design) constraints relational data Phase 5:Physical model Internal design Schema design (DBMS-dependent Phases of database design and Phase 6: System DDL statements Transaction implementation for implementation SDL statements and application large databases and tuning implementation DDL: data definition language Source: [1] 25 SDL: storage definition language" }, { "page_index": 208, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_028.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_028.png", "page_index": 208, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:11:33+07:00" }, "raw_text": "model mapping Data Mapping algorithms Automatically create a relational schema from a conceptual schema design Notes on data model mapping Slightly different for other post-relational data models as compared to the relational data model Constraints on databases Inherent model-based implicit constraints Schema-based constraints Application-based constraints 26" }, { "page_index": 209, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_029.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_029.png", "page_index": 209, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:11:41+07:00" }, "raw_text": "model mapping Data Informal measures of quality for relation schema design Semantics of the attributes How to interpret the attribute values stored in a tuple of the relation - how the attribute values in a tuple relate to one another Reducing the redundant values in tuples Storage space & update anomalies Reducing the null values in tuples Multiple interpretations of nu//s Disallowing the possibility of generating spurious tuples Join relations with eguality conditions on attributes that are either primary keys or foreign keys in a way that guarantees that no spurious tuples are generated 27" }, { "page_index": 210, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_030.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_030.png", "page_index": 210, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:11:48+07:00" }, "raw_text": "model mapping Data ERMODEL RELATIONALMODEL Entity type Entity relation 1:1 or 1:N relationship type Foreign key (or relationship relation) M:N relationship type Relationship relation and two foreign keys n-ary relationship type Relationship relation and n foreign keys Simple attribute Attribute Composite attribute Set of simple component attributes Multivalued attribute Relation and foreign key Value set Domain Key attribute Primary (or secondary) key Correspondence between the ER and Relational Models Source: [1] 28" }, { "page_index": 211, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_031.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_031.png", "page_index": 211, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:11:54+07:00" }, "raw_text": "model mapping Data Step 1: Mapping of Regular Entity Types Step 2: Mapping of Weak Entity Types Step 3: Mapping of Binary 1:1 Relationship Types Step 4: Mapping of Binary 1:N Relationship Types Step 5: Mapping of Binary M:N Relationship Types Step 6: Mapping of Multivalued Attributes 0 Step Z: Mapping of N-ary Relationship Types 0 Step 8: Mapping of Specialization or Generalization Step 9: Mapping of Union Types (Categories) 29" }, { "page_index": 212, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_032.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_032.png", "page_index": 212, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:00+07:00" }, "raw_text": "model mapping Data Step 1: Mapping of Regular Entity Types 0 For each regular entity type E, create a relation R that includes all the simple attributes of E. Include only the simple component attributes of a composite attribute. Choose one of the key attributes of E as the primary key for R. If the chosen key of E is a composite, then the set of simple attributes that form it will together form the primary key of R. If multiple keys were identified for E during the conceptual design, the information describing the attributes that form each additional key is kept in order to specify secondary (unique) keys of relation R. Knowledge about keys is also kept for indexing purposes and other types of analyses. The relations that are created from the mapping of entity types are sometimes called entity relations because each tuple represents an entity instance. 30" }, { "page_index": 213, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_033.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_033.png", "page_index": 213, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:08+07:00" }, "raw_text": "Fname Minit Lname What are regular entity types? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS_FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 31" }, { "page_index": 214, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_034.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_034.png", "page_index": 214, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:15+07:00" }, "raw_text": "model mapping Data Step 1: Mapping of Regular Entity Types 0 Entity Relation Schemas: Fname Minit Lname Bdate Name Address Salary EMPLOYEE (Ssn, Fname, Minit, Lname Ssn Sex Bdate, Address, Salary, Sex Primary key: Ssn EMPLOYEE Start_da DEPARTMENT (Number, Name) Locations WORKS_FOR Name Number Primary key: Number .Number_of_employees DEPARTMENT Secondary (unique, not null) key: Name N L PROJECT (Number, Name, Location) I_ON PROJECT Name Primary key: Number Location Number Secondary (unique, not null) key: Name 32" }, { "page_index": 215, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_035.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_035.png", "page_index": 215, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:23+07:00" }, "raw_text": "model mapping Data Step 2: Mapping of Weak Entity Types For each weak entity type w with owner entity type E create a relation R and include all simple attributes (or simple components of composite attributes) of W as attributes of R. In addition, include as foreign key attributes of R, the primary key attribute(s) of the relation(s) that correspond to the owner entity type(s); this takes care of mapping the identifying relationship type of W. The primary key of R is the combination of the primary key(s) of the owner(s) and the partial key of the weak entity type W, if any. If there is a weak entity type E2 whose owner is also a weak entity type E1, then E1 should be mapped before E2 to determine its primary key first. 33" }, { "page_index": 216, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_036.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_036.png", "page_index": 216, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:31+07:00" }, "raw_text": "Fname Minit Lname What are weak entity types? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS_FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 34" }, { "page_index": 217, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_037.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_037.png", "page_index": 217, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:36+07:00" }, "raw_text": "model mapping Data Step 2: Mapping of Weak Entity Types (and their identifying relationship types) Sex Name Birth date Ssn Relationship N 1 DEPENDENTS EMPLOYEE DEPENDENT _OF Relation Schemas : EMPLOYEE (Ssn, ...) Primary key: Ssn DEPENDENT (Ssn, Name, Birth_date, Sex, Relationship) Primary key : Ssn, Name Foreign key: Ssn with reference to EMPLOYEE.Ssn 35" }, { "page_index": 218, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_038.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_038.png", "page_index": 218, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:40+07:00" }, "raw_text": "model mapping Data Step 2: Mapping of Weak Entity Types Name Cname M N CANDIDATE CCI COMPANY Department Date K Dept_date M N NTERVIEW RESULTS IN JOB OFFER Relation Schemas : CANDIDATE (Name, ...) COMPANY (Cname, ...) INTERVIEW (Cname, Name, Department, Date) Primary key: Cname, Name, Department, Date Foreign key: Cname to COMPANY.Cname, Name to CANDIDATE.Name 36" }, { "page_index": 219, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_039.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_039.png", "page_index": 219, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:47+07:00" }, "raw_text": "model mapping Data Step 3: Mapping of Binary 1:1 Relationship Types 0 For each binary 1: 1 relationship type R, identify the relations S and T that correspond to the entity types participating in R. Foreign key approach: Choose one of the relations-S, say-and include as a foreign key in S the primary key of T. It is better to choose an entity type with total participation in R in the role of S. Include all the simple attributes (or simple components of composite attributes) of the 1:1 relationship type R as attributes of S Merged relation approach: An alternative mapping of a 1: 1 relationship type is to merge the two entity types and the relationship into a sing/e re/ation. This is possible when both participations are total, as this would indicate that the two tables will have the exact same number of tuples at all times. Cross-reference or relationship relation approach: The third option is to set up a third relation R for the purpose of cross-referencing the primary keys of the two relations S and T representing the entity types. As we will see, this approach is required for binary M:N relationships. The relation R is called a relationship relation (or sometimes a lookup table), because each tuple in R represents a relationship instance that relates one tuple from S with one tuple from T. The relation R will include the primary key attributes of S and T as foreign keys to S and T. The primary key of R will be one of the two foreign keys, and the other foreign key will be a unique key of R. The drawback is having an extra relation, and requiring an extra join operation when combining related tuples from the tables. 37" }, { "page_index": 220, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_040.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_040.png", "page_index": 220, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:53+07:00" }, "raw_text": "Fname Minit Lname What are 1:1 relationship types? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 38" }, { "page_index": 221, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_041.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_041.png", "page_index": 221, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:12:58+07:00" }, "raw_text": "model mapping Data Step 3: Mapping of Binary 1:1 Relationship Types Foreign key approach : EMPLOYEE (Ssn, ...) DEPARTMENT (Number, ..., Ssn, Start_date) Ssn Foreign key (on total participation) : Ssn to EMPLOYEE.Ssn NOT NULL: Ssn, Start_date (?) EMPLOYEE Uniqueness: Ssn Merged relation approach: Start date 1 Not applicab/e because only DEPARTMENT has total participation. MANAGES Relationship relation approach : 1 EMPLOYEE (Ssn, ...) Number DEPARTMENT (Number, ...) MANAGES (Ssn, Number, Start_date DEPARTMENT Primary key: Number Unique key: Ssn Foreign key: Ssn to EMPLOYEE.Ssn, Number to DEPARTMENT.Number NOT NULL: Ssn, Start_date (?)" }, { "page_index": 222, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_042.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_042.png", "page_index": 222, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:13:04+07:00" }, "raw_text": "model mapping Data Step 4: Mapping of Binary 1:N Relationship Types 0 For each regular binary 1:N relationship type R, identify the re/ation S that represents the participating entity type at the N-side of the relationship type. Include as foreign key in S the primary key of the relation T that represents the other entity type at the 1-side; because each entity instance on the N-side is related to at most one entity instance on the 1-side of the relationship type. Include any simple attributes (or simple components of composite attributes) of the 1:N relationship type as attributes of S. An alternative approach is to use the relationship relation (cross-reference) option. We create a separate relation R whose attributes are the primary keys of S and T, which will also be foreign keys to S and T. The primary key of R is the same as the primary key of S. This option can be used if few tuples in S participate in the relationship to avoid excessive NULL values in the foreign key. 40" }, { "page_index": 223, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_043.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_043.png", "page_index": 223, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:13:36+07:00" }, "raw_text": "Fname Minit Lname What are 1:N relationship types? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date 41 Relationship" }, { "page_index": 224, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_044.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_044.png", "page_index": 224, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:13:53+07:00" }, "raw_text": "model mapping Data Step 4: Mapping of Binary 1:N Relationship Types Ssn EMPLOYEE Supervisor Supervisee 1 N SUPERVISES Foreign key approach : EMPLOYEE (Ssn, ... Supervisor_Ssn) Foreign key (at the N-side): Supervisor_Ssn to EMPLOYEE.Ssn Relationship relation approach : EMPLOYEE (Ssn, ...) SUPERVISES (Supervisee_Ssn, Supervisor_Ssn) Primary key (at the N-side): Supervisee Ssn Foreign key: Supervisee_Ssn to EMPLOYEE.Ssn, Supervisor_Ssn to EMPLOYEE.Ssn NOT NULL: Supervisor Ssn 42" }, { "page_index": 225, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_045.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_045.png", "page_index": 225, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:02+07:00" }, "raw_text": "model mapping Data Step 4: Mapping of Binary 1:N Relationship Types Foreign key approach : Ssn DEPARTMENT (Number, ...) EMPLOYEE (Ssn,..., Number) EMPLOYEE Foreign key (at the N-side) of EMPLOYEE: Number to DEPARTMENT.Number NOT NULL: Number N Check total participation of DEPARTMENT.Number in EMPLOYEE WORKS FOR Relationship relation approach : 1 EMPLOYEE (Ssn, ...) DEPARTMENT (Number, ... WORKS_FOR (Ssn, Number) DEPARTMENT Primary key (at the N-side) : Ssn Foreign key: Ssn to EMPLOYEE.Ssn, Number to DEPARTMENT.Number Number NOT NULL: Number Check total participation of EMPLOYEE.Ssn and DEPARTMENT.Number in WORKS FOR 43" }, { "page_index": 226, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_046.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_046.png", "page_index": 226, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:09+07:00" }, "raw_text": "model mapping Data Step 4: Mapping of Binary 1:N Relationship Types Foreign key approach : Number DEPARTMENT (Number, ...) PROJECT (Number, ..., Department_Number) DEPARTMENT Foreign key (at the N-side) of PROJECT: Department_Number to DEPARTMENT.Number NOT NULL: Department Number 1 Relationship relation approach : CONTROLS DEPARTMENT (Number, ...) N PROJECT (Number, ...) CONTROLS (Proiect Number, Department Number) PROJECT Primary key (at the N-side): Proiect Number Foreign key: Project_Number to Project.Number Department_Number to DEPARTMENT.Number NOT NULL: Department_Number Number Check total participation of PROJECT.Number in CONTROLS 44" }, { "page_index": 227, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_047.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_047.png", "page_index": 227, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:16+07:00" }, "raw_text": "model mapping Data Step 5: Mapping of Binary M:N Relationship Types For each binary M:N relationship type R, create a new relation S to represent R. Include as foreign key attributes in S the primary keys of the relations that represent the participating entity types, their combination will form the primary key of S. Also include any simple attributes of the M: N relationship type (or simple components of composite attributes) as attributes of S. 45" }, { "page_index": 228, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_048.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_048.png", "page_index": 228, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:23+07:00" }, "raw_text": "Fname Minit Lname What are M:N relationship types? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 46" }, { "page_index": 229, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_049.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_049.png", "page_index": 229, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:29+07:00" }, "raw_text": "model mapping Data Step 5: Mapping of Binary M:N Relationship Types HOURS Ssn Number N M EMPLOYEE WORKS ON PROJECT Relationship relation approach : EMPLOYEE (Ssn, ...) PROJECT (Number, ...) WORKS ON (Ssn, Number, Hours) Primary key: Ssn, Number Foreign key: Ssn to EMPLOYEE.Ssn, Number to PROJECT.Number Check total participation of EMPLOYEE.Ssn and PROJECT.Number in WORKS ON 47" }, { "page_index": 230, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_050.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_050.png", "page_index": 230, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:35+07:00" }, "raw_text": "model mapping Data Step 5: Mapping of Binary M:N Relationship Types Name Cname M N CANDIDATE CCI COMPANY Department Date K Dept_date JobID M N INTERVIEW RESULTS IN JOB OFFER Relation Schemas: INTERVIEW (InterviewID, Cname, Name, Department, Date JOB OFFER (JobID, ...) RESULTS IN (InterviewID, JobID Primary key: InterviewID, JobID Foreign key: InterviewID to INTERVIEW.InterviewID, JobID to JOB OFFER.JobID 48" }, { "page_index": 231, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_051.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_051.png", "page_index": 231, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:40+07:00" }, "raw_text": "model mapping Data Step 6: Mapping of Multivalued Attributes For each multivalued attribute A, create a new relation R This relation R will include an attribute corresponding to A plus the primary key attribute K-as a foreign key in R-of the relation that represents the entity type or relationship type that has A as a multivalued attribute The primary key of R is the combination of A and K. If the multivalued attribute is composite, we include its simple components. 49" }, { "page_index": 232, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_052.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_052.png", "page_index": 232, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:49+07:00" }, "raw_text": "Fname Minit Lname What are multivalued attributes? How about their mappings? Bdate Name Address Salary Ssn Sex Locations N WORKS FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema diagram for the COMPANY database Source: [1] Name Sex Birth_date Relationship 50" }, { "page_index": 233, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_053.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_053.png", "page_index": 233, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:53+07:00" }, "raw_text": "model mapping Data Step 6: Mapping of Multivalued Attributes Relation Schemas : Locations DEPARTMENT (Number, ...) Name Number Locations (Number, ALocation) Primary key: Number ALocation DEPARTMENT Foreign key: Number to Department.Number 51" }, { "page_index": 234, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_054.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_054.png", "page_index": 234, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:14:59+07:00" }, "raw_text": "model mapping Data Step 6: Mapping of Multivalued Attributes Apartment Number Street number Area Phone. Street City State Zip code number address Address Phone Address _phone Relation Schemas : Ssn EMPLOYEE EMPLOYEE (Ssn, ...) Address_phone (Address_ID, Ssn, Number Street, Apartment_number City State, Zip Primary key: Address ID Foreign key: Ssn to EMPLOYEE.Ssn Phone (Address ID, Area code, Phone number) Primary key: Address ID, Area code, Phone number Foreign key: Address_ID to Address_phone.Address ID 52" }, { "page_index": 235, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_055.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_055.png", "page_index": 235, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:05+07:00" }, "raw_text": "model mapping Data Step Z: Mapping of N-ary Relationship Types For each N-ary relationship type R, where N > 2, create a new relation S to represent R. Include as foreign key attributes in S the primary keys of the relations that represent the participating entity types Also include any simple attributes of the N-ary relationship type (or simple components of composite attributes) as attributes of S. The primary key of S is usually a combination of all the foreign keys that reference the relations representing the participating entity types. However, if the cardinality constraints on any of the entity types E participating in R is 1, then the primary key of S should not include the foreign key attribute that references the relation E' corresponding to E. 53" }, { "page_index": 236, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_056.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_056.png", "page_index": 236, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:12+07:00" }, "raw_text": "model mapping Data Step Z: Mapping of N-ary Relationship Types Date Content Ssn LogId 1 1 DEVELOPER WRITES LOG 1 Sid SOETWARE Relationship Relation Schemas : DEVELOPER (Ssn, ...) SOFTWARE (Sid, ...) LOG (LogId, ...) WRITES (Ssn, Sid, LogId, Content, Date) Primary key: Ssn, Sid Secondary keys: Ssn, LogId, Sid, LogId Foreign key: Ssn to DEVELOPER.Ssn, Sid to SOFTWARE.Sid, LogId to LOG.LogId Check total participation of DEVELOPER.Ssn, LOG.LogId, and SOFTWARE.Sid in WRITES 54" }, { "page_index": 237, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_057.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_057.png", "page_index": 237, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:18+07:00" }, "raw_text": "model mapping Data Step Z: Mapping of N-ary Relationship Types Date Vin Ssn N 1 VEHICLE SALES CUSTOMER 1 Sid SALESPERSON Relationship Relation Schemas: VEHICLE (Vin, ...) SALESPERSON (Sid, ... CUSTOMER (Ssn, ...) SALES (Vin, Sid, Ssn, Date Primary key : Vin, Sid Secondary key: Vin, Ssn Foreign key: Vin to VEHICLE.Vin, Sid to SALESPERSON.Sid, Ssn to CUSTOMER.Ssn Check total participation of CUSTOMER.Ssn in SALES 55" }, { "page_index": 238, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_058.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_058.png", "page_index": 238, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:24+07:00" }, "raw_text": "model mapping Data Step Z: Mapping of N-ary Relationship Types Date Ssn Name N M STAR CONTRACTS MOVIE 1 Sid STUDIO Relationship Relation Schemas: STAR (Ssn, ...) MOVIE (Name, ...) STUDIO (Sid, ...) CONTRACTS (Ssn, Name, Sid, Date) Primary key: Ssn, Name Foreign key: Ssn to Star.Ssn, Name to MOVIE.Name, Sid to STUDIO.Sid Check total participation of MOVIE.Name in CONTRACTS 56" }, { "page_index": 239, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_059.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_059.png", "page_index": 239, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:30+07:00" }, "raw_text": "model mapping Data Step Z: Mapping of N-ary Relationship Types Quantity Sname Proi name N M SUPPLIER SUPPLY PROJECT K Part no PART Relationship Relation Schemas : SUPPLIER (Sname, ...) PROJECT (Proi name, ...) PART (Part_no, ...) SUPPLY (Sname, Proj name, Part_no, Quantity) Primary key: Sname, Proi name, Part no Foreign key: Sname to SUPPLIER.Sname, Proj_name to PROJECT.Proj_name, Part_no to PART.Part_no 57" }, { "page_index": 240, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_060.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_060.png", "page_index": 240, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:35+07:00" }, "raw_text": "model mapping Data Step 8: Mapping of Specialization or Generalization Convert each specialization with m subclasses {S1, S2, ..., Sm} and (generalized) superclass C, where the attributes of C are {k, a1, ..., an} and k is the (primary) key, into relation schemas : Multiple relations - one relation for superclass and one relation for each subclass Any specialization/ generalization Multiple relations - one relation for each subclass (total) Every entity in the superclass must belong to (at least) one of the subclasses. Single relation with one type attribute Subclasses are disjoint. Single relation with mu/tip/e type attributes each of which corresponds to each subclass Subclasses are overlapping (but able if disjoint) 58" }, { "page_index": 241, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_061.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_061.png", "page_index": 241, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:42+07:00" }, "raw_text": "model mapping Data Fname Minit Lname Name Ssn Birth date Address Job_type EMPLOYEE Job_type d Secretary Engineer lyping_speed Tgrade Eng_type Technician SECRETARY TECHNICIAN ENGINEER EMPLOYEE Ssn Fname Minit Lname Birth_date Address Job_type SECRETARY TECHNICIAN ENGINEER Ssn Ssn Tgrade Ssn Typing_speed Eng_type 59 Using Multiple relations - Superclass and subclasses" }, { "page_index": 242, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_062.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_062.png", "page_index": 242, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:48+07:00" }, "raw_text": "CAR Vehicleld LicensePlateNo Price MaxSpeed NoOfPassengers TRUCK Vehicleld LicensePlateNo Price NoOfAxles Tonnage Secondary key (UNIQUE, NOT NULL): LicensePlateNo Using Multiple relations - Subclass relations only (total) (b) LicensePlateNo Price Vehicleld Generalization VEHICLE Source: [1] What if using Multiple relations - Superclass and subclasses? d NoOfPassengers NoOfAxles Tonnage MaxSpeed CAR TRUCK" }, { "page_index": 243, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_063.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_063.png", "page_index": 243, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:15:54+07:00" }, "raw_text": "model mapping Data VEHICLE (Vehicle_id, License_plate_no, Price) Secondary key (UNIQUE, NOT NULL): License_plate_no CAR (Vehicle id, Max_speed, No_of_passengers) TRUCK (Vehicle id, No_of_axles, Tonnage) Foreign key (of CAR,TRUCK): Vehicle_id to VEHICLE.Vehicle_id Check total specialization of VEHICLE.Vehicle_id in CAR and TRUCK Using Multiple relations - Superclass and Subclasses (tota/) Generalization Vehicle_id License_plate_no Source: [1] Price VEHICLE What if using Multiple relations - Superclass and subclasses? No_of_passengers No_of_axles Max_speed Tonnage CAR TRUCK 61" }, { "page_index": 244, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_064.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_064.png", "page_index": 244, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:00+07:00" }, "raw_text": "model mapping Data Fname Minit Lname Name Ssn Birth_date Address Job_type EMPLOYEE Job_type d Secretary Engineer lyping_speed Tgrade Eng_type Technician SECRETARY TECHNICIAN ENGINEER EMPLOYEE Ssn Fname Minit Lname Birth_date Address Job_type Typing_speed Tgrade Eng_type Using a Single relation with one type attribute (disjoint) 62" }, { "page_index": 245, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_065.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_065.png", "page_index": 245, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:05+07:00" }, "raw_text": "PartNo Description PART ManufactureDate SupplierName DrawingNo BatchNo ListPrice MANUFACTURED_PART PURCHASED PARI PART PartNo Description MFlag DrawingNo ManufactureDate BatchNo PFlag SupplierName ListPrice Using a Single relation with multiple type attributes with Boolean fields MFlag and PFlag. Source: [1] 63" }, { "page_index": 246, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_066.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_066.png", "page_index": 246, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:10+07:00" }, "raw_text": "model mapping Data CAR Engine_size Vin Price VEHICLE TRUCK Tonnage d Model SUV No_seats Describe specialization/ generalization in this example. Using different options to map this example into relation schemas 64" }, { "page_index": 247, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_067.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_067.png", "page_index": 247, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:16+07:00" }, "raw_text": "model mapping Data CAR Engine_size Vin Price VEHICLE TRUCK Tonnage Model SUV No_seats Using multiple relations - superclass and subclasses VEHICLE (Vin, Model, Price) CAR (Vin, Engine_size) TRUCK (Vin, Tonnage) SUV (Vin, No_seats) Foreign key (of CAR, TRUCK, SUV): Vin to VEHICLE.Vin Check total specialization of VEHICLE.Vin in CAR, TRUCK, and SUV 65" }, { "page_index": 248, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_068.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_068.png", "page_index": 248, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:22+07:00" }, "raw_text": "model mapping Data CAR Engine_size Vin Price VEHICLE d TRUCK Tonnage Model SUV No_seats Using multiple relations - subclasses only (total) CAR (Vin, Engine_size, Model, Price) TRUCK (Vin, Tonnage, Model, Price SUV (Vin, No_seats, Model, Price) 66" }, { "page_index": 249, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_069.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_069.png", "page_index": 249, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:28+07:00" }, "raw_text": "model mapping Data CAR Engine_size Vin Price VEHICLE TRUCK Tonnage d Model SUV No_seats Using a single relation with one type attribute (disjoint) Vehicle (Vin, Model, Price, VehicleType, Engine_size, Tonnage, No_seats) 67" }, { "page_index": 250, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_070.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_070.png", "page_index": 250, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:32+07:00" }, "raw_text": "model mapping Data CAR Engine_size Vin Price VEHICLE TRUCK Tonnage d Model SUV No seats Using a single relation with multiple attributes. Why not? Vehicle (Vin, Model, Price, CarType, TruckType, SuVType, Engine_size, Tonnage, No_seats Vehicle (Vin, Model, Price, CarType, TruckType, SuVType, Engine_size, Tonnage, No_seats VehicleType 68" }, { "page_index": 251, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_071.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_071.png", "page_index": 251, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:39+07:00" }, "raw_text": "model mapping Data Step 9: Mapping of Union Types (Categories) For mapping a category whose defining different keys, it is customary superclasses have (traditional) to specify a new key attribute, called a surrogate key, when creating a relation to correspond to the category. Include the surrogate key attribute as foreign key in each relation corresponding to a superclass of the category, to specify the correspondence in values between the surrogate key and the key of each superclass. For a category whose superclasses have the same key, there is no need for a surrogate key. 69" }, { "page_index": 252, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_072.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_072.png", "page_index": 252, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:16:50+07:00" }, "raw_text": "Two categories (union types) : Bname Baddress OWNER and REGISTERED VEHICLE BANK Source: [1] Driver_license_no Name Address Cname Caddress PERSON Ssn PERSON COMPANY Ssn Driver_license_no Name Address Owner_id BANK Bname Baddress Owner_id OWNER COMPANY Lien_or_regular Cname Caddress Owner_id M OWNER Owner_id OWNS Purchase_date REGISTERED_VEHICLE N License_plate_no License_plate_number REGISTERED_VEHICLE CAR Vehicle_id Cstyle Cmake Cmodel Cyear License_plate_number TRUCK U Vehicle_id Vehicle_id Vehicle_id Tmake Tmodel Tonnage Tyear License_plate_number Cstyle Tonnage OWNS Cmake CAR TRUCK Tmake Owner_id License_plate_number Purchase_date Lien_or_regular Cyear Tyear Mapping the EER categories Cmodel Tmodel 70 Source: [1]" }, { "page_index": 253, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_073.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_073.png", "page_index": 253, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:00+07:00" }, "raw_text": "Two categories (union types) : Bname Baddress OWNER and REGISTERED VEHICLE BANK Source: [1] Driver_license_no Name Address Cname Caddress PERSON Ssn PERSON COMPANY Ssn Driver_license_no Name Address Owner_id BANK Bname Baddress Owner_id OWNER COMPANY Cname Lien_or_regular Caddress Owner_id M Owner id, Owner_type OWNER Owner_id OWNS Purchase_date REGISTERED VEHICLE License plate number, Vehicle_type N License_plate_no License_plate_number REGISTERED_VEHICLE CAR Vehicle_id Cstyle Cmake Cmodel Cyear License_plate_number TRUCK Vehicle_id Vehicle_id Vehicle_id Tmake Tmodel Tonnage Tyear License_plate_number Cstyle Tonnage OWNS Cmake CAR TRUCK Tmake Owner_id License_plate_number Purchase_date Lien_or_regular Cyear Tyear Mapping the EER categories Cmodel Tmodel 71 Source: [1]" }, { "page_index": 254, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_074.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_074.png", "page_index": 254, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:09+07:00" }, "raw_text": "The Entity-Relationship diagram for the CONFERENCE F REVIEW database 1 M contact Title email id Abstract N M Author of Paper File name technical Comment readability First Last merit scale M to scale name name committee Map this conceptual originality Written Scale review scale schema into a comment relevance relational database scale N Feedback Constraints : overall to author recommendation A contact author is one of the authors of the paper. Each paper is reviewed by 2-4 email Reviewer reviewers. topics Scales in [1,10] overall recommendation in First Last Phone Affiliation 72 {accept, reject} name name number" }, { "page_index": 255, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_075.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_075.png", "page_index": 255, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:17+07:00" }, "raw_text": "Data Modeling COffice Rank lOffice CName CPhone Id IName IPhone Mapping 1 1 COLLEGE DEAN INSTRUCTOR Given an ER CStartDate 1 1 CHAIR 1 ADMINS schema of a MName N N FName LName 1 EMPLOYS University Sld SName DName DOB Addr DCode 1 N DEPT HAS STUDENT Phone database, map DOffice Major DPhone 1 this schema 1 M Grade TEACHES OFFERS TAKES Into a relational N N N database Secld CCode N 1 COURSE SECS SECTION SecNo Credits schema. Sem CoName DaysTime Year CDesc CRoom Level Bldg RoomNo Constraint.atleast 5 students per section A University database schema Source: [1]" }, { "page_index": 256, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_076.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_076.png", "page_index": 256, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:26+07:00" }, "raw_text": "The EER diagram for the ONLINE_AUCTION database system in which members (buyers and sellers) participate in the sale of items bid price time of bid N M bid number N belongs member number item to M Class shipping bank name address account routing M Class number 1 buyer seller place N M rate superclass subclass M seller's upper feedback of comment transaction rate buyer's N feedback comment winner Map this conceptual schema into a relational database schema 74" }, { "page_index": 257, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_077.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_077.png", "page_index": 257, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:33+07:00" }, "raw_text": "A SMALL AIRPORT Salary Shift database schema Model Capacity Weight M N WORKS_ON EMPLOYEE Source: [1] N PLANE_TYPE MAINTAIN Map this Restr Lic_num conceptual schema M M N FLIES PILOT into a relational OF_TYPE Date Workcode database schema N Date/workcode SERVICE Hours Reg# N 1 AIRPLANE PLANE_SERVICE N Pdate STORED_IN OWNS OWNER M N HANGAR CORPORATION Ssn PERSON Number Location Name Phone Name Phone Capacity Address Address 75" }, { "page_index": 258, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_078.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_078.png", "page_index": 258, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:44+07:00" }, "raw_text": "Address Phone The LIBRARY SYSTEM database PhoneAddress Name Location Type EstablishedYear ContactAddress School 1 1 U Organization PrivateLibrary PublicLibrary - has N 1 belong to TrainingCenter d Name Name RegistrationDate BusinessArea Ordering Address Phone Number Name Affiliation Code ISBN Title NoOfCopies N 1 N N M Author Book Library LibraryBranch ID has available at belong to Summary Categories Keywords N BranchName N M Year publish Borrowed Publication DueDate 1 Date Edition loan K CardNo Name First Publisher ReturnedDate Borrower Address Name Middle 1 RegistrationDate has Last Phone Address N ExpiredDate Phone Validity Type Constraints and Domain Assumptions : JobTitle 1. School.Type in {primary, secondary, high-school, university} 2. Each library branch has at least two copies per book. Map this conceptual 3. Book.Code is composed of 12 digits. 4. DueDate - BorrowedDate = a month. schema into a relational 5. The maximum number of books that a borrower can borrow from a library branch is 5 for any date 6. If a borrower returns more than 3 books late, his/ her card becomes invalid. database schema 7. Year, Edition, EstablishedYear are positive integers. 8. TrainingCenter.RegistrationDate, BorrowedDate, DueDate, ReturnedDate, Validity.RegistrationDate, ExpiredDate are DATE values. 9. 76 The rest including the attributes not mentioned above are STRING values." }, { "page_index": 259, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_079.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_079.png", "page_index": 259, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:51+07:00" }, "raw_text": "A sample database application COMPANY The COMPANY database keeps track of a company's employees, departments, and projects. Suppose that after the requirements collection and analysis phase, the database designers provide the following description of the miniworld that will be represented in the database : - The company is organized into departments. Each department has a unique name, a unique number, and a particular employee who manages the department. We keep track of the start date when that employee began managing the department. A department may have several locations. - A department controls a number of projects, each of which has a unique name, a unique number, and a single location. - The database will store each employee's name, Social Security number (SsN address, salary, sex (gender), and birth date. An employee is assigned to one department, but may work on several projects, which are not necessarily controlled by the same department. It is required to keep track of the current number of hours per week that an employee works on each project, as well as the direct supervisor of each employee (who is another employee)- - The database will keep track of the dependents of each employee for insurance purposes, including each dependent's first name, sex, birth date, and relationship to the employee 77" }, { "page_index": 260, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_080.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_080.png", "page_index": 260, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:17:58+07:00" }, "raw_text": "Fname Minit Lname Bdate Name Address Salary Ssn Sex Locations N WORKS_FOR Name Number EMPLOYEE Start_date Number_of_employees DEPARTMENT MANAGES CONTROLS Hours N M N WORKS ON PROJECT Supervisor Supervisee N Name SUPERVISION Location Number DEPENDENTS OF N DEPENDENT An ER schema for the COMPANY database Source: [1] Name Sex Birth_date Relationship 78" }, { "page_index": 261, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_081.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_081.png", "page_index": 261, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:18:03+07:00" }, "raw_text": "EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno DEPARTMENT Dname Dnumber Mgr_ssn Mgr_start_date DEPT_LOCATIONS Dnumber Dlocation PROJECT Pname Pnumber Plocation Dnum WORKS_ON Essn Pno Hours DEPENDENT Essn Dependent_name Sex Bdate Relationship 79" }, { "page_index": 262, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_082.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_082.png", "page_index": 262, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:18:11+07:00" }, "raw_text": "CREATE SCHEMA COMPANY : c CREATE TABLE EMPLOYEE FNAME VARCHAR(15) NOT NULL , MINIT CHAR , VARCHAR(15) LNAME NOT NULL CHAR(9) , SSN BDATE DATE , VARCHAR(30) , ADDRESS SEX CHAR , DECIMAL(10,2) , SALARY CHAR(9) , SUPER SSN DNO INT NOT NULL , (SSn) , PRIMARY KEY (SUPER_SSN) (SSN) FOREIGN KEY REFERENCES EMPLOYEE ) ; TABLE C CREATE DEPENDENT CHAR(9) ESSN VARCHAR(15) , DEPENDENT NAME SEX CHAR , BDATE DATE , VARCHAR(8) , RELATIONSHIP KEY (ESSN DEPENDENT_NAME) PRIMARY KEY (ESSN) (SSn) FOREIGN REFERENCES EMPLOYEE ) ; 80" }, { "page_index": 263, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_083.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_083.png", "page_index": 263, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:18:18+07:00" }, "raw_text": "C CREATE TABLE DEPARTMENT DNAME VARCHAR(15) NOT NULL , DNUMBER INT , MGRSSN CHAR(9) NOT NULL MGRSTARTDATE DATE PRIMARY KEY (DNUMBER) (DNAME) , UNIQUE KEY (MGR_SSN) (SSN) FOREIGN REFERENCES EMPLOYEE ) ; CREATE TABLE DEPT LOCATIONS DNUMBER INT , VARCHAR(15) , DLOCATION PRIMARY KEY CDNUMBER DLOCATION) FOREIGN KEY (DNUMBER REFERENCES DEPARTMENT(DNUMBER) ) ; ALTER TABLE EMPLOYEE ADD FOREIGN KEY (DNO) REFERENCES DEPARTMENT (DNUMBER) ; 81" }, { "page_index": 264, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_084.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_084.png", "page_index": 264, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:18:26+07:00" }, "raw_text": "CREATE TABLE PROJECT VARCHAR(15) PNAME NOT NULL INT, PNUMBER VARCHAR(15) , PLOCATION DNUM INT NOT NULL (PNUMBER) , PRIMARY KEY UNIQUE (PNAME) , FOREIGN KEY (DNUM) REFERENCES DEPARTMENT (DNUMBER) ) ; CREATE TABLE WORKS_ON CHAR(9) , ESSN PNO INT, DECIMAL(3,1), HOURS PNO) , PRIMARY KEY (ESSN, KEY ESSN) (SSn) , FOREIGN REFERENCES EMPLOYEE FOREIGN KEY (PNO) REFERENCES PROJECT (PNUMBER) ) ; 82" }, { "page_index": 265, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_085.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_085.png", "page_index": 265, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:18:47+07:00" }, "raw_text": "EMPLOYEE The COMPANY Fname Mnit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren,Houston,TX M 30000 333445555 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston,TX M 40000 888665555 5 database Alicia Zelaya 999887777 1968-01-19 3321 Caste,Spring,TX F 25000 987654321 4 Jennifer s Wallace 987654321 1941-06-20 291 Berry,Beaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak,Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 1981-06-19 5 888665555 Bellaire 5 Sugarland 5 Houston WORKS_ON PROJECT Essn Pno Hours Pname Phumber Plocation Dnum 123456789 1 32.5 ProductX 1 Bellaire 5 123456789 2 7.5 ProductY 2 Sugarand 5 666884444 40.0 ProductZ 3 Houston 5 453453453 1 20.0 Computerization 10 Stafford 4 453453453 2 20.0 Reorganization 20 Houston 1 333445555 2 10.0 Newbenefits 30 Stafford 4 333445555 3 10.0 333445555 10 10.0 DEPENDENT 333445555 20 10.0 Essn Dependent_name Sex Bdate Relationship 999887777 30 30.0 333445555 Alice F 1986-04-05 Daughter 999887777 10 10.0 333445555 Theodore M 1983-10-25 Son 987987987 10 35.0 333445555 Joy F 1958-05-03 Spouse 987987987 30 5.0 987654321 Abner M 1942-02-28 Spouse 987654321 30 20.0 123456789 Michael M 1988-01-04 Son 987654321 20 15.0 123456789 Alice F 1988-12-30 Daughter Source: [1] 83 888665555 20 NULL 123456789 Elizabeth E 1967-05-05 Spouse" }, { "page_index": 266, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_086.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_086.png", "page_index": 266, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:00+07:00" }, "raw_text": "Part of the COMPANY database EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456788 1965-01-08 731Fondren,Houston,TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston.TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321Caste,Spring.TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291Berry,BeaireTX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975FireOak,Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-28 980Daas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 How to populate data into a relational database? How to remove data from a relational database? How to modify data in a relational database? How to extract data from a relational database? How to maintain the consistency of a relational database with respect to its constraints? 84" }, { "page_index": 267, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_087.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_087.png", "page_index": 267, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:06+07:00" }, "raw_text": "Relational Algebra The The relational algebra is the formal language for the relational data model. Operations to specify basic retrieval requests as relational algebra expressions, reflecting how a request is resolved A relational algebra expression produces a relation that represents the result of a query (or retrieval request) . Why is the relational algebra studied? It provides a formal foundation for relational model operations. It is used as a basis for implementing and optimizing queries in the query processing and optimization modules of relational database management systems (RDBMSs Some of its concepts are incorporated into the SQL standard query language for RDBMSs. The core operations and functions in the internal modules of most RDBMSs are based on relational algebra operations. Internal representation of a query is a query tree based on its corresponding relational algebra expressions. 85" }, { "page_index": 268, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_088.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_088.png", "page_index": 268, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:12+07:00" }, "raw_text": "Relational Algebra The The Relational Algebra The basic set of operations that specify basic retrieval requests The result of each operation is a new relation that has been formed from one or many relations. As a relation, it can be then used as an input of other operations. Evaluation is from the inner to the outer of an operation sequence Operations : Unary > relation' relation - operator * 0 X, Outer joins: X X X relation1 Binary X > relation' Semi-join: operator Anti-join : X relation2 o U, N, -, : , Rename: p 86" }, { "page_index": 269, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_089.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_089.png", "page_index": 269, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:21+07:00" }, "raw_text": "OPERATION PURPOSE NOTATION SELECT Selects all tuples that satisfy the selection condition from a relation R. PROJECT Produces a new relation with only some of the attrib- Tattribute list> (R) utes of R, and removes duplicate tuples. Produces all combinations of tuples from R and R2 Rr THETA JOIN that satisfy the join condition. EQUIJOIN Produces all the combinations of tuples from R, and R 4 R, that satisfy a join condition with only equality R4 (). comparisons. NATURAL JOIN Same as EQUIJOIN except that the join attributes of R, are not included in the resulting relation; if the join OR R* (). attributes have the same names, they do not have to be specified at all. ORR*R UNION Produces a relation that includes all the tuples in R. Rj U R2 or R, or both R, and R,; R, and R, must be union compatible. INTERSECTION Produces a relation that includes all the tuples in both RR R, and R,; R, and R, must be union compatible. DIFFERENCE Produces a relation that includes all the tuples in R. R-R2 that are not in R,; R, and R, must be union compatible. CARTESIAN Produces a relation that has the attributes of R, and R, X R, R, and includes as tuples all possible combinations of PRODUCT tuples from R and R DIVISION Produces a relation R(X) that includes all tuples t[X] R(Z)+R,(Y) in R,(Z) that appear in R, in combination with every 87 tuple from R,(Y),where Z = X U Y." }, { "page_index": 270, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_090.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_090.png", "page_index": 270, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:24+07:00" }, "raw_text": "Relational Algebra The A Complete Set of Relational Algebra Operations : {o, T, U, P, -, x} 0 = select 0 t = project U = union minus s (difference) x = Cartesian product" }, { "page_index": 271, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_091.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_091.png", "page_index": 271, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:29+07:00" }, "raw_text": "Relational Algebra The The RENAME operator: p (rho), a unary operator applied to a relation R (A1, A2, ..., An) of degree n to rename either the relation name or the attribute names, or both Change relation name: ps(R) Example 1: Employee (ssN, Fname, Lname, Dno) is changed to: Emp (SsN, Fname, Lname, Dno) PEmp(Employee) Example 2: Employee (ssN, Fname, Lname, Dno) is changed to: Employee (ssNumber, F_name, L_name, Dnumber) Example 3: Employee (ssN, Fname, Lname, Dno) is changed to. Emp (SsNumber, F_name, L_name, Dnumber)" }, { "page_index": 272, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_092.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_092.png", "page_index": 272, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:44+07:00" }, "raw_text": "Relational Algebra The Retrieve the tuples in relation R that satisfy . EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731Fondren.Houston.TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston,TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291Berry,Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak.Humble.TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 Retrieve all the information of each employee who is with department 4 and salary > 25000 or with department 5 and salary > 30000. Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno Franklin T Wong 333445555 1955-12-08 638 Voss,Houston.TX M 40000 888665555 5 Jennifer S Wallace 987654321 1941-06-20 291Berry,Bellaire,TX F 43000 888665555 4 88 Ramesh K Narayan 666884444 1962-09-15 975Fire Oak.Humble.TX M 38000 333445555 5" }, { "page_index": 273, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_093.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_093.png", "page_index": 273, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:19:50+07:00" }, "raw_text": "Relational Algebra The Retrieve the tuples in relation R that satisfy . (same attributes) as R. A cascade (sequence) of SELEcT operations in any order: 0(o >(R) SELECT is commutative: The number of tuples in the result of SELECT is Iess than or equal to the number of tuples in the input relation R Retrieve all the information of each employee who is with department 4 and salary > 25000. 89" }, { "page_index": 274, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_094.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_094.png", "page_index": 274, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:03+07:00" }, "raw_text": "Relational Algebra The (R) Return a relation of distinct tuples from relation R with the attributes listed in EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren.Houston.TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston,TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291Berry,Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak.Humble.TX M 38000 333445555 5 Ssn Joyce A Bdate Dno English 453453453 1972-07 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03 123456789 1965-01-09 5 25000 987654321 4 E Borg 333445555 1955-12-08 5 James 888665555 1937-11 55000 NULL 1 999887777 1968-01-19 4 Retrieve Ssn, date of birth 987654321 1941-06-20 4 TDno (EMPLOYEE) and department number of 666884444 1962-09-15 5 Dno each employee. 453453453 1972-07-31 5 5 987987987 1969-03-29 4 4 888665555 1937-11-10 1 90 1" }, { "page_index": 275, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_095.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_095.png", "page_index": 275, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:11+07:00" }, "raw_text": "Relational Algebra The CARTESIAN PRODUCT (CROSS JOIN) : R X S Produce a new relation T by combining every member (tuple) from one relation (set) with every member (tuple) from the other relation (set) Degree of T = Degree of R + Degree of S o Cardinality of T =Tl =R*1Sl DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 5 888665555 1981-06-19 Bellaire 5 Sugarland 5 Houston Return all the combinations of departments and their locations. DEPARTMENT X DEPT LOCATIONS? 91" }, { "page_index": 276, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_096.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_096.png", "page_index": 276, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:26+07:00" }, "raw_text": "Relational Algebra The DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-0522 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 888665555 1981-06-19 Bellaire 5 Sugarland 5 Houston DEPARTMENT x DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Research 5 333445555 1988-05-22 4 Stafford Research 5 333445555 1988-05-22 5 Bellaire Research 5 333445555 1988-05-22 5 Sugarland Research 5 333445555 1988-05-22 5 Houston Administration 4 987654321 1995-01-01 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Administration 4 987654321 1995-01-01 5 Bellaire Administration 4 987654321 1995-01-01 5 Sugarland Administration 4 987654321 1995-01-01 5 Houston Headquarters 1 888665555 1981-06-19 1 Houston Headquarters 1 888665555 1981-06-19 4 Stafford Headquarters 1 888665555 1981-06-19 5 Bellaire Headquarters 1 888665555 1981-06-19 5 Sugarland 92 Headquarters 1 888665555 1981-06-19 5 Houston" }, { "page_index": 277, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_097.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_097.png", "page_index": 277, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:33+07:00" }, "raw_text": "Relational Algebra The S Produce a new relation Q with n + m attributes Q (A1, Az ... , An, B1, Bz, ... , Bm in that order; Q has one tuple for each combination of tuples-one from R (A1, A2, ... , An) and one from S (B1, Bz, ... , Bm)-whenever the combination satisfies the join condition. (R x S) DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 1988-05-22 1 333445555 Houston Administration 4 4 987654321 1995-01-01 Stafford Headquarters 1 5 888665555 1981-06-19 Bellaire 5 Sugarland 5 Houston Return all the combinations of Research department with Houston location. 93" }, { "page_index": 278, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_098.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_098.png", "page_index": 278, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:46+07:00" }, "raw_text": "Relational Algebra The DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 888665555 1981-06-19 Bellaire Sugarland DEPARTMENT x DEPT_LOCATIONS 5 Houston Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Research 5 333445555 1988-05-22 4 Stafford Research 5 333445555 1988-05-22 5 Bellaire Research 5 333445555 1988-05-22 5 Sugarland Research 333445555 1988-05-22 5 Houston Administration 4 987654321 1995-01-01 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Administration 4 987654321 1995-01-01 5 Bellaire Administration 4 987654321 1995-01-01 5 Sugarland Administration 4 987654321 1995-01-01 5 Houston Headquarters 1 888665555 1981-06-19 1 Houston Headquarters 1 888665555 1981-06-19 4 Stafford Headquarters 1 888665555 1981-06-19 5 Bellaire Headquarters 1 888665555 1981-06-19 5 Sugarland 94 Headquarters 1 888665555 1981-06-19 5 Houston" }, { "page_index": 279, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_099.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_099.png", "page_index": 279, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:20:55+07:00" }, "raw_text": "Relational Algebra The DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Dnumber Dlocation Mgr_start_cate Research 5 1 333445555 1988-05-22 Houston 4 4 Administration 987654321 1995-01-01 Stafford Headquarters 1 5 888665555 1981-06-18 Bellaire 5 Sugarland 5 Houston Return all the combinations of Research department with Houston location Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Research 5 333445555 1988-05-22 5 Houston 95" }, { "page_index": 280, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_100.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_100.png", "page_index": 280, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:02+07:00" }, "raw_text": "Relational Algebra The o EQUIJOIN: THETA JOIN with equality (= comparisons only. S = 0 A=B R (R x S), where A are attributes A=B in R and B are attributes in S. DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Administration 4 4 987654321 199501-01 Stafford 1 6 Headquarters 1981-06-19 Bellaire 888665555 5 Sugarland 5 Houston Retrieve all the information of each department and its locations DEPT LOCATIONS? 96" }, { "page_index": 281, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_101.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_101.png", "page_index": 281, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:16+07:00" }, "raw_text": "DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 1 333445555 1988-05-22 Houston Administration 4 4 987654321 1995-01-01 Stafford 6 Headquarters 1 Bellaire 888665555 1981-06-19 6 Sugarland 6 Houston Retrieve all the information of each department and its locations. Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 1 Houston Research 5 333445555 1988-05-22 4 Stafford Research 333445555 1988-05-22 S Bellaire Research 333445555 1988-05-22 Sugarland Research 5 333445555 1988-05-22 Houston Administration 4 987654321 1995-01-01 1 Houston Administration 4 987654321 1995-01-01 4 Stafford Administration 4 987654321 1995-01-01 5 Bellaire Administration 4 987654321 1995-01-01 5 Sugarland Administration 4 987654321 1995-01-01 5 Houston Headquarters 1 888665555 1981-06-19 1 Houston Headquarters 1 888665555 1981-06-19 4 Stafford Headquarters 1 888665555 1981-06-19 5 Bellaire Headquarters 1 888665555 1981-06-19 5 Sugarland 97 Headquarters 1 888665555 1981-06-19 5 Houston" }, { "page_index": 282, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_102.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_102.png", "page_index": 282, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:24+07:00" }, "raw_text": "Relational Algebra The DEPARTMENT DEPT_LOCATIONS Dname Dnumber Dnumber Dlocation Mgr_ssn Mgr_start_date 5 1 Research 333445555 1988-05-22 Houston 4 4 Administration 987654321 1995-01-01 Stafford 1 5 Headquarters 888665555 1981-0619 Bellaire 5 Sugarland 5 Houston Retrieve all the information of each department and its locations. Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 5 Bellaire Research 5 333445555 1988-05-22 5 Sugarland Research 5 333445555 1988-05-22 5 Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 888665555 1981-06-19 1 Houston 98" }, { "page_index": 283, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_103.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_103.png", "page_index": 283, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:33+07:00" }, "raw_text": "Relational Algebra The NATURAL JOIN : EQUIJOIN I by getting rid of the second attribute in an equality condition when the two join attributes (or each pair of join attributes) have the same name in both relations * s DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1 1988-05-22 Houston Administration 4 4 987654321 199501-01 Stafford Headquarters 1 5 888665555 1981-06-19 Bellaire 5 Sugarland 5 Houston Retrieve all the information of each department and its locations DEPARTMENT * DEPT LOCATIONS? 99" }, { "page_index": 284, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_104.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_104.png", "page_index": 284, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:45+07:00" }, "raw_text": "DEPARTMENT DEPT_LOCATIONS Dname Dnumber Mgr_ssn Dnumber Mgr_start_date Dlocation Research 5 1 333445555 1988-05-22 Houston 4 4 Administration 987654321 1995-01-01 Stafford 1 5 Headquarters 888665555 1981-06-18 Bellaire Sugarland 5 Houston Retrieve all the information of each department and its locations. Dname Dnumber Mgr_ssn Mgr_start_date Dnumber Dlocation Research 5 333445555 1988-05-22 S Bellaire Research 5 333445555 1988-05-22 5 Sugarland Research 5 333445555 1988-05-22 S Houston Administration 4 987654321 1995-01-01 4 Stafford Headquarters 1 888665555 1981-06-19 1 Houston Retrieve all the information of each department and its locations DEPARTMENT * DEPT_LOCATIONS Dname Dnumber Mgr_ssn Mgr_start_date Dlocation Research 5 333445555 1988-05-22 Bellaire From Research 5 333445555 1988-05-22 Sugarland equijoin to Research 5 333445555 1988-05-22 Houston Administration 4 987654321 1995-01-01 Stafford natural join Headquarters 1 888665555 1981-06-19 Houston 100" }, { "page_index": 285, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_105.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_105.png", "page_index": 285, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:50+07:00" }, "raw_text": "Relational Algebra The OUTER JOIN: A set of operations, called outer joins, can be used when we want to keep all the tuples in R, or all those in S, or all those in both relations in the result of the JOIN, regardless of whether or not they have matching tuples in the other relation. Left outer join, right outer join, full outer join The join operations where only matching tuples are kept in the result are called inner joins. Theta join, equijoin, natural join 101" }, { "page_index": 286, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_106.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_106.png", "page_index": 286, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:21:56+07:00" }, "raw_text": "Relational Algebra The o LEFT OUTER JOIN: R XS In addition to the result of the corresponding inner join, the LEFT OUTER JOIN operation keeps every tuple in the first, or left, relation R in R S; if no matching tuple is found in S, then the attributes of S in the join result are filled or \"padded\" with null values. Return the information of all the employees and their departments that they manage EMPLOYEE DEPARTMENT Ssn = Mgr_ssn Return the information of all the employees and their departments that they manage if any X EMPLOYEE ssn = Mgr_ssn l DEPARTMENT 102" }, { "page_index": 287, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_107.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_107.png", "page_index": 287, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:10+07:00" }, "raw_text": "Relational Algebra The EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren,Houston,TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston,TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291 Berry, Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak,Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas, Houston, TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 DEPARTMENT Dname Dnumber Mgr_ssn Mgr_start_date Research 5 333445555 1988-05-22 Administration 4 987654321 1995-01-01 Headquarters 1 888665555 1981-06-19 103" }, { "page_index": 288, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_108.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_108.png", "page_index": 288, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:22+07:00" }, "raw_text": "Relational Algebra The Return the information of all the employees and their departments that they manage. EMPLOYEE Fname Minit Lname Ssn Bdat Address Sex Salary Super Dno Dname Dnumber Mgr_ Mgr_ e ssn ssn start_ date Franklin T Wong 33344 1955 638 M 40000 888665 5 Resear 5 3334 1988- 5555 -12- Voss, 555 ch 4555 05-22 08 Houst 5 on, TX Jennifer S Wallace 98765 1941 291 F 43000 888665 4 Admini 4 9876 1995- 4321 -06- Berry 555 stration 5432 01-01 20 Bellair 1 e, TX James E Borg 88866 1937 450 M 55000 NULL 1 Headqu 1 8886 1981- 5555 -11- Stone, aters 6555 06-09 10 Houst 5 on, TX 104" }, { "page_index": 289, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_109.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_109.png", "page_index": 289, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:37+07:00" }, "raw_text": "Relational Algebra The Return the information of all the employees and their departments that they manage if any. X EMPLOYEE Fname Minit Lname Ssn Bdat Address Sex Salary Super_ Dno Dname Dnumber Mgr_ Mgr_ e ssn ssn start_ date Franklin T Wong 3334 1955 638 M 40000 888665 5 Resear 5 3334 1988- 4555 -12- Voss, 555 ch 4555 05-22 5 08 Houst 5 on, TX Jennifer S Wallace 9876 1941 291 F 43000 888665 4 Admini 4 9876 1995- 5432 -06- Berry, 555 stration 5432 01-01 1 20 Bellair 1 e, TX James E Borg 8886 1937 450 M 55000 NULL 1 Headqu 1 8886 1981- 6555 -11- Stone, aters 6555 06-09 5 10 Houst 5 on, TX John B Smith 1234 1965 732 M 30000 333445 5 NULL NULL NULL NULL 5678 -01- Fondre 555 9 09 n, Houst on, TX Alicia j Zelaya 9997 4 NULL NULL NULL NULL 7888 8 Ramesh K Narayan 5 NULL NULL NULL NULL .. Joyce A English 5 NULL NULL NULL NULL .. Ahmad V Jabbar 4 NULL NULL NULL NULL" }, { "page_index": 290, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_110.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_110.png", "page_index": 290, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:42+07:00" }, "raw_text": "Relational Algebra The RIGHT OUTER JOIN : R X S In addition to the result of the corresponding inner join, the RIGHT OUTER JOIN operation keeps every tuple in the second, or right, relation S in RX S; if no matching tuple is found in R, then the attributes of R in the join result are filled or \"padded\" with null values. d FULL OUTER JOIN: R X S In addition to the result of the corresponding inner join, the FULL OUTER JOIN operation keeps every tuple in both the left and the right relations when no matching tuples are found, padding them with null values as needed. 106" }, { "page_index": 291, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_111.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_111.png", "page_index": 291, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:47+07:00" }, "raw_text": "Relational Algebra The T2 SEMI-JOIN: T1 A tuple of T1 is returned as soon as T1.X finds a match with any value of T2.Y without searching for further matches. This is in contrast to finding all possible matches in inner join. Semi-join is generally used for unnesting EXISTS, IN, and ANY subqueries. I can be extended with any conditions. SEMI-JOIN Return the information of all the departments with at /east one employee who has salary > 30000. DEPARTMENT 107" }, { "page_index": 292, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_112.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_112.png", "page_index": 292, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:52+07:00" }, "raw_text": "Relational Algebra The T2 o ANTI JOIN: T1 X = Y A tuple of T1 is returned, only if T1.X does not match with any value of T2.Y. A tuple of T1 is value of T2.Y. Anti-join is used for unnesting NOT EXISTS, NOT IN, and ALL subqueries. ANTI JOIN can be extended with any conditions Return the information of all the employees who do not work in any department which was managed since 1990 EMPLOYEE 108" }, { "page_index": 293, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_113.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_113.png", "page_index": 293, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:22:58+07:00" }, "raw_text": "Relational Algebra The UNION: R U S Union compatibility: R and S has the same degree and each corresponding pair of attributes has the same domain. Produce a new relation that includes all tuples that are either in R or in S or in both R and S. Duplicate tuples are eliminated. RESULT1 U RESULT2 RESULT1 SSN RESULT2 SSN RESULT SSN 123456789 333445555 123456789 333445555 888665555 333445555 666884444 666884444 453453453 453453453 888665555 109" }, { "page_index": 294, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_114.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_114.png", "page_index": 294, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:05+07:00" }, "raw_text": "Relational Algebra The INTERSECTION: R N S Union compatibility: R and S has the same degree and each corresponding pair of attributes has the same domain. Produce a new relation that includes all tuples that are in both R and S. STUDENT FN LN NSTRUCTOR FNAME LNAME Susan Yao John Smith Ramesh Shah Ricardo Browne Johnny Kohler Susan Yao Barbara Jones Francis Johnson Amy Ford Ramesh Shah Jimmy Wang Emest Gilbert STUDENT O INSTRUCTOR FN LN Susan Yao Ramesh Shah 110" }, { "page_index": 295, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_115.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_115.png", "page_index": 295, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:13+07:00" }, "raw_text": "Relational Algebra The DIFFERENCE: R - S Union compatibility: R and s has the same degree and each corresponding pair of attributes has the same domain. Produce a new relation that includes all tuples that are in R but not in S. STUDENT FN LN INSTRUCTOR FNAME LNAME Susan Yao John Smith Ramesh Shah Ricardo Browne Johnny Kohler Susan Yao Barbara Jones Francis Johnson Amy Ford Ramesh Shah Jimmy Wang Emest Gilbert STUDENT - INSTRUCTOR INSTRUCTOR - STUDENT FN LN FNAME LNAME Johnny Kohler John Smith Barbara Jones Ricardo Browne Amy Ford Francis Johnson Jimmy Wang Emest 111 Gilbert" }, { "page_index": 296, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_116.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_116.png", "page_index": 296, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:21+07:00" }, "raw_text": "Relational Algebra The DIVISION: T(Y) = R(Z) S(X), The projects of all employees SSN_PNOS ESSN PNO where X c Z,Y = Z -X 123456789 1 123456789 2 Produce a new relation T each 666884444 3 tuple of which appears in R in 453453453 1 combination with every tuple in S 453453453 2 333445555 2 A relation T(Y) includes a tuple t if 333445555 3 tuples tR appear in R with tR[YI = t, 333445555 10 333445555 20 and with tr[X] = ts for every tuple 999887777 30 ts in S. 999887777 10 987987987 10 DIVISION can be expressed for the 987987987 30 all condition as a sequence of t, x, 987654321 30 987654321 20 and - operations. 888665555 20 Return the employees who worked on Smith's projects all the projects that Smith worked: SMITH.PNOS PNO SSN PNOS % SMITH PNOS 1 2" }, { "page_index": 297, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_117.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_117.png", "page_index": 297, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:29+07:00" }, "raw_text": "Relational Algebra The DIVISION: T(Y) = R(Z) S(X), The projects of all employees SSN_PNOS ESSN PNO where X c Z, Y = Z-X 123456789 1 123456789 2 Produce a new relation T each 666884444 3 tuple of which appears in R in 453453453 1 combination with every tuple in S 453453453 2 333445555 2 T1 = Ty(R) 333445555 3 333445555 10 T2 = Ty(T1 x S - R) 333445555 20 999887777 30 T = T1 - T2 999887777 10 987987987 10 Return the employees who worked on 987987987 30 all the projects that Smith worked : 987654321 30 987654321 20 SSN PNOS : SMITH PNOS 888665555 20 SSNS SSN Smith's projects 123456789 SMITH_PNOS PNO 453453453 1 2" }, { "page_index": 298, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_118.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_118.png", "page_index": 298, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:34+07:00" }, "raw_text": "Relational Algebra The D AGGREGATION : 3 (R) is a list of attributes of R. is a list of ( ) pairs. In each such pair, is one of the allowed aggregate functions-such as SUM, AVERAGE, MAXIMUM, MINIMUM, COUNT- and is an attribute of R. The resulting relation has the grouping attributes plus one attribute for each element in the function list. How many employees work in the company? How many employees work in each department of the company? 114" }, { "page_index": 299, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_119.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_119.png", "page_index": 299, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:46+07:00" }, "raw_text": "Relational Algebra The D AGGREGATION : (R) EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren,Houston,TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss.Houston.TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291 Berry,Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak,Humble.TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 How many employees work in the company? COUNT_Ssn cOUNT Ssn (EMPLOYEE) 8 How many employees work in each department Dno COUNT_Ssn of the company? 5 4 4 3 Dno coUNT Ssn (EMPLOYEE) 1 1 115" }, { "page_index": 300, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_120.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_120.png", "page_index": 300, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:51+07:00" }, "raw_text": "Relational Algebra The PUT THEM ALTOGETHER : 1. Retrieve Ssn, name, and address of the employees who work in department 5. 2. Retrieve Ssn, name, and address of the employees who work in `Research' department. 3. Retrieve Ssn, name, and address of the employees who work in departments in Houston. 4. Return the average salary of the employees who work in department 1. 5. Return the maximum salary of the employees in each department. 6. Return the number of the employees who have salaries greater than the average salary of the employees who work In department 1. 116" }, { "page_index": 301, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_121.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_121.png", "page_index": 301, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:23:56+07:00" }, "raw_text": "Relational Algebra The PUT THEM ALTOGETHER: 7. For every project located in 'Stafford', list the project number, the controlling department number, and the department manager's last name, address, and birth date. 8. Find the names of employees who work on all the projects controlled by department number 5. 9. Make a list of project numbers for projects that involve an employee whose last name is 'Smith', either as a worker or as a manager of the department that controls the project 10. List the names of all employees with two or more dependents in department 5. 11. Retrieve the names of employees who have no dependents. 12. List the names of managers who have at least one dependent. 117" }, { "page_index": 302, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_122.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_122.png", "page_index": 302, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:00+07:00" }, "raw_text": "Summary The relational data model (representational) Relation Tuples Attributes Domains Primary key Constraints Domain constraints Key constraints Constraints on nulls Entity integrity constraints Referential integrity constraints 118" }, { "page_index": 303, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_123.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_123.png", "page_index": 303, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:04+07:00" }, "raw_text": "Summary Data model mapping Step 1: Mapping of Regular Entity Types Step 2: Mapping of Weak Entity Types Step 3: Mapping of Binary 1:1 Relationship Types Step 4: Mapping of Binary 1:N Relationship Types Step 5: Mapping of Binary M:N Relationship Types Step 6: Mapping of Multivalued Attributes Step Z: Mapping of N-ary Relationship Types Step 8: Mapping of Specialization or Generalization Step 9: Mapping of Union Types (Categories) Pay attention to Primary key, Foreign key, and other constraints 119" }, { "page_index": 304, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_124.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_124.png", "page_index": 304, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:10+07:00" }, "raw_text": "Summary The relational algebra The basic set of operations that specify basic retrieval requests The result is a new relation that has been formed from one or many relations. A basis for implementing and optimizing queries in relational database management systems Operations : Unary > relation relation - * operator o X, X Outer joins: XXX relation1 Binary Semi-join X > relation' operator Anti-join : X relation2 o U M, - 0 0 P 120" }, { "page_index": 305, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_125.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_125.png", "page_index": 305, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:14+07:00" }, "raw_text": "Chapter 3: The Relational Data Model uolsn ques wslin questi answel guestion quest questz question 2 estion 121" }, { "page_index": 306, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_126.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_126.png", "page_index": 306, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:21+07:00" }, "raw_text": "Review 1. Given the following examples, which one is a relation and which is not? Why not? If a relation, please specify its keys. iPhone Book ID Model Supplier Name ISBN Year Publisher 1120 8 FPT ABC 12345 2000 ACM 12810 10 DiDong EFGH 45932 2000 IEEE 1120 11pro VTA ABC 28018 2000 Elsevier I2020_12 12 FPT EFHIO 98712 2000 Springer I2020_1 12 TGV Customer Trainee SSN Name Start Contact Name Age Year 12345 NVA 09.20 123921 NVA 18 2000 92012 TTT 01.19 {212921,018271} NDV 20 2001 89213 CVV 02.20 890243 LAV 19 1999 78406 DMT 03.18 {821571, 901823,777890} NDV 20 2001 122" }, { "page_index": 307, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_127.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_127.png", "page_index": 307, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:25+07:00" }, "raw_text": "Review 2. Why are tuples in a relation not ordered? Why are duplicate tuples not allowed in a relation? 3. What is the difference between a key and a superkey? Why do we designate one of the candidate keys of a relation to be the primary key? 4. Discuss the various reasons that lead to the occurrence of NuLL values in relations. 5. Discuss the entity integrity and referential integrity constraints. Give examples for illustration. Why is each considered important? 123" }, { "page_index": 308, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_128.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_128.png", "page_index": 308, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:49+07:00" }, "raw_text": "EMPLOYEE 6. Given a part Fname Mnit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731Fondren.Houston.TX M 30000 333445555 5 of the COMPANY Franklin T Wong 333445555 1955-12-08 63B Voss,Houston.TX M 40000 888665555 5 Alicia Zelaya 999887777 1968-01-19 3321 Castle,Spring,TX F 25000 4 database. 987654321 Jennifer s Wallace 987654321 1941-06-20 291Berry,Beare,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-0915 975 FireOak,Humble,TX M 38000 333445555 5 Discuss all Joyce A English 453453453 1972-07-31 5631RiceHouston.TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980Dallas,HoustonTX M 25000 987654321 4 James E Borg 888665555 1937-11-10 450 Stone,Houston,TX M 55000 NULL 1 integrity DEPARTMENT DEPT_LOCATIONS Dnumber Mgr_ssn Dnumber Dlocation constraints Dname Mgr_start_date Research 5 333445555 1988-05-22 1 Houston Administration 4 987654321 1995-01-01 4 Stafford violated by each Headquarters 1 888665555 1981-06-19 5 Bellaire 5 Sugarland Houston operation 5 WORKS_ON PROJECT Essn Pno Hours Pname Phumber Plocation Dnum provided next, if 123456789 1 32.5 ProductX 1 Bellaire 5 123456789 2 7.5 ProductY 2 Sugarand 5 5 any, and the 666884444 3 40.0 ProductZ 3 Houston 453453453 1 20.0 Computerization 10 Stafford 4 453453453 2 20.0 Reorganization 20 Houston 1 different ways of 333445555 2 10.0 Newbenefits 30 Stafford 4 333445555 3 10.0 enforcing these 333445555 10 10.0 DEPENDENT 333445555 20 10.0 Essn Dependent_name Sex Bdate Relationship 999887777 30 30.0 333445555 Alice F 1986-04-05 Daughter constraints. 999887777 10 10.0 333445555 Theodore M 1983-10-25 Son 987987987 10 35.0 333445555 Joy F 1958-05-03 Spouse 987987987 30 5.0 987654321 Abner M 1942-02-28 Spouse 987654321 30 20.0 123456789 Michael M 1988-01-04 Son 987654321 20 15.0 123456789 Alice F 1988-12-30 Daughter 124 888665555 20 NULL 123456789 Elizabeth E 1967-05-05 Spouse" }, { "page_index": 309, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_129.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_129.png", "page_index": 309, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:24:56+07:00" }, "raw_text": " 6. Discuss all integrity constraints violated by each operation, if any, and the different ways of enforcing these constraints. a. Insert <`Robert' 'F' 'Scott', '943775543', '1972-06-21' '2365 Newcastle Rd, Bellaire, TX', M, 58000, `888665555', 1> int0 EMPLOYEE b. Insert <`ProductA', 4,`Bellaire', 2> into PROJECT. c. Insert <'Production', 4, '943775543', '2007-10-01'> into DEPARTMENT. d. Insert <`677678989', NULL,`40.0'> into WORKS ON e. Insert <`453453453', 'John', `M', '1990-12-12', `spouse'> into DEPENDENT f. Delete the WORKS_ON tuples with Essn = `333445555'. g. Delete the EMPLOYEE tuple with Ssn = `987654321'. h. Delete the PROJECT tuple with Pname = `ProductX'. i. Modify the Mgr_ssn and Mgr_start_date of the DEPARTMENT tuple with Dnumber = 5 to '123456789' and `2007-10-01' respectively j. Modify the Super_ssn attribute of the EMPLOYEE tuple with Ssn = 999887777' to `943775543'. k. Modify the Hours attribute of the WORKS_ON tuple with Essn = `999887777' and Pno = 10 to `5.0'. 125" }, { "page_index": 310, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_130.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_130.png", "page_index": 310, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:01+07:00" }, "raw_text": "Review ER schema of a TEACHING database, map Z. Given an i this schema into a relational database schema. Semester Year M TAUGHT DURING N Lname Sem_year M N INSTRUCTOR OFFERS SEMESTER N M K CAN TEACH OFFERED DURING Cnumber M N COURSE A TEACHING database schema 126 Source: [1]" }, { "page_index": 311, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_131.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_131.png", "page_index": 311, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:08+07:00" }, "raw_text": "Review 8. Given an ER schema Date 0 Time_stamp of a SHIP TRACKING Time SHIP MOVEMENT Longitude database, map this N Latitude schema into a relational HISTORY database schema. Type Tonnage Hull Sname N SHIP TYPE SHIP_TYPE Owner (0;) Start_date End_date N (1,1) SHIP AT HOME PORT PORT VISIT PORT Continent Name (0;) N 1 IN STATE/COUNTRY Name Pname PORT N 1 ON SEA/OCEAN/LAKE 127 Source: [1]" }, { "page_index": 312, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_132.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_132.png", "page_index": 312, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:17+07:00" }, "raw_text": "COffice Rank 1Office Review CName CPhone Id IName IPhone COLLEGE DEAN INSTRUCTOR (1,1) (0,1) 9. Given an ER (0,N) CStartDate (0,1) (0,N) CHAIR 1,1) schema of a ADMINS (1,1) MName FName LName University (1,1) EMPLOYS Sld SName DName (0,N) DOB Addr DCode database, map DEPT HAS STUDENT Phone DOffice (0,N) (0,1) Major DPhone (0,N) this schema (0,N) Grade TEACHES TAKES Into a relational OFFERS database (5,N) (1,1) (1,1) Secld CCode COURSE SECS SECTION SecNo Credits (0,N) (1,1) schema. Sem CoName DaysTime Year CDesc CRoom Level Bldg RoomNo A University database schema Source: [1]" }, { "page_index": 313, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_133.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_133.png", "page_index": 313, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:23+07:00" }, "raw_text": "BOOK Book_id Title Publisher_name Review BOOK AUTHORS Book_idAuthor_name 10. Try to map the relational schema of a LIBRARY PUBLISHER database into an ER Name Address Phone schema. BOOK COPIES This is part of a process Book_id Branch_id No_of_copies known as reverse BOOK LOANS engineering, where a Book_id Branch_id Card_no Date_out Due_date conceptual schema is created for an existing LIBRARY BRANCH Branch_id Branch_name Address implemented database. BORROWER State any assumptions you Card_no Name Address Phone make. 129" }, { "page_index": 314, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_134.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_134.png", "page_index": 314, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:28+07:00" }, "raw_text": "Review 11. Specify the following queries on the COMPANY relational database schema using the relational algebra : a. Retrieve the names of all employees in department 5 who work more than 10 hours per week on the ProductX project. b. List the names of all employees who have a dependent with the same first name as themselves. c. Find the names of all employees who are directly supervised by 'Franklin Wong'. d. For each project, list the project name and the total hours per week (by all employees) spent on that project e. Retrieve the names of all employees who work on every project. f. Retrieve the names of all employees who do not work on any project. g. For each department, retrieve the department name and the average salary of all employees working in that department. h. Retrieve the average salary of all female employees i. Find the names and addresses of all employees who work on at least one project located in Houston but whose department has no location in Houston. j. List the last names of all department managers who have no dependents. 130" }, { "page_index": 315, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_135.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_135.png", "page_index": 315, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:35+07:00" }, "raw_text": "Review 12. Specify the following queries on the LIBRARY relational 0 database schema in Question 10 using the relational algebra: a. How many copies of the book titled The Lost Tribe are owned by the library branch whose name is 'Sharpstown'? b. How many copies of the book titled The Lost Tribe are owned by each library branch? c. Retrieve the names of all borrowers who do not have any books checked out. d. For each book that is loaned out from the Sharpstown branch and whose Due_date is today, retrieve the book title, the borrower's name, and the borrower's address. e. For each library branch, retrieve the branch name and the total number of books loaned out from that branch. f. Retrieve the names, addresses, and number of books checked out for all borrowers who have more than five books checked out g. For each book authored (or coauthored) by Stephen King, retrieve the title and the number of copies owned by the library branch whose name is Central 131" }, { "page_index": 316, "chapter_num": 3, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_136.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_3/slide_136.png", "page_index": 316, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:38+07:00" }, "raw_text": "Next Chapter 4 : The SQL Language 4.1. Introduction to the SQL language o4.2. DDL 04.3. DML 04.4. DCL 4.5. Stored Functions 4.6. Stored Procedures 4.7. Triggers 132" }, { "page_index": 317, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_001.png", "page_index": 317, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:41+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Chapter 4: The SQL Language Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vö Thi Ngoc Chau (chauvtn@hcmut.edu.vn) Semester 1 - 2022-2023" }, { "page_index": 318, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_002.png", "page_index": 318, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:44+07:00" }, "raw_text": "Content Chapter 1 : An Overview of Database Systems 0 Chapter r 2: The Entity-Relationship Model Chapter 3: The Relational Data Model Chapter 4: The SQL Language Chapter 5: Relational Database Design Chapter 6: Physical Storage and Data Management Chapter 7 : Database Security 2" }, { "page_index": 319, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_003.png", "page_index": 319, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:47+07:00" }, "raw_text": "Chapter 4: The SQL Language 4.1. Introduction to the SQL language d4.2. DDL o4.3.DML 04.4. DCL 4.5. Stored Functions 4.6. Stored Procedures 4.7.Triggers 3" }, { "page_index": 320, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_004.png", "page_index": 320, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:52+07:00" }, "raw_text": "Main References Text: 1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References: [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd, 2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 7th Edition, McGraw-Hill, 2020. [4] H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. 5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 4th Edition, McGraw-Hill, 2018 [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Obiect- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007. 4" }, { "page_index": 321, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_005.png", "page_index": 321, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:25:58+07:00" }, "raw_text": "Introduction to the SQL language SQL (Structured Query Language) Paradigm Declarative Major implementations SQL (file format) Family Query language Many Filename extension .sq1 Dialects Internet application/sql[2][3] Designed by Donald D. media type Chamberlin SQL-86.SQL-89.SQL-92SQL:1999 Developed by ISO/IEC Raymond F.Boyce SQL2003SQL:2006SQL:2008. Initial release 1986 Developer ISO/IEC SQL:2011 SQL:2016 Type of format Database First appeared 1974;46 years ago Influenced by Standard ISO/IEC 9075 Open format? Yes Datalog Stable release SQL:2016/ December 2016; Influenced 3 years ago CQL,LINQ,SPARQL,SOQL,PowerShell,l1] JPQL Typing discipline Static, strong jOOQ,N1QL os Cross-platform Website www.iso.org/standard /63555.html SQL - Wikipedia, Accessed 28/09/2020 5" }, { "page_index": 322, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_006.png", "page_index": 322, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:06+07:00" }, "raw_text": "Year Name Alias Comments SQL- 1986SQL-86 First formalized by ANSI 87 FIPS 1989SQL-89 127- Minor revision that added integrity constraints, adopted as FIPS 127-1. 1 SQL2, FIPS 1992SQL-92 Major revision (ISO 9075), Entry Level SQL-92 adopted as FIPS 127-2. 127- 2 Added regular expression matching, recursive queries (e.g. transitive closure), triggers, support for procedural and 1999SQL1999SQL3 control-of-flow statements, non-scalar types (arrays), and some object-oriented features (e.g. structured types) Support for embedding SQL in Java (SQL/OLB) and vice versa (SQL/JRT) Introduced XML-related features (SQl/xML),window functions,standardized seguences,and columns with auto- 2003SQL2003 generated values (including identity-columns). ISO/IEC 9075-14:2006 defines ways that SQL can be used with XML.It defines ways of importing and storing XML data in an SQL database, manipulating it within the database, and publishing both XML and conventional SQL-data 2006SQL2006 in XML form. In addition, it lets applications integrate queries into their SQL code with XQuery, the XML Query Language published by the World Wide Web Consortium (W3C), to concurrently access ordinary SQL-data and XML documents.(34 2008SQL2008 Adds temporal data (PERIOD FOR)[36] (more information at: Temporal database#History). Enhancements for window 2011SQL2011 2016SQL2016 Adds row pattern matching, polymorphic table functions, JSON. 2019SQL2019 Adds Part 15, multidimensional arrays (MDarray type and operators) 6 SQL - Wikipedia, Accessed 28/09/2020" }, { "page_index": 323, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_007.png", "page_index": 323, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:10+07:00" }, "raw_text": "Introduction to the SQL language SQL = Structured Query Language A standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987 One of the first commercial languages to utilize the relational data model A declarative non-procedural language (4GL) supported by existing g RDBMSs Based on tuple relational calculus, associated with relational algebra for internal representation processing, and optimization Specify \"WHAT\" in data requests on a database NOT specify \"HOW\" to process s the data reguests 7" }, { "page_index": 324, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_008.png", "page_index": 324, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:15+07:00" }, "raw_text": "SQL vs. The Relational Model SQL The Relational Model Table (set if a primary key is Relation (set) specified) Column Attribute (+ attribute values) Row Tuple Domain Domain Data type (Data type) Primary key Primary key Uniqueness, NOT NULL Secondary key Foreign key Foreign key Defined and enforced with Semantic constraints CHECK, ASSERTION, TRIGGER 8" }, { "page_index": 325, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_009.png", "page_index": 325, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:20+07:00" }, "raw_text": "SQL Relational Algebra vs. The SQL The Relational Algebra SELECT statement Relational algebra expression - specifies WHAT - specifies WHAT + HOW FROM clause (none), x, *, other joins SELECTION (o) WHERE clause SELECT clause PROJECTION (x) (+ DISTINCT) Aggregate functions Aggregate functions GROUP BY clause 3 HAVING clause SELECTION on 3 ORDER BY clause (not available) UNION, INTERSECT, MINUS U,n, - INSERT, DELETE, UPDATE statements (not available) 9" }, { "page_index": 326, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_010.png", "page_index": 326, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:26+07:00" }, "raw_text": "DBMS-specific implementation SQL Data Types Predefined data types 0 Character Types: Character fixed (CHAR) (e.g. CHAR(10)), Character Varying (VARCHAR) (e.g. VARCHAR(20)), Character Large Object (CLOB) Binary Types: Binary (BINARY), Binary Varying (VARBINARY), Binary Large Object (BLOB) Numeric Types Exact Numeric Types (NUMERIC, DECIMAL, SMALLINT, INTEGER, BIGINT) 0 0 Approximate Numeric Types (FLOAT, REAL, DOUBLE PRECISION) Datetime Types (DATE, TIME, TIMESTAMP) Interval Type (INTERVAL) Boolean (three-valued logic (3VL): true, false, unknown (NULL) XML, JSON Constructed types ARRAY, MULTISET, REF(erence), or ROW User-defined types comparable to classes in object-oriented language with their own constructors, observers, mutators, methods, inheritance overloading, overwriting, interfaces, ... 10" }, { "page_index": 327, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_011.png", "page_index": 327, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:31+07:00" }, "raw_text": "SQL Data Types 3-Valued d Logic -1 True False Unknown AND NOT x (T) (F) (U) True T F U True F False F F F False T Unknown U F D Unknown U Unknown NULL OR True False Unknown True T T T x: True, False T F U False, Unknown T D U Unknown 11" }, { "page_index": 328, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_012.png", "page_index": 328, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:34+07:00" }, "raw_text": "Introduction to the e SQL language Data Definition Language (DDL) CREATE, ALTER, DROP Data Manipulation Language (DML) For queries: SELECT For data modifications: INSERT, DELETE, UPDATE Data Control Language (DCL) For access control: GRANT, REVOKE For transaction control: COMMIT, ROLLBACK SET AUTOCOMMIT OFF > SQL: case-insensitive, extended in DBMSs 12" }, { "page_index": 329, "chapter_num": 4, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_4/slide_013.png", "page_index": 329, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T07:26:41+07:00" }, "raw_text": "CREATETABLE([] {,[]} SQL [
{,
}] DROPTABLE
ALTER TABLE
ADD SELECT[DISTINCT] FROM(
{}){,(
{})} [WHERE] [GROUP BY[HAVING] ] [ORDERBY[]{,[]}] ::=(*((([DISTINCT]*))) {,[DISTINCT]*} ::={,} Simplified =ASCDESC SQL INSERT INTO
[({,})] VALUES,{}{,{,} Statements
(Checked [WHERE] UPDATE
with each SET={,=} [WHERE] DBMS) CREATE[UNIQUE] INDEX ON
[]{,[]} [CLUSTER] DROPINDEX CREATE VIEW[({,})] AS
( [] {, []} [CLUSTER] ; CREATE INDEX Dnolndex ON EMPLOYEE(Dno) CLUSTER; UNIQUE is used to guarantee that no two rows of a table have duplicate values in the key column or column. CLUSTER is used when the index to be created should also sort the data file records on the indexing attribute. Specifying CLUSTER on a key (unique) attribute would create some variation of a primary index, whereas specifying CLusTER on a nonkey (nonunique) attribute would create some variation of a clustering index. 112" }, { "page_index": 704, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_113.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_113.png", "page_index": 704, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:20+07:00" }, "raw_text": "in Today's Indexes 6 DBMSs Feature Support B-tree indexes Yes Features of InnoDB Backup/point-in-time recovery (Implemented in the server, Yes rather than in the storage engine.) storage engine in Cluster database support No Clustered indexes Yes MySQL 8.0 Compressed data Yes Data caches Yes Encrypted data Yes (Implemented in the server via encryption functions;In MySQL 5.7 and later, data-at-rest tablespace encryption is supported.) B-tree for Foreign key support Yes Full-text search indexes Yes(lnnoDB support for FULLTEXT index indexes is available in MySQL 5.6 and later.) Geospatial data type support Yes structures Geospatial indexing support Yes (InnoDB support for geospatial indexing is available in MySQL 5.7and later.) Hash indexes No(lnnoDB utilizes hash indexes internally for its Adaptive Hash Index feature.) Index caches Yes Locking granularity Row MVCC Yes Replication support(Implemented in the server,rather than Yes in the storage engine.) Storage limits 64TB T-tree indexes No Transactions Yes 113 Update statistics for data dictionary Yes" }, { "page_index": 705, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_114.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_114.png", "page_index": 705, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:27+07:00" }, "raw_text": "in Today's Indexes DBMSs Branch Blocks - 0..40 41..80 81..120 200..250 0..10 41..48 200..209 11..19 49..53 210..220 20..25 54..65 221..228 32..40 78..80 246..250 Leaf Blocks 0,rowid 11,rowid 221,rowid 246,rowid 0,rowid 11,rowid 222,rowid 248.rowid 12,rowid 223,rowid 248,rowid 10,rowid 19,rowid 228.rowid 250,rowid Internal structure of a B-tree index in Oracle 19c 114" }, { "page_index": 706, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_115.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_115.png", "page_index": 706, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:35+07:00" }, "raw_text": "in Today's Indexes s DBMSs Root=1page (Level 2) 12441.. 24881... Non-leaflevels - 2levelsroot+1 74641.. intermediatelevel) Totaloverheadin + + Intermediate level terms of disk space 74641.. = 7 pages (Level 1) 21... =8 pages(or < 1%) 41.. 79941... 79961... 1 12421. 79981.. 1 1 1 + + + + + 1 21... 41... 79941.. 79961.. 79981.. 2... 22... 42... 79942... 79962... 79982... 3... 23... 43... 79943... 79963... 79983... 20... 40... 60... 79960.. 79980.. 80000.. An adapted B-tree for a c/ustered index in MS SQL Server How about Co/umnstore Index in today's MS SQL Server? 115" }, { "page_index": 707, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_116.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_116.png", "page_index": 707, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:39+07:00" }, "raw_text": "6.2. Indexing Indexes: additional access structures for efficiency Created on one or many fields of a data file, called indexing fields Ordering key field => Primary indexes Ordering non-key field l => Clustering indexes Non-ordering field => Secondary indexes Also stored in index files on disk Single-level vs. Multilevel indexes Dynamic multilevel index structures: B-tree, B+-tree Support certain search conditions =, >, >=, <, <=, and \"between\" on indexing fields 116" }, { "page_index": 708, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_117.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_117.png", "page_index": 708, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:45+07:00" }, "raw_text": "6.3. Complex Data Management Approaches (Semi-structured and Unstructured Data) Structured data : data stored in relational databases which are 0 represented in a strict format. For example: data in the COMPANY database defined with the relational data model. Semistructured data: data that may have a certain structure, but not all the data collected will have the identical structure. Some attributes may be shared among the various entities, but other attributes may exist only in a few entities. Moreover, additional attributes can be introduced in some of the newer data items at any time, and there is no fixed predefined schema. Semistructured data are sometimes referred to as self-describing data. For example: data in the COMPANY database defined with XML (Extensible Markup Language) or JsON (Javascript Object Notation) format. Unstructured data: data for which there is very limited indication of the type of data. 117" }, { "page_index": 709, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_118.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_118.png", "page_index": 709, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:49+07:00" }, "raw_text": "6.3. Complex Data Management Approaches (Semi-structured and Unstructured Data) General-purpose DBMSs that support 0 complex data (Extended) Relational XML Object Object relational NoSQL NewSQL Specialized DBMSs that support 0 complex data Multimedia DBMSs 118" }, { "page_index": 710, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_119.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_119.png", "page_index": 710, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:54+07:00" }, "raw_text": "6.4. Massive Management Data Approaches How big is big? 1 exabyte (EB) = 1018 bytes = 1000 petabytes = 1 million terabytes = 1 billion gigabytes = 1 trillion megabytes 1 zettabyte (ZB) = 1000 exabytes = 1021 bytes Global Datasphere = 175 zettabytes of digital data by 2025 Source : Wikipedia for units. IDC Data Age 2025: the Digitization of the World from Edge to Core, November 2018 119 https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf" }, { "page_index": 711, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_120.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_120.png", "page_index": 711, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:47:58+07:00" }, "raw_text": "6.4. Massive Management Data Approaches Massive Data 0 Data sets that traditional data architectures are unable to handle efficiently Those in organizations such as Google, Amazon, Facebook, and Twitter and in applications such as social media, Web links, user profiles, marketing and sales, posts and tweets, road maps and spatial data, and e-mail Those with the following characteristics Three basic original V's characteristics: Volume (luong): too big Velocity (töc d6): arrives too fast Volume, Velocity, Variety Variability (su bién thien): changes too fast Veracity (d chinh xac) : contains too much noise Variety (do da dang): too diverse 120" }, { "page_index": 712, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_121.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_121.png", "page_index": 712, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:04+07:00" }, "raw_text": "6.4. Massive Management Data Approaches Massive data management systems SQL systems give an emphasis on immediate data consistency, powerful query languages, and structured data storage. For example: Oracle, PostgreSQL, DB2, MS SQL Server, MySQL, Informix, ... Most NoSQL systems are distributed database or distributed high performance, availability, data replication, and scalability. For example: MongoDB, Hbase, Cassandra, Neo4J, ... NewSQL systems are modern relational DBMSs that seek to provide the same scalable performance of NoSQL for OLTP read-write workloads while still maintaining ACID guarantees for transactions. For example: VoltDB, ... Andrew Pavlo and Mathew Aslett. What's really new with NewSQL? SIGMOD Record, vol. 45, no. 2, pp. 45-55, June 2016. 121" }, { "page_index": 713, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_122.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_122.png", "page_index": 713, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:09+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Data representation : most schemaless for self-describing data. 0 Constraint enforcement: most at the application programs. 0 Data manipulation: CRUD or SCRUD operations for search, 0 create, read, update, and delete with programming APIs. A few query languages like SQL: Cypher (Neo4J), CQL (Cassandra), N1QL (Couchbase), ... Versioning: storage of multiple versions of the data items, with the timestamps of when the data version was created. Data architecture: distributed systems. 0 Scalability: often horizontal by adding more nodes for data storage and processing as the volume of data grows Availability, Replication and Eventual Consistency: no concurrency control Replication: Master-Slave (write at master), Master-Master (reconciliation) Sharding of Files: horizontal partitioning High-Performance Data Access: hashing, range partitioning, and indexing on object keys 122" }, { "page_index": 714, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_123.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_123.png", "page_index": 714, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:15+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Three desirable properties of distributed systems with replicated data: CAP theorem (principle) C: consistency among replicated copies The nodes will have the same copies of a replicated data item visible for various transactions. A form of consistency known as eventua/ consistency is often adopted in NoSQL systems, different from that in ACID of SQL ones. A: availability of the system for read and write operations Each read or write request for a data item will either be processed successfully or will receive a message that the operation cannot be completed P: partition tolerance in the face of the nodes in the system being partitioned by a network fault The system can continue operating if the network connecting the nodes has a fault that results in two or more partitions, where the nodes in each partition can only communicate among each other. 123" }, { "page_index": 715, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_124.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_124.png", "page_index": 715, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:22+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Document-based NoSQL systems: MongoDB, CouchDB, ... 0 These systems store data in the form of documents using well-known formats, such as JsON (JavaScript Object Notation). Documents are accessible via their document id, but can also be accessed rapidly using other indexes. NoSQL key-value stores: DynamoDB, Cassandra, ... 0 These systems have a simple data model based on fast access by the key to the value associated with the key; the value can be a record or an object or a document or even have a more complex data structure. Column-based or wide column NoSQL systems : HBase, BigTable 0 These systems partition a table by column into column families, where each column family is stored in its own files. They also allow versioning of data values. Graph-based NoSQL systems: Neo4J, GraphBase, ... 0 Data is represented as graphs, and related nodes can be found by traversing the edges using path expressions. Multimodel systems: Cassandra (key-value, column), OrientDB 0 (document, key-value, graph), CouchBase (document, key- value), .. 124" }, { "page_index": 716, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_125.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_125.png", "page_index": 716, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:27+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Document-based NoSQL systems - MongoDB https://www.mongodb.com MongoDB documents are stored in BSON (Binary JSON) format which is a variation of JsON with some additional data types and is more efficient for storage than JsON. Individual documents ( rows records in relational databases) are stored in a collection ( table relation) - db.createCollection(\"project\", { capped : true, size : 1310720, max : 500 } ) Collection options : Collection name capped: true > storage option size: 1310720 > upper limits on storage space max: 500 > number of documents db.collection.createIndex(}): create an index using B-tree CRuD: create, insert, find (for read), update, remove (for delete) 125" }, { "page_index": 717, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_126.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_126.png", "page_index": 717, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:34+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Document-based NoSQL systems - MongoDB 0 https://www.mongodb.com MongoDB documents are stored in BSON (Binary JSON) format which is a variation of JsON with some additional data types and is more efficient for storage than JsON. Individual documents ( rows records in relational databases) are stored in a collection ( table relation) : db.createCollection(project\", { capped : true, size : 1310720, max : 500 } ) db.createCollection(\"worker\", { capped : true, size : 5242880, max : 2000 } ) db.project.insert( {_id: \"P1\", Pname: \"ProductX\", Plocation: \"Bellaire\" } ) db.worker.insert( [ {_id: \"W1\", Ename: \"John Smith\", Projectld: \"P1\", Hours: 32.5 } {_id: \"W2\", Ename: \"Joyce English\",Projectld: \"P1\" Hours: 20.0} ] ) db..insert() db..remove() db..find() 126" }, { "page_index": 718, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_127.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_127.png", "page_index": 718, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:40+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Document-based NoSQL systems - MongoDB 0 project document with an array of embedded workers: _id: \"P1\", Pname: \"ProductX\" project document with an embedded array of worker ids: Plocation: \"Bellaire\", Workers: [ _id: \"P1\" f Ename: \"John Smith\" Pname: \"ProductX\" Hours: 32.5 Plocation: \"Bellaire\", }, Workerlds: \"W1\"\"W2\" { Ename: \"Joyce English\" Hours: 20.0 {_id: \"W1\" 1 Ename: \"John Smith\" 1 Hours: 32.5 {_id: \"W2\", Ename: \"Joyce English\" Hours: 20.0 1 127" }, { "page_index": 719, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_128.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_128.png", "page_index": 719, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:45+07:00" }, "raw_text": "6.4. Massive Management Data Approaches - NoSQL Document-based NoSQL systems - MongoDB 0 Transaction support mainly for atomicity (all-or-nothing) : An operation on a single document is atomic. The two-phase commit method is used to ensure atomicity and consistency of multidocument transactions. Replication: master-slave: primary, secondaries primary: read/write > MongoDB can ensure that every read request gets the latest document value primary: write, secondaries: read > A read at a secondary is not guaranteed to get the latest version of a document. Sharding (horizontal partitioning) Horizontal scaling: add more nodes as needed 128" }, { "page_index": 720, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_129.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_129.png", "page_index": 720, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:49+07:00" }, "raw_text": "6.5. Quality Scalability, Effectiveness, Efficiency Data quality issues 0 Accuracy Timeliness Completeness Consistency Interpretability Accessibility Usability Trustworthiness Data management quality issues Reliability Scalability Effectiveness Efficiency 129" }, { "page_index": 721, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_130.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_130.png", "page_index": 721, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:54+07:00" }, "raw_text": "6.5. Data Quality Issues Chat luong (quality of data/information) Phu hp vói dac tä (specifications), yéu cäu tü ngui düng (user requirements), ngü cánh sü dung (context of use), ... \"A comprehensive list of commonly agreed quality dimensions is still not available.' Phan loai chiéu chat luong (quality dimensions) Schema quality dimensions -> structure Data quality dimensions -> instance C. Batini, B. Pernici. Data Quality Management and Evolution of Information Systems. In IFIP International Federation for Information Processing, volume 214, The Past and Future of Information Systems: 1976-2006 130 and Beyond, eds. D. Avison, S. Elliot, J. Krogstie, J. Pries-Heje, Boston: Springer, 2006, pp. 51-62." }, { "page_index": 722, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_131.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_131.png", "page_index": 722, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:48:58+07:00" }, "raw_text": "6.5. Data Quality Issues Data quality dimensions Accuracy: \"inaccuracy implies that the information system represents a real world state different from the one that should have been represented.\" Timeliness: refers to \"the delay between a change of the real-world state and the resulting modification of the information system state.' Comp/eteness: is \"the ability of an information to represent every meaningful state of the represented real world system' 1 C. Batini, B. Pernici. Data Quality Management and Evolution of Information Systems. In IFIP International Federation for Information Processing, volume 214, The Past and Future of Information Systems: 1976-2006 131 and Beyond, eds. D. Avison, S. Elliot, J. Krogstie, J. Pries-Heje, Boston: Springer, 2006, pp. 51-62." }, { "page_index": 723, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_132.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_132.png", "page_index": 723, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:04+07:00" }, "raw_text": "6.5. Data Quality Issues Data quality dimensions Consistency: consistency of data values occurs whether or not there is more than one state of the information system matching a state of the real world system, therefore, \"inconsistency would mean that the representation mapping is one-to-many. 7 Interpretability: concerns the documentation and metadata that are available to interpret correctly the meaning and properties of data sources C. Batini, B. Pernici. Data Quality Management and Evolution of Information Systems. In IFIP International Federation for Information Processing, volume 214, The Past and Future of Information Systems: 1976-2006 132 and Beyond, eds. D. Avison, S. Elliot, J. Krogstie, J. Pries-Heje, Boston: Springer, 2006, pp. 51-62." }, { "page_index": 724, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_133.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_133.png", "page_index": 724, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:09+07:00" }, "raw_text": "6.5. Data Quality Issues Data a quality dimensions 0 l Accessibility: measures the ability of the user to access the data as from his/her own culture, physical status/functions and technologies available satisfaction with which specified users perceive and make use of data Trustworthiness: measures how reliable the organization is in providing data sources C. Batini, B. Pernici. Data Quality Management and Evolution of Information Systems. In IFIP International Federation for Information Processing, volume 214, The Past and Future of Information Systems: 1976-2006 133 and Beyond, eds. D. Avison, S. Elliot, J. Krogstie, J. Pries-Heje, Boston: Springer, 2006, pp. 51-62." }, { "page_index": 725, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_134.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_134.png", "page_index": 725, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:14+07:00" }, "raw_text": "6.5. Data Management Quality Issues: Reliability, Scalability, Effectiveness, Efficiency Data a Management Quality Issues Reliability: broadly defined as the probability that a system is running (not down) at a certain time point. Scalability: the extent to which the system can expand its capacity (i.e. data volumes, users, connections) while continuing to operate without interruption. Effectiveness: how correctly a task has been resolved. Efficiency: how well resources have been used. 134" }, { "page_index": 726, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_135.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_135.png", "page_index": 726, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:20+07:00" }, "raw_text": "6.5. Data Management Quality Issues: Reliability, Scalability, Effectiveness, Efficiency Data Management Quality Issues 0 Reliability One common approach stresses fault tolerance; it recognizes that faults will 0 occur, and it designs mechanisms that can detect and remove faults before they can result in a system failure. Another more stringent (severe, very serious) approach attempts to ensure that 0 the final system does not contain any faults. This is done through an exhaustive design process followed by extensive quality control and testing. For example: improving reliability with RAID systems. Scalability Support for large databases. For example: 0 Scalability with storage technologies: NAS Scalability support from existing DBMSs MySQL: mentioned with 200,000 tables, 5,000,000,000 rows, up to 64 indexes per table, each index of 1 to 16 columns or parts of columns. Oracle 19c: unlimited for the max number of tables, the max number of rows per table, the max number of constraints per column, and the max number of indexes per table; restrictions for index-organized tables: the max number of columns: 1000, the max number of columns in a primary key: 32, the max number of columns in the index portion of a row: 255 Effectiveness 135 Efficiency" }, { "page_index": 727, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_136.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_136.png", "page_index": 727, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:25+07:00" }, "raw_text": "6.5. Data Management Quality Issues : Reliability, Scalability, Effectiveness, Efficiency Data Management Quality Issues 0 Reliability Scalability Effectiveness An assumption called the closed wor/d assumption states that the only true facts in the universe are those present within the extension (state) of the relation(s) : DBMSs must ensure any true fact can be retrieved from or updated to the database consistently. Query processing Data manipulation with constraint enforcement Efficiency Space and time in connection, data processing, concurrency control, recovery, and backup 136" }, { "page_index": 728, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_137.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_137.png", "page_index": 728, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:29+07:00" }, "raw_text": "Summary Storage devices Magnetic disks for large amounts of data Disk pack > cylinder > track > sector > bit Bit > byte > block > track > cylinder Block: data transfer unit between disks and main memory Block address = block pointer Data File of a Database 01 Bit > byte -> field -> record > file => disk blocks Blocking factor: the number of records/block Primary file organization for records of one type Unordered (heap) files Ordered (sequential) files Hashed files 137" }, { "page_index": 729, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_138.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_138.png", "page_index": 729, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:34+07:00" }, "raw_text": "Summary Indexes: additional access structures for efficiency Created on one or many fields of a data file, called indexing fields Ordering key field => Primary indexes Ordering non-key field l => Clustering indexes Non-ordering field => Secondary indexes Also stored in index files on disk Single-level vs. Multilevel indexes Dynamic multilevel index structures: B-tree, B+-tree Support certain search conditions =, >, >=, <, <=, and \"between\" on indexing fields 138" }, { "page_index": 730, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_139.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_139.png", "page_index": 730, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:37+07:00" }, "raw_text": "Summary Complex data management approaches Structured data Simple data Semi-structured data Complex data Unstructured data > Logical data representation > Database management systems: XML, Object Object Relational, NoSQL, NewSQL 139" }, { "page_index": 731, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_140.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_140.png", "page_index": 731, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:41+07:00" }, "raw_text": "Summary Massive data management approaches SQL vs. NoSQL vs. NewSQL NoSQL Representation: schemaless Document, key-value, column, graph, ... Constraint enforcement mostly at the application side Data manipulation: CRUD, SCRUD Versioning with timestamps Architecture: distributed with the CAP theorem Eventual consistency 140" }, { "page_index": 732, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_141.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_141.png", "page_index": 732, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:45+07:00" }, "raw_text": "Summary Data quality issues Data management 0 l quality issues Accuracy Reliability Timeliness Scalability Completeness Effectiveness Consistency Efficiency Interpretability Accessibility Usability Trustworthiness 141" }, { "page_index": 733, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_142.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_142.png", "page_index": 733, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:49+07:00" }, "raw_text": "Chapter 6: Physical Storage Data Management and ques wslin questi answer question quest quest tion question 142" }, { "page_index": 734, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_143.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_143.png", "page_index": 734, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:52+07:00" }, "raw_text": "Review 1. Describe the memory hierarchy for data storage. 2. Distinguish between persistent data and transient data. 3. Describe disk parameters when magnetic disks are used for storing large amounts of data. 4. Describe the read/write commands with magnetic disks. 143" }, { "page_index": 735, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_144.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_144.png", "page_index": 735, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:49:56+07:00" }, "raw_text": "Review 5. Distinguish between fixed-length records and variable-length records. 6. Distinguish between spanned records and unspanned records. 7. What is blocking factor? How to compute it? 8. What is file organization? What is its goal? 0 9. What is access method? How is it related to file organization? 144" }, { "page_index": 736, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_145.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_145.png", "page_index": 736, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:00+07:00" }, "raw_text": "Review 10. Distinguish between static files and dynamic files. unordered files, ordered files, 11. Compare 0 and hash files. 12. Which operations are more efficient for 0 each file organization: unordered, ordered, hash? Why? 13. Distinguish between static hashing and 0 dynamic hashing. 145" }, { "page_index": 737, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_146.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_146.png", "page_index": 737, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:04+07:00" }, "raw_text": "Review 14. What are indexes? Give at least three 0 examples. 15. What are primary, secondary, and 0 clustering indexes? Give at least one example for each. 16. Compare primary, secondary, and 0 clustering indexes with each other. Which are dense and which are not? Explain the characteristics in their corresponding data file that make them dense or sparse. 146" }, { "page_index": 738, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_147.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_147.png", "page_index": 738, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:08+07:00" }, "raw_text": "Review 17. Why can at most one primary or clustering index created on a data file, but zero or many secondary indexes? Give an example to demonstrate your answer. 18. Distinguish between single-level indexes and multilevel indexes. Give an example to demonstrate your answer. d B+-tree when they 19. Describe B-tree and 0 are used as secondary access structures for 1 a data file. Distinguish between B-tree and B+-tree. Give an example for each structure. 147" }, { "page_index": 739, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_148.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_148.png", "page_index": 739, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:13+07:00" }, "raw_text": "Review 20. For which types of applications were NoSQL systems 0 developed? 21. What are the main categories of NoSQL systems? List a few 0 of the NoSQL systems in each category. 22. What are the main characteristics of NoSQL systems in the areas related to data models and query languages? 23. What are the main characteristics of NoSQL systems in the 0 areas related to distributed systems and distributed databases? 24. What is the CAP theorem? Which of the three properties 0 (consistency, availability, partition tolerance) are most important in NoSQL systems? 25. What are the similarities and differences between using 0 consistency in CAP versus using consistency in ACID? 148" }, { "page_index": 740, "chapter_num": 6, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_149.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_6/slide_149.png", "page_index": 740, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:17+07:00" }, "raw_text": "Next Chapter 7 7: Database security 7.1. An overview of database security 0 0 g and revoking privileges granting 7.3. Mandatory access control and role-based access control for multilevel security 7.4. Inference control and flow control 7.5. Security in new DBMSs 149" }, { "page_index": 741, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_001.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_001.png", "page_index": 741, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:20+07:00" }, "raw_text": "Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Chapter Security 7: Database Database Systems (C02013) Computer Science Program Assoc. Prof. Dr. Vö Thi Ngoc Chau (chauvtn@hcmut.edu.vn) Semester 1 - 2022-2023" }, { "page_index": 742, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_002.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_002.png", "page_index": 742, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:24+07:00" }, "raw_text": "Content Chapter 1 : An Overview of Database Systems 0 Chapter r 2: The Entity-Relationship Model Chapter 3: The Relational Data Model Chapter 4: The SQL Language 0 Chapter 5: Relational Database Design Chapter 6: Physical Storage and Data Management . 7: Database Security Chapter 01 2" }, { "page_index": 743, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_003.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_003.png", "page_index": 743, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:27+07:00" }, "raw_text": "Chapter Security 7: Database 7.1. An overview of database security 0 0 granting and revoking privileges 7.3. Mandatory access control and role-based 0 access control for multilevel security 7.4. Inference control and flow control 0 7.5. Encryption and public key infrastructure 0 7.6. Security in new DBMSs 0 3" }, { "page_index": 744, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_004.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_004.png", "page_index": 744, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:32+07:00" }, "raw_text": "Main References Text: 1l R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 6th Edition, Pearson- Addison Wesley, 2011. R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. References: [1] S. Chittayasothorn, Relational Database Systems: Language, Conceptual Modeling and Design for Engineers, Nutcha Printing Co. Ltd, 2017. 3] A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 7th Edition, McGraw-Hill, 2020. [4] H. G. Molina, J. D. Ullman, J. Widom, Database Systems: The Complete Book - 2nd Edition, Prentice-Hall, 2009. 5] R. Ramakrishnan, J. Gehrke, Database Management Systems - 4th Edition, McGraw-Hill, 2018 [6] M. P. Papazoglou, S. Spaccapietra, Z. Tari, Advances in Obiect- Oriented Data Modeling, MIT Press, 2000. [7]. G. Simsion, Data Modeling: Theory and Practice, Technics Publications, LLC, 2007. 4" }, { "page_index": 745, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_005.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_005.png", "page_index": 745, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:36+07:00" }, "raw_text": "A simplified database system environment Users/Programmers use DATABASE SYSTEM Application Programs/Queries II DBMS SOFTWARE Software to Process Queries/Programs DBMS 1 Software to Access Stored Data Database - Stored Database Stored Definition Database (Meta-Data) 5" }, { "page_index": 746, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_006.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_006.png", "page_index": 746, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:38+07:00" }, "raw_text": " of database security An overview Security Protection of a person, building, organization or country against threats s such as crime or attacks by foreign countries [Dictionary] Protection Person, building, organization, country Threats (crime/attacks)/risks Foreign countries 6" }, { "page_index": 747, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_007.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_007.png", "page_index": 747, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:43+07:00" }, "raw_text": "An overview of database security Computer security (Bäo mat hé thóng may tinh/ thóng tin) The protection afforded to an automated information system in order to attain the applicable objectives of preserving the integrity, availability, and confidentiality of information system resources (includes hardware, software, firmware, information/data, and telecommunications The NIST Computer Security Handbook, 1995 NIST: National Institute of Standards and Technology (US) Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, Third Edition, Pearson Education, Inc., 2015. 7" }, { "page_index": 748, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_008.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_008.png", "page_index": 748, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:48+07:00" }, "raw_text": "v of database security An overview Computer security Computer system Computer system 4Sensitive files must be secure Data (file security) Data Data must be DAccess to the data securely transmitted must be controlled through networks (protection) (network security) Processesrepresenting users Processes representing users Guard Guard 1 1 2)Access to the computer facility must be controlled (user authentication) Users making requests Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, Third Edition, Pearson Education, Inc., 2015. 8" }, { "page_index": 749, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_009.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_009.png", "page_index": 749, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:55+07:00" }, "raw_text": "An overview of database security Threats to computer systems Availability Confidentiality Integrity Hardware Equipment is stolen or An unencrypted disabled, thus denying CD-ROM or DVD is service. stolen. Software Programs are deleted. An unauthorized copy of A working program is modi- denying access to users. software is made fied.either to cause it to fail during execution or to cause it to do some unintended task Data Files are deleted. Anunauthorized read Existing files are modified or denying access to users. of data is performed. An new files are fabricated. analysis of statistical data reveals underlying data Communication Messages are destroyed or Messages are read. The Messages are modified. Lines and deleted.Communication traffic pattern of delayed, reordered, or dupli Networks lines or networks are messages is observed cated.False messages are renderedunavailable fabricated. Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, Third Edition, Pearson Education, Inc., 2015. 9" }, { "page_index": 750, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_010.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_010.png", "page_index": 750, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:50:59+07:00" }, "raw_text": "An overview of database security Database security (Bao mat co sö dü liéu) Database security refers to (database) protection from malicious access. Absolute protection of the database from malicious abuse is not possible, but the cost to the perpetrator (t6i pham) can be made high enough to deter (ngän chan) most if not all attempts to access the database without proper authority (quyén hop phäp) Source: A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 6th Edition, McGraw-Hill, 2006.10" }, { "page_index": 751, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_011.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_011.png", "page_index": 751, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:05+07:00" }, "raw_text": "An overview of database security Database security (Bäo mat co sö dü lieu) 0 To protect the database, security measures must be taken at several levels : Database system. Some database-system users may be authorized to access only a limited portion of the database. Other users may be allowed to issue queries, but may be forbidden to modify the data. It is the responsibility of the database system to ensure that these authorization restrictions are not violated. Operating system. No matter how secure the database system is, weakness in operating system security may serve as a means of unauthorized access to the database Network. Since almost all database systems allow remote access through terminals or networks, software-level security within the network software is as important as physical security, both on the Internet and in private networks. Physica/. Sites with computer systems must be physically secured against armed or surreptitious (bi mat) entry by intruders. Human. Users must be authorized carefully to reduce the chance of any user giving access to an intruder in exchange for a bribe (hi /) or other favors. Source: A. Silberschatz, H. F. Korth, S. Sudarshan, Database System Concepts - 6th Edition, McGraw-Hill, 2006.11" }, { "page_index": 752, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_012.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_012.png", "page_index": 752, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:10+07:00" }, "raw_text": "An overview of database security Threats (M6i nguy hiém) to databases 0 Loss of confidentiality (Mat tinh bi mat). Database confidentiality refers to the protection of data from unauthorized disclosure (su phoi bay trái phép) The impact of unauthorized disclosure of confidential information can range from violation of the Data Privacy Act to the jeopardization (su nguy hai) of national security. Unauthorized, unanticipated, or unintentional disclosure could result in loss of public confidence, embarrassment, or legal action against the organization. Loss of integrity (Mat toan ven dü liéu). Database integrity refers to the requirement that information be protected from improper modification. Modification of data includes creating, inserting, and updating data; changing the status of data; and deleting data. Integrity is lost if unauthorized changes (thay dói trái phép) are made to the data by either intentional or accidental acts. If the loss of system or data integrity is not corrected, continued use of the contaminated (bi hu hóng) system or corrupted data could result in inaccuracy, fraud, or erroneous decisions. Loss of availability (Mat su sän düng). Database availability refers to making objects available to a human user or a program who/which has a legitimate right to those data objects. Loss of availability occurs when the authorized user or program cannot access these objects. 12 Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016." }, { "page_index": 753, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_013.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_013.png", "page_index": 753, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:15+07:00" }, "raw_text": " of database security An overview Threats to databases CIA triad to define database security objectives Confidentiality (not disclosed to unauthorized ones) Personal medical records of each patient about their disease and treatment must be kept confidential, only known by each patient and his/ her medication team (doctors/ nurses/ ...). Integrity (timely, accurate, complete, consistent) The drug use of a patient is not allowed to be changed to something else by other people once given by an in-charge doctor. Availability (not denied to authorized users) Upon a visit, a doctor can have access to the medica record of his/ her patient. 13" }, { "page_index": 754, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_014.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_014.png", "page_index": 754, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:18+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures (bién phäp d6i ph6) can be implemented: Access control (dieu khién truy cap) Inference control (diéu khién suy dién Flow control (diéu khién döng) Encryption (mä hóa) Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 14" }, { "page_index": 755, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_015.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_015.png", "page_index": 755, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:22+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures (bién phäp d6i ph6) can be implemented: Access control (diéu khién truy cap) A security mechanism to control access to data in a database system Preventing unauthorized persons from accessing the system, either to obtain information or to make malicious changes in the database 15 Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016" }, { "page_index": 756, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_016.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_016.png", "page_index": 756, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:26+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures: Access control (dieu khién truy cap) Discretionary access control (DAC) - Diéu khién truy cap tüy quyén Mandatory access control (MAC) - Diéu khién truy cap bat buóc Role-based access control (RBAC) - Diéu khién truy cap dua váo vai tr Attribute-based access control (ABAC - Diéu khién truy cap dua váo thuóc tinh Code-based access control (CBAC Diéu khién truy cap dua vao ma Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 16" }, { "page_index": 757, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_017.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_017.png", "page_index": 757, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:30+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures (bién phäp d6i ph6) can be implemented: Inference control (diéu khién suy dién A security mechanism to control inferences from statistical databases that infer certain facts concerning individua/s from queries involving only summary statistics on groups Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 17" }, { "page_index": 758, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_018.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_018.png", "page_index": 758, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:34+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures (bién phäp d6i ph6) can be implemented: Flow control (diéu khién döng) A security mechanism to prevent information from flowing in such a way that it reaches unauthorized users Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 18" }, { "page_index": 759, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_019.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_019.png", "page_index": 759, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:38+07:00" }, "raw_text": "An overview of database security To protect databases against these threats, four kinds of countermeasures (bién phäp dói ph6) can be implemented: Encryption (mä hóa) A security mechanism to protect sensitive data that is transmitted via some type of communications network by means of encrypting techniques The sensitive data, e.g. credit card number, is encoded using some coding algorithm. An unauthorized user who accesses encoded data will have difficulty deciphering it, but authorized users are given decoding or decrypting algorithms (or keys) to decipher the data. Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 19" }, { "page_index": 760, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_020.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_020.png", "page_index": 760, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:43+07:00" }, "raw_text": "An overview of database security Database Security and Database Administrator (DBA, 0 quän tri vién co s dü liéu) DBA is the central authority for managing a database system The responsibility of DBA: Administering the resources Primary resource : the database = perform DDL statements (CREATE/ ALTER/ DROP data objects (schema, table, index, trigger, constraint, ...) and CREATE/ ALTER/ DROP USER/ ROLE statements, ... Secondary resources: database management system (DBMS and other related softwares Authorizing access to the database => perform GRANT/ REVOKE Coordinating and monitoring the use of the database Acguiring software and hardware resources as needed Being accountable for problems such as security breaches and poor system response time 20 Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016." }, { "page_index": 761, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_021.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_021.png", "page_index": 761, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:48+07:00" }, "raw_text": "An overview of database security Database Security and Database Administrator (DBA, quán tri vién co s dü liéu) For database security, DBA has a DBA account in the DBMS, sometimes called a system or superuser account, which provides powerful capabilities that are not made available to regular database accounts and users. a root in MySQL sa in MS SQL Server a SYS, SYSTEM,DBSNMP in Oracle SYS: An account used to perform database administration tasks SYSTEM: A default generic database administrator account DBSNMP: An account used by the Management Agent component of Oracle Enterprise Manager to monitor and manage the database in cloud control Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016 21" }, { "page_index": 762, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_022.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_022.png", "page_index": 762, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:51:54+07:00" }, "raw_text": "An overview of database security Database Security and Database Administrator (DBA, quän tri vién co sδ dü liéu) For database security, DBA performs the actions Account creation (tao tai khoan). This action creates a new account and password for a user or a group of users to enable access to the DBMS. Privilege granting (cap quyén). This action permits the DBA to grant certain privileges to certain accounts. Privilege revocation (thu hoi quyén) This action permits the DBA to revoke (cancel) certain privileges that were previously given to certain accounts. Security level assignment (gan müc bao mat). This action consists of assigning user accounts to the appropriate security clearance level. Source: R. Elmasri, S. R. Navathe, Fundamentals of Database Systems- 7th Edition, Pearson, 2016. 22" }, { "page_index": 763, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_023.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_023.png", "page_index": 763, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:02+07:00" }, "raw_text": " of database security An overview Confidentiality (tinh bi mat) 0 Risk (rüi ro) 0 Integrity (tinh toan ven) 0 Threat (mói nguy hiém) 0 Availability (su sän düng) 0 Vulnerability (l hng) 0 Identification (dinh danh) 0 Safeguard (ban bao vé) Authentication (xäc thuc) 0 Asset (tai san) 0 Authorization (dinh quyén) Sensitive data (dü liéu quan trong 0 Auditing (kiém toán, kiém tra s ghi c6 tinh toan ven/ sän düng phai nhat ky cac truy cap va täc vu trén co duoc dám bao) sö dü liéu trong thi gian nhat dinh) Malicious code (ma dóc hai) 0 Audit trail (audit log, só ghi nhat ky Virus: a code segment that replicates by duoc düng cho muc dich bao mat) attaching copies of itself to existing Accountability (trách nhiém giai trinh) executables Trojan horse: a program that performs a Non-repudiation (chóng thoai thác) 0 desired task but also includes unexpected functions Privacy (right of retaining control over Worm: a self-replicating program personal data, what information is shared with whom, su riéng tu) Intruder (ké xam nhap) 0 Security policy (chinh sach bao mat) 0 Intrusion detection (phat hién xäm nhap) Recovery (phuc höi) 0 23" }, { "page_index": 764, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_024.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_024.png", "page_index": 764, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:06+07:00" }, "raw_text": " of database security An overview Information security policy is an aggregate of directives, rules, 0 and practices that prescribes how an organization manages, protects, and distributes information. Source: P. Bowen, J. Hash, M. Wilson. Information Security Handbook: A Guide for Managers, NIST Special Publication 800-10 2006. Identification and Authentication is a technical method that prevents unauthorized people (or unauthorized processes) from entering a system. Identification is the means by which a user provides a claimed identity to the system. Authentication is the means of establishing the validity of this identity claim. Source: An Introduction to Computer Security: The NIST Handbook, Special Publication 800-12. 24" }, { "page_index": 765, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_025.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_025.png", "page_index": 765, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:10+07:00" }, "raw_text": " of database security An overview There are three means of authenticating a user's identity which can be used alone or in combination : something the individual knows (a secret e.g.i a password, Personal Identification Number (PIN), or cryptographic key); something the individual possesses (a token e.g., an ATM card or a smart card); something the individual is (a biometric e.g.i such characteristics as a voice pattern, handwriting dynamics, or a fingerprint) Source: An Introduction to Computer Security: The NIST Handbook, Special Publication 800-12 25" }, { "page_index": 766, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_026.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_026.png", "page_index": 766, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:14+07:00" }, "raw_text": " of database security An overview ASSETS Data Facilities Hardware/Software THREAT VULNERABILITY THREAT VULNERABILITY THREAT SARERAAAES Safeguards prevent threats from harming assets. However, if an appropriate safeguard is not present, a vulnerability exists which can be exploited by a threat, thereby puttting assets at risk." }, { "page_index": 767, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_027.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_027.png", "page_index": 767, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:19+07:00" }, "raw_text": "An overview of database security Put them altogether for Security Owners Threatagents Value Wish to abuse Wish to Impose and/or minimize may damage Give rise to Countermeasures Assets To reduce Y To To Risk Threats That increase Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, Third Edition, Pearson Education, Inc., 2015. 27" }, { "page_index": 768, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_028.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_028.png", "page_index": 768, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:23+07:00" }, "raw_text": " of database security An overview A methodical approach to conducting a technical attack 1. Discovering the key elements of the system 2. Scanning for vulnerabilities 4. Hacking the system to gain root/administrator privileges 5. Disabling auditing and removing traces from log files 6. Stealing files, modifying data, and stealing source code or other valuable information 7. Installing back doors and Trojan horses that permit undetectable reentry 8. Returning at will to inflict more damage 28" }, { "page_index": 769, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_029.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_029.png", "page_index": 769, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:26+07:00" }, "raw_text": "v of database security An overview Legal issues Legal: obeying the law Issues: privacy, intellectual property, free speech, computer crimes, seller/buyer protection, Ethical issues 0 l Ethical: obeying the right actions (morals/responsibility) > subjective and circumstance-dependent Issues: privacy, accuracy, property, accessibility > F Relationship between legal/ethical issues 29" }, { "page_index": 770, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_030.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_030.png", "page_index": 770, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:31+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Discretionary access control (DAC) is one security scheme in which an entity may be granted access rights that permit the entity, by its own volition, to enable another entity to access some resource. A general approach to DAC, as exercised by an operating system or a database management system (DBMS), is that of an access matrix. One dimension of the matrix consists of identified subjects (users) that may attempt data access to the resources. The other dimension lists the obiects that may be accessed At the greatest level of detail, objects may be individual data fields. More aggregate groupings, such as records, files, or even the entire database, may also be objects in the matrix. Each entry in the matrix indicates the access rights of a particular subject for a particular object Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, 30 Third Edition, Pearson Education, Inc., 2015." }, { "page_index": 771, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_031.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_031.png", "page_index": 771, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:37+07:00" }, "raw_text": "Discretionary access control based on revoking privileges granting and An access matrix on the COMPANY database with three users: Normal Employee, Manager, Partner Normal Employee Manager Partner employee SELECT, UPDATE SELECT SELECT, INSERT dependent SELECT DELETE, UPDATE department SELECT SELECT, UPDATE SELECT dept_location SELECT SELECT, UPDATE SELECT SELECT, INSERT project SELECT SELECT DELETE, UPDATE SELECT, INSERT, works_on SELECT, UPDATE DELETE, UPDATE 31" }, { "page_index": 772, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_032.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_032.png", "page_index": 772, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:41+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and In practice, an access matrix is usually sparse and is implemented by decomposition. Decomposition by data objects: access control lists (ACLs) This data structure is not convenient for determining the access rights available to a specific user. Decomposition by subjects: capability tickets A capability ticket specifies authorized objects and operations for a particular user. Each user has a number of tickets and may be authorized to loan or give them to others. Because tickets may be dispersed around the system, they present a greater security problem than access control lists. Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, 32 Third Edition, Pearson Education, Inc., 2015." }, { "page_index": 773, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_033.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_033.png", "page_index": 773, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:46+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Many current relational DBMSs use some variation of this technique. The main idea for database access control is to include statements in the query language (e.g. SQL) that allow the DBA and selected users to grant and revoke privileges. Statement: GRANT, REVOKE User: an account through which you can log in to the database, and to establish the means s by which DBMS permits access by the user Privilege: the right to perform some action 33" }, { "page_index": 774, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_034.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_034.png", "page_index": 774, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:50+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and There are two levels for assigning privileges to use the database system (DBMS-specific implementation) : The account level. At this level, the DBA specifies the particular privileges that each account holds independently of the relations in the database. Some privileges are DROP ..., ... The relation (or table) level. At this level, the DBA can control the privilege to access each individual relation or view in the database. Some privileges are SELECT, INSERT DELETE, UPDATE, ... References privilege on a table R. This gives the account the capability to reference (or refer to) table R when specifying integrity constraints. This privilege can also be restricted to specific attributes of table R. 34" }, { "page_index": 775, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_035.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_035.png", "page_index": 775, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:55+07:00" }, "raw_text": "Discretionary access control based on 0 granting revoking privileges and Levels for assigning privileges to use the database system (DBMS-specific implementation) : Oracle 19c: System privileges and Object privileges MS SQL Server: Server permissions and Database permissions MySQL: Administrative privileges, Database privileges that apply to a database and to all objects within it, privileges for database objects such as tables, indexes, views, and stored routines 35" }, { "page_index": 776, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_036.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_036.png", "page_index": 776, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:52:59+07:00" }, "raw_text": "Discretionary access control based on 0 granting revoking privileges j and To control the granting and revoking of relation privileges, each relation R in a database is assigned an owner account, which is typically the account that was used when the relation was created in the first place. The owner of a relation is given all privileges on that relation. The owner account holder can pass privileges on any of the owned relations to other users by granting privileges to their accounts. DBMS-specific imp/ementation. In MS SQL Server? NOT in MySQL? 36" }, { "page_index": 777, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_037.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_037.png", "page_index": 777, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:04+07:00" }, "raw_text": "Discretionary access control based on granting and revoking privileges Specifying Privileges through the Use of Views The mechanism of views is an important discretionary authorization mechanism. Example 1: If the owner A of a relation R wants another account B to be able to retrieve on/y some fie/ds of R, then A can create a view V of R that includes only those attributes and then grant SELECT on V to B. Example 2: The same applies to limiting B to retrieving only certain tuples of R; a view V' can be created by defining the view by means of a query that selects only those tuples from R that A wants to allow B to access. 37" }, { "page_index": 778, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_038.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_038.png", "page_index": 778, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:09+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Propagation of Privileges Using the GRANT OPTION 0 Whenever the owner A of a relation R grants a privilege on R to another account B, the privilege can be given to B with or without the GRANT OPTION If the GRANT OPTION is given, this means that B can also grant that privilege on R to other accounts. Suppose that B is given the GRANT OPTION by A and that B then grants the privilege on R to a third account C, also with the GRANT OPTION. In this way, privileges on R can propagate to other accounts without the knowledge of the owner of R. If the owner account A now revokes the privilege granted to B, all the privileges that B propagated based on that privilege should automatically be revoked by the system. A DBMS that allows propagation of privileges must keep track of how all the privileges were granted in the form of some internal Ilog so that revoking of privileges can be done correctly and completely DBMS-specific imp/ementation. In MS SQL Server? In MySQL? 38" }, { "page_index": 779, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_039.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_039.png", "page_index": 779, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:15+07:00" }, "raw_text": "Discretionary access control based on granting and revoking privileges Specifying Limits on Propagation of Privileges Techniques to limit the propagation of privileges have been developed, although they have not yet been implemented in most DBMSs and are not a part of SQL. Limiting horizontal propagation to an integer number i B means that an account B given the GRANT OPTION can C D E grant the privilege to at most i other accounts. B Vertical propagation is more complicated; it limits the depth of the granting of privileges. Granting a privilege C with a vertical propagation of zero is equivalent to granting the privilege with no GRANT OPTION. D Horizontal and vertical propagations are designed to limit E the depth and breadth of propagation of privileges. 39" }, { "page_index": 780, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_040.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_040.png", "page_index": 780, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:20+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and A1 grants SELECT to A2 on the EMPLOYEE relation with horizontal propagation equal to 2 and vertical propagation equal to 3. A2 can then grant SELECT to at most two accounts because the horizontal propagation limitation is set to 2. Additionally, A2 can grant the privilege to other accounts with vertical propagation set to 0 (no GRANT OPTION), 1, or 2; this is because A2 must reduce the vertical propagation by at least 1 when passing the privilege to others. In addition, the horizontal propagation must be less than or 0 equal to the originally granted horizontal propagation. For example, if account A grants a privilege to account B with the horizontal propagation set to an integer number j > 0, this means that B can grant the privilege to other accounts only with a horizontal propagation /ess than or equal to j. 40" }, { "page_index": 781, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_041.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_041.png", "page_index": 781, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:25+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges l and Specifying Limits on Propagation of Privileges 0 A1 SELECT on empIoyee WITH GRANT OPTION Horizontal propagation = 2 Vertical propagation = 3 A2 SELECT on employee SELECT on employee WITH GRANT OPTION Horizontal propagation = 0 Horizontal propagation = 2 Vertical propagation = 0 Vertical propagation = 1 V A3 A4 SELECT on employee WITH GRANT OPTION Horizontal propagation = 1 Vertical propagation = 0 A5 GRANT graph (AUTHORIZATION graph) that shows propagation of privileges with GRANT OPTION 41" }, { "page_index": 782, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_042.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_042.png", "page_index": 782, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:30+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n DBA grants SELECT on PROJECT to user A with GRANT OPTION using horizontal propagation = 3 and vertical propagation = 3. n User A grants SELECT on PROJECT to user B with GRANT OPTION using horizontal propagation = 2 and vertical propagation = 1. n User A grants SELECT on PROJECT to user C with no GRANT OPTION n User A grant SELECT on PROJECT to user D with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 2. User B grants SELECT on PROJECT to user E with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 0. n User D grants SELECT on PROJECT to user F with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 1. 42" }, { "page_index": 783, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_043.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_043.png", "page_index": 783, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:34+07:00" }, "raw_text": "Discretionary access control based on 0 granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n DBA grants SELECT on PROJECT to user A with GRANT OPTION using horizontal propagation = 3 and vertical propagation = 3. DBA SELECT on project WITH GRANT OPTION V Horizontal = 3, Vertical = 3 A 43" }, { "page_index": 784, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_044.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_044.png", "page_index": 784, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:38+07:00" }, "raw_text": "Discretionary access control based on 0 granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User A grants SELECT on PROJECT to user B with GRANT OPTION using horizontal propagation = 2 and vertical propagation = 1. DBA SELECT on project WITH GRANT OPTION V Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION Horizontal = 2, Vertical = 1 B 44" }, { "page_index": 785, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_045.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_045.png", "page_index": 785, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:42+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User A grants SELECT on PROJECT to user C with no GRANT OPTION DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION Horizontal = 2, Vertical = 1 SELECT on project B C 45" }, { "page_index": 786, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_046.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_046.png", "page_index": 786, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:47+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User A grant SELECT on PROJECT to user D with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 2. DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 2 Horizontal = 2, Vertical = 1 SELECT on project B C D 46" }, { "page_index": 787, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_047.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_047.png", "page_index": 787, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:52+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User B grants SELECT on PROJECT to user E with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 0. DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 2 Horizontal = 2, Vertical = 1 SELECT on project B C D SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 0 E 47" }, { "page_index": 788, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_048.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_048.png", "page_index": 788, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:53:58+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User D grants SELECT on PROJECT to user F with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 1. DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 2 Horizontal = 2, Vertical = 1 SELECT on project B C D SELECT on project SELECT on project WITH GRANT OPTION WITH GRANT OPTION Horizontal = 1, Vertical = 0 Horizontal = 1, Vertical = 1 V W E F 48" }, { "page_index": 789, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_049.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_049.png", "page_index": 789, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:05+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User D grants SELECT on PROJECT to user F with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 1. DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 A SELECT on project WITH GRANT OPTION SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 2 Horizontal = 2, Vertical = 1 SELECT on project B C D SELECT on project SELECT on project WITH GRANT OPTION WITH GRANT OPTION Horizontal = 1, Vertical = 0 Horizontal = 1, Vertical = 1 W E F Who can keep granting SELECT on PROJECT to others? 49" }, { "page_index": 790, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_050.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_050.png", "page_index": 790, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:10+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Specifying Limits on Propagation of Privileges Draw a grant graph to show propagation of privileges SELECT on PROJECT of the COMPANY database as follows: n User D grants SELECT on PROJECT to user F with GRANT OPTION using horizontal propagation = 1 and vertical propagation = 1. DBA SELECT on project WITH GRANT OPTION Horizontal = 3, Vertical = 3 W A SELECT on project WITH GRANT OPTION SELECT on project WITH GRANT OPTION Horizontal = 1, Vertical = 2 Horizontal = 2, Vertical = 1 SELECT on project B C D SELECT on project SELECT on project WITH GRANT OPTION WITH GRANT OPTION Horizontal = 1, Vertical = 0 Horizontal = 1, Vertical = 1 W E F Who can keep granting SELECT on PROJECT to others? B, F 50" }, { "page_index": 791, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_051.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_051.png", "page_index": 791, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:17+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Demonstration on MySQL Syntax of GRANT/ REVOKE GRANT priv_type : { static l dynamic privileges } priv_type [(column list)] [, priv type [(column list)]] ON object_type: { [object type] priv level TO TABLE user or role [, user or role] FUNCTION [WITH GRANT OPTION] PROCEDURE [AS user WITH ROLE DEFAULT priv level: NONE * ALL ALL EXCEPT role [, role ] .. name.* role [, role ] .. db_name.tbl_name 1 1 tbl name alb name.routinename - Static privileges: built-in to the server Dynamic privileges: defined at runtime 51 Source: MySQL 8.0 Reference Manual, 2020" }, { "page_index": 792, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_052.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_052.png", "page_index": 792, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:23+07:00" }, "raw_text": "Discretionary access control based on granting and revoking privileges Demonstration on MySQL Syntax of GRANT/ REVOKE priv_type : { static l dynamic privileges } Table 13.11 Permissible Static Privileges for GRANT and REVOKE Privilege Meaning and Grantable Levels ALL [PRIVILEGES] Grant all privileges at specified access level except GRANT OPTIONand PROXY. ALTER Enable use of ALTERTABLE.Levels:Global.database.table ALTER ROUTINE Enable stored routines to be altered or dropped. Levels: Global, database,routine CREATE Enable database and table creation. Levels: Global,database,table CREATE ROLE Enable role creation.Level: Global. CREATE ROUTINE Enable stored routine creation.Levels: Global,database. CREATE TABLESPACE Enable tablespaces and log file groups to be created, altered, or dropped. Level:Global. 52 Source: MySQL 8.0 Reference Manual, 2020." }, { "page_index": 793, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_053.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_053.png", "page_index": 793, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:29+07:00" }, "raw_text": "Discretionary access control based on granting and revoking privileges Demonstration on MySQL Syntax of GRANT/ REVOKE priv_type : { static l dynamic privileges } Table 13.12 Permissible Dynamic Privileges for GRANT and REVOKE Privilege Meaning and Grantable Levels APPLICATION PASSwORD ADEnable dual password administration.Level: Global AUDIT ADMIN Enable audit log configuration. Level: Global. BACKUP ADMIN Enable backup administration. Level: Global. BINLOG ADMIN Enable binary log control. Level: Global. BINLOG ENCRYPTION ADMIN Enable activation and deactivation of binary log encryption. Level: Global. CLONE ADMIN Enable clone administration.Level:Global. CONNECTION ADMIN Enable connection limit/restriction control.Level:Global. ENCRYPTION KEY ADMIN Enable InnoDB key rotation. Level: Global. FIREWALL ADMIN Enable firewall rule administration, any user. Level: Global. 53 Source: MySQL 8.0 Reference Manual, 2020." }, { "page_index": 794, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_054.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_054.png", "page_index": 794, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:33+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Demonstration on MySQL SyntaX of GRANT/ REVOKE REVOKE priv type [(column list)] [, priv_type [(column list)]] ON [object_type] priv_level FROM user or rolel, REVOKEALL[PRIVILEGES], C GRANT OPTION FROM user or role [, Check partial revocations with MySQL. 54 Source: MySQL 8.0 Reference Manual, 2020" }, { "page_index": 795, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_055.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_055.png", "page_index": 795, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:39+07:00" }, "raw_text": "Discretionary y access control based on granting revoking privileges j and Demonstration on MySQL 0 Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: a. Account A can retrieve or modify any relation except DEPENDENT and can grant any of these privileges to other users. b. Account B can retrieve all the attributes of EMPLOYEE and DEPARTMENT except for Salary, Mgr_ssn, and Mgr_start_date. c. Account C can retrieve or modify WORKS_ON but can only retrieve the 0 Fname, Minit, Lname, and Ssn attributes of EMPLOYEE and the Pname and Pnumber attributes of PROJECT controlled by department Research. d. Account D can retrieve any attribute of EMPLOYEE or DEPENDENT and can modify DEPENDENT except for Relationship attribute and can grant any of these privileges to other users. e. Account E can retrieve or modify EMPLOYEE but only for EMPLOYEE tuples of the employees who work for projects and departments in Houston. f. Account F can retrieve or modify DEPARTMENT and DEPT_LOCATIONS but 0 can only retrieve the Pnumber, Dnum, and Plocation attributes of PROJECT. g. X wants to revoke the privileges from user A and the modification privileges on DEPENDENT from user D. 55" }, { "page_index": 796, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_056.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_056.png", "page_index": 796, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:44+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Demonstration on MySQL 0 Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: a. Account A can retrieve or modify any relation except DEPENDENT and can grant any of these privileges to other users. GRANT SELECT, INSERT, DELETE, UPDATE ON company.employee TO A WITH GRANT OPTION GRANT SELECT, INSERT, DELETE, UPDATE ON company.department TO A WITH GRANT OPTION; GRANT SELECT, INSERT, DELETE, UPDATE ON company.dept_locations TO A WITH GRANT OPTION; GRANT SELECT, INSERT, DELETE, UPDATE ON company.project TO A WITH GRANT OPTION; GRANT SELECT, INSERT, DELETE, UPDATE ON company.Works_on TO A WITH GRANT OPTION; 56" }, { "page_index": 797, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_057.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_057.png", "page_index": 797, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:48+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Demonstration on MySQL Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: b. Account B can retrieve all the attributes of EMPLOYEE and DEPARTMENT except for Salary, Mgr_ssn, and Mgr_start_date. GRANT SELECT(ssn, fname, minit, Iname, bdate, sex, address, super_ssn, dno ON company.employee TO B; GRANT SELECT(dnumber, dname) ON company.department TO B; 57" }, { "page_index": 798, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_058.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_058.png", "page_index": 798, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:53+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Demonstration on MySQL 0 l Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: c. Account C can retrieve or modify WORKS_ON but can only retrieve the Fname, Minit, Lname, and Ssn attributes of EMPLOYEE and the Pname and Pnumber attributes of PROJECT controlled by department Research. GRANT SELECT, INSERT, DELETE, UPDATE ON company.Works_on TO C; GRANT SELECT(fname, minit, Iname, ssn) ON company.employee TO C; CREATE VIEW cProject AS SELECT pname, pnumber FROM project WHERE dnum IN (SELECT dnumber FROM department WHERE dname = 'Research'); GRANT SELECT ON company.cProject TO C; Check UPDATABLE VIEW in DBMSs for INSERT, DELETE, UPDATE on vieWs" }, { "page_index": 799, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_059.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_059.png", "page_index": 799, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:54:59+07:00" }, "raw_text": "CREATE CREATE VIEW (MySQL) [OR REPLACE] IALGORITHM =IUNDEFINED IMERGEI TEMPTABLE} 1 DEFINER = userl [SQL SECURITY IDEFINER l INVOKER }1 vIEw view name [(column list)l AS select statement [WITH [CASCADED I LOCAL] CHECK OPTION1 1 Some views are updatable. That is, you can use them in statements such as UPDATE, DELETE, or INSERT to update the contents of the underlying table. For a view to be updatable, there must be a one-to-one relationship between the rows in the view and the rows in the underlying table. There are also certain other constructs that make a view nonupdatable. The wITH CHECK OPTION clause can be given for an updatable view to prevent inserts to rows for which the wHERE clause in the se1ect statement is not true. It also prevents updates to rows for which the wHERE clause is true but the update would cause it to be not true (in other words, it prevents visible rows from being updated to nonvisible rows). In a wITH CHECK OPTION clause for an updatable view, the LOCAL and CASCADED keywords determine the scope of check testing when the view is defined in terms of another view. The LocA keyword restricts the CHECK OPT ION only to the view being defined. CASCADED causes the checks for underlying views to be evaluated as well. When neither keyword is given, the default is cAscADED. 59" }, { "page_index": 800, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_060.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_060.png", "page_index": 800, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:05+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Demonstration on MySQL 0 Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: d. Account D can retrieve any attribute of EMPLOYEE or DEPENDENT and can modify DEPENDENT except for Relationship attribute and can grant any of these privileges to other users. GRANT SELECT ON company.employee TO D WITH GRANT OPTION; GRANT SELECT ON company.dependent TO D WITH GRANT OPTION; GRANT INSERT(essn, dependent_name, bdate, sex) DELETE, UPDATE(essn, dependent_name, bdate, sex) ON company.dependent TO D WITH GRANT OPTION; 60" }, { "page_index": 801, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_061.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_061.png", "page_index": 801, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:10+07:00" }, "raw_text": "Discretionary access control based on granting and revoking privileges Demonstration on MySQL 0 Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: e. Account E can retrieve or modify EMPLOYEE but only for EMPLOYEE tuples of the employees who work for projects and departments in Houston. CREATE VIEW eEmployee AS SELECT * FROM employee WHERE ssn IN (SELECT DISTINCT essn FROM works_on JOIN project ON pno = pnumber WHERE plocation = 'Houston') AND dno IN (SELECT dnumber FROM dept locations WHERE dlocation = 'Houston'); GRANT SELECT, INSERT, DELETE, UPDATE ON company.eEmployee TO E; Check UPDATABLE VIEW in DBMSs for INSERT, DELETE, UPDATE on vieWs.61" }, { "page_index": 802, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_062.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_062.png", "page_index": 802, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:16+07:00" }, "raw_text": "Discretionary access control based on c granting revoking privileges j and Demonstration on MySQL 0 Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: n f. Account F can retrieve or modify DEPARTMENT and DEPT_LOCATIONS but can only retrieve the Pnumber, Dnum, and Plocation attributes of PROJECT. GRANT SELECT, INSERT, DELETE, UPDATE ON company.department TO F; GRANT SELECT, INSERT, DELETE, UPDATE ON company.dept_locations TO F; CREATE VIEW fProject AS SELECT pnumber, dnum, plocation FROM project; GRANT SELECT ON company.fProject TO F. -- instead of view fProject GRANT SELECT (pnumber, dnum, plocation) ON company.project TO F: 62" }, { "page_index": 803, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_063.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_063.png", "page_index": 803, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:21+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges j and Demonstration on MySQL Some requirements on the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user root, who wants to grant/ revoke the following privileges to/ from user accounts A, B, C, D, E, and F: g. root wants to revoke the privileges from user A and the modification privileges on WORKS_ON from user C. REVOKE SELECT, INSERT, DELETE, UPDATE ON company.employee FROM A; REVOKE SELECT, INSERT, , DELETE, UPDATE ON company.department FROM A; REVOKE SELECT, INSERT, DELETE, UPDATE ON company.dept_locations FROM A; REVOKE SELECT, INSERT, DELETE, UPDATE ON company.project FROM A; REVOKE SELECT, INSERT, DELETE, UPDATE ON company.Works_on FROM A; -- REVOKE ALL PRIVILEGES ON company.* FROM A; REVOKE INSERT, DELETE, UPDATE ON company.Works_on FROM C; -- Check how well MySQL works with GRANT OPTION. 63" }, { "page_index": 804, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_064.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_064.png", "page_index": 804, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:25+07:00" }, "raw_text": "Discretionary access control based on 0 granting revoking privileges and Strengths of DAC for database security Ensure data availability for authorized users Weaknesses of DAC for database security An all-or-nothing method: A user either has or does not have a certain privilege. A finer privilege granularity Vulnerability to malicious attacks, such as Trojan horses embedded in application programs Discretionary authorization models do not impose any control on how information is propagated and used once it has been accessed by users authorized to do so. 64" }, { "page_index": 805, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_065.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_065.png", "page_index": 805, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:29+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Weaknesses of DAC for database security Trojan horses embedded in application programs DAC read Program Grade Trustin fail to read. Tricky Tricky failed to read Grade table! 65 Source: R. Ramakrishnan, J. Gehrke, Database Management Systems - 2nd Edition, McGraw-Hill, 20o0" }, { "page_index": 806, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_066.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_066.png", "page_index": 806, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:33+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Weaknesses of DAC for database security Trojan horses embedded in application programs DAC read Program Grade Trustin fail to read. MineAllMine Tricky Trojan Horse Tricky modified Program with Trojan Horse and MineAllMine. 66 Source: R. Ramakrishnan, J. Gehrke, Database Management Systems - 2nd Edition, McGraw-Hill, 20o0" }, { "page_index": 807, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_067.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_067.png", "page_index": 807, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:37+07:00" }, "raw_text": "Discretionary access control based on granting revoking privileges and Weaknesses of DAC for database security Trojan horses embedded in application programs DAC read Program Grade Trustin write MineAllMine Tricky Trojan Horse Tricky is now ab/e to read Grade table via MineAllMine table! 67 Source: R. Ramakrishnan, J. Gehrke, Database Management Systems - 2nd Edition, McGraw-Hill, 20o0" }, { "page_index": 808, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_068.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_068.png", "page_index": 808, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:43+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) : Controls access based on comparing security labels (which indicate how sensitive or critical system resources are) with security clearances (which indicate system entities are eligible to access certain resources) . This policy is termed mandatory because an entity that has clearance to access a resource may not, just by its own volition (i.e. the power to make own decisions, quyén tu quyét), enable another entity to access that resource. Role-based access control (RBAC): Controls access based on the roles that users have within the system and on rules stating what accesses are allowed to users in given roles. Attribute-based access control (ABAC) : Controls access based on attributes of the user, the resource to be accessed, and current environmental conditions. Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, 68 Third Edition, Pearson Education, Inc., 2015." }, { "page_index": 809, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_069.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_069.png", "page_index": 809, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:47+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) An approach that adds security classes of data and users into the discretionary access control mechanism Fine-grained access modes instead of the binary mode Multilevel security (MLS, bao mat da müc) The commonly used model for multilevel security, known as the Bell-LaPadula model Further reading : Bell, D., and LaPadula, L. \"Secure Computer Systems: Mathematical Foundations.\" MTR-2547, Vol. I, The MITRE Corporation, Bedford, MA, 1 March 1973. Bell, D. \"Looking Back at the Bell-Lapadula Model.\" Proceedings of the 21st Annual IEEE Computer Security Applications Conference, 2005. 69" }, { "page_index": 810, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_070.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_070.png", "page_index": 810, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:51+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) For simplicity, four security classification levels are used: top secret (Ts), secret (S), confidential (C), and unc/assified (U), where Ts is the highest level and U the lowest. TS z S z C z U Each subject (user, account, program) and object (relation, tuple, column, view, operation) are classified into one of the security classifications TS, S, C, or U. The clearance (classification) of a subject S is c/ass(S)) Decided according to the trustworthiness of each subject The classification of an object O is c/ass(O Decided according to the sensitivity of each object 70" }, { "page_index": 811, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_071.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_071.png", "page_index": 811, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:55:56+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory y access control (MAC) The requirement for confidentiality-centered multilevel security is that a subject at a high level may not convey information to a subject at a /ower /eve/ unless that flow accurately reflects the will of an authorized user as revealed by an authorized declassification. No information flows from higher to lower classifications. Multilevel security enforces: No read up: A subject S can on/y read an object O of /ess or equal security level : class(S) class(O) simple security property (ss-property) No write down: A subject S can on/y write into an object O of greater or equal security level : class(S) class(O). star-property (*-property) 71" }, { "page_index": 812, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_072.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_072.png", "page_index": 812, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:00+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) class class(Grade) = S (Trustin) class(Program) = S MAC read Program Grade Trustin c/ass(MineAllMine) = U class (Tricky) U fail to write MineAllMine Trojan Horse >k Tricky into less secure one: c/ass(Program) = S > c/ass(MineAllMine) = U 72" }, { "page_index": 813, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_073.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_073.png", "page_index": 813, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:04+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) The multilevel model = the relational data model + multilevel security A mu/tilevel re/ation schema R with n attributes would be represented as: R(A1 C Az, Cz ..,An Cn TC) Each C: represents the classification attribute associated with attribute A. - TC = a classification for the tuple t = the highest of all attribute classification values in t = max {C,, C,, ... , C.} The apparent key of a multilevel relation (khóa biéu kién cüa mt quan hé da müc) = the set of attributes that would have formed the primary key in a regular (single- level) relation 73" }, { "page_index": 814, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_074.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_074.png", "page_index": 814, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:08+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security The multilevel model A multilevel relation will appear to contain different data to subjects (users) with different clearance levels. In some cases, it is possible to store a single tuple in the relation at a higher classification level and produce the corresponding tuples at a lower-level classification through a process known as filtering (qua trinh loc) . After filtering, data query/ manipulation processing is normally conducted In other cases, it is necessary to store two or more tuples at different classification levels with the same value for the apparent key. Polyinstantiation (tinh da hinh) : several tuples can have the same apparent key value but have different attribute values for users at different clearance levels. 74" }, { "page_index": 815, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_075.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_075.png", "page_index": 815, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:14+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security The multilevel model The entity integrity rule for multilevel relations states that all attributes that are members of the apparent key must not be null and must have the same security classification within each individual tuple. All other attribute values in the tuple must have a security classification greater than or equal to the security classification of the apparent key. This constraint ensures that a user can see the key if the user is permitted to see any part of the tuple. Other integrity rules, called null integrity and interinstance integrity, informally ensure that if a tuple value at some security level can be filtered (derived) from a higher-classified tuple, then it is sufficient to store the higher-classified tuple in the multilevel relation. 75" }, { "page_index": 816, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_076.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_076.png", "page_index": 816, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:18+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security A multilevel relation: EMPLOYEE Name is an apparent key. EMPLOYEE Name Salary JobPerformance TC Smith U Fair S 40000 C S Brown C 80000 S Good C S class(TC(tuple Smith)) = S = max {U, C, S} class(TC(tuple Brown)) = S = max {C, S, C} class(Name(tuple Smith)) = U = min {U, C, S} class(Name(tuple Brown)) = C = min {C, S, C} 76" }, { "page_index": 817, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_077.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_077.png", "page_index": 817, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:24+07:00" }, "raw_text": "Mandatory access control and role-based A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by Ts users SELECT * FROM EMPLOYEE; EMPLOYEE Name Salary JobPerformance TC Smith U 40000 C Fair S S Brown C 80000 S Good C S Appearance of EMPLOYEE after filtering for classification TS users EMPLOYEE NO READ UP: class(Subject) > class(Object) Name Salary JobPerformance TC Smith U Fair s S 40000 0 Brown C 80000 S Good C S 77" }, { "page_index": 818, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_078.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_078.png", "page_index": 818, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:29+07:00" }, "raw_text": "Mandatory access control and role-based A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by S users SELECT * FROM EMPLOYEE; EMPLOYEE Name Salary JobPerformance TC Smith U 40000C Fair S S Brown C 80000 S Good C S Appearance of EMPLOYEE after filtering for classification S users EMPLOYEE NO READ UP: class(Subject) > class(Object) Name Salary JobPerformance TC Smith U 40000 C Fair S S Brown C 80000 S Good C S 78" }, { "page_index": 819, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_079.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_079.png", "page_index": 819, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:34+07:00" }, "raw_text": "Mandatory access control and role-based A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by C users SELECT * FROM EMPLOYEE; EMPLOYEE Name Salary TC JobPerformance Smith U 40000 Fair S S Brown C 80000 S Good C S Appearance of EMPLOYEE after filtering for classification C users EMPLOYEE NO READ UP: class(Subject) > class(Object) Name Salary JobPerformance TC Smith U 40000 C NULL C C Brown C NULL C Good C C 79" }, { "page_index": 820, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_080.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_080.png", "page_index": 820, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:38+07:00" }, "raw_text": "Mandatory access control and role-based A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by U users SELECT * FROM EMPLOYEE; EMPLOYEE Name Salary TC JobPerformance Smith U 40000 Fair S S Brown C 80000 S Good C S Appearance of EMPLOYEE after filtering for classification U users NO READ UP: class(Subject) class(Object) EMPLOYEE Name Salary JobPerformance TC Smith U NULL U NULL U U 80" }, { "page_index": 821, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_081.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_081.png", "page_index": 821, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:46+07:00" }, "raw_text": "Mandatory access control and role-based o A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by TS users UPDATE EMPLOYEE SET JobPerformance =`Excellent EMPLOYEE WHERE Name = `Smith'; Name Salary JobPerformance TC Smith U 40000 Fair S S Brown C 80000 S Good C S No update for the `Smith' tuple at the higher classification level TS of the user because the user is not allowed to overwrite the existing value of JobPerformance at the lower classification level S NO WRITE DOWN: class(Subject) < class(Object) EMPLOYEE Name Salary JobPerformance TC Smith U 40000 C Fair S S Brown C 80000 S Good C S 81" }, { "page_index": 822, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_082.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_082.png", "page_index": 822, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:52+07:00" }, "raw_text": "Mandatory access control and role-based o A multiIevel relation: EMPLOYEE Name is an apparent key. -- issued by S users UPDATE EMPLOYEE SET JobPerformance = `Excelent EMPLOYEE WHERE Name =`Smith'; Name Salary JobPerformance TC Smith U 40000 Fair S S Brown C 80000 S Good C S Update the `Smith' tuple at the same classification level S of the user because the user is allowed to overwrite the existing value of JobPerformance at the same classification level S NO WRITE DOWN: class(Subject) < class(Object EMPLOYEE Name Salary JobPerformance TC Smith U 40000C Excellent S S Brown C 80000 S Good C S 82" }, { "page_index": 823, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_083.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_083.png", "page_index": 823, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:56:59+07:00" }, "raw_text": "Mandatory access control and role-based o A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by C users UPDATE EMPLOYEE SET JobPerformance =`Excellent EMPLOYEE WHERE Name = `Smith'; Name Salary JobPerformance TC Smith U 40000 C Fair S S Brown C 80000 S Good C S Create a polyinstantiation for the 'Smith' tuple at the lower classification level C because the user is not allowed to overwrite the existing value of JobPerformance at the higher classification level NO WRITE DOWN: class(Subject) < class(Object) EMPLOYEE Name Salary JobPerformance TC Smith U 40000 C Fair S S Smith U 40000 C Excellent C C Brown C 80000 S Good C S 83" }, { "page_index": 824, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_084.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_084.png", "page_index": 824, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:06+07:00" }, "raw_text": "Mandatory access control and role-based o A multilevel relation: EMPLOYEE Name is an apparent key. -- issued by U users UPDATE EMPLOYEE SET JobPerformance =`Excellent EMPLOYEE WHERE Name = `Smith'; Name Salary JobPerformance TC Smith U 40000 C Fair S S Brown C 80000 S Good C S Create a polyinstantiation for the 'Smith' tuple at the lower classification level U because the user is not allowed to overwrite the existing value of JobPerformance at the higher classification level NO WRITE DOWN: class(Subject) < class(Object) EMPLOYEE Name Salary JobPerformance TC Smith U 40000C Fair S S Smith U NULL U Excellent U U Brown C 80000 S Good C S 84" }, { "page_index": 825, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_085.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_085.png", "page_index": 825, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:10+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Mandatory access control (MAC) Mandatory policies ensure a high degree of protection-in a way, they prevent any illegal flow of information for data confidentiality. MAC is suitable for military and high-security types of applications, which require a higher degree of protection. Weaknesses MAC is too rigid in that a strict c/assification of subiects and objects into security levels is required. MAC is applicable to few environments. Few DBMSs implemented MAC 85" }, { "page_index": 826, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_086.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_086.png", "page_index": 826, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:16+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Role-based access control (RBAC) 0 Role: a named set of privileges that can be granted to users or to other roles Its basic notion is that privileges and other permissions are associated with organizational roles rather than with individual users. Each user may have several different roles. However, they cannot be used simultaneously by the user. They are mutually exclusive. Mutual exclusion of roles can be categorized into two types namely authorization time exclusion (static) and runtime exclusion (dynamic) In authorization time exclusion, two roles that have been specified as mutually exclusive cannot be part of a user's authorization at the same time. In runtime exclusion, both these roles can be authorized to one user but cannot be activated by the user at the same time. 86" }, { "page_index": 827, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_087.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_087.png", "page_index": 827, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:20+07:00" }, "raw_text": "Mandatory access control and role-based access control for multilevel security Role-based access control (RBAC) Multiple individuals can be assigned to each role. Security privileges that are common to a role are granted to the role name, and any individual assigned to this role would automatically have those privileges granted. RBAC can be used with traditional discretionary and mandatory access controls. RBAC ensures that only authorized users in their specified roles are given access to certain data or resources. Many DBMSs have allowed the concept of roles, where privileges can be assigned to roles. Oracle, MS SQL Sever, MySQL, HBase, MongoDB, ... 87" }, { "page_index": 828, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_088.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_088.png", "page_index": 828, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:24+07:00" }, "raw_text": "Inference control Statistical databases are used mainly to produce 0 statistics about various populations. The database may contain confidential data about individuals; this information should be protected from user access. Users are permitted to retrieve statistical information about the populations, such as averages, sums, counts, maximums, minimums and standard deviations. Users are not allowed to retrieve individual data. PROBLEM: Inference can be made from statistical information to derive individual data. 88" }, { "page_index": 829, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_089.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_089.png", "page_index": 829, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:28+07:00" }, "raw_text": "Inference control Non sensitive Sensitive data Inference data Accesscontrol Authorized Unauthorized access access Metadata Figure 5.7 Indirect Information Access via Inference Channel Source: W. Stallings, L. Brown, Computer Security - Principles and Practice, 89 Third Edition, Pearson Education, Inc., 2015." }, { "page_index": 830, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_090.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_090.png", "page_index": 830, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:31+07:00" }, "raw_text": "Inference control Inference control is needed to prohibit the retrieval of individual data from statistical databases. This is related to privacy protection of users in the statistical database. For example, the COMPANY database is not allowed to be used for the queries on individual employees' salaries, but the aggregation queries. What happens if we obtain the number of employees and their average salary in department 1? 90" }, { "page_index": 831, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_091.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_091.png", "page_index": 831, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:40+07:00" }, "raw_text": "Inference control EMPLOYEE Fname Minit Lname Ssn Bdate Address Sex Salary Super_ssn Dno John B Smith 123456789 1965-01-09 731 Fondren.Houston.TX M 30000 333445555 5 Franklin T Wong 333445555 1955-12-08 638 Voss,Houston,TX M 40000 888665555 5 Alicia J Zelaya 999887777 1968-01-19 3321 Castle,Spring.TX F 25000 987654321 4 Jennifer S Wallace 987654321 1941-06-20 291Berry,Bellaire,TX F 43000 888665555 4 Ramesh K Narayan 666884444 1962-09-15 975 Fire Oak,Humble,TX M 38000 333445555 5 Joyce A English 453453453 1972-07-31 5631 Rice,Houston,TX F 25000 333445555 5 Ahmad V Jabbar 987987987 1969-03-29 980 Dallas,Houston,TX M 25000 987654321 4 James E Borg 888665555 1937·11-10 450 Stone,Houston,TX M 55000 NULL 1 What happens if we obtain the number of employees and their average salary in department 1? NumberOfEmployees AverageSalary SELECT COUNT(*), AVG(salary) 1 55000.000000 FROM employee If we know Borg with department 1 WHERE dno = 1; the average salary is his! 91" }, { "page_index": 832, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_092.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_092.png", "page_index": 832, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:44+07:00" }, "raw_text": "Inference control So/utions to inference control To disallow statistical queries whenever the number of tuples in the population specified by the selection condition falls below some threshold. To prohibit sequences of queries that refer repeatedly to the same population of tuples. To introduce slight inaccuracies or noise into the results of statistical queries deliberately, to make it difficult to deduce individual information from the results. Partitioning of the database: records are stored in groups of some minimum size, queries can refer to any complete group or set of groups, but never to subsets of records within a group. 92" }, { "page_index": 833, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_093.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_093.png", "page_index": 833, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:48+07:00" }, "raw_text": "Fow contro Flow control regulates the distribution or flow of information among accessible objects. C Flow controls check that information contained in some objects does not flow explicitly or implicitly into /ess protected objects. A flow between object X and object Y occurs when a program reads values from X and writes values into Y. Flow control ensures that a user cannot get indirectly in Y what he or she cannot get directly in X. 93" }, { "page_index": 834, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_094.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_094.png", "page_index": 834, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:53+07:00" }, "raw_text": "Fow control Most flow controls employ some concept of security class; the transfer of information from a sender to a receiver is allowed only if the receiver's security class is at least as privileged as the sender's. Examples of a flow control include preventing a service program from leaking a customer's confidential data, and blocking the transmission of secret military data to an unknown classified user. A flow policy specifies the channels along which information is allowed to move. For example, the simplest flow policy specifies just two classes of information-confidential (C) and non-confidential (N)-and allows all flows except those from class C to class N. Confidential Confidential Confidential x Non-confidential Non-confidential Confidential Non-confidential Non-confidential 94" }, { "page_index": 835, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_095.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_095.png", "page_index": 835, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:57:58+07:00" }, "raw_text": "Fow control Flow controls can be enforced by an extended access 0. control mechanism, which involves assigning a security class (usually called the clearance) to each running program. The program is allowed to read a particular memory segment only if its security class is as high as that of the segment. The program is allowed to write in a segment only if its class is as low as that of the segment. This automatically ensures that no information transmitted by the person can move from a higher to a lower class. For example, a military program with a secret clearance can only read from objects that are secret, unclassified, or confidential and can only write into objects that are secret and top secret read Secret program Secret/ Unclassified/ Confidential objects write Secret program Secret/ Top secret objects 95" }, { "page_index": 836, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_096.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_096.png", "page_index": 836, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:03+07:00" }, "raw_text": "Fow control Two types of flow can be distinguished: explicit flows, which occur as a consequence of assignment instructions: Y:= f(X1,Xn) Xn) then Y := f(X1, Xm) Flow control mechanisms must verify that only authorized flows, both explicit and implicit, are executed. A covert channel (kénh an) allows a transfer of information that violates the security or the policy, i.e. allows information to pass from a higher classification level to a lower classification Ievel through improper means. A timing channel: a channel where the information is conveyed (giao tiép) by the timing of events or processes. A storage channel: a channel where information is conveyed by accessing system information or what is otherwise inaccessible to the user. Covert channels are not a major problem in well-implemented robust database implementations. 96" }, { "page_index": 837, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_097.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_097.png", "page_index": 837, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:07+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Suppose data are being transferred (communicated), 0 but data falls into the hands of a nonlegitimate user (nguöi düng bat hop phap). By using encryption, the message can be disguised (bi thay dói) so that even if the transmission is diverted (bi dói huóng), the message will not be revealed (duoc biét). Encryption is the conversion of data into a form, called a ciphertext, that cannot be easily understood by unauthorized persons. Confidentiality is ensured. Encryption enhances security and privacy when access controls are bypassed, because in cases of data loss or theft, encrypted data cannot be easily understood by unauthorized persons. 97" }, { "page_index": 838, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_098.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_098.png", "page_index": 838, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:10+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Definition: change of electronic information or signals into a secret code (=system of letters, numbers or symbols) that people cannot understand or use on normal equipment Four parts of cryptography Plaintext (bän rö) Ciphertext (ban ma) Encryption algorithm (cipher/cryptosystem) (mä hóa) Key (khóa) 98" }, { "page_index": 839, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_099.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_099.png", "page_index": 839, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:14+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption process (quä trinh ma h6a) Encryption key This is 123@8@ Plaintext Encryption 0kf/30kfl Plaintext Ciphertext Decryption process (quä trinh giai mä) Decryption Key 123@8@ This is 0kfl30kfl Decryption Plaintext Plaintext Ciphertext 99" }, { "page_index": 840, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_100.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_100.png", "page_index": 840, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:17+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption types Symmetric (private/secret) key encryption The same secret key to encrypt/decrypt a message Sender/receiver must exchange the key securely. Algorithm: the Data Encryption Standard (DES) with a key length of 56 bits, Triple DES, the Advanced Encryption Standard (AES) by NIST, .. 100" }, { "page_index": 841, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_101.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_101.png", "page_index": 841, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:23+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption types Symmetric (private/secret) key encryption (ma h6a kh6a d6i xüng) Secret key shared by Secret key shared by sender and recipient 123@8 sender andrecipient Oktl30k1l K K This is Transmitted This is Plaintext x ciphertext Plaintext Y=E[K,X] X=D[K,Y] Plaintext Plaintext Encryption algorithm Decryption algorithm input output e.g.DES) (reverse ofencryption algorithm) Key transfer and management? 101" }, { "page_index": 842, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_102.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_102.png", "page_index": 842, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:28+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption types Asymmetric (public) key encryption Two keys for encryption/decryption: a public key and a private key The private key is kept secret by its owner. The public key is freely distributed If the public key is used to encrypt a message, only the corresponding private key can decrypt the corresponding ciphertext and vice versa. Algorithm: the RSA public key algorithm (www.rsasecurity.com with a key length of 512-1024 bits One of the first public key schemes was introduced in 1978 by Ron Rivest, Adi Shamir, and Len Adleman at MIT. 102" }, { "page_index": 843, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_103.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_103.png", "page_index": 843, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:34+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption types Asymmetric (public) key encryption (mä hóa kh6a bat dói xüng) Receiver's Receiver's public key private key 1238 This is This is Plaintext Encryption 0ktl30k1l Plaintext wyptian Ciphertext Plaintext Plaintext - Receiver's public key & receiver's private key - Sender's private key & sender's public key More complexity, slower than Symmetric Key Encryption! 103" }, { "page_index": 844, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_104.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_104.png", "page_index": 844, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:38+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Asymmetric (public) key encryption Bobs's public key ring Joy Ted 2 Alice Mike 1238 PUa Alice's public PRa Alice's private 0kt130k1l key key Transmitted x = This is This is x ciphertext D[PRaY] Plaintext Plaintext Y=E[PUaX] Plaintext Plaintext Encryption algorithm Decryption algorithm input output (e.g., RSA) Bob Alice (a) Encryption with public key Data Confidentiality 104" }, { "page_index": 845, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_105.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_105.png", "page_index": 845, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:44+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Asymmetric (public) key encryption Alice's public key ring 3 Joy Tec Mike Bob 1238 PRb PUb Bob's private Bob's public Oktl30k1l key key Transmitted x= This is This is x ciphertext D[PUbY] Plaintext Plaintext Y=E[PRpX] Plaintext Plaintext Encryption algorithm Decryption algorithm input output (e.g., RSA) Bob Alice (a) Encryption with public key Authentication / Data Integrity 105" }, { "page_index": 846, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_106.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_106.png", "page_index": 846, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:47+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Encryption types Asymmetric (public) key encryption for authentication Sender encrypt encrypt Plaintext Ciphertext Receiver's Sender's public key private key Signed Ciphertext Receiver decrypt decrypt Plaintext Ciphertext Receiver's Sender's private key public key authenticates sender 106" }, { "page_index": 847, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_107.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_107.png", "page_index": 847, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:50+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Key agreement protocols Combination of symmetric and public key encryption Rules for communication: exactly what encryption algorithm(s) is (are) going to be used? The most common key agreement protocol to exchange keys over an unsecure medium: a digital envelope 107" }, { "page_index": 848, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_108.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_108.png", "page_index": 848, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:54+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography Digital Envelope (phong bi s6) 1. encrypt Plaintext Ciphertext Symmetric secret key Ciphertext + Encrypted key Encrypted Digital Envelope Symmetric R 2. encrypt symmetric secret key Receiver's secret key public key Receiver 108" }, { "page_index": 849, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_109.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_109.png", "page_index": 849, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:58:57+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Encryption/Cryptography o b Digital Envelope 2. decrypt Ciphertext Ciphertext Plaintext + Encrypted key R 1. decrypt Symmetric Encrypted key secret key Receiver's private key Receiver 109" }, { "page_index": 850, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_110.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_110.png", "page_index": 850, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:01+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Electronic signatures (e-signatures, chü ky só) Definition : the electronic eguivalent of written signatures for authentication Types of e-signatures Signatures based on characters, digits, scanned images sound, .. Signatures based on passwords, PIN codes, biometrics, ... Signatures based on public keys Public Key Infrastructure (PKI), Digital Certificates Certification Authorities s (CA) to authenticate parties in a transaction 110" }, { "page_index": 851, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_111.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_111.png", "page_index": 851, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:05+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Electronic signatures (e-signatures, chü ky só) Definition: the electronic equivalent of written signatures for authentication Types of e-signatures: Signatures based on public keys Public Key Infrastructure (PKI, ha tang khóa cng khai), Digital Certificates (chúng thuc só), Certification Authorities (CA, bén cung cap chüng thuc só) to authenticate parties in a transaction A digital certificate is used to combine the value of a public key with the identity of the person or service that holds the corresponding private key into a digitally signed statement. Certificates are issued and signed by a certification authority (CA), trusted by the parties. 111" }, { "page_index": 852, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_112.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_112.png", "page_index": 852, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:07+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Digital signatures Electronic signatures based on public keys for authentication, integrity, and nonrepudiation Created using the contents of the document Different for each document digitally signed Associated with timestamping for nonrepudiation 112" }, { "page_index": 853, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_113.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_113.png", "page_index": 853, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:11+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Step1: Compute the message digestof the file Message Digest Digital Step2: Step3: Signature File +DigitalSignature Encrypt the message Send the file and (signed file) digital signature digest with sender's private key (signed file Steps in digital signature generation - Hashing the file to obtain the message digest 113" }, { "page_index": 854, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_114.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_114.png", "page_index": 854, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:15+07:00" }, "raw_text": "Encryption and Public Key Infrastructure Signed file Receiver Sender Digital File Signature Step1a: Step1b: Find themessage Decrypt the digital digest of the file signature with sender's public key Message Message Digest Digest Step2: Same Compare the two message Accept digests Different Reject Steps in digital signature verification 114" }, { "page_index": 855, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_115.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_115.png", "page_index": 855, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:23+07:00" }, "raw_text": "Security in Principals Sccurablcs DBMSs Windows Level new Windows group Windows domain logir Windows local login Principals : SQL Server Level Fixed server role Entities that can request SQL Server Login Microsoft SQL Server SQL Server resources, Arranged in a hierarchy SQL Server Login Endpoint Database Each has a security Database Level identifier. Fixed database role Database Database Database user Securab/es: The resources to Applicationrole Applicationrole Schema Assembly Asymmetric key which the SQL Server Certificate Schema Contract Database Engine Full-text catalog Message type Remote service binding Schema authorization system Role Route regulates access Service Symmetric key User Endpoint: Each database Schema Database mirroring server instance Schema requires a unique listener Database Table Schema View port that is assigned to the Function Procedure Schema database mirroring endpoint Queue Synonym of the instance. Type XMLschema collection Source: MS SQL Server Books Online 115" }, { "page_index": 856, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_116.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_116.png", "page_index": 856, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:28+07:00" }, "raw_text": "Security in new DBMSs Oracle 19c Oracle Database can authenticate users attempting to connect to a database by using information stored in that database itself. To configure Oracle Database to use database authentication, each user must be created with an associated password. Oracle Database generates a one-way hash of the user's password and stores it for use when verifying the provided login password. the salted SHA-1 hashing algorithm n the salted PKBDF2 SHA-2 SHA-512 hashing algorithm Oracle Database records the password versions in the DBA USERS data dictionary view 116 Source: 0racle Database Security Guide, 19c, E96299-10, 2020" }, { "page_index": 857, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_117.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_117.png", "page_index": 857, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:34+07:00" }, "raw_text": "Security in new DBMSs MySQL 8.0 SHA-256 Pluggable Authentication: two authentication plugins that implement SHA-256 hashing for user account passwords : sha256_password: Implements basic SHA-256 authentication. In the name sha256_password, \"sha256\" refers to the 256-bit digest length the plugin uses for encryption. caching sha2 password: Implements SHA-256 authentication (like sha256_password), but uses caching on the server side for better performance and has additional features for wider applicability The default authentication plugin rather than mysql_native_password. In the name caching_sha2_password, \"sha2\" refers more generally to the SHA-2 class of encryption algorithms, of which 256-bit encryption is one instance. The latter name choice leaves room for future expansion of possible digest lengths without changing the plugin name. 117 Source: MySQL 8.0 Reference Manual, 2020." }, { "page_index": 858, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_118.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_118.png", "page_index": 858, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:37+07:00" }, "raw_text": "Security in new DBMSs NoSQL DBMSs HBase e (The Hadoop Database, hbase.apache.org) write to a given HBase resource or execute a coprocessor endpoint, using the familiar paradigm of roles. D GRANT/ REVOKE 0 MongoDB (mongodb.org) RBAC: enabled or disabled (default) to govern each user's access to database resources and operations 118" }, { "page_index": 859, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_119.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_119.png", "page_index": 859, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:46+07:00" }, "raw_text": "Risk Management in the System Security Life Cycle STARTING POINT SPB00-37/ FIPS199/ FPS200/ SP800-53A SP800-60 SP800-53 Security Security Security Control Control Categorization Monitoring Selcction Continuously tack dhanges lo the -Define criticallysensitivity of .Seects baseline(mririmum) security informationsysterm that may affect irformation system according to controls ta protect the nformation security conlrclsandreassess polentialimpactofloss system.apply tailoring guidance as controleffeclivaness appropriate SP800-53/ SP800-37 SP800-30 Socurity Security Control Authorization Retinement -Detemmine risk to agency -Use r sk assessment results to operations.agency assels.o supplement the taiored security D'M1b individualsand.if accoptable control baeeineas needed to eneure authorize infomation system adequate security and cue diigence operation SP800-53A SP800-70 SP800-18 Security Security Security Control Control Control Assessment mplementation Documentation Determine secunty control lmplements security controls Document in the security plan,the effectiveneaa(i e..controls aoplysecurrycorfiglration secunity reguirementa for the implemented correcty.operating settings infomatior systerm the secur ty as irtended,meetng security controls planned cr in place requiremen.s) Source: P. Bowen, J. Hash, M. Wilson. Information Security Handbook: A Guide for Managers, NIsT 119 Special Publication 800-10, 2006." }, { "page_index": 860, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_120.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_120.png", "page_index": 860, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:49+07:00" }, "raw_text": "Summary Database security refers to protection from malicious 0 access : Unauthorized reading of data (theft of information), Unauthorized modification of data, Unauthorized destruction of data. To protect the database, security measures must be taken into account at several Ievels: Database system: authorization to data access Operating system: authorization to database system access Network: secured remote access via terminals and networks Physical: physically secured sites with computer systems Human: Users must be authorized carefully to reduce the chance of any user giving access to an intruder. 120" }, { "page_index": 861, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_121.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_121.png", "page_index": 861, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:53+07:00" }, "raw_text": "Summary Integrity constraints ensure that changes made to the database by authorized users do not result in a loss of data consistency. The data stored in the database need to be malicious destruction or alteration, and accidental introduction of inconsistency. Threats to databases Loss of integrity Loss of availability Loss of confidentiality 121" }, { "page_index": 862, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_122.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_122.png", "page_index": 862, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T11:59:57+07:00" }, "raw_text": "Summary Four main control measures are used to provide security of data in databases : Access control Inference control Flow control Data encryption In a muItiuser database system, the DBMS must provide techniques to enable certain users or user groups to access selected portions of a database without gaining access to the rest of the database. Discretionary security mechanisms Discretionary access control based on granting and revoking privileges Mandatory security mechanisms Mandatory access control and role-based access control for multilevel security 122" }, { "page_index": 863, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_123.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_123.png", "page_index": 863, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:01+07:00" }, "raw_text": "Summary The database administrator (DBA) is the central 0 authority for managing a database system. The DBA's responsibilities include granting privileges to users who need to use the system and classifying users and data in accordance with the policy of the organization. The DBA has a DBA account in the DBMS, sometimes called a system or superuser account, which provides powerful capabilities that are not made available to regular database accounts and users. DBA-privileged commands include commands for granting and revoking privileges to individual accounts, users, or user groups and for performing the following types of actions: Account creation Privilege granting Privilege revocation Security level assignment 123" }, { "page_index": 864, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_124.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_124.png", "page_index": 864, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:04+07:00" }, "raw_text": "Chapter Security 7 : Database gues wslin questi answer question uest questy tion cuestion uestion 124" }, { "page_index": 865, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_125.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_125.png", "page_index": 865, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:08+07:00" }, "raw_text": "Review 1. Discuss what is meant by each of the following terms: 0 database authorization, access control, data encryption privileged (system) account, database audit, audit trail, authentication. 2. What is the purpose of having separate categories for index authorization and resource authorization? 3. What are advantages of encrypting data stored in the database? 4. Perhaps the most important data items in any database system are the passwords that control access to the database Suggest a scheme for the secure storage of passwords. Be sure that your scheme allows the system to test passwords supplied by users who are attempting to login to the system. 5. Which account is designated as the owner of a relation? What privileges does the owner of a relation have? 6. Discuss the types of privileges at the account level and those at the relation level. 125" }, { "page_index": 866, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_126.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_126.png", "page_index": 866, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:13+07:00" }, "raw_text": "Review 7. Views are used to simplify access to the database by users who need to see only part of the database. Views are also used as a security mechanism. Do these two purposes for views ever conflict? Explain your answer. 8. How is the view mechanism particularly used as an authorization mechanism? 9. What is meant by granting a privilege? What is meant by revoking a privilege? 10. Discuss the system of propagation of privileges and the restraints imposed by horizontal and vertical propagation limits. 126" }, { "page_index": 867, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_127.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_127.png", "page_index": 867, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:17+07:00" }, "raw_text": "Review 11. What is the difference between discretionary and mandatory access control? 12. What are the typical security classifications? Discuss the simple security property and the *-property, and explain the justification behind these rules for enforcing multilevel security. 13. Describe the multilevel relational data model. Define the following terms: apparent key, polyinstantiation, filtering. 14. What are the relative merits of using DAC or MAC? 15. What is role-based access control? In what ways is it 0 superior to DAC and MAC? 16. What are the two types of mutual exclusion in role-based access control? 17. What is meant by row-level access control? 127" }, { "page_index": 868, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_128.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_128.png", "page_index": 868, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:22+07:00" }, "raw_text": "Review 18. What are the different types of SQL injection attacks? 0 19. What risks are associated with SQL injection attacks? 0 20. What preventive measures are possible against SQL injection 0 attacks? 21. What is a statistical database? Discuss the problem of 0 statistical database security. 22. How is privacy related to statistical database security? What 0 measures can be taken to ensure some degree of privacy in statistical databases? 23. What is flow control as a security measure? What types of flow control exist? 24. What are covert channels? Give examples of covert channels. 0 25. What is the goal of encryption? What process is involved in 0 encrypting data and then recovering it at the other end? 26. What is the public key infrastructure scheme? How does it 0 provide security? 128" }, { "page_index": 869, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_129.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_129.png", "page_index": 869, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:27+07:00" }, "raw_text": "Review 27. Consider the COMPANY database. Suppose that all the relations were created by (and hence are owned by) user X, who wants to grant the following ) I privileges to user accounts A, B, C, D, and E: a. Account A can retrieve or modify any relation except DEPENDENT and can grant any of these privileges to other users. b. Account B can retrieve all the attributes of EMPLOYEE and DEPARTMENT except for Salary, Mgr_ssn, and Mgr_start_date. c. Account C can retrieve or modify WORKS_ON but can only retrieve the Fname, Minit, Lname, and Ssn attributes of EMPLOYEE and the Pname and Pnumber attributes of PROJECT. d. Account D can retrieve any attribute of EMPLOYEE or DEPENDENT and can modify DEPENDENT e. Account E can retrieve any attribute of EMPLOYEE but only for EMPLOYEE tuples that have Dno = 3. Write SQL statements to grant these privileges. Use views where appropriate. 129" }, { "page_index": 870, "chapter_num": 7, "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_130.png", "metadata": { "doc_type": "slide", "course_id": "CO2013", "source_file": "/workspace/data/converted/CO2013_Database_Systems/Chapter_7/slide_130.png", "page_index": 870, "language": "en", "ocr_engine": "PaddleOCR 3.2", "extractor_version": "1.0.0", "timestamp": "2025-10-31T12:00:34+07:00" }, "raw_text": "Review 28. Suppose that privilege (a) of Review 27 is to be given with GRANT OPTION but only so that account A can grant it to at most five accounts, and each of these accounts can propagate the privilege to other accounts but without the GRANT OPTION privilege. What would the horizontal and vertical propagation limits be in this case? 29. Consider the relation EMPLOYEE below. How would it appear to a user with classification U? Suppose that a classification U user tries to update the salary of 'Smith' to $50,000; what would be the result of this action? EMPLOYEE Name Salary JobPerformance TC Smith U 40000C Fair S S Smith U 40000 C Excellent C C Brown C 80000 S Good C S A multilevel relation to illustrate multilevel security. Assume that the Name attribute is the apparent key, and consider the query: SELECT * FROM EMPLOYEE Polyinstantiation of the Smith tuple. 130" } ] }