diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..27d15443c3fe9913c729ead52acfe59e8efb8114
--- /dev/null
+++ b/README.md
@@ -0,0 +1,7 @@
+---
+license: apache-2.0
+---
+
+Link to original dataset: https://yale-lily.github.io/spider
+
+Yu, T., Zhang, R., Yang, K., Yasunaga, M., Wang, D., Li, Z., Ma, J., Li, I., Yao, Q., Roman, S. and Zhang, Z., 2018. Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task. arXiv preprint arXiv:1809.08887.
\ No newline at end of file
diff --git a/test_database/aan_1/aan_1.sqlite b/test_database/aan_1/aan_1.sqlite
new file mode 100644
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+++ b/test_database/aan_1/aan_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:54c45e431f0f654bfac741cf69e66ca34dacf42a0d0abbde6fd426a7a1e60c4b
+size 17154048
diff --git a/test_database/aan_1/annotation.json b/test_database/aan_1/annotation.json
new file mode 100644
index 0000000000000000000000000000000000000000..c1ce791b21e47a6c0914cdf399a3984565a4cc40
--- /dev/null
+++ b/test_database/aan_1/annotation.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ce4b0210d43f0d7552879fc6fd6ef5bae0ca4e1005d2c36ca162b7ae3581060
+size 65
diff --git a/test_database/aan_1/schema.sql b/test_database/aan_1/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/aan_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2a591352bcdd42bc4fd6a66ed112103c7198d5376c15fffa1861716cf7d4b36
+size 8143522
diff --git a/test_database/address_1/address_1.sqlite b/test_database/address_1/address_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..f036e0d236174405fa8a560be66979d33edd1310
--- /dev/null
+++ b/test_database/address_1/address_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5445559b7dfd1779cefb0198047cfb1de380a394e90ea33d1bc6c4d3a94e12f7
+size 20480
diff --git a/test_database/address_1/link.txt b/test_database/address_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ea1f8c1768ed7a6b4016d50573676a05b6f40e89
--- /dev/null
+++ b/test_database/address_1/link.txt
@@ -0,0 +1 @@
+http://www.cs.jhu.edu/~yarowsky/jhu.sql
diff --git a/test_database/address_1/schema.sql b/test_database/address_1/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..bb39dfa8ca7df6e7cb9c18fe4ce58b9db3401181
--- /dev/null
+++ b/test_database/address_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:909d6a0114f2f4c5b65c3483b2f2e449f77a64e83433d92f557219f490fa8f2d
+size 13417
diff --git a/test_database/advertising_agencies/advertising_agencies.sqlite b/test_database/advertising_agencies/advertising_agencies.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..2d2081c8bdd8a927cb17c5863884165ca6cc7ea0
--- /dev/null
+++ b/test_database/advertising_agencies/advertising_agencies.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/advertising_agencies/schema.sql b/test_database/advertising_agencies/schema.sql
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/test_database/art_1/art_1.sqlite b/test_database/art_1/art_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..76aa6aa81e6a6d8ab761baeea28aaf92fcee9058
--- /dev/null
+++ b/test_database/art_1/art_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ccfd00de54bbe9a7ce57f226e9634e8c4693520299795fb8da834017fc55d735
+size 8192
diff --git a/test_database/art_1/link.txt b/test_database/art_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2afe28bd9824dcf0a4ac995f632969e0b02b3561
--- /dev/null
+++ b/test_database/art_1/link.txt
@@ -0,0 +1 @@
+https://www.classes.cs.uchicago.edu/archive/2015/spring/23500-1/hw3.html
diff --git a/test_database/art_1/q.txt b/test_database/art_1/q.txt
new file mode 100644
index 0000000000000000000000000000000000000000..314b0d40208721600ee789b86609998eede2536d
--- /dev/null
+++ b/test_database/art_1/q.txt
@@ -0,0 +1,9 @@
+q0. Retrieve the title of each painting, the artist's last name, its height in inches and its width in inches in descending order of surface area.
+
+q1. Retrieve the artistID, first name, last name, and age at death of the artist(s) who was/were youngest at the time of death. (Note that since the birth and death dates are given as years only, any age computation is approximate, accurate plus or minus one.)
+
+q2. Retrieve the titles of all paintings and sculptures, with the artists' last names, in the database and the age the artist was at the time the work was produced, in order of youngest to oldest such age.
+
+q3. Retrieve the artist's last name and the title of all the undisplayed works.
+
+q4. Write a query to display the artistID, last name and all (distinct) media used by all artists in all paintings. Order the query result by last name, ascending. Your results should include not just the medium ("oil") but the surface the medium is on ("oil on canvas"). Use GROUP_CONCAT to denormalize the data and produce comma-delimited results like this:
diff --git a/test_database/bakery_1/annotation.json b/test_database/bakery_1/annotation.json
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f13f512f7f1ed20e20e5df75439c866cc18aed69f87db2fe07d6878fcdfda7b1
+size 2373
diff --git a/test_database/bakery_1/bakery_1.json b/test_database/bakery_1/bakery_1.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ad8cd59564977febe785bc23b0ea3e7ad85f848
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+++ b/test_database/bakery_1/bakery_1.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f29e25797bdd3ad9e95aee4fa9e0eef1d2d88031d3310732c655f44e430259ae
+size 3682
diff --git a/test_database/bakery_1/bakery_1.sql b/test_database/bakery_1/bakery_1.sql
new file mode 100644
index 0000000000000000000000000000000000000000..bb4d7178e2b51cac6c708b93d88d85bd97ac97d1
--- /dev/null
+++ b/test_database/bakery_1/bakery_1.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7456ce1c3625a368f463efe86524013074c75bc21522ae90c0f8ee95ddd72da8
+size 560
diff --git a/test_database/bakery_1/bakery_1.sqlite b/test_database/bakery_1/bakery_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..102324073c0f9de09c867d4776ed8cfe4bbb8e44
--- /dev/null
+++ b/test_database/bakery_1/bakery_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab55eb34c0ea8cbe29f9651ec3deae620ba8558e03b0e7740daa871e4eba025
+size 57344
diff --git a/test_database/bakery_1/bakery_1_michi.txt b/test_database/bakery_1/bakery_1_michi.txt
new file mode 100644
index 0000000000000000000000000000000000000000..58f6c0506e87b84f3bb49a7afc4162c273d96f54
--- /dev/null
+++ b/test_database/bakery_1/bakery_1_michi.txt
@@ -0,0 +1,411 @@
+Total # = 51
+
+1. What is the most expensive cake and its flavor?
+
+select id, flavor
+from goods
+where food = "Cake"
+order by price desc
+limit 1
+
+What is the cheapest cookie and its flavor?
+
+select id, flavor
+from goods
+where food = "Cookie"
+order by price
+limit 1
+
+2. Find the ids of goods that have apple flavor.
+
+Select id
+From goods
+Where flavor = "Apple"
+
+What are the ids of goods that cost less than 3 dollars?
+
+Select id
+From goods
+Where price < 3
+
+
+3. List the distinct ids of all customers who bought a lemon cake?
+
+Select DISTINCT T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.Id = T2.Item and T2.Receipt = T3.ReceiptNumber
+Where T1.Flavor = "Lemon" and T1.Food = "Cake"
+
+
+For each type of food, tell me how many customers have ever bought it.
+
+Select T1.food, count(distinct T3.CustomerId)
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.Id = T2.Item and T2.Receipt = T3.ReceiptNumber
+Group by T1.food
+
+
+4. Find the id of customers who shopped at the bakery at least 15 times.
+
+Select CustomerId
+From receipts
+Group by CustomerId
+having count(*) >= 15
+
+What is the last name of the customers who shopped at the bakery more than 10 times?
+
+Select T2.LastName
+From receipts as T1 JOIN customers as T2 ON T1.CustomerId = T2.id
+Group by T2.id
+having count(*) > 10
+
+
+5. How many types of Cake does this bakery sell?
+
+Select count(*)
+From goods
+where food = "Cake"
+
+List all the flavors of Croissant available in this bakery.
+
+Select flavor
+From goods
+where food = "Croissant"
+
+
+6. Give me a list of all the distinct items bought by the customer number 15.
+
+Select distinct T1.item
+from items as T1 JOIN receipts as T2 ON T1.receipt = T2.ReceiptNumber
+Where T2.CustomerId = 15
+
+
+For each type of food, what are the average, maximum and minimum price?
+
+Select food, avg(price), max(price), min(price)
+from goods
+Group by food
+
+
+7. Find the receipt numbers where both Cake and Cookie were bought.
+
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Cake"
+INTERSECT
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Cookie"
+
+
+Find all the receipt numbers in which customer id 5 purchased Croissant.
+
+Select ReceiptNumber
+From receipts
+Where CustomerId = 5
+INTERSECT
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Croissant"
+
+
+8. What is the receipt number and date of the receipt in which the most expensive item was bought?
+
+Select T1.ReceiptNumber, T1.Date
+From receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Order by T3.price Desc
+LIMIT 1
+
+
+What is the item that was bought the least number of times?
+Select item
+From items
+Group by item
+Order by count(*)
+LIMIT 1
+
+
+9. How many goods are available for each food type?
+
+Select count(*), food
+From goods
+group by food
+
+What is the average price for each food type?
+
+Select avg(price), food
+From goods
+group by food
+
+
+10. What are the goods that have Apricot flavor and are cheaper than 5 dollars?
+
+Select id
+From goods
+where flavor = "Apricot" and price < 5
+
+Find flavor of cakes that cost more than 10 dollars.
+
+Select flavor
+From goods
+where food = "Cake" and price > 10
+
+
+11. Give me the distinct id and price for all goods whose price is below the average of all goods?
+
+Select distinct id, price
+From goods
+where price < (Select avg(price) From goods)
+
+
+What are the distinct ids of all goods that are cheaper than some goods of type Tart?
+
+Select distinct T1.id
+From goods as T1, goods as T2
+where T1.price < T2.price and T2.food = "Tart"
+
+
+12. List distinct receipt numbers for which someone bought a good that costs more than 13 dollars.
+
+Select distinct T1.ReceiptNumber
+from receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Where T3.price > 13
+
+
+On which date did some customer buy a good that costs more than 15 dollars?
+
+Select distinct T1.date
+from receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Where T3.price > 15
+
+
+13. Give me the list of all goods whose id has "APP".
+
+Select id
+from goods
+Where id LIKE "%APP%"
+
+Which good has "70" in its id? And what is its price?
+
+Select id, price
+from goods
+Where id LIKE "%70%"
+
+
+14. List the last names of all customers in an alphabetical oder.
+
+Select distinct LastName
+From customers
+Order by LastName
+
+Return the ordered list of all good ids.
+
+Select distinct id
+From goods
+Order by id
+
+
+15. Find all receipts in which either apple flavor pie was bought or customer id 12 shopped.
+
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+where T2.flavor = "Apple" and T2.food = "Pie"
+UNION
+Select ReceiptNumber
+From receipts
+where CustomerId = 12
+
+
+Find all receipts which has the latest date. Also tell me that date.
+
+Select ReceiptNumber, date
+From receipts
+where date = (Select date From receipts Order by date Desc LIMIT 1)
+
+
+Find all receipts which either has the earliest date or has a good with price above 10.
+
+Select T1.Receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+where T2.price > 10
+UNION
+Select ReceiptNumber
+From receipts
+where date = (Select date From receipts Order by date LIMIT 1)
+
+
+16. What are the ids of Cookie and Cake that cost between 3 and 7 dollars.
+
+Select id
+From goods
+where (food = "Cookie" or food = "Cake") and price between 3 and 7
+
+
+Find the first name and last name of a customer who visited on the earliest date.
+
+Select T1.FirstName, T1.LastName
+From customers as T1 JOIN receipts as T2 ON T1.id = T2.CustomerId
+Order by T2.date
+LIMIT 1
+
+
+
+17. What is average price of goods whose flavor is blackberry or blueberry?
+
+Select avg(price)
+From goods
+where flavor = "Blackberry" or flavor = "Blueberry"
+
+
+Return the cheapest price for goods with cheese flavor.
+
+Select min(price)
+From goods
+where flavor = "Cheese"
+
+
+18. What are highest, lowest, and average prices of goods, grouped and ordered by flavor?
+
+Select max(price), min(price), avg(price), flavor
+From goods
+group by flavor
+order by flavor
+
+
+Return the lowest and highest prices of goods grouped and ordered by food type.
+
+Select min(price), max(price), food
+From goods
+group by food
+order by food
+
+
+19. Find the top three dates when the most goods were sold.
+
+Select date
+From receipts
+Group by date
+Order by count(*)
+LIMIT 3
+
+Which customer shopped most often? How many times?
+
+Select CustomerId, count(*)
+From receipts
+Group by CustomerId
+Order by count(*)
+LIMIT 1
+
+
+20. For each date, return how many distinct customers visited on that day.
+
+Select date, count (distinct CustomerId)
+from receipts
+Group by date
+
+
+Give me the first name and last name of customers who have bought apple flavor Tart.
+
+Select distinct T4.FirstName, T4.LastName
+from goods as T1 JOIN items as T2 JOIN receipts as T3 JOIN customers as T4 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber and T3.CustomerId = T4.id
+where T1.flavor = "Apple" and T1.food = "Tart"
+
+
+21. What are the ids of Cookies whose price is lower than any Croissant?
+
+Select id
+From goods
+where food = "Cookie" and price < (select min(price)
+ from goods
+ where food = 'Croissant')
+
+
+Give me the ids of Cakes whose price is at least three times as much as the average price of Tart?
+
+Select id
+From goods
+where food = "Cake" and price >= 3 * (select avg(price)
+ from goods
+ where food = "Tart")
+
+
+What are the ids of goods whose price is above twice the average price of all goods?
+
+Select id
+From goods
+where price > 2 * (select avg(price)
+ from goods)
+
+
+22. List the id, flavor and type of food of goods ordered by price.
+
+Select id, flavor, food
+From goods
+order by price
+
+
+Return a list of the id and flavor for Cakes ordered by flavor.
+
+Select id, flavor
+From goods
+where food = "Cake"
+order by flavor
+
+
+
+23. Find all the items that have chocolate flavor but were not bought more than 10 times.
+
+Select distinct T1.item
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.flavor = "Chocolate"
+EXCEPT
+Select distinct item
+From items
+Group by item
+having count(*) > 10
+
+
+What are the flavors available for Cake but not for Tart?
+
+Select distinct flavor
+From goods
+where food = "Cake"
+EXCEPT
+Select distinct flavor
+From goods
+where food = "Tart"
+
+
+24. What is the three most popular goods in this bakery?
+
+Select item
+From items
+Group by item
+Order by count (*) DESC
+LIMIT 3
+
+
+
+25. Find the ids of customers who have spent more than 150 dollars in total.
+
+Select T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.CustomerId
+having sum(T1.price) > 150
+
+
+Find the ids of customers whose average spending for each good is above 5.
+
+Select T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.CustomerId
+having avg(T1.price) > 5
+
+
+
+On which day did the bakery sell more than 100 dollars in total.
+
+Select T3.date
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.date
+having sum(T1.price) > 100
+
+
diff --git a/test_database/bakery_1/data_csv/README.BAKERY.TXT b/test_database/bakery_1/data_csv/README.BAKERY.TXT
new file mode 100644
index 0000000000000000000000000000000000000000..73bf3ee1ebe8c77fc21fd2c77c8a96a35a143bfa
--- /dev/null
+++ b/test_database/bakery_1/data_csv/README.BAKERY.TXT
@@ -0,0 +1,110 @@
+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@csc.calpoly.edu
+*****************************************************
+ BAKERY DATASET
+ Version 1.0
+ October 1, 2007
+*****************************************************
+Sources: this is a synthesized dataset.
+
+******************************************************
+
+This file describes the contents of the BAKERY dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information about one month worth
+of sales information for a small bakery shop. The sales
+are made to known customers. The dataset contains
+information about the customers, the assortments of
+baked goods offered for sale and the purchases made.
+
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+
+
+ The dataset consists of the following files:
+
+ - customers.csv : information about the bakery's customers
+ - goods.csv : information about the baked goods offered
+ for sale by the bakery
+ - items.csv : itemized reciept infromation for purchases
+ - reciepts.csv : general reciept information for purchases
+
+
+ reciepts.csv stores information about individual reciepts
+(purchases by customers). Each purchase may contain from
+one two five items, regardless of whether any items
+purchased are of the same kind (e.g., two "chocolate cakes"
+will be billed as two separate items on the reciept).
+items.csv contains itemized reciept information.
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+ customers.csv
+
+ Id: unique identifier of the customer
+ LastName: last name of the customer
+ FirstName: first name of the customer
+
+
+
+**************************************************************************
+
+
+ goods.csv
+
+ Id : unique identifier of the baked good
+ Flavor: flavor/type of the good (e.g., "chocolate", "lemon")
+ Food: category of the good (e.g., "cake", "tart")
+ Price: price (in dollars)
+
+
+
+**************************************************************************
+
+items.csv
+
+ Reciept : reciept number (see reciepts.RecieptNumber)
+ Ordinal : position of the purchased item on the
+ reciepts. (i.e., first purchased item,
+ second purchased item, etc...)
+ Item : identifier of the item purchased (see goods.Id)
+
+
+
+**************************************************************************
+
+reciepts.csv
+
+RecieptNumber : unique identifier of the reciept
+ Date : date of the purchase. The date is
+ in DD-Mon-YYY format, which is the
+ default Oracle's format for DATE data type.
+ CustomerId : id of the customer (see customers.Id)
+
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form,
+provided this file is kept unchanged and is distributed together with the
+data.
+
+Permission granted to modify and expand this dataset, provided this
+file is updated accordingly with new information.
+
+**************************************************************************
+**************************************************************************
diff --git a/test_database/bakery_1/data_csv/customers.csv b/test_database/bakery_1/data_csv/customers.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e2259c3e567e40983d805c8b85d6924f0c85e23b
--- /dev/null
+++ b/test_database/bakery_1/data_csv/customers.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4fa3ff7fe166ed5532eaa19938c5be357335fe82dad84ad5825a2562dba2668b
+size 490
diff --git a/test_database/bakery_1/data_csv/customers_t.csv b/test_database/bakery_1/data_csv/customers_t.csv
new file mode 100644
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--- /dev/null
+++ b/test_database/bakery_1/data_csv/customers_t.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/bakery_1/data_csv/goods.csv b/test_database/bakery_1/data_csv/goods.csv
new file mode 100644
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--- /dev/null
+++ b/test_database/bakery_1/data_csv/goods.csv
@@ -0,0 +1,3 @@
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diff --git a/test_database/bakery_1/data_csv/goods_t.csv b/test_database/bakery_1/data_csv/goods_t.csv
new file mode 100644
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@@ -0,0 +1,3 @@
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diff --git a/test_database/bakery_1/data_csv/items (3:11:18, 5:53 PM)_original.csv b/test_database/bakery_1/data_csv/items (3:11:18, 5:53 PM)_original.csv
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
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@@ -0,0 +1,3 @@
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--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/test_database/bakery_1/data_csv/receipts (3:11:18, 5:53 PM)_original.csv b/test_database/bakery_1/data_csv/receipts (3:11:18, 5:53 PM)_original.csv
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@@ -0,0 +1,3 @@
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diff --git a/test_database/bakery_1/data_csv/receipts.csv b/test_database/bakery_1/data_csv/receipts.csv
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--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/test_database/bakery_1/data_csv/receipts_t.csv b/test_database/bakery_1/data_csv/receipts_t.csv
new file mode 100644
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--- /dev/null
+++ b/test_database/bakery_1/data_csv/receipts_t.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/bakery_1/link.txt b/test_database/bakery_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..94c167197fe075c59a0eb4db5c0ce5bf25f766e7
--- /dev/null
+++ b/test_database/bakery_1/link.txt
@@ -0,0 +1 @@
+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html
\ No newline at end of file
diff --git a/test_database/bakery_1/q.txt b/test_database/bakery_1/q.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f38dd91a24f10decd8ccc5d49553eea07a9b5f58
--- /dev/null
+++ b/test_database/bakery_1/q.txt
@@ -0,0 +1,25 @@
+Find all chocolate-flavored items on the menu whose price is under $5.00. For each item output the flavor, the name (food type) of the item, and the price.
+
+Report the prices of any lemon-flavored items. Output the flavor, the name (food type) and the price of each pastry.
+
+Find all customers who made a purchase on October 3, 2007. Report the name of the customer (first, last).
+
+Find all types of cookies purchased by KIP ARNN during the month of October of 2007. Report each cookie type (flavor, food type) exactly once.
+
+Report the total amount of money NATACHA STENZ spent at the bakery during the month of October, 2007.
+
+Find all customers who purchased, during the same trip to the bakery, two different Croissants. Report first and last names of the customers.
+
+Find the total amount of money the bakery earned in October 2007 from selling eclairs. Report just the amount.
+
+Report all days on which more than ten tarts were purchased.
+
+For each purchase made by NATACHA STENZ output the receipt number, the date of purchase, the total number of items purchased and the amount paid.
+
+Find the customer(s) who spent the most on pastries in October of 2007. Report first and last name.
+
+Find the type of baked good (food type, flavor) responsible for highest total revenue.
+
+Find the day of the highest revenue in the month of October, 2007.
+
+Find the best-selling item (by number of purchases) on the day of the highest revenue in October of 2007.
diff --git a/test_database/bbc_channels/bbc_channels.sqlite b/test_database/bbc_channels/bbc_channels.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..025c2b614cd6b26e586d8ed79f0c805056ad0c45
--- /dev/null
+++ b/test_database/bbc_channels/bbc_channels.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1b9a7e6de6706734736e869180334b35420de138b1ee47b0b0f7822758cbf01a
+size 36864
diff --git a/test_database/bbc_channels/schema.sql b/test_database/bbc_channels/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5edbd6198ccec4d0dae07cb7da85649f8eb47179
--- /dev/null
+++ b/test_database/bbc_channels/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b77ce8175e7f333f662c52bf79817596cd881d6fbe9b4d02a5c10e85d626ba9b
+size 3235
diff --git a/test_database/bike_racing/bike_racing.sqlite b/test_database/bike_racing/bike_racing.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..1ce03d5d6ca023eb005552d8f726acee83f0199d
--- /dev/null
+++ b/test_database/bike_racing/bike_racing.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5d485e48c937b87f80c4e2bcc588d88042b1f52b8596b1f47afa33da674c8a5d
+size 28672
diff --git a/test_database/bike_racing/schema.sql b/test_database/bike_racing/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..096dd6c0f0e6c66b7ebe7dadd6c5c19e61103e96
--- /dev/null
+++ b/test_database/bike_racing/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:65f36652dd91fecafb140b167c9924a83ebf3e0413ea9a2095eb5d95c8592952
+size 2436
diff --git a/test_database/bike_racing/schema_old.sql b/test_database/bike_racing/schema_old.sql
new file mode 100644
index 0000000000000000000000000000000000000000..520dc165a60ac474c1bd352be2622805a3c7b006
--- /dev/null
+++ b/test_database/bike_racing/schema_old.sql
@@ -0,0 +1,3 @@
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+oid sha256:5f9eb86f1e82b40eeb1e6c014709c997d0708f13bfc68048f26627799ac85ddf
+size 2436
diff --git a/test_database/boat_1/Boats.csv b/test_database/boat_1/Boats.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c66d016d736f36918c716efb96cb702895205b12
--- /dev/null
+++ b/test_database/boat_1/Boats.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:05b90485f1752cc133d04391e011b8b604f2a391c8b270e8533057cb2d0059fe
+size 58
diff --git a/test_database/boat_1/Reserves.csv b/test_database/boat_1/Reserves.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b3a0402d50d041172a842ba9be50edf34d6aa84
--- /dev/null
+++ b/test_database/boat_1/Reserves.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:86eac26ef3ef915c403628c6d6edf8cb89e0a6c11ec509774703fcc410a6b45d
+size 56
diff --git a/test_database/boat_1/Sailors.csv b/test_database/boat_1/Sailors.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3b04df3be3896b964da4cf2029de54d0c9bbabb
--- /dev/null
+++ b/test_database/boat_1/Sailors.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:586d1cb0034162eb8aeb941939f41aaf441b567da8c1f088cdc9f8ef267fd61a
+size 61
diff --git a/test_database/boat_1/boat_1.sqlite b/test_database/boat_1/boat_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..f42ec791f9f148bd17b55d95676e486381ca34c4
--- /dev/null
+++ b/test_database/boat_1/boat_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 16384
diff --git a/test_database/boat_1/schema.sql b/test_database/boat_1/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..f1f82431d75d33f73cf01f951623d99405c9ab88
--- /dev/null
+++ b/test_database/boat_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/book_1/annotation.json b/test_database/book_1/annotation.json
new file mode 100644
index 0000000000000000000000000000000000000000..1145a0ed44f0e563e8ce27d2d9d9d53b418b387a
--- /dev/null
+++ b/test_database/book_1/annotation.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 5554
diff --git a/test_database/book_1/book_1.sqlite b/test_database/book_1/book_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..c8687b61fa3afde40f301a08b7eddcebed98bee1
--- /dev/null
+++ b/test_database/book_1/book_1.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab0fcc505f150d8904d62f639cfcbd01497ef755bb5926ed2acff3152eb662a2
+size 53248
diff --git a/test_database/book_1/link.txt b/test_database/book_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9d174be7acf171489bda354bef7424b09989b7d7
--- /dev/null
+++ b/test_database/book_1/link.txt
@@ -0,0 +1 @@
+https://github.com/ferreiro/SQL-Oracle-databases/blob/master/2_SQL_Queries/Block1%20(AllTheBooks%20Table).sql
\ No newline at end of file
diff --git a/test_database/book_1/q.txt b/test_database/book_1/q.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6028329a0b375926d4967617403d5132454db76c
--- /dev/null
+++ b/test_database/book_1/q.txt
@@ -0,0 +1,37 @@
+List of books, the publication year of each of them and their authors, ordered by publication year
+
+List of books that were published before 01-01-2000.
+
+List of clients that have bought at least one book.
+
+List of clients that bought the book whose ISBN= 4554672899910.
+
+List of clients whose name contains ‘Jo’ and the books that they have bought.
+
+List of clients that have bought at least a book whose price is greater than 10.
+
+List of clients that have placed more than one order in the same date.
+
+List of clients and dates in which they have placed orders that have not been sent yet.
+
+List of clients that have not bought books whose price is greater than 10.
+
+List of books whose sale price is greater than 30€ or that were published before 2000.
+
+List of books and amount of copies of each of them that have been sold.
+
+List of clients and the total amount that they have spent in the bookstore.
+
+Profits obtained from sales of books.
+
+Orders whose total amount is greater than 100.
+
+Orders and the total amount of each of them that contains more than a book (title).
+
+Orders and the total amount of each of them that contains more than 4 copies
+
+List of the most expensive books.
+
+List of books that have not been sold or that have been sold but the profit per copy is less than 5
+
+List of clients that have bought more than one copy of a book sometime
\ No newline at end of file
diff --git a/test_database/book_1/schema.sql b/test_database/book_1/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..705e6dd5c94fa4393b5685141f4d32e165265bd6
--- /dev/null
+++ b/test_database/book_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1a80236ad41dc1d434fd5917b00b53fd50c3899816df026cad8bb76f71d3d6c2
+size 4218
diff --git a/test_database/book_1/schema_old.sql b/test_database/book_1/schema_old.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b37029b9ace17531072817872275e46df6f42f57
--- /dev/null
+++ b/test_database/book_1/schema_old.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58f57222f82dabd3b8d95b554a51ed3dbc35251c1aa714821257b2a15292449f
+size 4178
diff --git a/test_database/book_1/sql.txt b/test_database/book_1/sql.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4f0ff2b741b9304570d8e7288e2071e35e5bc098
--- /dev/null
+++ b/test_database/book_1/sql.txt
@@ -0,0 +1,97 @@
+SELECT TITLE, AÑO "YEAR", NAME "Author name"
+FROM BOOK NATURAL JOIN AUTHOR_BOOK, AUTHOR
+WHERE AUTHOR_BOOK.AUTHOR=AUTHOR.IDAUTHOR
+ORDER BY AÑO;
+
+SELECT TITLE, AÑO
+FROM BOOK
+WHERE AÑO<'2000';
+
+SELECT DISTINCT IDCLIENT, NAME
+FROM CLIENT NATURAL JOIN ORDERS;
+select distinct client.name, Client.IdClient
+from Client, Orders where
+Client.IdClient=Orders.IdClient;
+
+SELECT IDCLIENT, NAME
+FROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER
+WHERE ISBN='4554672899910';
+
+SELECT IDCLIENT, NAME, TITLE
+FROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK
+WHERE NAME LIKE '%Jo%';
+
+SELECT DISTINCT IDCLIENT, NAME
+FROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK
+WHERE BOOK.SALEPRICE>10;
+
+SELECT IDCLIENT, NAME
+FROM CLIENT
+WHERE IDCLIENT=(
+ SELECT IDCLIENT
+ FROM ORDERS
+ GROUP BY(IDCLIENT,DATEORDER)
+ HAVING COUNT(DATEORDER)>1
+);
+
+SELECT IDCLIENT, NAME, DATEORDER
+FROM CLIENT NATURAL JOIN ORDERS
+WHERE DATEEXPED IS NULL;
+
+SELECT DISTINCT IDCLIENT, NAME
+FROM CLIENT
+WHERE IDCLIENT NOT IN (
+ SELECT IDCLIENT
+ FROM ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK
+ WHERE SALEPRICE < 10
+);
+
+SELECT TITLE, AÑO, SALEPRICE
+FROM BOOK
+WHERE AÑO<'2000' OR SALEPRICE>30;
+
+SELECT TITLE, ISBN, SUM(AMOUNT)
+FROM BOOKS_ORDER NATURAL JOIN BOOK
+GROUP BY TITLE, ISBN
+ORDER BY SUM(AMOUNT) DESC;
+
+SELECT IDCLIENT, NAME, SUM(AMOUNT*SALEPRICE) "Total"
+FROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK
+GROUP BY IDCLIENT, NAME;
+
+SELECT SUM(AMOUNT*(SALEPRICE-PURCHASEPRICE)) "Total"
+FROM BOOKS_ORDER NATURAL JOIN BOOK;
+
+SELECT IDORDER, SUM(AMOUNT*SALEPRICE) "TOTAL"
+FROM BOOKS_ORDER NATURAL JOIN BOOK
+GROUP BY IDORDER
+HAVING SUM(AMOUNT*SALEPRICE)>100
+ORDER BY IDORDER;
+
+SELECT IDORDER, SUM(AMOUNT*SALEPRICE) "TOTAL"
+FROM BOOKS_ORDER NATURAL JOIN BOOK
+GROUP BY IDORDER
+HAVING COUNT(TITLE)>1;
+
+SELECT IDORDER, SUM(AMOUNT*SALEPRICE) "Total"
+FROM BOOKS_ORDER NATURAL JOIN BOOK
+WHERE AMOUNT>4
+GROUP BY IDORDER;
+
+SELECT ISBN, TITLE, SALEPRICE
+FROM BOOK
+WHERE SALEPRICE IN (SELECT MAX(SALEPRICE) FROM BOOK);
+
+SELECT ISBN, TITLE
+FROM BOOK
+WHERE(SALEPRICE-PURCHASEPRICE)<5 OR ISBN NOT IN(
+ SELECT DISTINCT ISBN FROM BOOKS_ORDER
+);
+
+SELECT NAME
+FROM CLIENT NATURAL JOIN ORDERS
+WHERE IDORDER IN (
+ SELECT IDORDER
+ FROM BOOKS_ORDER
+ WHERE AMOUNT>1
+);
\ No newline at end of file
diff --git a/test_database/book_press/book_press.sqlite b/test_database/book_press/book_press.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..22da7323947e258e38c5e200349a262a3a72efac
--- /dev/null
+++ b/test_database/book_press/book_press.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c8748351b418fb213f3e4871471f8b923011323df6d341fb96796bb36f466acb
+size 28672
diff --git a/test_database/book_press/schema.sql b/test_database/book_press/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/book_press/schema.sql
@@ -0,0 +1,3 @@
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+size 2416
diff --git a/test_database/book_review/book_review.sqlite b/test_database/book_review/book_review.sqlite
new file mode 100644
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--- /dev/null
+++ b/test_database/book_review/book_review.sqlite
@@ -0,0 +1,3 @@
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diff --git a/test_database/book_review/schema.sql b/test_database/book_review/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/book_review/schema.sql
@@ -0,0 +1,3 @@
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diff --git a/test_database/book_review/schema_old.sql b/test_database/book_review/schema_old.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/book_review/schema_old.sql
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diff --git a/test_database/car_racing/car_racing.sqlite b/test_database/car_racing/car_racing.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..46debdeca94d55f475f5f7166714394de25ca9a7
--- /dev/null
+++ b/test_database/car_racing/car_racing.sqlite
@@ -0,0 +1,3 @@
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diff --git a/test_database/car_racing/schema.sql b/test_database/car_racing/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/car_racing/schema.sql
@@ -0,0 +1,3 @@
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new file mode 100644
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--- /dev/null
+++ b/test_database/movie_2/link.txt
@@ -0,0 +1 @@
+https://github.com/XD-DENG/SQL-exercise
\ No newline at end of file
diff --git a/test_database/movie_2/movie_2.sqlite b/test_database/movie_2/movie_2.sqlite
new file mode 100644
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--- /dev/null
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diff --git a/test_database/movie_2/q.txt b/test_database/movie_2/q.txt
new file mode 100644
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--- /dev/null
+++ b/test_database/movie_2/q.txt
@@ -0,0 +1,13 @@
+Select the title of all movies.
+
+Show all the distinct ratings in the database.
+
+Show all unrated movies.
+
+Select all movie theaters that are not currently showing a movie.
+
+Select all data from all movie theaters and, additionally, the data from the movie that is being shown in the theater (if one is being shown).
+
+Select all data from all movies and, if that movie is being shown in a theater, show the data from the theater.
+
+Show the titles of movies not currently being shown in any theaters.
\ No newline at end of file
diff --git a/test_database/movie_2/schema.sql b/test_database/movie_2/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..012e05311cb3f0a49481b952acdd6e95172012cc
--- /dev/null
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diff --git a/test_database/movie_2/sql.txt b/test_database/movie_2/sql.txt
new file mode 100644
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--- /dev/null
+++ b/test_database/movie_2/sql.txt
@@ -0,0 +1,29 @@
+select title from movies;
+
+select distinct rating from movies;
+
+select *
+from movies
+where rating is NULL;
+
+select * from MovieTheaters
+where Movie is NULL;
+
+SELECT *
+ FROM MovieTheaters LEFT JOIN Movies
+ ON MovieTheaters.Movie = Movies.Code;
+
+SELECT *
+ FROM Movies LEFT JOIN MovieTheaters
+ ON Movies.Code = MovieTheaters.Movie;
+
+SELECT Movies.Title
+ FROM MovieTheaters RIGHT JOIN Movies
+ ON MovieTheaters.Movie = Movies.Code
+ WHERE MovieTheaters.Movie IS NULL;
+SELECT Title FROM Movies
+ WHERE Code NOT IN
+ (
+ SELECT Movie FROM MovieTheaters
+ WHERE Movie IS NOT NULL
+ );
\ No newline at end of file
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new file mode 100644
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--- /dev/null
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new file mode 100644
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--- /dev/null
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diff --git a/test_database/pilot_1/link.txt b/test_database/pilot_1/link.txt
new file mode 100644
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--- /dev/null
+++ b/test_database/pilot_1/link.txt
@@ -0,0 +1 @@
+http://www.cs.dartmouth.edu/~cs61/Examples/
diff --git a/test_database/pilot_1/pilot_1.sqlite b/test_database/pilot_1/pilot_1.sqlite
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/pilot_1/schema.sql b/test_database/pilot_1/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/pilot_1/schema.sql
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+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/pilot_1/sql.txt b/test_database/pilot_1/sql.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ecf3d502d18182e7162396ab6cad640b768a0cfd
--- /dev/null
+++ b/test_database/pilot_1/sql.txt
@@ -0,0 +1,43 @@
+/*** Division with a remainder */
+SELECT DISTINCT pilot_name
+ FROM PilotSkills AS PS1
+ WHERE NOT EXISTS
+ (SELECT *
+ FROM Hangar
+ WHERE NOT EXISTS
+ (SELECT *
+ FROM PilotSkills AS PS2
+ WHERE (PS1.pilot_name = PS2.pilot_name)
+ AND (PS2.plane_name = Hangar.plane_name)));
+
+/* alternatively */
+SELECT PS1.pilot_name
+ FROM PilotSkills AS PS1, Hangar AS H1
+ WHERE PS1.plane_name = H1.plane_name
+ GROUP BY PS1.pilot_name
+ HAVING COUNT(PS1.plane_name) = (SELECT COUNT(plane_name) FROM Hangar);
+
+/* Exact division */
+SELECT PS1.pilot_name
+ FROM PilotSkills AS PS1
+ LEFT OUTER JOIN
+ Hangar AS H1
+ ON PS1.plane_name = H1.plane_name
+ GROUP BY PS1.pilot_name
+HAVING COUNT(PS1.plane_name) = (SELECT COUNT(plane_name) FROM Hangar)
+ AND COUNT(H1.plane_name) = (SELECT COUNT(plane_name) FROM Hangar);
+
+/* Division with JOINS */
+SELECT SP1.Pilot_name
+ FROM (((SELECT plane_name FROM Hangar) AS H1
+ INNER JOIN
+ (SELECT pilot_name, plane_name FROM PilotSkills) AS SP1
+ ON H1.plane_name = SP1.plane_name)
+ INNER JOIN (SELECT *
+ FROM PilotSkills
+ WHERE pilot_name = 'Higgins') AS H2
+ ON H2.plane_name = H1.plane_name)
+ GROUP BY SP1.Pilot_name
+HAVING COUNT(*) >= (SELECT COUNT(*)
+ FROM PilotSkills
+ WHERE pilot_name = 'Higgins');
diff --git a/test_database/planet_1/annotation.json b/test_database/planet_1/annotation.json
new file mode 100644
index 0000000000000000000000000000000000000000..6b31ea5bd99af2f3f5df93d73547bdc232b9e9ad
--- /dev/null
+++ b/test_database/planet_1/annotation.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64e2980eea88bd94fcd29c4e7d878d9680aca84b515861d503fa713e985e8c7f
+size 694
diff --git a/test_database/planet_1/link.txt b/test_database/planet_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3059cf106f2404fc358aa51ea4b71679aecd65d8
--- /dev/null
+++ b/test_database/planet_1/link.txt
@@ -0,0 +1 @@
+https://github.com/XD-DENG/SQL-exercise
\ No newline at end of file
diff --git a/test_database/planet_1/planet_1.sqlite b/test_database/planet_1/planet_1.sqlite
new file mode 100644
index 0000000000000000000000000000000000000000..fc34084384cef68a1e4691e7e14e5ea1c96f8630
--- /dev/null
+++ b/test_database/planet_1/planet_1.sqlite
@@ -0,0 +1,3 @@
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diff --git a/test_database/planet_1/q.txt b/test_database/planet_1/q.txt
new file mode 100644
index 0000000000000000000000000000000000000000..180f4d4d400729c39c29b75c9954f61465a571ba
--- /dev/null
+++ b/test_database/planet_1/q.txt
@@ -0,0 +1,3 @@
+Who receieved a 1.5kg package?
+
+What is the total weight of all the packages that he sent?
\ No newline at end of file
diff --git a/test_database/planet_1/schema.sql b/test_database/planet_1/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..04b0d371e8b95f52a2ab51aa855cb822df405554
--- /dev/null
+++ b/test_database/planet_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/planet_1/sql.txt b/test_database/planet_1/sql.txt
new file mode 100644
index 0000000000000000000000000000000000000000..eaec40108d96a5193f7ad59e79eb158836979b32
--- /dev/null
+++ b/test_database/planet_1/sql.txt
@@ -0,0 +1,14 @@
+select client.name
+from client join Package
+on client.AccountNumber = Package.Recipient
+where package.Weight = 1.5;
+
+select sum(weight) from Package
+where Sender = (
+select Recipient from Package where Weight = 1.5
+);
+SELECT SUM(p.weight)
+FROM Client AS c
+ JOIN Package as P
+ ON c.AccountNumber = p.Sender
+WHERE c.Name = "Al Gore's Head";
\ No newline at end of file
diff --git a/test_database/real_estate_rentals/real_estate_rentals.sqlite b/test_database/real_estate_rentals/real_estate_rentals.sqlite
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c8bf5b0de09d48b6f73e82e404b221741e9f8ec40020b83f666e9f5f470a45f
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new file mode 100644
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diff --git a/test_database/region_building/region_building.sqlite b/test_database/region_building/region_building.sqlite
new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/test_database/soccer_3/schema.sql b/test_database/soccer_3/schema.sql
new file mode 100644
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diff --git a/test_database/soccer_3/soccer_3.sqlite b/test_database/soccer_3/soccer_3.sqlite
new file mode 100644
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+++ b/test_database/soccer_3/soccer_3.sqlite
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diff --git a/test_database/tv_shows/schema.sql b/test_database/tv_shows/schema.sql
new file mode 100644
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--- /dev/null
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+size 5070
diff --git a/test_database/tv_shows/tv_shows.sqlite b/test_database/tv_shows/tv_shows.sqlite
new file mode 100644
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--- /dev/null
+++ b/test_database/tv_shows/tv_shows.sqlite
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+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/university_rank/schema.sql b/test_database/university_rank/schema.sql
new file mode 100644
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--- /dev/null
+++ b/test_database/university_rank/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:883e424dfb6354f3647ad42ce6e9e0584abec9d3dc9f5bdc9aafe1c2a75030f2
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diff --git a/test_database/university_rank/university_rank.sqlite b/test_database/university_rank/university_rank.sqlite
new file mode 100644
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--- /dev/null
+++ b/test_database/university_rank/university_rank.sqlite
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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new file mode 100644
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--- /dev/null
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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--- /dev/null
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new file mode 100644
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--- /dev/null
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diff --git a/test_database/warehouse_1/annotation.json b/test_database/warehouse_1/annotation.json
new file mode 100644
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--- /dev/null
+++ b/test_database/warehouse_1/annotation.json
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+version https://git-lfs.github.com/spec/v1
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+size 2668
diff --git a/test_database/warehouse_1/link.txt b/test_database/warehouse_1/link.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3059cf106f2404fc358aa51ea4b71679aecd65d8
--- /dev/null
+++ b/test_database/warehouse_1/link.txt
@@ -0,0 +1 @@
+https://github.com/XD-DENG/SQL-exercise
\ No newline at end of file
diff --git a/test_database/warehouse_1/q.txt b/test_database/warehouse_1/q.txt
new file mode 100644
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--- /dev/null
+++ b/test_database/warehouse_1/q.txt
@@ -0,0 +1,19 @@
+Select all warehouses.
+
+Select all boxes with a value larger than $150.
+
+Select all distinct contents in all the boxes.
+
+Select the average value of all the boxes.
+
+Select the warehouse code and the average value of the boxes in each warehouse.
+
+Same as previous exercise, but select only those warehouses where the average value of the boxes is greater than 150.
+
+Select the code of each box, along with the name of the city the box is located in.
+
+Select the warehouse codes, along with the number of boxes in each warehouse.
+
+Select the codes of all warehouses that are saturated (a warehouse is saturated if the number of boxes in it is larger than the warehouse's capacity).
+
+Select the codes of all the boxes located in Chicago.
\ No newline at end of file
diff --git a/test_database/warehouse_1/schema.sql b/test_database/warehouse_1/schema.sql
new file mode 100644
index 0000000000000000000000000000000000000000..6e270f18d3fcf6aa1985a17718e4fcbe4d6aa485
--- /dev/null
+++ b/test_database/warehouse_1/schema.sql
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/test_database/warehouse_1/sql.txt b/test_database/warehouse_1/sql.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e6934fc5555662acc1722e14cafae2964bbade73
--- /dev/null
+++ b/test_database/warehouse_1/sql.txt
@@ -0,0 +1,47 @@
+select * from warehouses;
+
+select * from boxes where Value>150;
+
+select distinct contents from boxes;
+
+select avg(value) from boxes;
+
+select warehouse, avg(value) from boxes group by warehouse;
+
+select warehouse, avg(value)
+from boxes
+group by warehouse
+having avg(value)> 150;
+
+select boxes.code, warehouses.location
+from boxes join warehouses
+on boxes.Warehouse = Warehouses.Code;
+SELECT Boxes.Code, Location
+ FROM Warehouses
+INNER JOIN Boxes ON Warehouses.Code = Boxes.Warehouse;
+
+select Warehouse, count(*)
+from boxes
+group by warehouse;
+
+SELECT Code
+ FROM Warehouses
+ WHERE Capacity <
+ (
+ SELECT COUNT(*)
+ FROM Boxes
+ WHERE Warehouse = Warehouses.Code
+ );
+
+select Boxes.code
+from boxes join Warehouses
+on boxes.warehouse = warehouses.code
+where warehouses.location = 'Chicago';
+SELECT Code
+FROM Boxes
+ WHERE Warehouse IN
+ (
+ SELECT Code
+ FROM Warehouses
+ WHERE Location = 'Chicago'
+ );
\ No newline at end of file
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diff --git a/train_database/activity_1/activity_1.sqlite b/train_database/activity_1/activity_1.sqlite
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diff --git a/train_database/aircraft/aircraft.sqlite b/train_database/aircraft/aircraft.sqlite
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--- /dev/null
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new file mode 100755
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--- /dev/null
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--- /dev/null
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diff --git a/train_database/gymnast/schema.sql b/train_database/gymnast/schema.sql
new file mode 100755
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--- /dev/null
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diff --git a/train_database/hospital_1/hospital_1.sqlite b/train_database/hospital_1/hospital_1.sqlite
new file mode 100644
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new file mode 100644
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diff --git a/train_database/icfp_1/icfp_1.sqlite b/train_database/icfp_1/icfp_1.sqlite
new file mode 100755
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--- /dev/null
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diff --git a/train_database/icfp_1/link.txt b/train_database/icfp_1/link.txt
new file mode 100755
index 0000000000000000000000000000000000000000..2afe28bd9824dcf0a4ac995f632969e0b02b3561
--- /dev/null
+++ b/train_database/icfp_1/link.txt
@@ -0,0 +1 @@
+https://www.classes.cs.uchicago.edu/archive/2015/spring/23500-1/hw3.html
diff --git a/train_database/icfp_1/q.txt b/train_database/icfp_1/q.txt
new file mode 100755
index 0000000000000000000000000000000000000000..f5d8d4b3ac26aa0f6534f95e3f34aec0738a1b2c
--- /dev/null
+++ b/train_database/icfp_1/q.txt
@@ -0,0 +1,9 @@
+q5. Retrieve the titles of all papers with a single author.
+
+q6. Retrieve the titles and number of affiliated institutions of all papers with authors from more than one institution.
+
+q7. Retrieve the title(s) and number of authors of the paper(s) with the most authors in the database instance. For example, if there is one paper with three authors in the whole batch, and every other paper has one or two authors (that's the case in the database you are given), identify that paper.
+
+q8. Retrieve the authors' authID, first and last names, in alphabetical order, and the number of papers on which they have authorship.
+
+q9. Retrieve the authID, first and last name of the author(s) and their number of collaborators (shared authorships), in alphabetical order.
diff --git a/train_database/inn_1/annotation.json b/train_database/inn_1/annotation.json
new file mode 100644
index 0000000000000000000000000000000000000000..f7a8ac4068269a69c49705068d51986f5d83a0e2
--- /dev/null
+++ b/train_database/inn_1/annotation.json
@@ -0,0 +1,3 @@
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+size 1516
diff --git a/train_database/inn_1/change_date.py b/train_database/inn_1/change_date.py
new file mode 100644
index 0000000000000000000000000000000000000000..d9e3c015ddcbb526c25932b4c981c4ded1d993b6
--- /dev/null
+++ b/train_database/inn_1/change_date.py
@@ -0,0 +1,26 @@
+import pandas as pd
+month_to_name={
+ 'JAN' : "01",
+ 'FEB' : "02",
+ 'MAR' : "03",
+ 'APR' : "04",
+ 'MAY' : "05",
+ 'JUN' : "06",
+ 'JUL' : "07",
+ 'AUG' : "08",
+ 'SEP' : "09",
+ 'OCT' : "10",
+ 'NOV' : "11",
+ 'DEC' : "12"
+};
+df = pd.read_csv('./data_csv/Reservations.csv')
+def change_date(x):
+ x = x.split("-")
+ x[2] = "20"+x[2][:len(x[2])-1]
+ x[1] = month_to_name[x[1]]
+ x = "-".join([x[2],x[1],x[0][1:]])
+ print x
+ return x
+df["CheckIn"] = df["CheckIn"].apply(change_date)
+df["CheckOut"] = df["CheckOut"].apply(change_date)
+df.to_csv('./data_csv/Reservations_t.csv', encoding='utf-8', index=False)
diff --git a/train_database/inn_1/data_csv/README.INN.TXT b/train_database/inn_1/data_csv/README.INN.TXT
new file mode 100755
index 0000000000000000000000000000000000000000..f68b7923672ca5dbb5e4c59d7db4fba24ad81dcc
--- /dev/null
+++ b/train_database/inn_1/data_csv/README.INN.TXT
@@ -0,0 +1,87 @@
+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@calpoly.edu
+*****************************************************
+ INN DATASET
+ Version 1.0
+ April 6, 2011
+*****************************************************
+Sources: this is a synthesized dataset.
+
+******************************************************
+
+This file describes the contents of the INN dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information a one year worth of reservations
+at a fictional Bed & Breakfast hotel called Seaside Grove Inn.
+The hotel has 10 rooms. The dataset contains information about
+the completed (i.e., guests arrived and stayed) reservations for
+one year of the hotel's operation.
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+
+
+ The dataset consists of the following files:
+
+ - Rooms.csv : list of Seaside Grove Inn rooms
+ - Reservations.csv : list of completed room reservations
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+Rooms.csv
+
+ RoomId : a three-letter unique Id code of a room
+ roomName : official name of the room (all rooms in B&B inns
+ typically have names)
+ beds : number of beds in the room
+ bedType : type of the bed(s) in the room. All beds in each room
+ are of the same type.
+ maxOccupancy : maximum number of people allowed to stay in the room
+ basePrice : base price (in US dollars) of one night of stay in the room.
+ decor : decoration style of the room
+
+**************************************************************************
+
+Reservations.csv
+
+ Code : reservation code
+ Room : the three-letter room code (see Rooms.RoomId)
+ CheckIn : date of check-in/arrival
+ CheckOut : date of check-out/departure
+ Rate : actual nightly rate. Each night of stay on one reservation
+ always costs the same amount, although rates may vary
+ for the same room from one reservation to another
+ LastName : last name of the person who made the reservation
+ FirstName : first name of the person who made the reservation
+ Adults : number of adults (18 and above) staying in the room. Each
+ reservation must have at least one adult
+ Kids : number of kids (ages 0-17) staying in the room.
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form,
+provided this file is kept unchanged and is distributed together with the
+data.
+
+Permission granted to modify and expand this dataset, provided this
+file is updated accordingly with new information.
+
+Acknowledgements. We thank Dr. Clint Staley for the software script that
+produced the names of the rooms.
+
+**************************************************************************
+**************************************************************************
diff --git a/train_database/inn_1/data_csv/Reservations.csv b/train_database/inn_1/data_csv/Reservations.csv
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diff --git a/train_database/inn_1/inn_1.sql b/train_database/inn_1/inn_1.sql
new file mode 100755
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--- /dev/null
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--- /dev/null
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diff --git a/train_database/inn_1/link.txt b/train_database/inn_1/link.txt
new file mode 100755
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--- /dev/null
+++ b/train_database/inn_1/link.txt
@@ -0,0 +1 @@
+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html
\ No newline at end of file
diff --git a/train_database/inn_1/q.txt b/train_database/inn_1/q.txt
new file mode 100755
index 0000000000000000000000000000000000000000..b198bd1554245a14463633715aa03757a67152ef
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+++ b/train_database/inn_1/q.txt
@@ -0,0 +1,15 @@
+Find all modern rooms with a base price below $160 and two beds. Report room names and codes
+
+Find all rooms occupied on February 6, 2010. Report full name of the room, the check-in and checkout dates of the reservation.
+
+For each reservation that starts on December 31, 2010 report the room name, nightly rate, number of nights spent and the total amount of money paid.
+
+Find the names of all people1 staying at the inn at the same time as HERBERT FRYDAY.
+
+Find the number of August reservations (both checkin and checkout dates are in August) where two adults are staying with two children.
+
+Find the most popular room in the hotel. The most popular room is the room that had seen the largest number of reservations
+
+Find the room that has been occupied the largest number of days based on the reservations. Report the room name
+
+For each room, report the most expensive reservation. Report the full room name, dates of stay
diff --git a/train_database/insurance_and_eClaims/insurance_and_eClaims.sqlite b/train_database/insurance_and_eClaims/insurance_and_eClaims.sqlite
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new file mode 100755
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--- /dev/null
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diff --git a/train_database/storm_record/schema.sql b/train_database/storm_record/schema.sql
new file mode 100755
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--- /dev/null
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diff --git a/train_database/student_1/annotation.json b/train_database/student_1/annotation.json
new file mode 100644
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diff --git a/train_database/student_1/data_csv/README.STUDENTS.TXT b/train_database/student_1/data_csv/README.STUDENTS.TXT
new file mode 100755
index 0000000000000000000000000000000000000000..9aa2888e3474c4a861e416f7042cce3b2d7f3c9e
--- /dev/null
+++ b/train_database/student_1/data_csv/README.STUDENTS.TXT
@@ -0,0 +1,68 @@
+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@csc.calpoly.edu
+*****************************************************
+ STUDENTS DATASET
+ Version 1.0
+ October 1, 2007
+*****************************************************
+Sources: this is a synthesized dataset.
+
+******************************************************
+
+This file describes the contents of the STUDENTS dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information about students of a small elementary
+school. Each student goes to a specific classroom and a specific
+grade. A teacher is assigned to each classroom.
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+
+
+ The dataset consists of the following files:
+
+ - list.csv : list of students
+ - teachers.csv : list of teachers
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+list.csv
+
+ LastName : last name of the student
+ FirstName : first name of the student
+ Grade : grade the student attends
+ Classroom : classroom the student is assigned to
+
+**************************************************************************
+
+teachers.csv
+
+ LastName : last name of the teacher
+ FirstName : first name of the teacher
+ Classroom : classroom the teacher is assigned to
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form,
+provided this file is kept unchanged and is distributed together with the
+data.
+
+Permission granted to modify and expand this dataset, provided this
+file is updated accordingly with new information.
+
+**************************************************************************
+**************************************************************************
diff --git a/train_database/student_1/data_csv/list.csv b/train_database/student_1/data_csv/list.csv
new file mode 100755
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diff --git a/train_database/student_1/data_csv/teachers.csv b/train_database/student_1/data_csv/teachers.csv
new file mode 100755
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--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/train_database/student_1/link.txt b/train_database/student_1/link.txt
new file mode 100755
index 0000000000000000000000000000000000000000..94c167197fe075c59a0eb4db5c0ce5bf25f766e7
--- /dev/null
+++ b/train_database/student_1/link.txt
@@ -0,0 +1 @@
+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html
\ No newline at end of file
diff --git a/train_database/student_1/q.txt b/train_database/student_1/q.txt
new file mode 100755
index 0000000000000000000000000000000000000000..31d3be49945822a349d7af36eea9ac02b79ec609
--- /dev/null
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@@ -0,0 +1,25 @@
+Find all students who study in classroom 111. For each student list first and last name.
+
+For each classroom report the grade that is taught in it. Report just the classroom number and the grade number.
+
+Find all teachers who teach fifth grade. Report first and last name of the teachers and the room number.
+
+Find all students taught by OTHA MOYER. Output first and last names of students
+
+For each teacher teaching grades K through 3, report the grade (s)he teaches. Each name has to be reported exactly once.
+
+Find all first-grade students who are NOT taught by OTHA MOYER. Report their first and last names
+
+Find and report the number of students taught by LORIA ONDERSMA.
+
+For each grade, report the number of classrooms in which it is taught and the toal number of students in the grade.
+
+Report the names of teachers who have between seven and eight students in their classes.
+
+For each kindergarden classroom, report the total number of students.
+
+Find the teacher name who teach(es) the largest number of students.
+
+Findallclassroomswhichhavefewerstudentsinthemthantheaverage number of students in a classroom in the school. Report the classroom numbers
+
+For each grade with more than one classroom, report the last name of the teacher who teachers the classroom with the largest number of students in the grade.
diff --git a/train_database/student_1/student_1.sql b/train_database/student_1/student_1.sql
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diff --git a/train_database/twitter_1/queries/oracle-dialects.xml b/train_database/twitter_1/queries/oracle-dialects.xml
new file mode 100755
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--- /dev/null
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@@ -0,0 +1,36 @@
+
+
+
+
+
+ SELECT * FROM "tweets" WHERE id = ?
+
+
+
+
+ SELECT f2 FROM "follows" WHERE f1 = ? AND ROWNUM <= 20
+
+
+ SELECT * FROM "tweets" WHERE uuid IN (??)
+
+
+
+
+ SELECT f2 FROM "followers" WHERE f1 = ? AND ROWNUM <= 20
+
+
+ SELECT uuid, name FROM "user_profiles" WHERE uuid IN (??)
+
+
+
+
+ SELECT * FROM "tweets" WHERE uuid = ? AND ROWNUM <= 10
+
+
+
+
+ INSERT INTO "added_tweets" VALUES (tweet_idseq.nextval, ?, ?, ?)
+
+
+
+
diff --git a/train_database/twitter_1/queries/postgres-dialects.xml b/train_database/twitter_1/queries/postgres-dialects.xml
new file mode 100755
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--- /dev/null
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@@ -0,0 +1,36 @@
+
+
+
+
+
+ SELECT * FROM "tweets" WHERE id = ?
+
+
+
+
+ SELECT f2 FROM "follows" WHERE f1 = ? LIMIT 20
+
+
+ SELECT * FROM "tweets" WHERE uid IN (??)
+
+
+
+
+ SELECT f2 FROM "followers" WHERE f1 = ? LIMIT 20
+
+
+ SELECT uid, name FROM "user_profiles" WHERE uid IN (??)
+
+
+
+
+ SELECT * FROM "tweets" WHERE uid = ? LIMIT 10
+
+
+
+
+ INSERT INTO "added_tweets" VALUES (default, ?, ?, ?)
+
+
+
+
diff --git a/train_database/twitter_1/queries/sqlserver-dialects.xml b/train_database/twitter_1/queries/sqlserver-dialects.xml
new file mode 100755
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--- /dev/null
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@@ -0,0 +1,31 @@
+
+
+
+
+
+ SELECT * FROM "tweets" WHERE id = ?
+
+
+
+
+ SELECT TOP 20 f2 FROM "follows" WHERE f1 = ?
+
+
+ SELECT * FROM "tweets" WHERE uid IN (??)
+
+
+
+
+ SELECT TOP 20 f2 FROM "followers" WHERE f1 = ?
+
+
+ SELECT uid, name FROM "user_profiles" WHERE uid IN (??)
+
+
+
+
+ SELECT TOP 10 * FROM "tweets" WHERE uid = ?
+
+
+
+
diff --git a/train_database/twitter_1/twitter_1.sqlite b/train_database/twitter_1/twitter_1.sqlite
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diff --git a/train_database/wine_1/data_csv/README.WINE.txt b/train_database/wine_1/data_csv/README.WINE.txt
new file mode 100755
index 0000000000000000000000000000000000000000..9d909d2b5da05ac3bc77f6a5db59998b82c5dcf3
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@@ -0,0 +1,110 @@
+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@csc.calpoly.edu
+*****************************************************
+ WINE DATASET
+ Version 1.0
+ March 27, 2011
+************************************************************
+Sources: This dataset contains wine ratings from a
+ collection of 2007-2011 Wine Spectator magazines
+
+************************************************************
+
+This file describes the contents of the WINE dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information about the ratings of a variety of
+wines produced in California. The ratings were published
+in a number of issues of the Wine Spectator magazine. Version 1.0
+of the dataset includes only the wines produced out of a single grape
+and only the wines produced in the state of California.
+
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+
+
+ The dataset consists of the following files:
+
+ - appelations.csv : list of appelations/American Viticultural Areas (AVAs)
+ - grapes.csv : list of grape varieties
+ - wine.csv : list of wines and their ratings
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+appelations.csv
+
+ No : line number in the CSV file
+ Appelation: name of the appelation/AVA/grape-growing region
+ County: county (if applicable) in which the area is located
+ State: state in which the area is located
+ Area: general geographic area in which the grape-growing region is located
+ isAVA: a flag specifying whether the region is recognized as an American
+ Viticultural Area (AVA) by federal regulations.
+
+Notes: "Appelation" is a general term for geographic grape origins in a wine.
+ Grape origins are always listed on wine labels.
+ In the US, appropriate origins are either AVAs (American Viticultural Areas)
+ or counties, in which the grapes were grown. Most AVAs respect geographical
+ boundaries (state, county, so on), but some - do not.
+ In the dataset, some AVAs shown as located in a single county are actually
+ located in multiple counties (we chose the "main" county of location).
+ This is done to simplify the dataset. Other AVAs transcend county borders
+ in ways that make county attribution meaningless. The value 'N/a' is used
+ in such cases. General geographic areas, as they are currently used
+ are subregions of a single state.
+
+**************************************************************************
+
+grapes.csv
+
+ ID: unique identifier of a grape (line number in the CSV file)
+ Grape: name of the grape varietal
+ Color: color of the grape (a.k.a, color of the wine when made solely of
+ this grape)
+
+**************************************************************************
+
+wine.csv
+
+ No.: unique identifier of the wine (line number in the CSV file)
+ Grape: grape varietal from which the wine is made (see grapes.Grape)
+ Winery: maker of the wine (usually a winery name)
+Appelation: origin of the grapes (see applations.Appelation)
+ State: state of the grapes' origin (same as appelations.State)
+ Name: name of the wine
+ Year: year of the wine vintage
+ Price: price of one bottle of wine in (whole) US dollars
+ Score: Wine Spectator magazine rating of the wine on the 100 point scale
+ Cases: number of cases of the wine produced by its maker
+ Drink: drinking advice
+
+Notes: only wines produced from a single grape are included in the dataset (no blends).
+All wines in the dataset are from California. Drinking advice is simplified. Either
+the field contains the value 'now' which means that wine can be enjoyed to its fullest
+potential at the moment it was rated by the Wine Spectator magazine, or
+it contains a year in which the wine is predicted to reach its full potential.
+Wine name is either a special name given to the wine by its makers and found on
+the label, or is the name of the grape varietal.
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form,
+provided this file is kept unchanged and is distributed together with the
+data.
+
+**************************************************************************
+**************************************************************************
diff --git a/train_database/wine_1/data_csv/appellations.csv b/train_database/wine_1/data_csv/appellations.csv
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+size 3740
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diff --git a/train_database/wine_1/link.txt b/train_database/wine_1/link.txt
new file mode 100755
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--- /dev/null
+++ b/train_database/wine_1/link.txt
@@ -0,0 +1 @@
+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html
\ No newline at end of file
diff --git a/train_database/wine_1/q.txt b/train_database/wine_1/q.txt
new file mode 100755
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+List all AVAs located in Monterey county. Output just the names of the AVA appellations
+
+List all white grape varieties for which at least one wine of the 2008 vintage is rated at 90 points or above in the database.
+
+List all Sonoma county appellations for which the database contains at least one rating for a ’Grenache’. For each appellation list its name and county.
+
+List all vintage years in which at least one Zinfandel from Sonoma County (any appellation) scored above 92.
+
+A case of wine is 12 bottles. For each Carlisle (name of the winery) Syrah compute the total revenue assuming that all the wine sold at the specified price.
+
+Find the total revenue from all red wines made by Kosta Browne.
+
+Find the average number of cases of a Pinor Noir produced from grapes sourced from the Central Coast.
+
+For each year, report the total number of red Sonoma County wines whose scores are 90 or above.
+
+Find the most popular red grape (i.e., the grape that is used to make the largest number of white wines) in San Luis Obispo County.
+
+Report the grape with the largest number of high-ranked wines (wines ranked 93 or higher).
+
+Report the appellation responsible for the largest number of high-ranked wines (score of 93 and above). Report just the name of the appellation.
+
+Find if there are any 2008 Zinfandels that scored better than all 2007 Grenaches. Report winery, wine name, score and price.
+
+Find how many cases were produced of the most expensive red wine from Napa county.
diff --git a/train_database/wine_1/wine_1.sql b/train_database/wine_1/wine_1.sql
new file mode 100755
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diff --git a/validation_database/car_1/data_csv/README.CARS.TXT b/validation_database/car_1/data_csv/README.CARS.TXT
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+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@csc.calpoly.edu
+*****************************************************
+ CARS DATASET
+ Version 1.0
+ September 26, 2007
+*****************************************************
+Sources:
+ The Committee on Statistical Graphics of
+ the American Statistical Association (ASA)
+ 1983 Cars dataset
+ available (among other places) from
+ CMU's StatLib server:
+ http://lib.stat.cmu.edu/datasets/
+
+******************************************************
+
+
+This file describes the contents of the CARS dataset
+developed for the CPE 365, Introduction to Databases
+course at Cal Poly.
+
+The dataset is a normalized and slightly enhanced version
+of the ASA's Committee on Statistical Graphics "cars"
+dataset offered in 1983 for the visualization competition.
+Please refer to the original dataset description
+in the file "cars.desc" included with this distribution for
+historical purposes. (please, note, cars.desc file does not
+describe the format of this dataset correctly).
+
+
+The dataset describes the origins and different parameters
+of 406 car models produced in the world between 1970 and 1982.
+The dataset consists of the following files:
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data
+ 3. All string values are enclosed in single quotes (')
+
+ - car-makers.csv : information about companies that produce cars
+ - car-names.csv : information about specific cars (by name)
+ - cars-data.csv : operational parameters of the cars
+ - continents.csv : list of continents
+ - countries.csv : list of countries
+ - model-list.csv : information about car models produced by car makers
+
+
+The core of the dataset consists of four files: car-makes.csv, model-list.csv,
+car-names.csv and cars-data.csv. The first file identifies companies
+that produce cars (e.g, "Ford Motor Company", "Toyota"), the second file
+lists various models and identified their makes (e.g., "Ford" and "Mercury"
+produced by Ford, "Oldsmobile" and "Chevrolet" produced by GM). The third
+file is the masterlist of 406 car makes considered in the database
+(e.g., "ford torino" or "amc rebel set"). The fourth file contains information
+about the operating parameters (see below for a full list) for each make.
+
+
+Individual files have the following formats.
+
+
+**************************************************************************
+
+car-makers.csv
+
+ Id : unique identifier of the car maker
+ Maker : short nickname for the car maker
+ FullName : full name of the car maker
+ Country : Id of the home country of the maker (see countries.CountryId)
+
+
+
+**************************************************************************
+
+car-names.csv
+
+ MakeId : unique identifier of the car make
+ Model : unique name of the car model (see model-list.Model)
+ MakeDescription : description (name) of the car make
+
+
+
+**************************************************************************
+
+
+cars-data.csv
+
+ Id : unique identifier of the car make (see car-names.MakeId)
+ MPG : milage per gallon
+ Cylinders : number of cylinders
+ Edispl : engine displacement volume in cubic inches
+ Horsepower : power of the engine in horsepowers
+ Weight : weight of the car in lbs
+ Accelerate : time to accelerate from 0 to 60mph in seconds (possibly
+ with fractions of a second)
+ Year : year the car was made
+
+
+NOTE: this file adds the Id attribute to the original cars.data file from
+ the ASA cars dataset, removes the Origin attribute (the origin is
+ now dealt with elsewhere), and modifies year to be the actual year
+ rather than "year - 1900".
+
+
+
+**************************************************************************
+
+
+continents.csv
+
+ ContId : unique identifier of the continent
+ Continent : name of the continent
+
+
+**************************************************************************
+
+countries.csv
+
+ CountryId : unique identifier of the country
+ CountryName : name of the country
+ Continent : unique identifier of the continent the country is on
+ (see continents.ContId)
+
+
+**************************************************************************
+
+model-list.csv
+
+ ModelId : unique identifier of the car model
+ Maker : unique identifier of the car maker (see car-makers.id)
+ Model : name of the car model (also unique)
+
+
+
+**************************************************************************
+**************************************************************************
+
+
+
+
+
+
+
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+The Committee on Statistical Graphics of the American Statistical
+Association (ASA) invites you to participate in its Second (1983)
+Exposition of Statistical Graphics Technology. The purposes of the
+Exposition are (l) to provide a forum in which users and providers of
+statistical graphics technology can exchange information and ideas and
+(2) to expose those members of the ASA community who are less familiar
+with statistical graphics to its capabilities and potential benefits
+to them. The Exposition wil1 be held in conjunction with the Annual
+Meetings in Toronto, August 15-18, 1983 and is tentatively scheduled
+for the afternoon of Wednesday, August 17.
+
+Seven providers of statistical graphics technology participated in the
+l982 Exposition. By all accounts, the Exposition was well received by
+the ASA community and was a worthwhile experience for the
+participants. We hope to have those seven involved again this year,
+along with as many new participants as we can muster. The 1982
+Exposition was summarized in a paper to appear in the Proceeding of
+the Statistical Computing Section. A copy of that paper is enclosed
+for your information.
+
+The basic format of the 1983 Exposition will be similar to that of
+1982. However, based upon comments received and experience gained,
+there are some changes. The basic structure, intended to be simpler
+and more flexible than last year, is as follows:
+
+A fixed data set is to be analyzed. This data set is a version of the
+CRCARS data set of
+
+ Donoho, David and Ramos, Ernesto (1982), ``PRIMDATA:
+ Data Sets for Use With PRIM-H'' (DRAFT).
+
+Because of the Committee's limited (zero) budget for the Exposition,
+we are forced to provide the data in hardcopy form only (enclosed).
+(Sorry!)
+
+There are 406 observations on the following 8 variables: MPG (miles
+per gallon), # cylinders, engine displacement (cu. inches), horsepower,
+vehicle weight (lbs.), time to accelerate from O to 60 mph (sec.),
+model year (modulo 100), and origin of car (1. American, 2. European,
+3. Japanese). These data appear on seven pages. Also provided are the
+car labels (types) in the same order as the 8 variables on seven
+separate pages. Missing data values are marked by series of question
+marks.
+
+You are asked to analyze these data using your statistical graphics
+software. Your objective should be to achieve graphical displays which
+will be meaningful to the viewers and highlight relevant aspects of
+the data. If you can best achieve this using simple graphical formats,
+fine. If you choose to illustrate some of the more sophisticated
+capabilities of your software and can do so without losing relevancy
+to the data, that is fine, too. This year, there will be no Committee
+commentary on the individual presentations, so you are not competing
+with other presenters. The role of each presenter is to do his/her
+best job of presenting their statistical graphics technology to the
+viewers.
+
+Each participant will be provided with a 6'(long) by 4'(tall)
+posterboard on which to display the results of their analyses. This is
+the same format as last year. You are encouraged to remain by your
+presentation during the Exposition to answer viewers' questions. Three
+copies of your presentation must be submitted to me by July 1. Movie
+or slide show presentations cannot be accommodated (sorry). The
+Committee will prepare its own poster presentation which will orient
+the viewers to the data and the purposes of the Exposition.
+
+The ASA has asked us to remind all participants that the Exposition is
+intended for educational and scientific purposes and is not a
+marketing activity. Even though last year's participants did an
+excellent job of maintaining that distinction, a cautionary note at
+this point is appropriate.
+
+Those of us who were involved with the 1982 Exposition found it
+worthwhile and fun to do. We would very much like to have you
+participate this year. For planning purposes, please RSVP (to me, in
+writing please) by April 15 as to whether you plan to accept the
+Committee's invitation.
+
+If you have any questions about the Exposition, please call me on
+(301/763-5350). If you have specific questions about the data, or the
+analysis, please call Karen Kafadar on (301/921-3651). If you cannot
+participate but know of another person or group in your organization
+who can, please pass this invitation along to them.
+
+Sincerely,
+
+
+
+LAWRENCE H. COX
+Statistical Research Division
+Bureau of the Census
+Room 3524-3
+Washington, DC 20233
+
+
diff --git a/validation_database/car_1/data_csv/continents.csv b/validation_database/car_1/data_csv/continents.csv
new file mode 100755
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diff --git a/validation_database/car_1/data_csv/countries.csv b/validation_database/car_1/data_csv/countries.csv
new file mode 100755
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new file mode 100755
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new file mode 100755
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+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html
\ No newline at end of file
diff --git a/validation_database/car_1/q.txt b/validation_database/car_1/q.txt
new file mode 100755
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--- /dev/null
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@@ -0,0 +1,27 @@
+Find all Reanults (’renault’) in the database. For each, report the name and the year.
+
+Find all cars produced by Volvo between 1977 and 1981 (inclusive). Report the name of the car and the year it was produced.
+
+Report all Asian automakers. Output the full name of the automaker and the country of origin
+
+Find all non-four cylinder cars produced in 1980 that have a better fuel economy better than 20 MPG and that accelerate to 60 mph faster than in 15 seconds. Report the name of the car and the name of the automaker.
+
+For each saab released after 1978, compute the ratio between the weight of the car and its number of horsepowers. Report the full name of the car, the year it was produced and the ratio.
+
+Find the average, maximum and minimum horsepower for 4-cylinder vehicles manufactured by renault between 1971 and 1976 inclusively.
+
+Find how many different car manufacturers produced a vehicle heavier than 4000 lbs.
+
+Find the minimum horsepower for 4-cylinder vehicles manufactured by renault between 1971 and 1976 inclusively.
+
+For each year when US-manufactured cars averaged less than 100 horsepowers, report the highest and the lowest engine displacement number.
+
+For each year in which honda produced more than 2 models, report the best, the worst and the average gas milage of a toyota vehicle.
+
+Report all vehicles with the best gas mileage. For each vehicle, report its full name and the year of production.
+
+Among the vehicles with the gas mileage, report the one with the best acceleration. Report full name and the year of production.
+
+For each country report the automaker with the largest number of cars in the database. Report the name of the country.
+
+Find the difference in gas milage between the most fuel-efficient 8-cylinder model and the least fuel-efficient 4-cylinder model. Report just the number.
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diff --git a/validation_database/flight_2/data_csv/README.AIRLINES.txt b/validation_database/flight_2/data_csv/README.AIRLINES.txt
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@@ -0,0 +1,96 @@
+*****************************************************
+CPE 365 Alex Dekhtyar
+Cal Poly Computer Science Department
+San Luis Obispo College of Engineering
+California dekhtyar@csc.calpoly.edu
+*****************************************************
+ AIRLINES DATASET
+ Version 1.0
+ November 19, 2007
+*****************************************************
+Sources: the list of US airports is from
+ http://www.world-airport-codes.com/
+
+ the list of airlines is from http://www.wikipedia.org
+
+ the list of flights is synthesized.
+
+******************************************************
+
+This file describes the contents of the AIRLINES dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information about some US airlines and
+airports, and routes flown by the airlines between these airports.
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+ columns. Second line may be empty, or may contain
+ the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+ 4. All string values in the airports.csv and flights.csv files
+ have a trailing space.This is important to note, because
+ one of the string columns, airport code is the unique identifier
+ of the airport. This issue needs to be dealt with programmatically.
+
+
+ The dataset consists of the following files:
+
+
+ - airlines.csv : list of airlines
+ - airports100.csv : list of airports
+ - flights.csv : list of flights
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+airlines.csv
+
+ Id : unique identifier of the airline
+ Airline : full name of the airline
+ Abbreviation : abbreviated name of the airline
+ Country : country of the airline
+
+
+
+**************************************************************************
+
+airports100.csv
+
+ City : location of the airport
+ AirportCode : unique three-letter airport code
+ AirportName : name of the airport
+ Country : country of the airport
+CountryAbbrev : abbreviation of the country
+
+
+
+**************************************************************************
+
+flights.csv
+
+ Airline : airline that manages the flight
+ FlightNo : flight number (unique for each airline, may repeat
+ for different airlines)
+SourceAirport : Code for the airport from which the flight originates
+ (see airports100.AirportCode)
+ DestAirport : Code for the airport at which the flight terminates
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form,
+provided this file is kept unchanged and is distributed together with the
+data.
+
+Permission granted to modify and expand this dataset, provided this
+file is updated accordingly with new information.
+
+**************************************************************************
+**************************************************************************
+
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\ No newline at end of file
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+Find all airlines that have at least one flight out of AXX airport. Report the full name and the abbreviation of each airline
+
+Find all destinations served from the AXX airport by Northwest. Re- port flight number, airport code and the full name of the airport.
+
+Find all airports served by ALL five of the airlines listed below: Delta, Frontier, USAir, UAL and Southwest. Report just the airport codes.
+
+Find all airports that are served by at least three Southwest flights. Report just the three-letter codes of the airports
+
+Find the number of airports from which airport ANP can be reached with exactly one transfer.
+
+Find the number of airports from which airport ATE can be reached with at most one transfer. (make sure to exclude ATE itself from the count). Report just the number.
+
+Find all airports with exactly 17 outgoing flights. Report airport code and the full name of the airport
+
+For each room report the total revenue for all stays and the average revenue per stay generated by stays in the room that originated in the months of September
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