Upload 249 files

.gitattributes

@@ -53,3 +53,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/aan_1/aan_1.sqlite filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/bike_1/bike_1.sqlite filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/college_2/college_2.sqlite filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/formula_1/data_csv/lapTimes.csv filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/formula_1/formula_1.sqlite filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/sakila_1/sakila_1.sqlite filter=lfs diff=lfs merge=lfs -text
+spider-corpus-test/test_database/wta_1/wta_1.sqlite filter=lfs diff=lfs merge=lfs -text

spider-corpus-test/test_database/aan_1/aan_1.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:54c45e431f0f654bfac741cf69e66ca34dacf42a0d0abbde6fd426a7a1e60c4b
+size 17154048

spider-corpus-test/test_database/aan_1/annotation.json

@@ -0,0 +1,5 @@
+{
+    "label_id": null, 
+    "data": [], 
+    "review_id": null
+}

spider-corpus-test/test_database/academic/schema.sql

@@ -0,0 +1,108 @@
+PRAGMA foreign_keys = ON;
+CREATE TABLE "author" (
+"aid" int,
+"homepage" text,
+"name" text,
+"oid" int,
+primary key("aid")
+);
+CREATE TABLE "conference" (
+"cid" int,
+"homepage" text,
+"name" text,
+primary key ("cid")
+);
+CREATE TABLE "domain" (
+"did" int,
+"name" text,
+primary key ("did")
+);
+CREATE TABLE "domain_author" (
+"aid" int, 
+"did" int,
+primary key ("did", "aid"),
+foreign key("aid") references `author`("aid"),
+foreign key("did") references `domain`("did")
+);
+
+CREATE TABLE "domain_conference" (
+"cid" int,
+"did" int,
+primary key ("did", "cid"),
+foreign key("cid") references `conference`("cid"),
+foreign key("did") references `domain`("did")
+);
+CREATE TABLE "journal" (
+"homepage" text,
+"jid" int,
+"name" text,
+primary key("jid")
+);
+CREATE TABLE "domain_journal" (
+"did" int,
+"jid" int,
+primary key ("did", "jid"),
+foreign key("jid") references "journal"("jid"),
+foreign key("did") references "domain"("did")
+);
+CREATE TABLE "keyword" (
+"keyword" text,
+"kid" int,
+primary key("kid")
+);
+CREATE TABLE "domain_keyword" (
+"did" int,
+"kid" int,
+primary key ("did", "kid"),
+foreign key("kid") references "keyword"("kid"),
+foreign key("did") references "domain"("did")
+);
+CREATE TABLE "publication" (
+"abstract" text,
+"cid" text,
+"citation_num" int,
+"jid" int,
+"pid" int,
+"reference_num" int,
+"title" text,
+"year" int,
+primary key("pid"),
+foreign key("jid") references "journal"("jid"),
+foreign key("cid") references "conference"("cid")
+);
+CREATE TABLE "domain_publication" (
+"did" int,
+"pid" int,
+primary key ("did", "pid"),
+foreign key("pid") references "publication"("pid"),
+foreign key("did") references "domain"("did")
+);
+
+CREATE TABLE "organization" (
+"continent" text,
+"homepage" text,
+"name" text,
+"oid" int,
+primary key("oid")
+);
+
+CREATE TABLE "publication_keyword" (
+"pid" int,
+"kid" int,
+primary key ("kid", "pid"),
+foreign key("pid") references "publication"("pid"),
+foreign key("kid") references "keyword"("kid")
+);
+CREATE TABLE "writes" (
+"aid" int,
+"pid" int,
+primary key ("aid", "pid"),
+foreign key("pid") references "publication"("pid"),
+foreign key("aid") references "author"("aid")
+);
+CREATE TABLE "cite" (
+"cited" int,
+"citing"  int,
+foreign key("cited") references "publication"("pid"),
+foreign key("citing") references "publication"("pid")
+);

spider-corpus-test/test_database/address_1/link.txt

@@ -0,0 +1 @@
+http://www.cs.jhu.edu/~yarowsky/jhu.sql

spider-corpus-test/test_database/address_1/schema.sql

@@ -0,0 +1,218 @@
+create table Student (
+        StuID        INTEGER PRIMARY KEY,
+        LName        VARCHAR(12),
+        Fname        VARCHAR(12),
+        Age      INTEGER,
+        Sex      VARCHAR(1),
+        Major        INTEGER,
+        Advisor      INTEGER,
+        city_code    VARCHAR(3),
+        FOREIGN KEY(city_code) REFERENCES City(city_code)
+ );
+
+create table Direct_distance (
+  city1_code varchar(3) ,
+  city2_code varchar(3) ,
+  distance INTEGER,
+  FOREIGN KEY(city1_code) REFERENCES City(city_code),
+  FOREIGN KEY(city2_code) REFERENCES City(city_code)
+  
+) ;
+
+
+create table City (
+       city_code  	VARCHAR(3) PRIMARY KEY,
+       city_name  	VARCHAR(25),
+       state		VARCHAR(2),
+       country		VARCHAR(25),
+       latitude		FLOAT,
+       longitude	FLOAT
+);
+
+
+insert into Student values ( 1001, 'Smith', 'Linda', 18, 'F', 600, 1121,'BAL');
+ insert into Student values ( 1002, 'Kim', 'Tracy', 19, 'F', 600, 7712,'HKG');
+ insert into Student values ( 1003, 'Jones', 'Shiela', 21, 'F', 600, 7792,'WAS');
+ insert into Student values ( 1004, 'Kumar', 'Dinesh', 20, 'M', 600, 8423,'CHI');
+ insert into Student values ( 1005, 'Gompers', 'Paul', 26, 'M', 600, 1121,'YYZ');
+ insert into Student values ( 1006, 'Schultz', 'Andy', 18, 'M', 600, 1148,'BAL');
+ insert into Student values ( 1007, 'Apap', 'Lisa', 18, 'F', 600, 8918,'PIT');
+ insert into Student values ( 1008, 'Nelson', 'Jandy', 20, 'F', 600, 9172,'BAL');
+ insert into Student values ( 1009, 'Tai', 'Eric', 19, 'M', 600, 2192,'YYZ');
+ insert into Student values ( 1010, 'Lee', 'Derek', 17, 'M', 600, 2192,'HOU');
+ insert into Student values ( 1011, 'Adams', 'David', 22, 'M', 600, 1148,'PHL');
+ insert into Student values ( 1012, 'Davis', 'Steven', 20, 'M', 600, 7723,'PIT');
+ insert into Student values ( 1014, 'Norris', 'Charles', 18, 'M', 600, 8741, 'DAL');
+ insert into Student values ( 1015, 'Lee', 'Susan', 16, 'F', 600, 8721,'HKG');
+ insert into Student values ( 1016, 'Schwartz', 'Mark', 17, 'M', 600, 2192,'DET');
+ insert into Student values ( 1017, 'Wilson', 'Bruce', 27, 'M', 600, 1148,'LON');
+ insert into Student values ( 1018, 'Leighton', 'Michael', 20, 'M', 600, 1121, 'PIT');
+ insert into Student values ( 1019, 'Pang', 'Arthur', 18, 'M', 600, 2192,'WAS');
+ insert into Student values ( 1020, 'Thornton', 'Ian', 22, 'M', 520, 7271,'NYC');
+ insert into Student values ( 1021, 'Andreou', 'George', 19, 'M', 520, 8722, 'NYC');
+ insert into Student values ( 1022, 'Woods', 'Michael', 17, 'M', 540, 8722,'PHL');
+ insert into Student values ( 1023, 'Shieber', 'David', 20, 'M', 520, 8722,'NYC');
+ insert into Student values ( 1024, 'Prater', 'Stacy', 18, 'F', 540, 7271,'BAL');
+ insert into Student values ( 1025, 'Goldman', 'Mark', 18, 'M', 520, 7134,'PIT');
+ insert into Student values ( 1026, 'Pang', 'Eric', 19, 'M', 520, 7134,'HKG');
+ insert into Student values ( 1027, 'Brody', 'Paul', 18, 'M', 520, 8723,'LOS');
+ insert into Student values ( 1028, 'Rugh', 'Eric', 20, 'M', 550, 2311,'ROC');
+ insert into Student values ( 1029, 'Han', 'Jun', 17, 'M', 100, 2311,'PEK');
+ insert into Student values ( 1030, 'Cheng', 'Lisa', 21, 'F', 550, 2311,'SFO');
+ insert into Student values ( 1031, 'Smith', 'Sarah', 20, 'F', 550, 8772,'PHL');
+ insert into Student values ( 1032, 'Brown', 'Eric', 20, 'M', 550, 8772,'ATL');
+ insert into Student values ( 1033, 'Simms', 'William', 18, 'M', 550, 8772,'NAR');
+ insert into Student values ( 1034, 'Epp', 'Eric', 18, 'M', 050, 5718,'BOS');
+ insert into Student values ( 1035, 'Schmidt', 'Sarah', 26, 'F', 050, 5718,'WAS');
+
+insert into Direct_distance values ( 'BAL' , 'ATL' , 576 ) ;
+insert into Direct_distance values ( 'BAL' , 'BAL' , 0 ) ;
+insert into Direct_distance values ( 'BAL' , 'BKK' , 9631 ) ;
+insert into Direct_distance values ( 'BAL' , 'BOS' , 370 ) ;
+insert into Direct_distance values ( 'BAL' , 'CHI' , 621 ) ;
+insert into Direct_distance values ( 'BAL' , 'CPK' , 21 ) ;
+insert into Direct_distance values ( 'BAL' , 'DAL' , 1217 ) ;
+insert into Direct_distance values ( 'BAL' , 'DEL' , 7469 ) ;
+insert into Direct_distance values ( 'BAL' , 'DET' , 408 ) ;
+insert into Direct_distance values ( 'BAL' , 'EWR' , 169 ) ;
+insert into Direct_distance values ( 'BAL' , 'FRE' , 35 ) ;
+insert into Direct_distance values ( 'BAL' , 'HKG' , 8409 ) ;
+insert into Direct_distance values ( 'BAL' , 'HON' , 4832 ) ;
+insert into Direct_distance values ( 'BAL' , 'HOU' , 1240 ) ;
+insert into Direct_distance values ( 'BAL' , 'JNB' , 7850 ) ;
+insert into Direct_distance values ( 'BAL' , 'LON' , 3652 ) ;
+insert into Direct_distance values ( 'BAL' , 'LOS' , 2329 ) ;
+insert into Direct_distance values ( 'BAL' , 'MIA' , 946 ) ;
+insert into Direct_distance values ( 'BAL' , 'NAR' , 71 ) ;
+insert into Direct_distance values ( 'BAL' , 'NYC' , 185 ) ;
+insert into Direct_distance values ( 'BAL' , 'PAR' , 3800 ) ;
+insert into Direct_distance values ( 'BAL' , 'PEK' , 8041 ) ;
+insert into Direct_distance values ( 'BAL' , 'PHL' , 105 ) ;
+insert into Direct_distance values ( 'BAL' , 'PIT' , 210 ) ;
+insert into Direct_distance values ( 'BAL' , 'PVD' , 328 ) ;
+insert into Direct_distance values ( 'BAL' , 'ROC' , 277 ) ;
+insert into Direct_distance values ( 'BAL' , 'SAN' , 2295 ) ;
+insert into Direct_distance values ( 'BAL' , 'SFO' , 2457 ) ;
+insert into Direct_distance values ( 'BAL' , 'TYO' , 6740 ) ;
+insert into Direct_distance values ( 'BAL' , 'WAS' , 35 ) ;
+insert into Direct_distance values ( 'BAL' , 'YYZ' , 347 ) ;
+insert into Direct_distance values ( 'ATL' , 'BAL' , 576 ) ;
+insert into Direct_distance values ( 'ATL' , 'PHL' , 665 ) ;
+insert into Direct_distance values ( 'BKK' , 'BAL' , 9631 ) ;
+insert into Direct_distance values ( 'BOS' , 'BAL' , 370 ) ;
+insert into Direct_distance values ( 'BOS' , 'EWR' , 200 ) ;
+insert into Direct_distance values ( 'BOS' , 'PAR' , 3448 ) ;
+insert into Direct_distance values ( 'BOS' , 'PHL' , 280 ) ;
+insert into Direct_distance values ( 'CHI' , 'BAL' , 621 ) ;
+insert into Direct_distance values ( 'CHI' , 'PHL' , 678 ) ;
+insert into Direct_distance values ( 'CPK' , 'BAL' , 21 ) ;
+insert into Direct_distance values ( 'DAL' , 'BAL' , 1217 ) ;
+insert into Direct_distance values ( 'DEL' , 'BAL' , 7469 ) ;
+insert into Direct_distance values ( 'DET' , 'BAL' , 408 ) ;
+insert into Direct_distance values ( 'DET' , 'EWR' , 488 ) ;
+insert into Direct_distance values ( 'DET' , 'PHL' , 453 ) ;
+insert into Direct_distance values ( 'EWR' , 'BAL' , 169 ) ;
+insert into Direct_distance values ( 'EWR' , 'BOS' , 200 ) ;
+insert into Direct_distance values ( 'EWR' , 'DET' , 488 ) ;
+insert into Direct_distance values ( 'EWR' , 'LON' , 3458 ) ;
+insert into Direct_distance values ( 'EWR' , 'LOS' , 2454 ) ;
+insert into Direct_distance values ( 'EWR' , 'LOS' , 2454 ) ;
+insert into Direct_distance values ( 'EWR' , 'PHL' , 89 ) ;
+insert into Direct_distance values ( 'EWR' , 'SAN' , 2425 ) ;
+insert into Direct_distance values ( 'EWR' , 'WAS' , 199 ) ;
+insert into Direct_distance values ( 'FRE' , 'BAL' , 35 ) ;
+insert into Direct_distance values ( 'HKG' , 'BAL' , 8409 ) ;
+insert into Direct_distance values ( 'HON' , 'BAL' , 4832 ) ;
+insert into Direct_distance values ( 'HOU' , 'BAL' , 1240 ) ;
+insert into Direct_distance values ( 'HOU' , 'LOS' , 1385 ) ;
+insert into Direct_distance values ( 'HOU' , 'PHL' , 1324 ) ;
+insert into Direct_distance values ( 'HOU' , 'SAN' , 1270 ) ;
+insert into Direct_distance values ( 'HOU' , 'SFO' , 1635 ) ;
+insert into Direct_distance values ( 'JNB' , 'BAL' , 7850 ) ;
+insert into Direct_distance values ( 'LON' , 'BAL' , 3652 ) ;
+insert into Direct_distance values ( 'LON' , 'EWR' , 3458 ) ;
+insert into Direct_distance values ( 'LON' , 'NYC' , 3452 ) ;
+insert into Direct_distance values ( 'LON' , 'PHL' , 3546 ) ;
+insert into Direct_distance values ( 'LON' , 'TYO' , 5975 ) ;
+insert into Direct_distance values ( 'LON' , 'WAS' , 3650 ) ;
+insert into Direct_distance values ( 'LOS' , 'BAL' , 2329 ) ;
+insert into Direct_distance values ( 'LOS' , 'EWR' , 2454 ) ;
+insert into Direct_distance values ( 'LOS' , 'EWR' , 2454 ) ;
+insert into Direct_distance values ( 'LOS' , 'HOU' , 1385 ) ;
+insert into Direct_distance values ( 'LOS' , 'PHL' , 2401 ) ;
+insert into Direct_distance values ( 'LOS' , 'SAN' , 109 ) ;
+insert into Direct_distance values ( 'MIA' , 'BAL' , 946 ) ;
+insert into Direct_distance values ( 'NAR' , 'BAL' , 71 ) ;
+insert into Direct_distance values ( 'NYC' , 'BAL' , 185 ) ;
+insert into Direct_distance values ( 'NYC' , 'LON' , 3452 ) ;
+insert into Direct_distance values ( 'PAR' , 'BAL' , 3800 ) ;
+insert into Direct_distance values ( 'PAR' , 'BOS' , 3448 ) ;
+insert into Direct_distance values ( 'PEK' , 'BAL' , 8041 ) ;
+insert into Direct_distance values ( 'PHL' , 'ATL' , 665 ) ;
+insert into Direct_distance values ( 'PHL' , 'BAL' , 105 ) ;
+insert into Direct_distance values ( 'PHL' , 'BOS' , 280 ) ;
+insert into Direct_distance values ( 'PHL' , 'CHI' , 678 ) ;
+insert into Direct_distance values ( 'PHL' , 'DET' , 453 ) ;
+insert into Direct_distance values ( 'PHL' , 'EWR' , 89 ) ;
+insert into Direct_distance values ( 'PHL' , 'HOU' , 1324 ) ;
+insert into Direct_distance values ( 'PHL' , 'LON' , 3546 ) ;
+insert into Direct_distance values ( 'PHL' , 'LOS' , 2401 ) ;
+insert into Direct_distance values ( 'PHL' , 'PIT' , 267 ) ;
+insert into Direct_distance values ( 'PHL' , 'SAN' , 2369 ) ;
+insert into Direct_distance values ( 'PHL' , 'SFO' , 2521 ) ;
+insert into Direct_distance values ( 'PHL' , 'WAS' , 119 ) ;
+insert into Direct_distance values ( 'PIT' , 'BAL' , 210 ) ;
+insert into Direct_distance values ( 'PIT' , 'PHL' , 267 ) ;
+insert into Direct_distance values ( 'PIT' , 'SAN' , 2106 ) ;
+insert into Direct_distance values ( 'PVD' , 'BAL' , 328 ) ;
+insert into Direct_distance values ( 'ROC' , 'BAL' , 277 ) ;
+insert into Direct_distance values ( 'ROC' , 'WAS' , 296 ) ;
+insert into Direct_distance values ( 'SAN' , 'BAL' , 2295 ) ;
+insert into Direct_distance values ( 'SAN' , 'EWR' , 2425 ) ;
+insert into Direct_distance values ( 'SAN' , 'HOU' , 1270 ) ;
+insert into Direct_distance values ( 'SAN' , 'LOS' , 109 ) ;
+insert into Direct_distance values ( 'SAN' , 'PHL' , 2369 ) ;
+insert into Direct_distance values ( 'SAN' , 'PIT' , 2106 ) ;
+insert into Direct_distance values ( 'SFO' , 'BAL' , 2457 ) ;
+insert into Direct_distance values ( 'SFO' , 'HOU' , 1635 ) ;
+insert into Direct_distance values ( 'SFO' , 'PHL' , 2521 ) ;
+insert into Direct_distance values ( 'TYO' , 'BAL' , 6740 ) ;
+insert into Direct_distance values ( 'TYO' , 'LON' , 5975 ) ;
+insert into Direct_distance values ( 'WAS' , 'BAL' , 35 ) ;
+insert into Direct_distance values ( 'WAS' , 'EWR' , 199 ) ;
+insert into Direct_distance values ( 'WAS' , 'LON' , 3650 ) ;
+insert into Direct_distance values ( 'WAS' , 'PHL' , 119 ) ;
+insert into Direct_distance values ( 'WAS' , 'ROC' , 296 ) ;
+insert into Direct_distance values ( 'YYZ' , 'BAL' , 347 ) ;
+
+insert into City values ( 'BAL' , 'Baltimore' , 'MD' , 'USA' , 39.288 , -76.617 ) ;
+insert into City values ( 'PIT' , 'Pittsburgh' , 'PA' , 'USA' , 40.437 , -80.000 ) ;
+insert into City values ( 'PHL' , 'Philadelphia' , 'PA' , 'USA' , 39.950 , -75.150 ) ;
+insert into City values ( 'WAS' , 'Washington' , 'DC' , 'USA' , 38.892 , -77.017 ) ;
+insert into City values ( 'NYC' , 'New York' , 'NY' , 'USA' , 40.849 , -73.867) ;
+insert into City values ( 'ATL' , 'Atlanta' , 'GA' , 'USA' , 33.763 , -84.317 ) ;
+insert into City values ( 'EWR' , 'Newark' , 'NJ' , 'USA' , 40.737 , -74.167 );
+insert into City values ( 'FRE' , 'Frederick' , 'MD' , 'USA' , 39.415 , -77.417 ) ;
+insert into City values ( 'NAR' , 'Newark' , 'DE' , 'USA' , 39.683 , -75.750 );
+insert into City values ( 'SAN' , 'San Diego' , 'CA' , 'USA' , 32.713 , -117.150) ;
+insert into City values ( 'LOS' , 'Los Angeles' , 'CA' , 'USA' , 34.058 ,-118.250) ;
+insert into City values ( 'HON' , 'Honolulu' , 'HI' , 'USA' , 21.313 , -157.850 ) ;
+insert into City values ( 'SFO' , 'San Francisco' , 'CA' , 'USA' , 37.775 ,-122.417) ;
+insert into City values ( 'PVD' , 'Providence' , 'RI' , 'USA' , 41.817 , -71.400 ) ;
+insert into City values ( 'BOS' , 'Boston' , 'MA' , 'USA' , 42.362 , -71.050 );
+insert into City values ( 'DET' , 'Detroit' , 'MI' , 'USA' , 42.323 , -83.167 ) ;
+insert into City values ( 'CHI' , 'Chicago' , 'IL' , 'USA' , 41.883 , -87.617 ) ;
+insert into City values ( 'ROC' , 'Rochester' , 'NY' , 'USA' , 43.158 , -77.600 ) ;
+insert into City values ( 'DAL' , 'Dallas' , 'TX' , 'USA' , 32.777 , -96.800 );
+insert into City values ( 'HOU' , 'Houston' , 'TX' , 'USA' , 29.834 , -95.000 ) ;
+insert into City values ( 'MIA' , 'Miami' , 'FL' , 'USA' , 25.465 , -80.150 ) ;
+insert into City values ( 'CPK' , 'College Park' , 'MD' , 'USA' , 38.987 ,-76.933) ;
+insert into City values ( 'YYZ' , 'Toronto' , 'ON' , 'CANADA' , 43.650 , -79.333 ) ;
+insert into City values ( 'DEL' , 'Delhi' , 'DE' , 'INDIA' , 28.617 , 77.217 );
+insert into City values ( 'PEK' , 'Beijing' , 'BE' , 'CHINA' , 39.917 ,116.417) ;
+insert into City values ( 'HKG' , 'Hong Kong' , 'HK' , 'CHINA' , 22.250 ,114.167) ;
+insert into City values ( 'TYO' , 'Tokyo' , 'XX' , 'JAPAN' , 35.700 , 139.767 ) ;
+insert into City values ( 'LON' , 'London' , 'EN' , 'UK' , 51.500 , -0.167 ) ;
+insert into City values ( 'PAR' , 'Paris' , 'XX' , 'FRANCE' , 48.867 , 2.333 );
+insert into City values ( 'JNB' , 'Johannesburg' , 'XX' , 'SAFRICA' , -25.550 , 28.000 ) ;
+insert into City values ( 'BKK' , 'Bangkok' , 'XX' , 'THAILAND' , 13.733 , 100.500 ) ;

spider-corpus-test/test_database/advertising_agencies/schema.sql

@@ -0,0 +1,162 @@
+PRAGMA foreign_keys = ON;
+CREATE TABLE `Agencies` (
+`agency_id` INTEGER PRIMARY KEY,
+`agency_details` VARCHAR(255) NOT NULL
+);
+
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (1, 'Heller-Muller');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (2, 'Bergstrom, Koss and Ebert');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (3, 'Douglas-Langworth');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (4, 'Fadel Group');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (5, 'White, Corwin and Rath');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (6, 'Beatty-Sipes');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (7, 'West, Grady and Durgan');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (8, 'Hickle-Durgan');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (9, 'Grant, Jaskolski and Brekke');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (10, 'Muller, Klein and Kunde');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (11, 'Bins-Strosin');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (12, 'Emard-Fisher');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (13, 'Upton, Hayes and Schumm');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (14, 'Renner LLC');
+INSERT INTO Agencies (`agency_id`, `agency_details`) VALUES (15, 'Cartwright, Ullrich and Gulgowski');
+
+
+CREATE TABLE `Staff` (
+`staff_id` INTEGER PRIMARY KEY,
+`agency_id` INTEGER NOT NULL,
+`staff_details` VARCHAR(255) NOT NULL
+);
+
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (1, 6, 'Rubie');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (2, 7, 'Sheridan');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (3, 10, 'Annabell');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (4, 2, 'Kendra');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (5, 7, 'Amara');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (6, 15, 'Lolita');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (7, 2, 'Hailie');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (8, 14, 'Armando');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (9, 10, 'Elroy');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (10, 8, 'Parker');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (11, 11, 'Clarissa');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (12, 5, 'Joaquin');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (13, 14, 'Antone');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (14, 14, 'Marques');
+INSERT INTO Staff (`staff_id`, `agency_id`, `staff_details`) VALUES (15, 15, 'Margaret');
+
+
+CREATE TABLE `Clients` (
+`client_id` INTEGER PRIMARY KEY,
+`agency_id` INTEGER NOT NULL,
+`sic_code` VARCHAR(10) NOT NULL,
+`client_details` VARCHAR(255) NOT NULL,
+FOREIGN KEY (`agency_id` ) REFERENCES `Agencies`(`agency_id` )
+);INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (1, 8, 'Mutual', 'Alta');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (2, 5, 'Bad', 'Mac');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (3, 3, 'Bad', 'Johnpaul');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (4, 5, 'Bad', 'Taurean');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (5, 14, 'Bad', 'Lucie');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (6, 8, 'Mutual', 'Rosa');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (7, 9, 'Mutual', 'Kirsten');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (8, 1, 'Mutual', 'Vincent');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (9, 9, 'Mutual', 'Heber');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (10, 9, 'Mutual', 'Callie');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (11, 14, 'Bad', 'Vaughn');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (12, 7, 'Mutual', 'Rae');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (13, 9, 'Mutual', 'Eloise');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (14, 11, 'Bad', 'Philip');
+INSERT INTO Clients (`client_id`, `agency_id`, `sic_code`, `client_details`) VALUES (15, 1, 'Bad', 'Maximo');
+
+
+
+CREATE TABLE `Invoices` (
+`invoice_id` INTEGER PRIMARY KEY,
+`client_id` INTEGER NOT NULL,
+`invoice_status` VARCHAR(10) NOT NULL,
+`invoice_details` VARCHAR(255) NOT NULL,
+FOREIGN KEY (`client_id` ) REFERENCES `Clients`(`client_id` )
+);
+CREATE TABLE `Meetings` (
+`meeting_id` INTEGER PRIMARY KEY,
+`client_id` INTEGER NOT NULL,
+`meeting_outcome` VARCHAR(10) NOT NULL,
+`meeting_type` VARCHAR(10) NOT NULL,
+`billable_yn` VARCHAR(1),
+`start_date_time` DATETIME,
+`end_date_time` DATETIME,
+`purpose_of_meeting` VARCHAR(255),
+`other_details` VARCHAR(255) NOT NULL,
+FOREIGN KEY (`client_id` ) REFERENCES `Clients`(`client_id` )
+);
+CREATE TABLE `Payments` (
+`payment_id` INTEGER NOT NULL ,
+`invoice_id` INTEGER NOT NULL,
+`payment_details` VARCHAR(255) NOT NULL,
+FOREIGN KEY (`invoice_id` ) REFERENCES `Invoices`(`invoice_id` )
+);
+
+CREATE TABLE `Staff_in_Meetings` (
+`meeting_id` INTEGER NOT NULL,
+`staff_id` INTEGER NOT NULL,
+FOREIGN KEY (`meeting_id` ) REFERENCES `Meetings`(`meeting_id` ),
+FOREIGN KEY (`staff_id` ) REFERENCES `Staff`(`staff_id` )
+);
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (1, 5, 'Working', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (2, 9, 'Starting', 'good');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (3, 15, 'Starting', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (4, 8, 'Starting', 'ok');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (5, 7, 'Finish', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (6, 8, 'Working', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (7, 7, 'Finish', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (8, 14, 'Finish', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (9, 12, 'Starting', 'good');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (10, 2, 'Finish', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (11, 11, 'Working', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (12, 9, 'Starting', 'good');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (13, 4, 'Starting', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (14, 14, 'Working', 'excellent');
+INSERT INTO Invoices (`invoice_id`, `client_id`, `invoice_status`, `invoice_details`) VALUES (15, 14, 'Working', 'excellent');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (1, 15, 'Report', 'Team', '0', '2018-03-06 05:07:33', '2018-03-21 09:26:41', 'get proposal done', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (2, 3, 'Summary', 'Group', '0', '2018-03-16 02:24:10', '2018-03-21 17:57:59', 'vote for solutions', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (3, 4, 'Summary', 'Team', '1', '2018-03-06 21:02:06', '2018-03-01 05:10:01', 'get proposal done', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (4, 5, 'Vote results', 'Company', '1', '2018-03-10 05:03:46', '2018-02-25 23:20:12', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (5, 14, 'Summary', 'Company', '1', '2018-02-26 18:35:24', '2018-03-12 18:48:55', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (6, 8, 'Vote results', 'Team', '0', '2018-03-20 08:56:47', '2018-02-24 22:36:35', 'weekly report', 'absent staff');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (7, 13, 'Vote results', 'Group', '1', '2018-03-01 22:20:09', '2018-03-21 04:24:57', 'vote for solutions', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (8, 8, 'Report', 'Company', '0', '2018-03-16 06:38:16', '2018-03-20 12:24:04', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (9, 4, 'Report', 'Group', '1', '2018-03-18 15:35:54', '2018-03-05 13:33:21', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (10, 7, 'Summary', 'Team', '0', '2018-02-27 07:43:53', '2018-02-27 02:40:21', 'vote for solutions', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (11, 6, 'Summary', 'Team', '1', '2018-03-21 19:18:39', '2018-03-17 15:38:01', 'get proposal done', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (12, 10, 'Summary', 'Company', '0', '2018-03-17 09:56:49', '2018-03-03 21:51:07', 'monthly report', 'absent staff');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (13, 2, 'Report', 'Team', '1', '2018-02-28 15:39:03', '2018-03-17 13:09:45', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (14, 2, 'Vote results', 'Group', '1', '2018-03-02 19:04:27', '2018-03-15 04:21:40', 'weekly report', '0');
+INSERT INTO Meetings (`meeting_id`, `client_id`, `meeting_outcome`, `meeting_type`, `billable_yn`, `start_date_time`, `end_date_time`, `purpose_of_meeting`, `other_details`) VALUES (15, 2, 'Vote results', 'Company', '0', '2018-02-25 07:06:48', '2018-02-25 09:39:29', 'weekly report', '');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (1, 3, 'MasterCard');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (2, 5, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (3, 8, 'Discover Card');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (4, 11, 'MasterCard');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (5, 12, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (6, 9, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (7, 14, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (8, 2, 'American Express');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (9, 8, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (10, 8, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (11, 12, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (12, 11, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (13, 2, 'MasterCard');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (14, 6, 'Visa');
+INSERT INTO Payments (`payment_id`, `invoice_id`, `payment_details`) VALUES (15, 3, 'Visa');
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (6, 7);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (14, 3);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (4, 5);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (1, 11);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (2, 10);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (9, 1);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (8, 3);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (8, 7);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (8, 6);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (3, 5);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (11, 2);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (10, 12);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (2, 8);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (6, 4);
+INSERT INTO Staff_in_Meetings (`meeting_id`, `staff_id`) VALUES (14, 3);

spider-corpus-test/test_database/aircraft/schema.sql

@@ -0,0 +1,108 @@
+
+PRAGMA foreign_keys = ON;
+
+
+CREATE TABLE `pilot` (
+  `Pilot_Id` int(11) NOT NULL,
+  `Name` varchar(50) NOT NULL,
+  `Age` int(11) NOT NULL,
+  PRIMARY KEY (`Pilot_Id`)
+);
+
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (1, 'Prof. Zackery Collins', 23);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (2, 'Katheryn Gorczany IV', 20);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (3, 'Mr. Cristian Halvorson II', 23);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (4, 'Ayana Spencer', 25);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (5, 'Ellen Ledner III', 31);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (6, 'Elisha Hickle V', 37);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (7, 'Dr. Jade Bradtke V', 26);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (8, 'Winnifred Boyle', 30);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (9, 'Della Lindgren', 29);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (10, 'Maxwell Graham', 26);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (11, 'Blaise Muller', 33);
+INSERT INTO `pilot` (`Pilot_Id`, `Name`, `age`) VALUES (12, 'Baylee Steuber', 30);
+
+
+CREATE TABLE `aircraft` (
+  "Aircraft_ID" int(11) NOT NULL,
+  "Aircraft" varchar(50) NOT NULL,
+  "Description" varchar(50) NOT NULL,
+  "Max_Gross_Weight" varchar(50) NOT NULL,
+  "Total_disk_area" varchar(50) NOT NULL,
+  "Max_disk_Loading" varchar(50) NOT NULL,
+  PRIMARY KEY (`Aircraft_ID`)
+);
+
+
+CREATE TABLE `match` (
+"Round" real,
+"Location" text,
+"Country" text,
+"Date" text,
+"Fastest_Qualifying" text,
+"Winning_Pilot" text,
+"Winning_Aircraft" text,
+PRIMARY KEY ("Round"),
+FOREIGN KEY (`Winning_Aircraft`) REFERENCES `aircraft`(`Aircraft_ID`),
+FOREIGN KEY (`Winning_Pilot`) REFERENCES `pilot`(`Pilot_Id`)
+);
+
+CREATE TABLE `airport` (
+"Airport_ID" int,
+"Airport_Name" text,
+"Total_Passengers" real,
+"%_Change_2007" text,
+"International_Passengers" real,
+"Domestic_Passengers" real,
+"Transit_Passengers" real,
+"Aircraft_Movements" real,
+"Freight_Metric_Tonnes" real,
+PRIMARY KEY ("Airport_ID")
+);
+
+CREATE TABLE `airport_aircraft` (
+"ID" int,
+"Airport_ID" int,
+"Aircraft_ID" int,
+PRIMARY KEY ("Airport_ID","Aircraft_ID"),
+FOREIGN KEY ("Airport_ID") REFERENCES `airport`(`Airport_ID`),
+FOREIGN KEY ("Aircraft_ID") REFERENCES `aircraft`(`Aircraft_ID`)
+);
+
+
+
+INSERT INTO  "aircraft" VALUES (1,"Robinson R-22","Light utility helicopter","1,370 lb (635 kg)","497 ft² (46.2 m²)","2.6 lb/ft² (14 kg/m²)");
+INSERT INTO  "aircraft" VALUES (2,"Bell 206B3 JetRanger","Turboshaft utility helicopter","3,200 lb (1,451 kg)","872 ft² (81.1 m²)","3.7 lb/ft² (18 kg/m²)");
+INSERT INTO  "aircraft" VALUES (3,"CH-47D Chinook","Tandem rotor helicopter","50,000 lb (22,680 kg)","5,655 ft² (526 m²)","8.8 lb/ft² (43 kg/m²)");
+INSERT INTO  "aircraft" VALUES (4,"Mil Mi-26","Heavy-lift helicopter","123,500 lb (56,000 kg)","8,495 ft² (789 m²)","14.5 lb/ft² (71 kg/m²)");
+INSERT INTO  "aircraft" VALUES (5,"CH-53E Super Stallion","Heavy-lift helicopter","73,500 lb (33,300 kg)","4,900 ft² (460 m²)","15 lb/ft² (72 kg/m²)");
+
+
+INSERT INTO  "match" VALUES ("1","Mina' Zayid , Abu Dhabi","United Arab Emirates","March 26–27","Hannes Arch",1,1);
+INSERT INTO  "match" VALUES ("2","Swan River , Perth","Australia","April 17–18","Paul Bonhomme",4,1);
+INSERT INTO  "match" VALUES ("3","Flamengo Beach , Rio de Janeiro","Brazil","May 8–9","Hannes Arch",6,2);
+INSERT INTO  "match" VALUES ("4","Windsor , Ontario","Canada","June 5–6","Nigel Lamb",4,4);
+INSERT INTO  "match" VALUES ("5","New York City","United States","June 19–20","Hannes Arch",9,3);
+INSERT INTO  "match" VALUES ("6","EuroSpeedway Lausitz","Germany","August 7–8","Paul Bonhomme",2,4);
+INSERT INTO  "match" VALUES ("7","River Danube , Budapest","Hungary","Cancelled","Cancelled",6,5);
+
+
+
+INSERT INTO  "airport" VALUES (1,"London Heathrow","67054745","1.5%","61344438","5562516","147791","478693","1397054");
+INSERT INTO  "airport" VALUES (2,"London Gatwick","34205887","2.9%","30431051","3730963","43873","263653","107702");
+INSERT INTO  "airport" VALUES (3,"London Stansted","22360364","6.0%","19996947","2343428","19989","193282","197738");
+INSERT INTO  "airport" VALUES (4,"Manchester","21219195","4.0%","18119230","2943719","156246","204610","141781");
+INSERT INTO  "airport" VALUES (5,"London Luton","10180734","2.6%","8853224","1320678","6832","117859","40518");
+INSERT INTO  "airport" VALUES (6,"Birmingham Airport","9627589","4.3%","8105162","1471538","50889","112227","12192");
+INSERT INTO  "airport" VALUES (7,"Edinburgh","9006702","0.5%","3711140","5281038","14524","125550","12418");
+INSERT INTO  "airport" VALUES (8,"Glasgow International","8178891","7.0%","3943139","4192121","43631","100087","3546");
+INSERT INTO  "airport" VALUES (9,"Bristol","6267114","5.7%","5057051","1171605","38458","76517","3");
+INSERT INTO  "airport" VALUES (10,"East Midlands","5620673","3.8%","4870184","746094","4395","93038","261507");
+
+
+
+INSERT INTO  "airport_aircraft" VALUES (1,6,5);
+INSERT INTO  "airport_aircraft" VALUES (2,2,1);
+INSERT INTO  "airport_aircraft" VALUES (3,1,2);
+INSERT INTO  "airport_aircraft" VALUES (4,9,3);
+

spider-corpus-test/test_database/bbc_channels/schema.sql

@@ -0,0 +1,83 @@
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "channel" (
+"Channel_ID" int,
+"Name" text,
+"Analogue_terrestrial_channel" text,
+"Digital_terrestrial_channel" text,
+"Internet" text,
+PRIMARY KEY ("Channel_ID")
+);
+
+
+CREATE TABLE "director" (
+"Director_ID" int,
+"Name" text,
+"Age" int,
+PRIMARY KEY ("Director_ID")
+);
+
+INSERT INTO  "channel" VALUES ("1","BBC One","1","HD","bbc.co.uk");
+INSERT INTO  "channel" VALUES ("2","ITV","3","HD","ITV - itv.com");
+INSERT INTO  "channel" VALUES ("3","BBC Two","2","2","bbc.co.uk");
+INSERT INTO  "channel" VALUES ("4","Channel 4","4","8","channel4.com");
+INSERT INTO  "channel" VALUES ("5","Channel 5","5","44","unavailable");
+INSERT INTO  "channel" VALUES ("6","ITV3","unavailable","10","itv.com");
+INSERT INTO  "channel" VALUES ("7","ITV2","unavailable","6","itv.com");
+INSERT INTO  "channel" VALUES ("8","E4","unavailable","28","e4.com");
+INSERT INTO  "channel" VALUES ("9","Sky Sports 1","unavailable","unavailable","skysports.com");
+INSERT INTO  "channel" VALUES ("10","Sky1","unavailable","unavailable","sky.com");
+INSERT INTO  "channel" VALUES ("11","CBeebies","unavailable","71","bbc.co.uk");
+INSERT INTO  "channel" VALUES ("12","ITV4","unavailable","24","itv.com");
+INSERT INTO  "channel" VALUES ("13","BBC Three","unavailable","7","bbc.co.uk");
+INSERT INTO  "channel" VALUES ("14","Dave","unavailable","12","dave.uktv.co.uk");
+
+
+INSERT INTO  "director" VALUES (1,"DeSean Jackson","60");
+INSERT INTO  "director" VALUES (2,"Hank Baskett","90");
+INSERT INTO  "director" VALUES (3,"Greg Lewis","52");
+INSERT INTO  "director" VALUES (4,"Brent Celek","44");
+INSERT INTO  "director" VALUES (5,"Correll Buckhalter","59");
+INSERT INTO  "director" VALUES (6,"Reggie Brown","40");
+INSERT INTO  "director" VALUES (7,"Brian Westbrook","47");
+INSERT INTO  "director" VALUES (8,"Jason Avant","31");
+INSERT INTO  "director" VALUES (9,"Kevin Curtis","32");
+INSERT INTO  "director" VALUES (10,"L.J. Smith","43");
+
+
+CREATE TABLE "program" (
+"Program_ID" int,
+"Start_Year" real,
+"Title" text,
+"Director_ID" int,
+"Channel_ID" int,
+PRIMARY KEY ("Program_ID"),
+FOREIGN KEY ("Director_ID") REFERENCES "director"("Director_ID"),
+FOREIGN KEY ("Channel_ID") REFERENCES "channel"("Channel_ID")
+);
+
+
+INSERT INTO  "program" VALUES (1,"2002","The Angry Brigade",1,14);
+INSERT INTO  "program" VALUES (2,"2006","Dracula",2,10);
+INSERT INTO  "program" VALUES (3,"2006","Another Country",3,3);
+INSERT INTO  "program" VALUES (4,"2007","Caesar III: An Empire Without End",5,14);
+INSERT INTO  "program" VALUES (5,"2008","Othello",3,7);
+INSERT INTO  "program" VALUES (6,"2008","The Leopard",6,7);
+INSERT INTO  "program" VALUES (7,"2008","Cyrano de Bergerac",10,14);
+INSERT INTO  "program" VALUES (8,"2009","Carnival",9,10);
+
+
+CREATE TABLE "director_admin" (
+"Director_ID" int,
+"Channel_ID" int,
+"Is_first_director" bool,
+PRIMARY KEY ("Director_ID","Channel_ID"),
+FOREIGN KEY ("Director_ID") REFERENCES "director"("Director_ID"),
+FOREIGN KEY ("Channel_ID") REFERENCES "channel"("Channel_ID")
+);
+INSERT INTO  "director_admin" VALUES (1,14,"T");
+INSERT INTO  "director_admin" VALUES (5,14,"F");
+INSERT INTO  "director_admin" VALUES (3,14,"F");
+INSERT INTO  "director_admin" VALUES (4,7,"T");
+INSERT INTO  "director_admin" VALUES (6,7,"F");
+

spider-corpus-test/test_database/bike_1/bike_1.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5ae0e24e3a9d860a38ec6256828e3b9e37691c80931ef554adc202f8eb2950c
+size 1785856

spider-corpus-test/test_database/boat_1/Boats.csv

@@ -0,0 +1,4 @@
+bid,name,color
+101,Legacy,red
+102,Melon,blue
+103,Mars,red

spider-corpus-test/test_database/boat_1/Reserves.csv

@@ -0,0 +1,5 @@
+sid,bid,day
+1,102,9/12
+2,102,9/13
+2,103,9/14
+2,103,9/15

spider-corpus-test/test_database/boat_1/Sailors.csv

@@ -0,0 +1,4 @@
+sid,name,rating,age
+1,Eugene,7,22
+2,Luis, 2, 39
+3,Ken, 8, 27

spider-corpus-test/test_database/boat_1/schema.sql

@@ -0,0 +1,20 @@
+create table Sailors (
+sid INTEGER primary key,
+name TEXT,
+rating INTEGER,
+age INTEGER
+);
+
+CREATE TABLE Boats (
+  bid INTEGER primary key,
+  name TEXT,
+  color TEXT
+);
+
+CREATE TABLE Reserves (
+  sid INTEGER,
+  bid INTEGER,
+  day TEXT,
+  foreign key (sid) references Sailors(sid),
+  foreign key (bid) references Boats(bid)
+);

spider-corpus-test/test_database/book_1/annotation.json

@@ -0,0 +1,101 @@
+{
+    "label_id": null, 
+    "data": [
+        {
+            "nl": "List of books, the publication year of each of them and their authors, ordered by publication year\n", 
+            "id": 0, 
+            "sql": "SELECT TITLE, A\u00d1O \"YEAR\", NAME \"Author name\"\nFROM BOOK NATURAL JOIN AUTHOR_BOOK, AUTHOR\nWHERE AUTHOR_BOOK.AUTHOR=AUTHOR.IDAUTHOR\nORDER BY A\u00d1O;\n"
+        }, 
+        {
+            "nl": "List of books that were published before 01-01-2000.\n", 
+            "id": 1, 
+            "sql": "SELECT TITLE, A\u00d1O\nFROM BOOK\nWHERE A\u00d1O<'2000';\n"
+        }, 
+        {
+            "nl": "List of clients that have bought at least one book. \n", 
+            "id": 2, 
+            "sql": "SELECT DISTINCT IDCLIENT, NAME\nFROM CLIENT NATURAL JOIN ORDERS;\nselect distinct client.name, Client.IdClient\nfrom Client, Orders where\nClient.IdClient=Orders.IdClient;\n"
+        }, 
+        {
+            "nl": "List of clients that bought the book whose ISBN= 4554672899910.\n", 
+            "id": 3, 
+            "sql": "SELECT IDCLIENT, NAME\nFROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER\nWHERE ISBN='4554672899910';\n"
+        }, 
+        {
+            "nl": "List of clients whose name contains  \u2018Jo\u2019 and the books that they have bought. \n", 
+            "id": 4, 
+            "sql": "SELECT IDCLIENT, NAME, TITLE\nFROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK\nWHERE NAME LIKE '%Jo%';\n"
+        }, 
+        {
+            "nl": "List of clients that have bought at least a book whose price is greater than 10.\n", 
+            "id": 5, 
+            "sql": "SELECT DISTINCT IDCLIENT, NAME\nFROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK\nWHERE BOOK.SALEPRICE>10;\n"
+        }, 
+        {
+            "nl": "List of clients that have placed more than one order in the same date. \n", 
+            "id": 6, 
+            "sql": "SELECT IDCLIENT, NAME\nFROM CLIENT\nWHERE IDCLIENT=(\n  SELECT IDCLIENT\n  FROM ORDERS\n  GROUP BY(IDCLIENT,DATEORDER)\n  HAVING COUNT(DATEORDER)>1\n);\n"
+        }, 
+        {
+            "nl": "List of clients and dates in which they have placed orders that have not been sent yet. \n", 
+            "id": 7, 
+            "sql": "SELECT IDCLIENT, NAME, DATEORDER\nFROM CLIENT NATURAL JOIN ORDERS\nWHERE DATEEXPED IS NULL;\n"
+        }, 
+        {
+            "nl": "List of clients that have not bought books whose price is greater than 10.\n", 
+            "id": 8, 
+            "sql": "SELECT DISTINCT IDCLIENT, NAME\nFROM CLIENT\nWHERE IDCLIENT NOT IN (\n  SELECT IDCLIENT\n  FROM ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK\n  WHERE SALEPRICE < 10\n);\n"
+        }, 
+        {
+            "nl": "List of books whose sale price is greater than 30\u20ac or that were published before 2000. \n", 
+            "id": 9, 
+            "sql": "SELECT TITLE, A\u00d1O, SALEPRICE\nFROM BOOK\nWHERE A\u00d1O<'2000' OR SALEPRICE>30;\n"
+        }, 
+        {
+            "nl": "List of books and amount of copies of each of them that have been sold. \n", 
+            "id": 10, 
+            "sql": "SELECT TITLE, ISBN, SUM(AMOUNT)\nFROM BOOKS_ORDER NATURAL JOIN BOOK\nGROUP BY TITLE, ISBN\nORDER BY SUM(AMOUNT) DESC;\n"
+        }, 
+        {
+            "nl": "List of clients and the total amount that they have spent in the bookstore. \n", 
+            "id": 11, 
+            "sql": "SELECT IDCLIENT, NAME, SUM(AMOUNT*SALEPRICE) \"Total\"\nFROM CLIENT NATURAL JOIN ORDERS NATURAL JOIN BOOKS_ORDER NATURAL JOIN BOOK\nGROUP BY IDCLIENT, NAME;\n"
+        }, 
+        {
+            "nl": "Profits obtained from sales of books. \n", 
+            "id": 12, 
+            "sql": "SELECT SUM(AMOUNT*(SALEPRICE-PURCHASEPRICE)) \"Total\"\nFROM BOOKS_ORDER NATURAL JOIN BOOK;\n"
+        }, 
+        {
+            "nl": "Orders whose total amount is greater than 100.\n", 
+            "id": 13, 
+            "sql": "SELECT IDORDER, SUM(AMOUNT*SALEPRICE) \"TOTAL\"\nFROM BOOKS_ORDER NATURAL JOIN BOOK\nGROUP BY IDORDER\nHAVING SUM(AMOUNT*SALEPRICE)>100\nORDER BY IDORDER;\n"
+        }, 
+        {
+            "nl": "Orders and the total amount of each of them that contains more than a book (title). \n", 
+            "id": 14, 
+            "sql": "SELECT IDORDER, SUM(AMOUNT*SALEPRICE) \"TOTAL\"\nFROM BOOKS_ORDER NATURAL JOIN BOOK\nGROUP BY IDORDER\nHAVING COUNT(TITLE)>1;\n"
+        }, 
+        {
+            "nl": "Orders and the total amount of each of them that contains more than 4 copies\n", 
+            "id": 15, 
+            "sql": "SELECT IDORDER, SUM(AMOUNT*SALEPRICE) \"Total\"\nFROM BOOKS_ORDER NATURAL JOIN BOOK \nWHERE AMOUNT>4\nGROUP BY IDORDER;\n"
+        }, 
+        {
+            "nl": "List of the most expensive books. \n", 
+            "id": 16, 
+            "sql": "SELECT ISBN, TITLE, SALEPRICE\nFROM BOOK\nWHERE SALEPRICE IN (SELECT MAX(SALEPRICE) FROM BOOK);\n"
+        }, 
+        {
+            "nl": "List of books that have not been sold or that have been sold but the profit per copy is less than 5\n", 
+            "id": 17, 
+            "sql": "SELECT ISBN, TITLE\nFROM BOOK\nWHERE(SALEPRICE-PURCHASEPRICE)<5 OR ISBN NOT IN(\n  SELECT DISTINCT ISBN FROM BOOKS_ORDER\n);\n"
+        }, 
+        {
+            "nl": "List of clients that have bought more than one copy of a book sometime", 
+            "id": 18, 
+            "sql": "SELECT NAME\nFROM CLIENT NATURAL JOIN ORDERS\nWHERE IDORDER IN (\n  SELECT IDORDER\n  FROM BOOKS_ORDER\n  WHERE AMOUNT>1\n);"
+        }
+    ], 
+    "review_id": null
+}

spider-corpus-test/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

spider-corpus-test/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

spider-corpus-test/test_database/book_1/schema.sql

@@ -0,0 +1,91 @@
+
+create table Client
+(IdClient CHAR(10) PRIMARY KEY,
+ Name VARCHAR(25) NOT NULL,
+ Address VARCHAR(60) NOT NULL,
+ NumCC CHAR(16) NOT NULL);
+ 
+create table Orders
+(IdOrder CHAR(10) PRIMARY KEY,
+ IdClient CHAR(10) NOT NULL REFERENCES Client on delete cascade,
+ DateOrder DATE,
+ DateExped DATE);
+
+create table Author
+( idAuthor NUMBER PRIMARY KEY,
+  Name VARCHAR(25));
+
+create table Book
+(ISBN CHAR(15) PRIMARY KEY,
+Title VARCHAR(60) NOT NULL,
+Author CHAR(4) NOT NULL,
+PurchasePrice NUMBER(6,2) DEFAULT 0,
+SalePrice NUMBER(6,2) DEFAULT 0);
+
+create table Author_Book
+(ISBN CHAR(15),
+Author NUMBER,
+CONSTRAINT al_PK PRIMARY KEY (ISBN, Author),
+CONSTRAINT BookA_FK FOREIGN KEY (ISBN) REFERENCES `Book`(ISBN) on delete cascade,
+CONSTRAINT Author_FK FOREIGN KEY (Author) REFERENCES `Author`(idAuthorA));
+
+
+create table Books_Order(
+ISBN CHAR(15),
+IdOrder CHAR(10),
+amount NUMBER(3) CHECK (amount >0),
+CONSTRAINT lp_PK PRIMARY KEY (ISBN, idOrder),
+CONSTRAINT Book_FK FOREIGN KEY (ISBN) REFERENCES `Book`(ISBN) on delete cascade,
+CONSTRAINT pedido_FK FOREIGN KEY (IdOrder) REFERENCES `Orders`(IdOrder) on delete cascade);
+
+insert into Client values ('0000001','James Smith', 'Picadilly 2','1234567890123456');
+insert into Client values ('0000002','Laura Jones', 'Holland Park 13', '1234567756953456');
+insert into Client values ('0000003','Peter Doe', 'High Street 42', '1237596390123456');
+insert into Client values ('0000004','Rose Johnson', 'Notting Hill 46', '4896357890123456');
+insert into Client values ('0000005','Joseph Clinton', 'Leicester Square 1', '1224569890123456');
+insert into Client values ('0000006','Betty Fraser', 'Whitehall 32', '2444889890123456' );
+
+
+insert into Orders values ('0000001P','0000001', DATE('01/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000002P','0000001', DATE('01/12/2011'),null);
+insert into Orders values ('0000003P','0000002', DATE('02/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000004P','0000004', DATE('02/12/2011'),DATE('05/12/2011'));
+insert into Orders values ('0000005P','0000005', DATE('03/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000006P','0000003', DATE('04/12/2011'),null);
+
+insert into Author values (1,'Jane Austin');
+insert into Author values (2,'George Orwell');
+insert into Author values (3,'J.R.R Tolkien');
+insert into Author values (4,'Antoine de Saint-Exupy');
+insert into Author values (5,'Bram Stoker');
+insert into Author values (6,'Plato');
+insert into Author values (7,'Vladimir Nabokov');
+
+insert into Book values ('8233771378567', 'Pride and Prejudice', '2008', 9.45, 13.45);
+insert into Book values ('1235271378662', '1984', '2009', 12.50, 19.25);
+insert into Book values ('4554672899910', 'The Hobbit', '2002', 19.00, 33.15);
+insert into Book values ('5463467723747', 'The Little Prince', '2000', 49.00, 73.45);
+insert into Book values ('0853477468299', 'Dracula', '2011', 9.45, 13.45);
+insert into Book values ('1243415243666', 'The Republic', '1997', 10.45, 15.75);
+insert into Book values ('0482174555366', 'Lolita', '1998', 4.00, 9.45);
+
+
+insert into Author_Book values ('8233771378567',1);
+insert into Author_Book values ('1235271378662',2);
+insert into Author_Book values ('4554672899910',3);
+insert into Author_Book values ('5463467723747',4);
+insert into Author_Book values ('0853477468299',5);
+insert into Author_Book values ('1243415243666',6);
+insert into Author_Book values ('0482174555366',7);
+
+insert into Books_Order values ('8233771378567','0000001P', 1);
+insert into Books_Order values ('5463467723747','0000001P', 2);
+insert into Books_Order values ('0482174555366','0000002P', 1);
+insert into Books_Order values ('4554672899910','0000003P', 1);
+insert into Books_Order values ('8233771378567','0000003P', 1);
+insert into Books_Order values ('1243415243666','0000003P', 1);
+insert into Books_Order values ('8233771378567','0000004P', 1);
+insert into Books_Order values ('4554672899910','0000005P', 1);
+insert into Books_Order values ('1243415243666','0000005P', 1);
+insert into Books_Order values ('5463467723747','0000005P', 3);
+insert into Books_Order values ('8233771378567','0000006P', 5); 

spider-corpus-test/test_database/book_1/schema_old.sql

@@ -0,0 +1,91 @@
+
+create table Client
+(IdClient CHAR(10) PRIMARY KEY,
+ Name VARCHAR(25) NOT NULL,
+ Address VARCHAR(60) NOT NULL,
+ NumCC CHAR(16) NOT NULL);
+ 
+create table Orders
+(IdOrder CHAR(10) PRIMARY KEY,
+ IdClient CHAR(10) NOT NULL REFERENCES Client on delete cascade,
+ DateOrder DATE,
+ DateExped DATE);
+
+create table Author
+( idAuthor NUMBER PRIMARY KEY,
+  Name VARCHAR(25));
+
+create table Book
+(ISBN CHAR(15) PRIMARY KEY,
+Title VARCHAR(60) NOT NULL,
+Author CHAR(4) NOT NULL,
+PurchasePrice NUMBER(6,2) DEFAULT 0,
+SalePrice NUMBER(6,2) DEFAULT 0);
+
+create table Author_Book
+(ISBN CHAR(15),
+Author NUMBER,
+CONSTRAINT al_PK PRIMARY KEY (ISBN, Author),
+CONSTRAINT BookA_FK FOREIGN KEY (ISBN) REFERENCES Book on delete cascade,
+CONSTRAINT Author_FK FOREIGN KEY (Author) REFERENCES Author);
+
+
+create table Books_Order(
+ISBN CHAR(15),
+IdOrder CHAR(10),
+amount NUMBER(3) CHECK (amount >0),
+CONSTRAINT lp_PK PRIMARY KEY (ISBN, idOrder),
+CONSTRAINT Book_FK FOREIGN KEY (ISBN) REFERENCES Book on delete cascade,
+CONSTRAINT pedido_FK FOREIGN KEY (IdOrder) REFERENCES Orders on delete cascade);
+
+insert into Client values ('0000001','James Smith', 'Picadilly 2','1234567890123456');
+insert into Client values ('0000002','Laura Jones', 'Holland Park 13', '1234567756953456');
+insert into Client values ('0000003','Peter Doe', 'High Street 42', '1237596390123456');
+insert into Client values ('0000004','Rose Johnson', 'Notting Hill 46', '4896357890123456');
+insert into Client values ('0000005','Joseph Clinton', 'Leicester Square 1', '1224569890123456');
+insert into Client values ('0000006','Betty Fraser', 'Whitehall 32', '2444889890123456' );
+
+
+insert into Orders values ('0000001P','0000001', DATE('01/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000002P','0000001', DATE('01/12/2011'),null);
+insert into Orders values ('0000003P','0000002', DATE('02/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000004P','0000004', DATE('02/12/2011'),DATE('05/12/2011'));
+insert into Orders values ('0000005P','0000005', DATE('03/12/2011'),DATE('03/12/2011'));
+insert into Orders values ('0000006P','0000003', DATE('04/12/2011'),null);
+
+insert into Author values (1,'Jane Austin');
+insert into Author values (2,'George Orwell');
+insert into Author values (3,'J.R.R Tolkien');
+insert into Author values (4,'Antoine de Saint-Exupy');
+insert into Author values (5,'Bram Stoker');
+insert into Author values (6,'Plato');
+insert into Author values (7,'Vladimir Nabokov');
+
+insert into Book values ('8233771378567', 'Pride and Prejudice', '2008', 9.45, 13.45);
+insert into Book values ('1235271378662', '1984', '2009', 12.50, 19.25);
+insert into Book values ('4554672899910', 'The Hobbit', '2002', 19.00, 33.15);
+insert into Book values ('5463467723747', 'The Little Prince', '2000', 49.00, 73.45);
+insert into Book values ('0853477468299', 'Dracula', '2011', 9.45, 13.45);
+insert into Book values ('1243415243666', 'The Republic', '1997', 10.45, 15.75);
+insert into Book values ('0482174555366', 'Lolita', '1998', 4.00, 9.45);
+
+
+insert into Author_Book values ('8233771378567',1);
+insert into Author_Book values ('1235271378662',2);
+insert into Author_Book values ('4554672899910',3);
+insert into Author_Book values ('5463467723747',4);
+insert into Author_Book values ('0853477468299',5);
+insert into Author_Book values ('1243415243666',6);
+insert into Author_Book values ('0482174555366',7);
+
+insert into Books_Order values ('8233771378567','0000001P', 1);
+insert into Books_Order values ('5463467723747','0000001P', 2);
+insert into Books_Order values ('0482174555366','0000002P', 1);
+insert into Books_Order values ('4554672899910','0000003P', 1);
+insert into Books_Order values ('8233771378567','0000003P', 1);
+insert into Books_Order values ('1243415243666','0000003P', 1);
+insert into Books_Order values ('8233771378567','0000004P', 1);
+insert into Books_Order values ('4554672899910','0000005P', 1);
+insert into Books_Order values ('1243415243666','0000005P', 1);
+insert into Books_Order values ('5463467723747','0000005P', 3);
+insert into Books_Order values ('8233771378567','0000006P', 5); 

spider-corpus-test/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
+);

spider-corpus-test/test_database/browser_web/schema.sql

@@ -0,0 +1,58 @@
+PRAGMA foreign_keys=OFF;
+BEGIN TRANSACTION;
+CREATE TABLE IF NOT EXISTS "Web_client_accelerator" (
+"id" int,
+"name" text,
+"Operating_system" text,
+"Client" text,
+"Connection" text,
+primary key("id")
+);
+INSERT INTO Web_client_accelerator VALUES(1,'CACHEbox','Appliance (Linux)','End user, ISP','Broadband, Satellite, Wireless, Fiber, DSL');
+INSERT INTO Web_client_accelerator VALUES(2,'CProxy','Windows','user','up to 756kbit/s');
+INSERT INTO Web_client_accelerator VALUES(3,'Fasterfox','Windows, Mac, Linux and Mobile devices','user','Dialup, Wireless, Broadband, DSL');
+INSERT INTO Web_client_accelerator VALUES(4,'fasTun','Any','All','Any');
+INSERT INTO Web_client_accelerator VALUES(5,'Freewire','Windows, except NT and 95','ISP','Dial-up');
+INSERT INTO Web_client_accelerator VALUES(6,'Google Web Accelerator (discontinued)','Windows','user/Google server','Broadband');
+INSERT INTO Web_client_accelerator VALUES(7,'Heigh Speed','Windows','All','Any');
+INSERT INTO Web_client_accelerator VALUES(8,'Netfury','Windows, Mac','End User, ISP','Dial-up, Broadband, DSL, ISDN, Satellite, Wireless');
+INSERT INTO Web_client_accelerator VALUES(9,'Nitro','Windows, Mac','End User, ISP','Dial-up, Broadband, DSL, ISDN, Satellite, Wireless');
+INSERT INTO Web_client_accelerator VALUES(10,'ONSPEED','Windows, Mac and Mobile devices','user','Dialup, Wireless, Broadband, DSL');
+INSERT INTO Web_client_accelerator VALUES(11,'Opera Turbo','Android, Linux, Mac and Windows devices','user/Opera server','Any');
+INSERT INTO Web_client_accelerator VALUES(12,'Polipo','Unix (Linux, *BSD, Mac OS X, others), Windows','user/ISP','Any');
+INSERT INTO Web_client_accelerator VALUES(13,'Propel','Windows, Mac','End User, ISP','Dial, DSL, ISDN, Satellite, wireless');
+INSERT INTO Web_client_accelerator VALUES(14,'Proxyconn Web Accelerator','Windows, Mac, Mobile devices','user','Dialup, Wireless, Broadband, DSL');
+INSERT INTO Web_client_accelerator VALUES(15,'RabbIT','Any system with Java 1.6 VM available','ISP','Any');
+INSERT INTO Web_client_accelerator VALUES(16,'Squid','Unix (Linux, *BSD, Mac OS X, others), Windows','user/ISP','Any');
+INSERT INTO Web_client_accelerator VALUES(17,'Toonel','Windows, Linux, Mac OS, Symbian, WindowsMobile','user/ISP','Any');
+INSERT INTO Web_client_accelerator VALUES(18,'WinGate','Windows (2000 onwards)','All','Any');
+INSERT INTO Web_client_accelerator VALUES(19,'Ziproxy','Unix (Linux, *BSD, Mac OS X, others)','ISP','Any');
+CREATE TABLE IF NOT EXISTS "browser" (
+"id" int,
+"name" text,
+"market_share" real,
+primary key("id")
+);
+INSERT INTO browser VALUES(1,'Internet Explorer',28.960000000000000852);
+INSERT INTO browser VALUES(2,'Firefox',18.109999999999999431);
+INSERT INTO browser VALUES(3,'Safari',8.5399999999999991473);
+INSERT INTO browser VALUES(4,'Opera',1.1999999999999999555);
+CREATE TABLE IF NOT EXISTS "accelerator_compatible_browser" (
+"accelerator_id" int,
+"browser_id" int,
+"compatible_since_year" int,
+primary key("accelerator_id", "browser_id"),
+foreign key ("accelerator_id") references `Web_client_accelerator`("id"),
+foreign key ("browser_id") references `browser`("id")
+);
+INSERT INTO accelerator_compatible_browser VALUES(1,1,1995);
+INSERT INTO accelerator_compatible_browser VALUES(1,2,1996);
+INSERT INTO accelerator_compatible_browser VALUES(2,3,1996);
+INSERT INTO accelerator_compatible_browser VALUES(2,4,2000);
+INSERT INTO accelerator_compatible_browser VALUES(3,1,2005);
+INSERT INTO accelerator_compatible_browser VALUES(3,2,2007);
+INSERT INTO accelerator_compatible_browser VALUES(3,3,2008);
+INSERT INTO accelerator_compatible_browser VALUES(4,4,2009);
+INSERT INTO accelerator_compatible_browser VALUES(9,1,2010);
+COMMIT;
+

spider-corpus-test/test_database/candidate_poll/schema.sql

@@ -0,0 +1,42 @@
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "candidate" (
+"Candidate_ID" int,
+"People_ID" int,
+"Poll_Source" text,
+"Date" text,
+"Support_rate" real,
+"Consider_rate" real,
+"Oppose_rate" real,
+"Unsure_rate" real,
+PRIMARY KEY ("Candidate_ID"),
+FOREIGN KEY ("People_ID") REFERENCES "people"("People_ID")
+);
+
+CREATE TABLE "people" (
+"People_ID" int,
+"Sex" text,
+"Name" text,
+"Date_of_Birth" text,
+"Height" real,
+"Weight" real,
+PRIMARY KEY ("People_ID")
+);
+
+INSERT INTO  "people" VALUES (1,"M","Hubert Henno","06.10.1976","188","83");
+INSERT INTO  "people" VALUES (2,"M","Dominique Daquin","10.11.1972","197","85");
+INSERT INTO  "people" VALUES (3,"F","Stéphane Antiga","03.02.1976","200","94");
+INSERT INTO  "people" VALUES (4,"M","Laurent Capet","05.05.1972","202","92");
+INSERT INTO  "people" VALUES (5,"F","Frantz Granvorka","10.03.1976","195","90");
+INSERT INTO  "people" VALUES (6,"M","Vincent Montméat","01.09.1977","196","88");
+INSERT INTO  "people" VALUES (7,"M","Loïc De Kergret","20.08.1970","193","89");
+INSERT INTO  "people" VALUES (8,"M","Philippe Barça-Cysique","22.04.1977","194","88");
+INSERT INTO  "people" VALUES (9,"M","Guillaume Samica","28.09.1981","196","82");
+
+INSERT INTO  "candidate" VALUES (1,1,"WNBC/Marist Poll","Feb 12–15, 2007","0.25","0.30","0.43","0.2");
+INSERT INTO  "candidate" VALUES (2,3,"WNBC/Marist Poll","Feb 12–15, 2007","0.17","0.42","0.32","0.9");
+INSERT INTO  "candidate" VALUES (3,4,"FOX News/Opinion Dynamics Poll","Feb 13–14, 2007","0.18","0.34","0.44","0.3");
+INSERT INTO  "candidate" VALUES (4,6,"Newsweek Poll","Nov 9–10, 2006","0.33","0.20","0.45","0.2");
+INSERT INTO  "candidate" VALUES (5,7,"Newsweek Poll","Nov 9–10, 2006","0.24","0.30","0.32","0.4");
+INSERT INTO  "candidate" VALUES (6,9,"Newsweek Poll","Nov 9–10, 2006","0.24","0.27","0.43","0.2");
+

spider-corpus-test/test_database/car_1/annotation.json

@@ -0,0 +1,62 @@
+{
+    "label_id": null, 
+    "data": [
+        {
+            "nl": "Find all Reanults (\u2019renault\u2019) in the database. For each, report the name and the year.\n", 
+            "id": 0
+        }, 
+        {
+            "nl": "Find all cars produced by Volvo between 1977 and 1981 (inclusive). Report the name of the car and the year it was produced.\n", 
+            "id": 1
+        }, 
+        {
+            "nl": "Report all Asian automakers. Output the full name of the automaker and the country of origin\n", 
+            "id": 2
+        }, 
+        {
+            "nl": "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.\n", 
+            "id": 3
+        }, 
+        {
+            "nl": "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.\n", 
+            "id": 4
+        }, 
+        {
+            "nl": "Find the average, maximum and minimum horsepower for 4-cylinder vehicles manufactured by renault between 1971 and 1976 inclusively.\n", 
+            "id": 5
+        }, 
+        {
+            "nl": "Find how many different car manufacturers produced a vehicle heavier than 4000 lbs.\n", 
+            "id": 6
+        }, 
+        {
+            "nl": "Find the minimum horsepower for 4-cylinder vehicles manufactured by renault between 1971 and 1976 inclusively.\n", 
+            "id": 7
+        }, 
+        {
+            "nl": "For each year when US-manufactured cars averaged less than 100 horsepowers, report the highest and the lowest engine displacement number.\n", 
+            "id": 8
+        }, 
+        {
+            "nl": "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.\n", 
+            "id": 9
+        }, 
+        {
+            "nl": "Report all vehicles with the best gas mileage. For each vehicle, report its full name and the year of production.\n", 
+            "id": 10
+        }, 
+        {
+            "nl": "Among the vehicles with the gas mileage, report the one with the best acceleration. Report full name and the year of production.\n", 
+            "id": 11
+        }, 
+        {
+            "nl": "For each country report the automaker with the largest number of cars in the database. Report the name of the country.\n", 
+            "id": 12
+        }, 
+        {
+            "nl": "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.\n", 
+            "id": 13
+        }
+    ], 
+    "review_id": null
+}

spider-corpus-test/test_database/car_1/car_1.json

@@ -0,0 +1,216 @@
+[
+    {
+        "col_data": [
+            {
+                "column_name": "ContId",
+                "data_type": "INTEGER",
+                "default_column_name": "ContId",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "Continent",
+                "data_type": "TEXT",
+                "default_column_name": "Continent",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "continents"
+    },
+    {
+        "col_data": [
+            {
+                "column_name": "CountryId",
+                "data_type": "INTEGER",
+                "default_column_name": "CountryId",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "CountryName",
+                "data_type": "TEXT",
+                "default_column_name": "CountryName",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Continent",
+                "data_type": "INTEGER",
+                "default_column_name": "Continent",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "countries"
+    },
+    {
+        "col_data": [
+            {
+                "column_name": "Id",
+                "data_type": "INTEGER",
+                "default_column_name": "Id",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "Maker",
+                "data_type": "TEXT",
+                "default_column_name": "Maker",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "FullName",
+                "data_type": "TEXT",
+                "default_column_name": "FullName",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Country",
+                "data_type": "TEXT",
+                "default_column_name": "Country",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "car-makers"
+    },
+    {
+        "col_data": [
+            {
+                "column_name": "MakeId",
+                "data_type": "INTEGER",
+                "default_column_name": "MakeId",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "Model",
+                "data_type": "TEXT",
+                "default_column_name": "Model",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Make",
+                "data_type": "TEXT",
+                "default_column_name": "Make",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "car-names"
+    },
+    {
+        "col_data": [
+            {
+                "column_name": "Id",
+                "data_type": "INTEGER",
+                "default_column_name": "Id",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "MPG",
+                "data_type": "TEXT",
+                "default_column_name": "MPG",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Cylinders",
+                "data_type": "INTEGER",
+                "default_column_name": "Cylinders",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Edispl",
+                "data_type": "REAL",
+                "default_column_name": "Edispl",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Horsepower",
+                "data_type": "TEXT",
+                "default_column_name": "Horsepower",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Weight",
+                "data_type": "INTEGER",
+                "default_column_name": "Weight",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Accelerate",
+                "data_type": "REAL",
+                "default_column_name": "Accelerate",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Year",
+                "data_type": "INTEGER",
+                "default_column_name": "Year",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "cars-data"
+    },
+    {
+        "col_data": [
+            {
+                "column_name": "ModelId",
+                "data_type": "INTEGER",
+                "default_column_name": "ModelId",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 1
+            },
+            {
+                "column_name": "Maker",
+                "data_type": "INTEGER",
+                "default_column_name": "Maker",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            },
+            {
+                "column_name": "Model",
+                "data_type": "TEXT",
+                "default_column_name": "Model",
+                "default_value": null,
+                "not_null": 0,
+                "primary_key": 0
+            }
+        ],
+        "table": "model-list"
+    }
+]

spider-corpus-test/test_database/car_1/car_1.sql

@@ -0,0 +1,52 @@
+CREATE TABLE "continents" ( 
+	"ContId" INTEGER PRIMARY KEY, 
+	"Continent" TEXT 
+);
+
+CREATE TABLE "countries" (
+	"CountryId" INTEGER PRIMARY KEY, 
+	"CountryName" TEXT, 
+	"Continent" INTEGER,
+	FOREIGN KEY (Continent) REFERENCES continents(ContId)
+);
+
+
+CREATE TABLE "car_makers" ( 
+	"Id" INTEGER PRIMARY KEY, 
+	"Maker" TEXT, 
+	"FullName" TEXT, 
+	"Country" TEXT,
+	FOREIGN KEY (Country) REFERENCES countries(CountryId)
+);
+
+
+CREATE TABLE "model_list" ( 
+	"ModelId" INTEGER PRIMARY KEY, 
+	"Maker" INTEGER, 
+	"Model" TEXT UNIQUE,
+	FOREIGN KEY (Maker) REFERENCES car_makers (Id)
+
+);
+
+
+
+CREATE TABLE "car_names" ( 
+	"MakeId" INTEGER PRIMARY KEY, 
+	"Model" TEXT, 
+	"Make" TEXT,
+	FOREIGN KEY (Model) REFERENCES model_list (Model)
+);
+
+CREATE TABLE "cars_data" (
+	"Id" INTEGER PRIMARY KEY, 
+	"MPG" TEXT, 
+	"Cylinders" INTEGER, 
+	"Edispl" REAL, 
+	"Horsepower" TEXT, 
+	"Weight" INTEGER, 
+	"Accelerate" REAL, 
+	"Year" INTEGER,
+	FOREIGN KEY (Id) REFERENCES car_names (MakeId)
+);
+
+

spider-corpus-test/test_database/car_1/data_csv/README.CARS.TXT

@@ -0,0 +1,149 @@
+*****************************************************
+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)
+
+
+
+**************************************************************************
+**************************************************************************
+
+
+
+
+
+
+

spider-corpus-test/test_database/car_1/data_csv/car-makers.csv

@@ -0,0 +1,24 @@
+Id,Maker,FullName,Country
+1,'amc','American Motor Company',1
+2,'volkswagen','Volkswagen',2
+3,'bmw','BMW',2
+4,'gm','General Motors',1
+5,'ford','Ford Motor Company',1
+6,'chrysler','Chrysler',1
+7,'citroen','Citroen',3
+8,'nissan','Nissan Motors',4
+9,'fiat','Fiat',5
+10,'hi','hi',null
+11,'honda','Honda',4
+12,'mazda','Mazda',4
+13,'daimler benz','Daimler Benz',2
+14,'opel','Opel',2
+15,'peugeaut','Peugeaut',3
+16,'renault','Renault',3
+17,'saab','Saab',6
+18,'subaru','Subaru',4
+19,'toyota','Toyota',4
+20,'triumph','Triumph',7
+21,'volvo','Volvo',6
+22,'kia','Kia Motors',8
+23,'hyundai','Hyundai',8

spider-corpus-test/test_database/car_1/data_csv/car-names.csv

@@ -0,0 +1,407 @@
+Id,Model,Make
+1,'chevrolet','chevrolet chevelle malibu'
+2,'buick','buick skylark 320'
+3,'plymouth','plymouth satellite'
+4,'amc','amc rebel sst'
+5,'ford','ford torino'
+6,'ford','ford galaxie 500'
+7,'chevrolet','chevrolet impala'
+8,'plymouth','plymouth fury iii'
+9,'pontiac','pontiac catalina'
+10,'amc','amc ambassador dpl'
+11,'citroen','citroen ds-21 pallas'
+12,'chevrolet','chevrolet chevelle concours (sw)'
+13,'ford','ford torino (sw)'
+14,'plymouth','plymouth satellite (sw)'
+15,'amc','amc rebel sst (sw)'
+16,'dodge','dodge challenger se'
+17,'plymouth','plymouth cuda 340'
+18,'ford','ford mustang boss 302'
+19,'chevrolet','chevrolet monte carlo'
+20,'buick','buick estate wagon (sw)'
+21,'toyota','toyota corona mark ii'
+22,'plymouth','plymouth duster'
+23,'amc','amc hornet'
+24,'ford','ford maverick'
+25,'datsun','datsun pl510'
+26,'volkswagen','volkswagen 1131 deluxe sedan'
+27,'peugeot','peugeot 504'
+28,'audi','audi 100 ls'
+29,'saab','saab 99e'
+30,'bmw','bmw 2002'
+31,'amc','amc gremlin'
+32,'ford','ford f250'
+33,'chevrolet','chevy c20'
+34,'dodge','dodge d200'
+35,'hi','hi 1200d'
+36,'datsun','datsun pl510'
+37,'chevrolet','chevrolet vega 2300'
+38,'toyota','toyota corona'
+39,'ford','ford pinto'
+40,'volkswagen','volkswagen super beetle 117'
+41,'amc','amc gremlin'
+42,'plymouth','plymouth satellite custom'
+43,'chevrolet','chevrolet chevelle malibu'
+44,'ford','ford torino 500'
+45,'amc','amc matador'
+46,'chevrolet','chevrolet impala'
+47,'pontiac','pontiac catalina brougham'
+48,'ford','ford galaxie 500'
+49,'plymouth','plymouth fury iii'
+50,'dodge','dodge monaco (sw)'
+51,'ford','ford country squire (sw)'
+52,'pontiac','pontiac safari (sw)'
+53,'amc','amc hornet sportabout (sw)'
+54,'chevrolet','chevrolet vega (sw)'
+55,'pontiac','pontiac firebird'
+56,'ford','ford mustang'
+57,'mercury','mercury capri 2000'
+58,'opel','opel 1900'
+59,'peugeot','peugeot 304'
+60,'fiat','fiat 124b'
+61,'toyota','toyota corolla 1200'
+62,'datsun','datsun 1200'
+63,'volkswagen','volkswagen model 111'
+64,'plymouth','plymouth cricket'
+65,'toyota','toyota corona hardtop'
+66,'dodge','dodge colt hardtop'
+67,'volkswagen','volkswagen type 3'
+68,'chevrolet','chevrolet vega'
+69,'ford','ford pinto runabout'
+70,'chevrolet','chevrolet impala'
+71,'pontiac','pontiac catalina'
+72,'plymouth','plymouth fury iii'
+73,'ford','ford galaxie 500'
+74,'amc','amc ambassador sst'
+75,'mercury','mercury marquis'
+76,'buick','buick lesabre custom'
+77,'oldsmobile','oldsmobile delta 88 royale'
+78,'chrysler','chrysler newport royal'
+79,'mazda','mazda rx2 coupe'
+80,'amc','amc matador (sw)'
+81,'chevrolet','chevrolet chevelle concours (sw)'
+82,'ford','ford gran torino (sw)'
+83,'plymouth','plymouth satellite custom (sw)'
+84,'volvo','volvo 145e (sw)'
+85,'volkswagen','volkswagen 411 (sw)'
+86,'peugeot','peugeot 504 (sw)'
+87,'renault','renault 12 (sw)'
+88,'ford','ford pinto (sw)'
+89,'datsun','datsun 510 (sw)'
+90,'toyota','toyota corona mark ii (sw)'
+91,'dodge','dodge colt (sw)'
+92,'toyota','toyota corolla 1600 (sw)'
+93,'buick','buick century 350'
+94,'amc','amc matador'
+95,'chevrolet','chevrolet malibu'
+96,'ford','ford gran torino'
+97,'dodge','dodge coronet custom'
+98,'mercury','mercury marquis brougham'
+99,'chevrolet','chevrolet caprice classic'
+100,'ford','ford ltd'
+101,'plymouth','plymouth fury gran sedan'
+102,'chrysler','chrysler new yorker brougham'
+103,'buick','buick electra 225 custom'
+104,'amc','amc ambassador brougham'
+105,'plymouth','plymouth valiant'
+106,'chevrolet','chevrolet nova custom'
+107,'amc','amc hornet'
+108,'ford','ford maverick'
+109,'plymouth','plymouth duster'
+110,'volkswagen','volkswagen super beetle'
+111,'chevrolet','chevrolet impala'
+112,'ford','ford country'
+113,'plymouth','plymouth custom suburb'
+114,'oldsmobile','oldsmobile vista cruiser'
+115,'amc','amc gremlin'
+116,'toyota','toyota carina'
+117,'chevrolet','chevrolet vega'
+118,'datsun','datsun 610'
+119,'mazda','mazda rx3'
+120,'ford','ford pinto'
+121,'mercury','mercury capri v6'
+122,'fiat','fiat 124 sport coupe'
+123,'chevrolet','chevrolet monte carlo s'
+124,'pontiac','pontiac grand prix'
+125,'fiat','fiat 128'
+126,'opel','opel manta'
+127,'audi','audi 100ls'
+128,'volvo','volvo 144ea'
+129,'dodge','dodge dart custom'
+130,'saab','saab 99le'
+131,'toyota','toyota mark ii'
+132,'oldsmobile','oldsmobile omega'
+133,'plymouth','plymouth duster'
+134,'ford','ford maverick'
+135,'amc','amc hornet'
+136,'chevrolet','chevrolet nova'
+137,'datsun','datsun b210'
+138,'ford','ford pinto'
+139,'toyota','toyota corolla 1200'
+140,'chevrolet','chevrolet vega'
+141,'chevrolet','chevrolet chevelle malibu classic'
+142,'amc','amc matador'
+143,'plymouth','plymouth satellite sebring'
+144,'ford','ford gran torino'
+145,'buick','buick century luxus (sw)'
+146,'dodge','dodge coronet custom (sw)'
+147,'ford','ford gran torino (sw)'
+148,'amc','amc matador (sw)'
+149,'audi','audi fox'
+150,'volkswagen','volkswagen dasher'
+151,'opel','opel manta'
+152,'toyota','toyota corona'
+153,'datsun','datsun 710'
+154,'dodge','dodge colt'
+155,'fiat','fiat 128'
+156,'fiat','fiat 124 tc'
+157,'honda','honda civic'
+158,'subaru','subaru'
+159,'fiat','fiat x1.9'
+160,'plymouth','plymouth valiant custom'
+161,'chevrolet','chevrolet nova'
+162,'mercury','mercury monarch'
+163,'ford','ford maverick'
+164,'pontiac','pontiac catalina'
+165,'chevrolet','chevrolet bel air'
+166,'plymouth','plymouth grand fury'
+167,'ford','ford ltd'
+168,'buick','buick century'
+169,'chevrolet','chevrolet chevelle malibu'
+170,'amc','amc matador'
+171,'plymouth','plymouth fury'
+172,'buick','buick skyhawk'
+173,'chevrolet','chevrolet monza 2+2'
+174,'ford','ford mustang ii'
+175,'toyota','toyota corolla'
+176,'ford','ford pinto'
+177,'amc','amc gremlin'
+178,'pontiac','pontiac astro'
+179,'toyota','toyota corona'
+180,'volkswagen','volkswagen dasher'
+181,'datsun','datsun 710'
+182,'ford','ford pinto'
+183,'volkswagen','volkswagen rabbit'
+184,'amc','amc pacer'
+185,'audi','audi 100ls'
+186,'peugeot','peugeot 504'
+187,'volvo','volvo 244dl'
+188,'saab','saab 99le'
+189,'honda','honda civic cvcc'
+190,'fiat','fiat 131'
+191,'opel','opel 1900'
+192,'capri','capri ii'
+193,'dodge','dodge colt'
+194,'renault','renault 12tl'
+195,'chevrolet','chevrolet chevelle malibu classic'
+196,'dodge','dodge coronet brougham'
+197,'amc','amc matador'
+198,'ford','ford gran torino'
+199,'plymouth','plymouth valiant'
+200,'chevrolet','chevrolet nova'
+201,'ford','ford maverick'
+202,'amc','amc hornet'
+203,'chevrolet','chevrolet chevette'
+204,'chevrolet','chevrolet woody'
+205,'volkswagen','vw rabbit'
+206,'honda','honda civic'
+207,'dodge','dodge aspen se'
+208,'ford','ford granada ghia'
+209,'pontiac','pontiac ventura sj'
+210,'amc','amc pacer d/l'
+211,'volkswagen','volkswagen rabbit'
+212,'datsun','datsun b-210'
+213,'toyota','toyota corolla'
+214,'ford','ford pinto'
+215,'volvo','volvo 245'
+216,'plymouth','plymouth volare premier v8'
+217,'peugeot','peugeot 504'
+218,'toyota','toyota mark ii'
+219,'mercedes-benz','mercedes-benz 280s'
+220,'cadillac','cadillac seville'
+221,'chevrolet','chevy c10'
+222,'ford','ford f108'
+223,'dodge','dodge d100'
+224,'honda','honda accord cvcc'
+225,'buick','buick opel isuzu deluxe'
+226,'renault','renault 5 gtl'
+227,'plymouth','plymouth arrow gs'
+228,'datsun','datsun f-10 hatchback'
+229,'chevrolet','chevrolet caprice classic'
+230,'oldsmobile','oldsmobile cutlass supreme'
+231,'dodge','dodge monaco brougham'
+232,'mercury','mercury cougar brougham'
+233,'chevrolet','chevrolet concours'
+234,'buick','buick skylark'
+235,'plymouth','plymouth volare custom'
+236,'ford','ford granada'
+237,'pontiac','pontiac grand prix lj'
+238,'chevrolet','chevrolet monte carlo landau'
+239,'chrysler','chrysler cordoba'
+240,'ford','ford thunderbird'
+241,'volkswagen','volkswagen rabbit custom'
+242,'pontiac','pontiac sunbird coupe'
+243,'toyota','toyota corolla liftback'
+244,'ford','ford mustang ii 2+2'
+245,'chevrolet','chevrolet chevette'
+246,'dodge','dodge colt m/m'
+247,'subaru','subaru dl'
+248,'volkswagen','volkswagen dasher'
+249,'datsun','datsun 810'
+250,'bmw','bmw 320i'
+251,'mazda','mazda rx-4'
+252,'volkswagen','volkswagen rabbit custom diesel'
+253,'ford','ford fiesta'
+254,'mazda','mazda glc deluxe'
+255,'datsun','datsun b210 gx'
+256,'honda','honda civic cvcc'
+257,'oldsmobile','oldsmobile cutlass salon brougham'
+258,'dodge','dodge diplomat'
+259,'mercury','mercury monarch ghia'
+260,'pontiac','pontiac phoenix lj'
+261,'chevrolet','chevrolet malibu'
+262,'ford','ford fairmont (auto)'
+263,'ford','ford fairmont (man)'
+264,'plymouth','plymouth volare'
+265,'amc','amc concord'
+266,'buick','buick century special'
+267,'mercury','mercury zephyr'
+268,'dodge','dodge aspen'
+269,'amc','amc concord d/l'
+270,'chevrolet','chevrolet monte carlo landau'
+271,'buick','buick regal sport coupe (turbo)'
+272,'ford','ford futura'
+273,'dodge','dodge magnum xe'
+274,'chevrolet','chevrolet chevette'
+275,'toyota','toyota corona'
+276,'datsun','datsun 510'
+277,'dodge','dodge omni'
+278,'toyota','toyota celica gt liftback'
+279,'plymouth','plymouth sapporo'
+280,'oldsmobile','oldsmobile starfire sx'
+281,'datsun','datsun 200-sx'
+282,'audi','audi 5000'
+283,'volvo','volvo 264gl'
+284,'saab','saab 99gle'
+285,'peugeot','peugeot 604sl'
+286,'volkswagen','volkswagen scirocco'
+287,'honda','honda accord lx'
+288,'pontiac','pontiac lemans v6'
+289,'mercury','mercury zephyr 6'
+290,'ford','ford fairmont 4'
+291,'amc','amc concord dl 6'
+292,'dodge','dodge aspen 6'
+293,'chevrolet','chevrolet caprice classic'
+294,'ford','ford ltd landau'
+295,'mercury','mercury grand marquis'
+296,'dodge','dodge st. regis'
+297,'buick','buick estate wagon (sw)'
+298,'ford','ford country squire (sw)'
+299,'chevrolet','chevrolet malibu classic (sw)'
+300,'chrysler','chrysler lebaron town @ country (sw)'
+301,'volkswagen','vw rabbit custom'
+302,'mazda', 'mazda glc deluxe'
+303,'dodge','dodge colt hatchback custom'
+304,'amc','amc spirit dl'
+305,'mercedes','mercedes benz 300d'
+306,'cadillac','cadillac eldorado'
+307,'peugeot','peugeot 504'
+308,'oldsmobile','oldsmobile cutlass salon brougham'
+309,'plymouth','plymouth horizon'
+310,'plymouth','plymouth horizon tc3'
+311,'datsun','datsun 210'
+312,'fiat','fiat strada custom'
+313,'buick','buick skylark limited'
+314,'chevrolet','chevrolet citation'
+315,'oldsmobile','oldsmobile omega brougham'
+316,'pontiac','pontiac phoenix'
+317,'volkswagen','vw rabbit'
+318,'toyota','toyota corolla tercel'
+319,'chevrolet','chevrolet chevette'
+320,'datsun','datsun 310'
+321,'chevrolet','chevrolet citation'
+322,'ford','ford fairmont'
+323,'amc','amc concord'
+324,'dodge','dodge aspen'
+325,'audi','audi 4000'
+326,'toyota','toyota corona liftback'
+327,'mazda','mazda 626'
+328,'datsun','datsun 510 hatchback'
+329,'toyota','toyota corolla'
+330,'mazda','mazda glc'
+331,'dodge','dodge colt'
+332,'datsun','datsun 210'
+333,'volkswagen','vw rabbit c (diesel)'
+334,'volkswagen','vw dasher (diesel)'
+335,'audi','audi 5000s (diesel)'
+336,'mercedes-benz','mercedes-benz 240d'
+337,'honda','honda civic 1500 gl'
+338,'renault','renault lecar deluxe'
+339,'subaru','subaru dl'
+340, 'volkswagen','volkswagen rabbit'
+341,'datsun','datsun 280-zx'
+342,'mazda','mazda rx-7 gs'
+343,'triumph','triumph tr7 coupe'
+344,'ford','ford mustang cobra'
+345,'honda','honda accord'
+346,'plymouth','plymouth reliant'
+347,'buick','buick skylark'
+348,'dodge','dodge aries wagon (sw)'
+349,'chevrolet','chevrolet citation'
+350,'plymouth','plymouth reliant'
+351,'toyota','toyota starlet'
+352,'plymouth','plymouth champ'
+353,'honda','honda civic 1300'
+354,'subaru','subaru'
+355,'datsun','datsun 210 mpg'
+356,'toyota','toyota tercel'
+357,'mazda','mazda glc 4'
+358,'plymouth','plymouth horizon 4'
+359,'ford','ford escort 4w'
+360,'ford','ford escort 2h'
+361,'volkswagen','volkswagen jetta'
+362,'renault','renault 18i'
+363,'honda','honda prelude'
+364,'toyota','toyota corolla'
+365,'datsun','datsun 200sx'
+366,'mazda','mazda 626'
+367,'peugeot','peugeot 505s turbo diesel'
+368,'saab','saab 900s'
+369,'volvo','volvo diesel'
+370,'toyota','toyota cressida'
+371,'datsun','datsun 810 maxima'
+372,'buick','buick century'
+373,'oldsmobile','oldsmobile cutlass ls'
+374,'ford','ford granada gl'
+375,'chrysler','chrysler lebaron salon'
+376,'chevrolet','chevrolet cavalier'
+377,'chevrolet','chevrolet cavalier wagon'
+378,'chevrolet','chevrolet cavalier 2-door'
+379,'pontiac','pontiac j2000 se hatchback'
+380,'dodge','dodge aries se'
+381,'pontiac','pontiac phoenix'
+382,'ford','ford fairmont futura'
+383,'amc','amc concord dl'
+384,'volkswagen','volkswagen rabbit l'
+385,'mazda','mazda glc custom l'
+386,'mazda','mazda glc custom'
+387,'plymouth','plymouth horizon miser'
+388,'mercury','mercury lynx l'
+389,'nissan','nissan stanza xe'
+390,'honda','honda accord'
+391,'toyota','toyota corolla'
+392,'honda','honda civic'
+393,'honda','honda civic (auto)'
+394,'datsun','datsun 310 gx'
+395,'buick','buick century limited'
+396,'oldsmobile','oldsmobile cutlass ciera (diesel)'
+397,'chrysler','chrysler lebaron medallion'
+398,'ford','ford granada l'
+399,'toyota','toyota celica gt'
+400,'dodge','dodge charger 2.2'
+401,'chevrolet','chevrolet camaro'
+402,'ford','ford mustang gl'
+403,'volkswagen','vw pickup'
+404,'dodge','dodge rampage'
+405,'ford','ford ranger'
+406,'chevrolet','chevy s-10'

spider-corpus-test/test_database/car_1/data_csv/cars-data.csv

@@ -0,0 +1,407 @@
+Id,MPG,Cylinders,Edispl,Horsepower,Weight,Accelerate,Year
+1,18,8,307,130,3504,12,1970
+2,15,8,350,165,3693,11.5,1970
+3,18,8,318,150,3436,11,1970
+4,16,8,304,150,3433,12,1970
+5,17,8,302,140,3449,10.5,1970
+6,15,8,429,198,4341,10,1970
+7,14,8,454,220,4354,9,1970
+8,14,8,440,215,4312,8.5,1970
+9,14,8,455,225,4425,10,1970
+10,15,8,390,190,3850,8.5,1970
+11,null,4,133,115,3090,17.5,1970
+12,null,8,350,165,4142,11.5,1970
+13,null,8,351,153,4034,11,1970
+14,null,8,383,175,4166,10.5,1970
+15,null,8,360,175,3850,11,1970
+16,15,8,383,170,3563,10,1970
+17,14,8,340,160,3609,8,1970
+18,null,8,302,140,3353,8,1970
+19,15,8,400,150,3761,9.5,1970
+20,14,8,455,225,3086,10,1970
+21,24,4,113,95,2372,15,1970
+22,22,6,198,95,2833,15.5,1970
+23,18,6,199,97,2774,15.5,1970
+24,21,6,200,85,2587,16,1970
+25,27,4,97,88,2130,14.5,1970
+26,26,4,97,46,1835,20.5,1970
+27,25,4,110,87,2672,17.5,1970
+28,24,4,107,90,2430,14.5,1970
+29,25,4,104,95,2375,17.5,1970
+30,26,4,121,113,2234,12.5,1970
+31,21,6,199,90,2648,15,1970
+32,10,8,360,215,4615,14,1970
+33,10,8,307,200,4376,15,1970
+34,11,8,318,210,4382,13.5,1970
+35,9,8,304,193,4732,18.5,1970
+36,27,4,97,88,2130,14.5,1971
+37,28,4,140,90,2264,15.5,1971
+38,25,4,113,95,2228,14,1971
+39,25,4,98,null,2046,19,1971
+40,null,4,97,48,1978,20,1971
+41,19,6,232,100,2634,13,1971
+42,16,6,225,105,3439,15.5,1971
+43,17,6,250,100,3329,15.5,1971
+44,19,6,250,88,3302,15.5,1971
+45,18,6,232,100,3288,15.5,1971
+46,14,8,350,165,4209,12,1971
+47,14,8,400,175,4464,11.5,1971
+48,14,8,351,153,4154,13.5,1971
+49,14,8,318,150,4096,13,1971
+50,12,8,383,180,4955,11.5,1971
+51,13,8,400,170,4746,12,1971
+52,13,8,400,175,5140,12,1971
+53,18,6,258,110,2962,13.5,1971
+54,22,4,140,72,2408,19,1971
+55,19,6,250,100,3282,15,1971
+56,18,6,250,88,3139,14.5,1971
+57,23,4,122,86,2220,14,1971
+58,28,4,116,90,2123,14,1971
+59,30,4,79,70,2074,19.5,1971
+60,30,4,88,76,2065,14.5,1971
+61,31,4,71,65,1773,19,1971
+62,35,4,72,69,1613,18,1971
+63,27,4,97,60,1834,19,1971
+64,26,4,91,70,1955,20.5,1971
+65,24,4,113,95,2278,15.5,1972
+66,25,4,97.5,80,2126,17,1972
+67,23,4,97,54,2254,23.5,1972
+68,20,4,140,90,2408,19.5,1972
+69,21,4,122,86,2226,16.5,1972
+70,13,8,350,165,4274,12,1972
+71,14,8,400,175,4385,12,1972
+72,15,8,318,150,4135,13.5,1972
+73,14,8,351,153,4129,13,1972
+74,17,8,304,150,3672,11.5,1972
+75,11,8,429,208,4633,11,1972
+76,13,8,350,155,4502,13.5,1972
+77,12,8,350,160,4456,13.5,1972
+78,13,8,400,190,4422,12.5,1972
+79,19,3,70,97,2330,13.5,1972
+80,15,8,304,150,3892,12.5,1972
+81,13,8,307,130,4098,14,1972
+82,13,8,302,140,4294,16,1972
+83,14,8,318,150,4077,14,1972
+84,18,4,121,112,2933,14.5,1972
+85,22,4,121,76,2511,18,1972
+86,21,4,120,87,2979,19.5,1972
+87,26,4,96,69,2189,18,1972
+88,22,4,122,86,2395,16,1972
+89,28,4,97,92,2288,17,1972
+90,23,4,120,97,2506,14.5,1972
+91,28,4,98,80,2164,15,1972
+92,27,4,97,88,2100,16.5,1972
+93,13,8,350,175,4100,13,1973
+94,14,8,304,150,3672,11.5,1973
+95,13,8,350,145,3988,13,1973
+96,14,8,302,137,4042,14.5,1973
+97,15,8,318,150,3777,12.5,1973
+98,12,8,429,198,4952,11.5,1973
+99,13,8,400,150,4464,12,1973
+100,13,8,351,158,4363,13,1973
+101,14,8,318,150,4237,14.5,1973
+102,13,8,440,215,4735,11,1973
+103,12,8,455,225,4951,11,1973
+104,13,8,360,175,3821,11,1973
+105,18,6,225,105,3121,16.5,1973
+106,16,6,250,100,3278,18,1973
+107,18,6,232,100,2945,16,1973
+108,18,6,250,88,3021,16.5,1973
+109,23,6,198,95,2904,16,1973
+110,26,4,97,46,1950,21,1973
+111,11,8,400,150,4997,14,1973
+112,12,8,400,167,4906,12.5,1973
+113,13,8,360,170,4654,13,1973
+114,12,8,350,180,4499,12.5,1973
+115,18,6,232,100,2789,15,1973
+116,20,4,97,88,2279,19,1973
+117,21,4,140,72,2401,19.5,1973
+118,22,4,108,94,2379,16.5,1973
+119,18,3,70,90,2124,13.5,1973
+120,19,4,122,85,2310,18.5,1973
+121,21,6,155,107,2472,14,1973
+122,26,4,98,90,2265,15.5,1973
+123,15,8,350,145,4082,13,1973
+124,16,8,400,230,4278,9.5,1973
+125,29,4,68,49,1867,19.5,1973
+126,24,4,116,75,2158,15.5,1973
+127,20,4,114,91,2582,14,1973
+128,19,4,121,112,2868,15.5,1973
+129,15,8,318,150,3399,11,1973
+130,24,4,121,110,2660,14,1973
+131,20,6,156,122,2807,13.5,1973
+132,11,8,350,180,3664,11,1973
+133,20,6,198,95,3102,16.5,1974
+134,21,6,200,null,2875,17,1974
+135,19,6,232,100,2901,16,1974
+136,15,6,250,100,3336,17,1974
+137,31,4,79,67,1950,19,1974
+138,26,4,122,80,2451,16.5,1974
+139,32,4,71,65,1836,21,1974
+140,25,4,140,75,2542,17,1974
+141,16,6,250,100,3781,17,1974
+142,16,6,258,110,3632,18,1974
+143,18,6,225,105,3613,16.5,1974
+144,16,8,302,140,4141,14,1974
+145,13,8,350,150,4699,14.5,1974
+146,14,8,318,150,4457,13.5,1974
+147,14,8,302,140,4638,16,1974
+148,14,8,304,150,4257,15.5,1974
+149,29,4,98,83,2219,16.5,1974
+150,26,4,79,67,1963,15.5,1974
+151,26,4,97,78,2300,14.5,1974
+152,31,4,76,52,1649,16.5,1974
+153,32,4,83,61,2003,19,1974
+154,28,4,90,75,2125,14.5,1974
+155,24,4,90,75,2108,15.5,1974
+156,26,4,116,75,2246,14,1974
+157,24,4,120,97,2489,15,1974
+158,26,4,108,93,2391,15.5,1974
+159,31,4,79,67,2000,16,1974
+160,19,6,225,95,3264,16,1975
+161,18,6,250,105,3459,16,1975
+162,15,6,250,72,3432,21,1975
+163,15,6,250,72,3158,19.5,1975
+164,16,8,400,170,4668,11.5,1975
+165,15,8,350,145,4440,14,1975
+166,16,8,318,150,4498,14.5,1975
+167,14,8,351,148,4657,13.5,1975
+168,17,6,231,110,3907,21,1975
+169,16,6,250,105,3897,18.5,1975
+170,15,6,258,110,3730,19,1975
+171,18,6,225,95,3785,19,1975
+172,21,6,231,110,3039,15,1975
+173,20,8,262,110,3221,13.5,1975
+174,13,8,302,129,3169,12,1975
+175,29,4,97,75,2171,16,1975
+176,23,4,140,83,2639,17,1975
+177,20,6,232,100,2914,16,1975
+178,23,4,140,78,2592,18.5,1975
+179,24,4,134,96,2702,13.5,1975
+180,25,4,90,71,2223,16.5,1975
+181,24,4,119,97,2545,17,1975
+182,18,6,171,97,2984,14.5,1975
+183,29,4,90,70,1937,14,1975
+184,19,6,232,90,3211,17,1975
+185,23,4,115,95,2694,15,1975
+186,23,4,120,88,2957,17,1975
+187,22,4,121,98,2945,14.5,1975
+188,25,4,121,115,2671,13.5,1975
+189,33,4,91,53,1795,17.5,1975
+190,28,4,107,86,2464,15.5,1976
+191,25,4,116,81,2220,16.9,1976
+192,25,4,140,92,2572,14.9,1976
+193,26,4,98,79,2255,17.7,1976
+194,27,4,101,83,2202,15.3,1976
+195,17.5,8,305,140,4215,13,1976
+196,16,8,318,150,4190,13,1976
+197,15.5,8,304,120,3962,13.9,1976
+198,14.5,8,351,152,4215,12.8,1976
+199,22,6,225,100,3233,15.4,1976
+200,22,6,250,105,3353,14.5,1976
+201,24,6,200,81,3012,17.6,1976
+202,22.5,6,232,90,3085,17.6,1976
+203,29,4,85,52,2035,22.2,1976
+204,24.5,4,98,60,2164,22.1,1976
+205,29,4,90,70,1937,14.2,1976
+206,33,4,91,53,1795,17.4,1976
+207,20,6,225,100,3651,17.7,1976
+208,18,6,250,78,3574,21,1976
+209,18.5,6,250,110,3645,16.2,1976
+210,17.5,6,258,95,3193,17.8,1976
+211,29.5,4,97,71,1825,12.2,1976
+212,32,4,85,70,1990,17,1976
+213,28,4,97,75,2155,16.4,1976
+214,26.5,4,140,72,2565,13.6,1976
+215,20,4,130,102,3150,15.7,1976
+216,13,8,318,150,3940,13.2,1976
+217,19,4,120,88,3270,21.9,1976
+218,19,6,156,108,2930,15.5,1976
+219,16.5,6,168,120,3820,16.7,1976
+220,16.5,8,350,180,4380,12.1,1976
+221,13,8,350,145,4055,12,1976
+222,13,8,302,130,3870,15,1976
+223,13,8,318,150,3755,14,1976
+224,31.5,4,98,68,2045,18.5,1977
+225,30,4,111,80,2155,14.8,1977
+226,36,4,79,58,1825,18.6,1977
+227,25.5,4,122,96,2300,15.5,1977
+228,33.5,4,85,70,1945,16.8,1977
+229,17.5,8,305,145,3880,12.5,1977
+230,17,8,260,110,4060,19,1977
+231,15.5,8,318,145,4140,13.7,1977
+232,15,8,302,130,4295,14.9,1977
+233,17.5,6,250,110,3520,16.4,1977
+234,20.5,6,231,105,3425,16.9,1977
+235,19,6,225,100,3630,17.7,1977
+236,18.5,6,250,98,3525,19,1977
+237,16,8,400,180,4220,11.1,1977
+238,15.5,8,350,170,4165,11.4,1977
+239,15.5,8,400,190,4325,12.2,1977
+240,16,8,351,149,4335,14.5,1977
+241,29,4,97,78,1940,14.5,1977
+242,24.5,4,151,88,2740,16,1977
+243,26,4,97,75,2265,18.2,1977
+244,25.5,4,140,89,2755,15.8,1977
+245,30.5,4,98,63,2051,17,1977
+246,33.5,4,98,83,2075,15.9,1977
+247,30,4,97,67,1985,16.4,1977
+248,30.5,4,97,78,2190,14.1,1977
+249,22,6,146,97,2815,14.5,1977
+250,21.5,4,121,110,2600,12.8,1977
+251,21.5,3,80,110,2720,13.5,1977
+252,43.1,4,90,48,1985,21.5,1978
+253,36.1,4,98,66,1800,14.4,1978
+254,32.8,4,78,52,1985,19.4,1978
+255,39.4,4,85,70,2070,18.6,1978
+256,36.1,4,91,60,1800,16.4,1978
+257,19.9,8,260,110,3365,15.5,1978
+258,19.4,8,318,140,3735,13.2,1978
+259,20.2,8,302,139,3570,12.8,1978
+260,19.2,6,231,105,3535,19.2,1978
+261,20.5,6,200,95,3155,18.2,1978
+262,20.2,6,200,85,2965,15.8,1978
+263,25.1,4,140,88,2720,15.4,1978
+264,20.5,6,225,100,3430,17.2,1978
+265,19.4,6,232,90,3210,17.2,1978
+266,20.6,6,231,105,3380,15.8,1978
+267,20.8,6,200,85,3070,16.7,1978
+268,18.6,6,225,110,3620,18.7,1978
+269,18.1,6,258,120,3410,15.1,1978
+270,19.2,8,305,145,3425,13.2,1978
+271,17.7,6,231,165,3445,13.4,1978
+272,18.1,8,302,139,3205,11.2,1978
+273,17.5,8,318,140,4080,13.7,1978
+274,30,4,98,68,2155,16.5,1978
+275,27.5,4,134,95,2560,14.2,1978
+276,27.2,4,119,97,2300,14.7,1978
+277,30.9,4,105,75,2230,14.5,1978
+278,21.1,4,134,95,2515,14.8,1978
+279,23.2,4,156,105,2745,16.7,1978
+280,23.8,4,151,85,2855,17.6,1978
+281,23.9,4,119,97,2405,14.9,1978
+282,20.3,5,131,103,2830,15.9,1978
+283,17,6,163,125,3140,13.6,1978
+284,21.6,4,121,115,2795,15.7,1978
+285,16.2,6,163,133,3410,15.8,1978
+286,31.5,4,89,71,1990,14.9,1978
+287,29.5,4,98,68,2135,16.6,1978
+288,21.5,6,231,115,3245,15.4,1979
+289,19.8,6,200,85,2990,18.2,1979
+290,22.3,4,140,88,2890,17.3,1979
+291,20.2,6,232,90,3265,18.2,1979
+292,20.6,6,225,110,3360,16.6,1979
+293,17,8,305,130,3840,15.4,1979
+294,17.6,8,302,129,3725,13.4,1979
+295,16.5,8,351,138,3955,13.2,1979
+296,18.2,8,318,135,3830,15.2,1979
+297,16.9,8,350,155,4360,14.9,1979
+298,15.5,8,351,142,4054,14.3,1979
+299,19.2,8,267,125,3605,15,1979
+300,18.5,8,360,150,3940,13,1979
+301,31.9,4,89,71,1925,14,1979
+302,34.1,4,86,65,1975,15.2,1979
+303,35.7,4,98,80,1915,14.4,1979
+304,27.4,4,121,80,2670,15,1979
+305,25.4,5,183,77,3530,20.1,1979
+306,23,8,350,125,3900,17.4,1979
+307,27.2,4,141,71,3190,24.8,1979
+308,23.9,8,260,90,3420,22.2,1979
+309,34.2,4,105,70,2200,13.2,1979
+310,34.5,4,105,70,2150,14.9,1979
+311,31.8,4,85,65,2020,19.2,1979
+312,37.3,4,91,69,2130,14.7,1979
+313,28.4,4,151,90,2670,16,1979
+314,28.8,6,173,115,2595,11.3,1979
+315,26.8,6,173,115,2700,12.9,1979
+316,33.5,4,151,90,2556,13.2,1979
+317,41.5,4,98,76,2144,14.7,1980
+318,38.1,4,89,60,1968,18.8,1980
+319,32.1,4,98,70,2120,15.5,1980
+320,37.2,4,86,65,2019,16.4,1980
+321,28,4,151,90,2678,16.5,1980
+322,26.4,4,140,88,2870,18.1,1980
+323,24.3,4,151,90,3003,20.1,1980
+324,19.1,6,225,90,3381,18.7,1980
+325,34.3,4,97,78,2188,15.8,1980
+326,29.8,4,134,90,2711,15.5,1980
+327,31.3,4,120,75,2542,17.5,1980
+328,37,4,119,92,2434,15,1980
+329,32.2,4,108,75,2265,15.2,1980
+330,46.6,4,86,65,2110,17.9,1980
+331,27.9,4,156,105,2800,14.4,1980
+332,40.8,4,85,65,2110,19.2,1980
+333,44.3,4,90,48,2085,21.7,1980
+334,43.4,4,90,48,2335,23.7,1980
+335,36.4,5,121,67,2950,19.9,1980
+336,30,4,146,67,3250,21.8,1980
+337,44.6,4,91,67,1850,13.8,1980
+338,40.9,4,85,null,1835,17.3,1980
+339,33.8,4,97,67,2145,18,1980
+340,29.8,4,89,62,1845,15.3,1980
+341,32.7,6,168,132,2910,11.4,1980
+342,23.7,3,70,100,2420,12.5,1980
+343,35,4,122,88,2500,15.1,1980
+344,23.6,4,140,null,2905,14.3,1980
+345,32.4,4,107,72,2290,17,1980
+346,27.2,4,135,84,2490,15.7,1981
+347,26.6,4,151,84,2635,16.4,1981
+348,25.8,4,156,92,2620,14.4,1981
+349,23.5,6,173,110,2725,12.6,1981
+350,30,4,135,84,2385,12.9,1981
+351,39.1,4,79,58,1755,16.9,1981
+352,39,4,86,64,1875,16.4,1981
+353,35.1,4,81,60,1760,16.1,1981
+354,32.3,4,97,67,2065,17.8,1981
+355,37,4,85,65,1975,19.4,1981
+356,37.7,4,89,62,2050,17.3,1981
+357,34.1,4,91,68,1985,16,1981
+358,34.7,4,105,63,2215,14.9,1981
+359,34.4,4,98,65,2045,16.2,1981
+360,29.9,4,98,65,2380,20.7,1981
+361,33,4,105,74,2190,14.2,1981
+362,34.5,4,100,null,2320,15.8,1981
+363,33.7,4,107,75,2210,14.4,1981
+364,32.4,4,108,75,2350,16.8,1981
+365,32.9,4,119,100,2615,14.8,1981
+366,31.6,4,120,74,2635,18.3,1981
+367,28.1,4,141,80,3230,20.4,1981
+368,null,4,121,110,2800,15.4,1981
+369,30.7,6,145,76,3160,19.6,1981
+370,25.4,6,168,116,2900,12.6,1981
+371,24.2,6,146,120,2930,13.8,1981
+372,22.4,6,231,110,3415,15.8,1981
+373,26.6,8,350,105,3725,19,1981
+374,20.2,6,200,88,3060,17.1,1981
+375,17.6,6,225,85,3465,16.6,1981
+376,28,4,112,88,2605,19.6,1982
+377,27,4,112,88,2640,18.6,1982
+378,34,4,112,88,2395,18,1982
+379,31,4,112,85,2575,16.2,1982
+380,29,4,135,84,2525,16,1982
+381,27,4,151,90,2735,18,1982
+382,24,4,140,92,2865,16.4,1982
+383,23,4,151,null,3035,20.5,1982
+384,36,4,105,74,1980,15.3,1982
+385,37,4,91,68,2025,18.2,1982
+386,31,4,91,68,1970,17.6,1982
+387,38,4,105,63,2125,14.7,1982
+388,36,4,98,70,2125,17.3,1982
+389,36,4,120,88,2160,14.5,1982
+390,36,4,107,75,2205,14.5,1982
+391,34,4,108,70,2245,16.9,1982
+392,38,4,91,67,1965,15,1982
+393,32,4,91,67,1965,15.7,1982
+394,38,4,91,67,1995,16.2,1982
+395,25,6,181,110,2945,16.4,1982
+396,38,6,262,85,3015,17,1982
+397,26,4,156,92,2585,14.5,1982
+398,22,6,232,112,2835,14.7,1982
+399,32,4,144,96,2665,13.9,1982
+400,36,4,135,84,2370,13,1982
+401,27,4,151,90,2950,17.3,1982
+402,27,4,140,86,2790,15.6,1982
+403,44,4,97,52,2130,24.6,1982
+404,32,4,135,84,2295,11.6,1982
+405,28,4,120,79,2625,18.6,1982
+406,31,4,119,82,2720,19.4,1982

spider-corpus-test/test_database/car_1/data_csv/cars.desc

@@ -0,0 +1,94 @@
+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
+
+               

spider-corpus-test/test_database/car_1/data_csv/continents.csv

@@ -0,0 +1,6 @@
+ContId,Continent
+1,'america'
+2,'europe'
+3,'asia'
+4,'africa'
+5,'australia'

spider-corpus-test/test_database/car_1/data_csv/countries.csv

@@ -0,0 +1,16 @@
+CountryId,CountryName,Continent
+1,'usa',1
+2,'germany',2
+3,'france',2
+4,'japan',3
+5,'italy',2
+6,'sweden',2
+7,'uk',2
+8,'korea',3
+9,'russia',2
+10,'nigeria',4
+11,'australia',5
+12,'new zealand',5
+13,'egypt',4
+14,'mexico',1
+15,'brazil',1

spider-corpus-test/test_database/car_1/data_csv/model-list.csv

@@ -0,0 +1,37 @@
+ModelId,Maker,Model
+1,1,'amc'
+2,2,'audi'
+3,3,'bmw'
+4,4,'buick'
+5,4,'cadillac'
+6,5,'capri'
+7,4,'chevrolet'
+8,6,'chrysler'
+9,7,'citroen'
+10,8,'datsun'
+11,6,'dodge'
+12,9,'fiat'
+13,5,'ford'
+14,10,'hi'
+15,11,'honda'
+16,12,'mazda'
+17,13,'mercedes'
+18,13,'mercedes-benz'
+19,5,'mercury'
+20,8,'nissan'
+21,4,'oldsmobile'
+22,14,'opel'
+23,15,'peugeot'
+24,6,'plymouth'
+25,4,'pontiac'
+26,16,'renault'
+27,17,'saab'
+28,18,'subaru'
+29,19,'toyota'
+30,20,'triumph'
+31,2,'volkswagen'
+32,21,'volvo'
+33,22,'kia'
+34,23,'hyundai'
+35,6,'jeep'
+36,19,'scion'

spider-corpus-test/test_database/car_1/link.txt

@@ -0,0 +1 @@
+http://users.csc.calpoly.edu/~dekhtyar/365-Spring2017/index.html

spider-corpus-test/test_database/car_1/q.txt

@@ -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.

spider-corpus-test/test_database/car_racing/schema.sql

@@ -0,0 +1,91 @@
+PRAGMA foreign_keys = ON;
+
+
+CREATE TABLE "country" (
+"Country_Id" int,
+"Country" text,
+"Capital" text,
+"Official_native_language" text,
+"Regoin" text,
+PRIMARY KEY ("Country_Id")
+);
+
+INSERT INTO  "country" VALUES (1,"Japan","Tokyo","Japanese","Asia");
+INSERT INTO  "country" VALUES (2,"USA","Washington","English","North America");
+INSERT INTO  "country" VALUES (6,"Britain","London","British English","Europe");
+INSERT INTO  "country" VALUES (3,"China","Beijing","Chinese","Asia");
+INSERT INTO  "country" VALUES (4,"Ireland","Dublin","Irish English","Europe");
+INSERT INTO  "country" VALUES (5,"Isle of Man","Douglas","English Manx","Europe");
+
+
+
+CREATE TABLE `team` (
+"Team_ID" int,
+"Team" text,
+"Make" text,
+"Manager" text,
+"Sponsor" text,
+"Car_Owner" text,
+PRIMARY KEY ("Team_ID")
+);
+
+CREATE TABLE `driver` (
+"Driver_ID" int,
+"Driver" text,
+"Country" int,
+"Age" int,
+"Car_#" real,
+"Make" text,
+"Points" text,
+"Laps" real,
+"Winnings" text,
+PRIMARY KEY ("Driver_ID"),
+FOREIGN KEY (`Country`) REFERENCES `country`(`Country_ID`)
+);
+
+
+
+CREATE TABLE `team_driver` (
+"Team_ID" int,
+"Driver_ID" int,
+PRIMARY KEY ("Team_ID","Driver_ID"),
+FOREIGN KEY (`Team_ID`) REFERENCES `team`(`Team_ID`),
+FOREIGN KEY (`Driver_ID`) REFERENCES `driver`(`Driver_ID`)
+);
+
+
+INSERT INTO  "team" VALUES (1,"Arrington Racing","Chrysler Imperial","Buddy Arrington","Arrington Racing","Buddy Arrington");
+INSERT INTO  "team" VALUES (2,"Benfield Racing","Buick Regal","Joe Ruttman","Levi Garrett","Ron Benfield");
+INSERT INTO  "team" VALUES (3,"Blue Max Racing","Pontiac Grand Prix","Tim Richmond","Old Milwaukee","Raymond Beadle");
+INSERT INTO  "team" VALUES (4,"Bobby Hawkins Racing","Chevrolet Monte Carlo","David Pearson","Chattanooga Chew","Bobby Hawkins");
+INSERT INTO  "team" VALUES (5,"Bud Moore Engineering","Ford Thunderbird","Dale Earnhardt","Wrangler Jeans","Bud Moore");
+INSERT INTO  "team" VALUES (6,"Cliff Stewart Racing","Pontiac Grand Prix","Geoff Bodine","Gatorade","Cliff Stewart");
+INSERT INTO  "team" VALUES (7,"DiGard Motorsports","Buick Regal","Bobby Allison","Miller American","Bill Gardner");
+INSERT INTO  "team" VALUES (8,"Donlavey Racing","Ford Thunderbird","Dick Brooks","Chameleon Sunglasses","Junie Donlavey");
+INSERT INTO  "team" VALUES (9,"Ellington Racing","Chevrolet Monte Carlo","Lake Speed","UNO / Bull Frog Knits","Hoss Ellington");
+INSERT INTO  "team" VALUES (10,"Hagan Racing","Chevrolet Monte Carlo","Terry Labonte","Budweiser","Billy Hagan");
+INSERT INTO  "team" VALUES (11,"Hamby Motorsports","Pontiac Grand Prix","Sterling Marlin (R)","Hesco Exhaust Systems","Roger Hamby");
+INSERT INTO  "team" VALUES (12,"Henderson Motorsports","Chevrolet Monte Carlo Buick Regal","Ronnie Hopkins (R)","Food Country USA","Charlie Henderson");
+
+INSERT INTO  "driver" VALUES (1,"Kasey Kahne",2,23,"9","Dodge","185","334","$530,164");
+INSERT INTO  "driver" VALUES (2,"Matt Kenseth",2,21,"17","Ford","175","334","$362,491");
+INSERT INTO  "driver" VALUES (3,"Tony Stewart",2,19,"20","Chevrolet","175","334","$286,386");
+INSERT INTO  "driver" VALUES (4,"Denny Hamlin *",2,25,"11","Chevrolet","165","334","$208,500");
+INSERT INTO  "driver" VALUES (5,"Kevin Li",3,23,"29","Chevrolet","160","334","$204,511");
+INSERT INTO  "driver" VALUES (6,"Jeff Chen",3,25,"31","Chevrolet","150","334","$172,220");
+INSERT INTO  "driver" VALUES (7,"Scott Riggs",1,22,"10","Dodge","146","334","$133,850");
+INSERT INTO  "driver" VALUES (8,"Mali Lu Jr. *",3,29,"1","Chevrolet","147","334","$156,608");
+INSERT INTO  "driver" VALUES (9,"Mark Martin",5,21,"6","Ford","143","334","$151,850");
+INSERT INTO  "driver" VALUES (10,"Bobby Labonte",4,25,"43","Dodge","134","334","$164,211");
+
+INSERT INTO  "team_driver" VALUES (1,1);
+INSERT INTO  "team_driver" VALUES (2,3);
+INSERT INTO  "team_driver" VALUES (1,5);
+INSERT INTO  "team_driver" VALUES (5,4);
+INSERT INTO  "team_driver" VALUES (1,9);
+INSERT INTO  "team_driver" VALUES (1,10);
+INSERT INTO  "team_driver" VALUES (10,7);
+INSERT INTO  "team_driver" VALUES (9,6);
+INSERT INTO  "team_driver" VALUES (1,2);
+INSERT INTO  "team_driver" VALUES (1,8);
+