fix: only retained needed db files for test split

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

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f5ae0e24e3a9d860a38ec6256828e3b9e37691c80931ef554adc202f8eb2950c
-size 1785856
+oid sha256:df77f2b1673ce3dd0f42d3a227a4b594c6f38ee390940a75f525bbaa0e71b8e4
+size 25647102

test_database/academic/academic.sqlite

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9ca59ebaa830731011a222885480e4b9f9d49c3e36849dee25b769fb74f296c2
-size 122880

test_database/academic/schema.sql

@@ -1,108 +0,0 @@
-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")
-);

test_database/aircraft/schema.sql

@@ -1,108 +0,0 @@
-
-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);
-

test_database/{car_1/data_csv/countries.csv → art_1/art_1.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ec03acf6d53e10e6299279f46a544952d18a247ad096d7f5fb6231e542032e70
-size 248
+oid sha256:ccfd00de54bbe9a7ce57f226e9634e8c4693520299795fb8da834017fc55d735
+size 8192

test_database/art_1/q.txt

@@ -0,0 +1,9 @@
+q0. Retrieve the title of each painting, the artist's last name, its height in inches and its width in inches in descending order of surface area.
+
+q1. Retrieve the artistID, first name, last name, and age at death of the artist(s) who was/were youngest at the time of death. (Note that since the birth and death dates are given as years only, any age computation is approximate, accurate plus or minus one.)
+
+q2. Retrieve the titles of all paintings and sculptures, with the artists' last names, in the database and the age the artist was at the time the work was produced, in order of youngest to oldest such age.
+
+q3. Retrieve the artist's last name and the title of all the undisplayed works.
+
+q4. Write a query to display the artistID, last name and all (distinct) media used by all artists in all paintings. Order the query result by last name, ascending. Your results should include not just the medium ("oil") but the surface the medium is on ("oil on canvas"). Use GROUP_CONCAT to denormalize the data and produce comma-delimited results like this:

test_database/bakery_1/annotation.json

@@ -0,0 +1,58 @@
+{
+    "label_id": null, 
+    "data": [
+        {
+            "nl": "Find all chocolate-flavored items on the menu whose price is under $5.00. For each item output the flavor, the name (food type) of the item, and the price.\n", 
+            "id": 0
+        }, 
+        {
+            "nl": "Report the prices of any lemon-flavored items. Output the flavor, the name (food type) and the price of each pastry.\n", 
+            "id": 1
+        }, 
+        {
+            "nl": "Find all customers who made a purchase on October 3, 2007. Report the name of the customer (first, last).\n", 
+            "id": 2
+        }, 
+        {
+            "nl": "Find all types of cookies purchased by KIP ARNN during the month of October of 2007. Report each cookie type (flavor, food type) exactly once.\n", 
+            "id": 3
+        }, 
+        {
+            "nl": "Report the total amount of money NATACHA STENZ spent at the bakery during the month of October, 2007.\n", 
+            "id": 4
+        }, 
+        {
+            "nl": "Find all customers who purchased, during the same trip to the bakery, two different Croissants. Report first and last names of the customers.\n", 
+            "id": 5
+        }, 
+        {
+            "nl": "Find the total amount of money the bakery earned in October 2007 from selling eclairs. Report just the amount.\n", 
+            "id": 6
+        }, 
+        {
+            "nl": "Report all days on which more than ten tarts were purchased.\n", 
+            "id": 7
+        }, 
+        {
+            "nl": "For each purchase made by NATACHA STENZ output the receipt number, the date of purchase, the total number of items purchased and the amount paid.\n", 
+            "id": 8
+        }, 
+        {
+            "nl": "Find the customer(s) who spent the most on pastries in October of 2007. Report first and last name.\n", 
+            "id": 9
+        }, 
+        {
+            "nl": "Find the type of baked good (food type, flavor) responsible for highest total revenue.\n", 
+            "id": 10
+        }, 
+        {
+            "nl": "Find the day of the highest revenue in the month of October, 2007.\n", 
+            "id": 11
+        }, 
+        {
+            "nl": "Find the best-selling item (by number of purchases) on the day of the highest revenue in October of 2007.\n", 
+            "id": 12
+        }
+    ], 
+    "review_id": null
+}

test_database/{car_1/car_1.json → bakery_1/bakery_1.json}

@@ -2,215 +2,125 @@
     {
         "col_data": [
             {
-                "column_name": "ContId",
+                "column_name": "id",
                 "data_type": "INTEGER",
-                "default_column_name": "ContId",
+                "default_column_name": "Id",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 1
             },
             {
-                "column_name": "Continent",
+                "column_name": "last_name",
                 "data_type": "TEXT",
-                "default_column_name": "Continent",
+                "default_column_name": "LastName",
                 "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",
+                "column_name": "first_name",
                 "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_column_name": "FirstName",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             }
         ],
-        "table": "countries"
+        "table": "customers"
     },
     {
         "col_data": [
             {
-                "column_name": "Id",
-                "data_type": "INTEGER",
+                "column_name": "id",
+                "data_type": "TEXT",
                 "default_column_name": "Id",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 1
             },
             {
-                "column_name": "Maker",
+                "column_name": "flavor",
                 "data_type": "TEXT",
-                "default_column_name": "Maker",
+                "default_column_name": "Flavor",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             },
             {
-                "column_name": "FullName",
+                "column_name": "food",
                 "data_type": "TEXT",
-                "default_column_name": "FullName",
+                "default_column_name": "Food",
                 "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",
+                "column_name": "price",
+                "data_type": "REAL",
+                "default_column_name": "Price",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             }
         ],
-        "table": "car-names"
+        "table": "goods"
     },
     {
         "col_data": [
             {
-                "column_name": "Id",
+                "column_name": "reciept_number",
                 "data_type": "INTEGER",
-                "default_column_name": "Id",
+                "default_column_name": "RecieptNumber",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 1
             },
             {
-                "column_name": "MPG",
+                "column_name": "date",
                 "data_type": "TEXT",
-                "default_column_name": "MPG",
+                "default_column_name": "Date",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             },
             {
-                "column_name": "Cylinders",
+                "column_name": "customer_id",
                 "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_column_name": "CustomerId",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             }
         ],
-        "table": "cars-data"
+        "table": "receipts"
     },
     {
         "col_data": [
             {
-                "column_name": "ModelId",
+                "column_name": "reciept",
                 "data_type": "INTEGER",
-                "default_column_name": "ModelId",
+                "default_column_name": "Reciept",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 1
             },
             {
-                "column_name": "Maker",
+                "column_name": "ordinal",
                 "data_type": "INTEGER",
-                "default_column_name": "Maker",
+                "default_column_name": "Ordinal",
                 "default_value": null,
                 "not_null": 0,
-                "primary_key": 0
+                "primary_key": 2
             },
             {
-                "column_name": "Model",
+                "column_name": "item",
                 "data_type": "TEXT",
-                "default_column_name": "Model",
+                "default_column_name": "Item",
                 "default_value": null,
                 "not_null": 0,
                 "primary_key": 0
             }
         ],
-        "table": "model-list"
+        "table": "items"
     }
-]
+]

test_database/bakery_1/bakery_1.sql

@@ -0,0 +1,30 @@
+CREATE TABLE "customers" (
+	"Id" INTEGER PRIMARY KEY,
+	"LastName" TEXT,
+	"FirstName" TEXT
+);
+
+
+CREATE TABLE "goods" (
+	"Id" TEXT PRIMARY KEY,
+	"Flavor" TEXT,
+	"Food" TEXT,
+	"Price" REAL
+);
+
+
+CREATE TABLE "items" (
+	"Receipt" INTEGER,
+	"Ordinal" INTEGER,
+	"Item" TEXT,
+	PRIMARY KEY(Receipt, Ordinal),
+	FOREIGN KEY (Item) REFERENCES goods(Id)
+    FOREIGN KEY (Receipt) REFERENCES receipts(ReceiptNumber)
+);
+
+CREATE TABLE "receipts" (
+	"ReceiptNumber" INTEGER PRIMARY KEY,
+	"Date" TEXT,
+	"CustomerId" INTEGER,
+	FOREIGN KEY(CustomerId) REFERENCES customers(Id)
+);

test_database/{geo/geo.sqlite → bakery_1/bakery_1.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:becb9fc6faf0d87b2b396100d962ed6d9de0fd4e5e03ad102bacec73529ffbc8
+oid sha256:8ab55eb34c0ea8cbe29f9651ec3deae620ba8558e03b0e7740daa871e4eba025
 size 57344

test_database/bakery_1/bakery_1_michi.txt

@@ -0,0 +1,411 @@
+Total # = 51
+
+1. What is the most expensive cake and its flavor?
+
+select id, flavor
+from goods
+where food = "Cake"
+order by price desc
+limit 1
+
+What is the cheapest cookie and its flavor?
+
+select id, flavor
+from goods
+where food = "Cookie"
+order by price
+limit 1
+
+2. Find the ids of goods that have apple flavor.
+
+Select id
+From goods
+Where flavor = "Apple"
+
+What are the ids of goods that cost less than 3 dollars?
+
+Select id
+From goods
+Where price < 3
+
+
+3. List the distinct ids of all customers who bought a lemon cake?
+
+Select DISTINCT T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.Id = T2.Item and T2.Receipt = T3.ReceiptNumber
+Where T1.Flavor = "Lemon" and T1.Food = "Cake"
+
+
+For each type of food, tell me how many customers have ever bought it.
+
+Select T1.food, count(distinct T3.CustomerId)
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.Id = T2.Item and T2.Receipt = T3.ReceiptNumber
+Group by T1.food
+
+
+4. Find the id of customers who shopped at the bakery at least 15 times.
+
+Select CustomerId
+From receipts
+Group by CustomerId
+having count(*) >= 15
+
+What is the last name of the customers who shopped at the bakery more than 10 times?
+
+Select T2.LastName
+From receipts as T1 JOIN customers as T2 ON T1.CustomerId = T2.id
+Group by T2.id
+having count(*) > 10
+
+
+5. How many types of Cake does this bakery sell?
+
+Select count(*)
+From goods
+where food = "Cake"
+
+List all the flavors of Croissant available in this bakery.
+
+Select flavor
+From goods
+where food = "Croissant"
+
+
+6. Give me a list of all the distinct items bought by the customer number 15.
+
+Select distinct T1.item
+from items as T1 JOIN receipts as T2 ON T1.receipt = T2.ReceiptNumber 
+Where T2.CustomerId = 15
+
+
+For each type of food, what are the average, maximum and minimum price?
+
+Select food, avg(price), max(price), min(price)
+from goods
+Group by food
+
+
+7. Find the receipt numbers where both Cake and Cookie were bought.
+
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Cake"
+INTERSECT
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Cookie"
+
+
+Find all the receipt numbers in which customer id 5 purchased Croissant.
+
+Select ReceiptNumber
+From receipts
+Where CustomerId = 5
+INTERSECT
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.food = "Croissant"
+
+
+8. What is the receipt number and date of the receipt in which the most expensive item was bought?
+
+Select T1.ReceiptNumber, T1.Date
+From receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Order by T3.price Desc
+LIMIT 1
+
+
+What is the item that was bought the least number of times?
+Select item
+From items
+Group by item
+Order by count(*)
+LIMIT 1
+
+
+9. How many goods are available for each food type?
+
+Select count(*), food
+From goods
+group by food
+
+What is the average price for each food type?
+
+Select avg(price), food
+From goods
+group by food
+
+
+10. What are the goods that have Apricot flavor and are cheaper than 5 dollars?
+
+Select id
+From goods
+where flavor = "Apricot" and price < 5
+
+Find flavor of cakes that cost more than 10 dollars.
+
+Select flavor
+From goods
+where food = "Cake" and price > 10
+
+
+11. Give me the distinct id and price for all goods whose price is below the average of all goods?
+
+Select distinct id, price
+From goods
+where price < (Select avg(price) From goods)
+  
+
+What are the distinct ids of all goods that are cheaper than some goods of type Tart?
+
+Select distinct T1.id
+From goods as T1, goods as T2
+where T1.price < T2.price and T2.food = "Tart"
+
+
+12.  List distinct receipt numbers for which someone bought a good that costs more than 13 dollars.
+
+Select distinct T1.ReceiptNumber
+from receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Where T3.price > 13
+
+
+On which date did some customer buy a good that costs more than 15 dollars?
+
+Select distinct T1.date
+from receipts as T1 JOIN items as T2 JOIN goods as T3 ON T1.ReceiptNumber = T2.receipt and T2.item = T3.id
+Where T3.price > 15
+
+
+13. Give me the list of all goods whose id has "APP".
+
+Select id
+from goods
+Where id LIKE "%APP%"
+
+Which good has "70" in its id? And what is its price?
+
+Select id, price
+from goods
+Where id LIKE "%70%"
+
+
+14. List the last names of all customers in an alphabetical oder.
+
+Select distinct LastName
+From customers
+Order by LastName
+
+Return the ordered list of all good ids.
+
+Select distinct id
+From goods
+Order by id
+
+
+15. Find all receipts in which either apple flavor pie was bought or customer id 12 shopped.
+
+Select T1.receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+where T2.flavor = "Apple" and T2.food = "Pie"
+UNION
+Select ReceiptNumber
+From receipts
+where CustomerId = 12
+
+
+Find all receipts which has the latest date. Also tell me that date.
+
+Select ReceiptNumber, date
+From receipts
+where date = (Select date From receipts Order by date Desc LIMIT 1)
+
+
+Find all receipts which either has the earliest date or has a good with price above 10.
+
+Select T1.Receipt
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+where T2.price > 10
+UNION
+Select ReceiptNumber
+From receipts
+where date = (Select date From receipts Order by date LIMIT 1)
+
+
+16. What are the ids of Cookie and Cake that cost between 3 and 7 dollars.
+
+Select id
+From goods
+where (food = "Cookie" or food = "Cake") and price between 3 and 7 
+
+
+Find the first name and last name of a customer who visited on the earliest date.
+
+Select T1.FirstName, T1.LastName
+From customers as T1 JOIN receipts as T2 ON T1.id = T2.CustomerId
+Order by T2.date
+LIMIT 1
+
+
+
+17. What is average price of goods whose flavor is blackberry or blueberry?
+
+Select avg(price)
+From goods
+where flavor = "Blackberry" or flavor = "Blueberry"
+
+
+Return the cheapest price for goods with cheese flavor.
+
+Select min(price)
+From goods
+where flavor = "Cheese"
+
+
+18. What are highest, lowest, and average prices of goods, grouped and ordered by flavor?
+
+Select max(price), min(price), avg(price), flavor
+From goods
+group by flavor
+order by flavor
+
+
+Return the lowest and highest prices of goods grouped and ordered by food type.
+
+Select min(price), max(price), food
+From goods
+group by food
+order by food
+
+
+19. Find the top three dates when the most goods were sold.
+
+Select date
+From receipts
+Group by date
+Order by count(*)
+LIMIT 3
+
+Which customer shopped most often? How many times?
+
+Select CustomerId, count(*)
+From receipts
+Group by CustomerId
+Order by count(*)
+LIMIT 1
+
+
+20. For each date, return how many distinct customers visited on that day.
+
+Select date, count (distinct CustomerId)
+from receipts
+Group by date
+
+
+Give me the first name and last name of customers who have bought apple flavor Tart.
+
+Select distinct T4.FirstName, T4.LastName
+from goods as T1 JOIN items as T2 JOIN receipts as T3 JOIN customers as T4 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber and T3.CustomerId = T4.id
+where T1.flavor = "Apple" and T1.food = "Tart"
+
+
+21. What are the ids of Cookies whose price is lower than any Croissant?
+
+Select id
+From goods
+where food = "Cookie" and price <  (select min(price)
+                             from goods
+                             where food = 'Croissant')
+
+
+Give me the ids of Cakes whose price is at least three times as much as the average price of Tart?
+
+Select id
+From goods
+where food = "Cake" and price >= 3 * (select avg(price)
+                             from goods
+                             where food = "Tart")
+
+
+What are the ids of goods whose price is above twice the average price of all goods?
+
+Select id
+From goods
+where price > 2 * (select avg(price)
+                             from goods)
+
+
+22. List the id, flavor and type of food of goods ordered by price.
+
+Select id, flavor, food
+From goods
+order by price
+
+
+Return a list of the id and flavor for Cakes ordered by flavor.
+
+Select id, flavor
+From goods
+where food = "Cake"
+order by flavor
+
+
+
+23. Find all the items that have chocolate flavor but were not bought more than 10 times. 
+
+Select distinct T1.item
+From items as T1 JOIN goods as T2 ON T1.item = T2.id
+Where T2.flavor = "Chocolate"
+EXCEPT 
+Select distinct item
+From items
+Group by item
+having count(*) > 10
+
+
+What are the flavors available for Cake but not for Tart?
+
+Select distinct flavor
+From goods
+where food = "Cake"
+EXCEPT 
+Select distinct flavor
+From goods
+where food = "Tart"
+
+
+24. What is the three most popular goods in this bakery?
+
+Select item
+From items
+Group by item
+Order by count (*) DESC
+LIMIT 3
+
+
+
+25. Find the ids of customers who have spent more than 150 dollars in total.
+
+Select T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.CustomerId
+having sum(T1.price) > 150
+
+
+Find the ids of customers whose average spending for each good is above 5.
+
+Select T3.CustomerId
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.CustomerId
+having avg(T1.price) > 5
+
+
+
+On which day did the bakery sell more than 100 dollars in total.
+
+Select T3.date
+From goods as T1 JOIN items as T2 JOIN receipts as T3 ON T1.id = T2.item and T2.receipt = T3.ReceiptNumber
+Group by T3.date
+having sum(T1.price) > 100
+
+

test_database/bakery_1/data_csv/README.BAKERY.TXT

@@ -0,0 +1,110 @@
+*****************************************************
+CPE 365                                 Alex Dekhtyar
+Cal Poly		  Computer Science Department
+San Luis Obispo                College of Engineering 
+California                   dekhtyar@csc.calpoly.edu   
+*****************************************************
+		  BAKERY DATASET
+                   Version 1.0
+                October 1, 2007
+*****************************************************
+Sources:  this is a synthesized dataset. 
+
+******************************************************
+
+This file describes the contents of the BAKERY dataset
+developed for the CPE 365, Introduction to Databases,
+course at Cal Poly.
+
+The dataset contains information about one month worth
+of sales information for a small bakery shop. The sales
+are made to known customers. The dataset contains
+information about the customers, the assortments of
+baked goods offered for sale and the purchases made.
+
+
+General Conventions.
+
+ 1. All files in the dataset are CSV (comma-separated values) files.
+ 2. First line of each file provides the names of
+    columns. Second line may be empty, or may contain
+    the first row of the data.
+ 3. All string values are enclosed in single quotes (')
+
+
+  The dataset consists of the following files:
+
+   - customers.csv : information about the bakery's customers
+   - goods.csv     : information about the baked goods offered
+                     for sale by the bakery
+   - items.csv     : itemized reciept infromation for purchases
+   - reciepts.csv  : general reciept information for purchases
+
+
+ reciepts.csv stores information about individual reciepts
+(purchases by customers). Each purchase may contain from
+one two five items, regardless of whether any items
+purchased are of the same kind (e.g., two "chocolate cakes"
+will be billed as two separate items on the reciept).
+items.csv contains itemized reciept information.
+
+
+ Individual files have the following formats.
+
+**************************************************************************
+
+ customers.csv
+
+        Id: unique identifier of the customer
+  LastName: last name of the customer
+ FirstName: first name of the customer
+
+
+
+**************************************************************************
+
+
+ goods.csv
+
+     Id : unique identifier of the baked good
+  Flavor: flavor/type of the good (e.g., "chocolate", "lemon")
+    Food: category of the good (e.g., "cake", "tart")
+   Price: price (in dollars) 
+
+
+
+**************************************************************************
+
+items.csv
+
+    Reciept : reciept number (see reciepts.RecieptNumber)
+    Ordinal : position of the purchased item on the
+              reciepts. (i.e., first purchased item,
+              second purchased item, etc...)
+    Item    : identifier of the item purchased (see goods.Id)
+    
+
+
+**************************************************************************
+
+reciepts.csv
+
+RecieptNumber : unique identifier of the reciept
+         Date : date of the purchase. The date is
+                in  DD-Mon-YYY format, which is the
+                default Oracle's format for DATE data type.
+   CustomerId : id of the customer (see customers.Id)
+
+
+**************************************************************************
+**************************************************************************
+
+Permission granted to use and distribute this dataset in its current form, 
+provided this file  is kept unchanged and is distributed together with the 
+data.
+
+Permission granted to modify and expand this dataset, provided this
+file is updated accordingly with new information.
+
+**************************************************************************
+**************************************************************************

test_database/{car_1/data_csv/car-makers.csv → bakery_1/data_csv/customers.csv}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e799cefbae504a6d2f616c99e64017b5124e37e98eadc41a8cedc4b3a6f98506
-size 588
+oid sha256:4fa3ff7fe166ed5532eaa19938c5be357335fe82dad84ad5825a2562dba2668b
+size 490

test_database/{car_1/data_csv/continents.csv → bakery_1/data_csv/customers_t.csv}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:20735553edaaa41856e3413ffc22de9026649db723928a72a8e896a0143b311d
-size 80
+oid sha256:873596b8573f92372c6354f62d348d8150bf186a9b9b163801a663ed754c2110
+size 368

test_database/{car_1/data_csv/model-list.csv → bakery_1/data_csv/goods.csv}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5362df5563333aa282c8ca9f6ddbf24c5b9b2799305f6711e7c0cd342fa5694f
-size 569
+oid sha256:0676f451bf024fde17687d84c56196bc266bca69713bddf6577711df986d43ae
+size 1411

test_database/bakery_1/data_csv/goods_t.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f330742d8a5e312ba1d5a84d06a44f4eb9d05cc5c5eccedf824bb9674766dac4
+size 1171

test_database/{car_1/car_1.sqlite → bakery_1/data_csv/items (3:11:18, 5:53 PM)_original.csv}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9d851e396e02997a1de073ae982fe1e4b1769fdffce2fac6e325857a3a938709
-size 65536
+oid sha256:20b755b8d33b14fb87e922c6869f9fe51cf85811b991de41d674850a4571b1e6
+size 11817

test_database/{aircraft/aircraft.sqlite → bakery_1/data_csv/items.csv}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2b92973e99d8348a324e318fd4d62645ebe428e7346b51277e78385d1ad3b1ef
-size 45056
+oid sha256:90323310375d4d72b3a7e97d503afb78a1674c6944474195c8d48504301dbc26
+size 11817

test_database/bakery_1/data_csv/items_t.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a692759e583e70eec78dd4e8947f15b6d8046c5df3c7d31893e5e88c840dce6c
+size 9030

test_database/bakery_1/data_csv/receipts (3:11:18, 5:53 PM)_original.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eee2a10433b03b832649c0d41ef467efc0bb430afcec10452cfa73255971d377
+size 4883

test_database/bakery_1/data_csv/receipts.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c83039e0c6e4271862d128f474051ba500f97ca15edcfce88e82b9f47dff32b6
+size 4883

test_database/bakery_1/data_csv/receipts_t.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:16f643a31ccce616a3c94620278de4c7119b60dc64ffc644cd0a1fe2bb3aa873
+size 4081

test_database/bakery_1/q.txt

@@ -0,0 +1,25 @@
+Find all chocolate-flavored items on the menu whose price is under $5.00. For each item output the flavor, the name (food type) of the item, and the price.
+
+Report the prices of any lemon-flavored items. Output the flavor, the name (food type) and the price of each pastry.
+
+Find all customers who made a purchase on October 3, 2007. Report the name of the customer (first, last).
+
+Find all types of cookies purchased by KIP ARNN during the month of October of 2007. Report each cookie type (flavor, food type) exactly once.
+
+Report the total amount of money NATACHA STENZ spent at the bakery during the month of October, 2007.
+
+Find all customers who purchased, during the same trip to the bakery, two different Croissants. Report first and last names of the customers.
+
+Find the total amount of money the bakery earned in October 2007 from selling eclairs. Report just the amount.
+
+Report all days on which more than ten tarts were purchased.
+
+For each purchase made by NATACHA STENZ output the receipt number, the date of purchase, the total number of items purchased and the amount paid.
+
+Find the customer(s) who spent the most on pastries in October of 2007. Report first and last name.
+
+Find the type of baked good (food type, flavor) responsible for highest total revenue.
+
+Find the day of the highest revenue in the month of October, 2007.
+
+Find the best-selling item (by number of purchases) on the day of the highest revenue in October of 2007.

test_database/{cinema/cinema.sqlite → bike_racing/bike_racing.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9fbcc850e33d813a792417291ddfb1cebc4a31716621284ed28ef53df360a14e
+oid sha256:5d485e48c937b87f80c4e2bcc588d88042b1f52b8596b1f47afa33da674c8a5d
 size 28672

test_database/bike_racing/schema.sql

@@ -0,0 +1,56 @@
+PRAGMA foreign_keys=ON;
+BEGIN TRANSACTION;
+CREATE TABLE IF NOT EXISTS "bike" (
+    "id" int,
+    "product_name" text,
+    "weight" int,
+    "price" real,
+    "material" text,
+    primary key("id")
+);
+INSERT INTO bike VALUES(1,'BIANCHI SPECIALISSIMA',780,9998.9999999999999999,'Carbon CC');
+INSERT INTO bike VALUES(2,'CANNONDALE SUPERSIX EVO HI-MOD DURA ACE',850,5329.9999999999999999,'carbon fiber');
+INSERT INTO bike VALUES(3,'CANYON AEROAD CF SLX 8.0 DI2',880,3049.9999999999999999,'Toray T700 and T800 carbon fiber');
+INSERT INTO bike VALUES(4,'GIANT TCR ADVANCED SL 0',750,9000.0,'Carbon CC');
+INSERT INTO bike VALUES(5,'Ibis',800,3598.9999999999999998,'Carbon CC');
+INSERT INTO bike VALUES(6,'Ibis ||',760,5000, 'carbon fiber');
+CREATE TABLE IF NOT EXISTS "cyclist" (
+    "id" int,
+    "heat" int,
+    "name" text,
+    "nation" text,
+    "result" real,
+    primary key("id")
+);
+INSERT INTO cyclist VALUES(1,4,'Bradley Wiggins','Great Britain','4:16.571');
+INSERT INTO cyclist VALUES(2,3,'Hayden Roulston','New Zealand','4:19.232');
+INSERT INTO cyclist VALUES(3,1,'Steven Burke','Great Britain','4:21.558');
+INSERT INTO cyclist VALUES(4,2,'Alexei Markov','Russia','4:22.308');
+INSERT INTO cyclist VALUES(5,1,'Volodymyr Dyudya','Ukraine','4:22.471');
+INSERT INTO cyclist VALUES(6,2,'Antonio Tauler','Spain','4:24.974');
+INSERT INTO cyclist VALUES(7,4,'Alexander Serov','Russia','4:25.391');
+INSERT INTO cyclist VALUES(8,3,'Taylor Phinney','United States','4:26.644');
+CREATE TABLE IF NOT EXISTS "cyclists_own_bikes" (
+    "cyclist_id" int,
+    "bike_id" int,
+    "purchase_year" int,
+    primary key("cyclist_id", "bike_id"),
+    foreign key("cyclist_id") references `cyclist`("id"),
+    foreign key("bike_id") references `bike`("id")
+);
+INSERT INTO cyclists_own_bikes VALUES(1,2,2011);
+INSERT INTO cyclists_own_bikes VALUES(1,3,2015);
+INSERT INTO cyclists_own_bikes VALUES(2,3,2017);
+INSERT INTO cyclists_own_bikes VALUES(2,5,2013);
+INSERT INTO cyclists_own_bikes VALUES(2,4,2018);
+INSERT INTO cyclists_own_bikes VALUES(3,4,2017);
+INSERT INTO cyclists_own_bikes VALUES(4,4,2017);
+INSERT INTO cyclists_own_bikes VALUES(5,5,2016);
+INSERT INTO cyclists_own_bikes VALUES(6,5,2016);
+INSERT INTO cyclists_own_bikes VALUES(7,5,2010);
+INSERT INTO cyclists_own_bikes VALUES(7,4,2011);
+INSERT INTO cyclists_own_bikes VALUES(7,2,2012);
+INSERT INTO cyclists_own_bikes VALUES(7,1,2013);
+INSERT INTO cyclists_own_bikes VALUES(7,3,2014);
+COMMIT;
+

test_database/bike_racing/schema_old.sql

@@ -0,0 +1,56 @@
+PRAGMA foreign_keys=ON;
+BEGIN TRANSACTION;
+CREATE TABLE IF NOT EXISTS "bike" (
+    "id" int,
+    "product_name" text,
+    "weight" int,
+    "price" real,
+    "material" text,
+    primary key("id")
+);
+INSERT INTO bike VALUES(1,'BIANCHI SPECIALISSIMA',780,9998.9999999999999999,'Carbon CC');
+INSERT INTO bike VALUES(2,'CANNONDALE SUPERSIX EVO HI-MOD DURA ACE',850,5329.9999999999999999,'carbon fiber');
+INSERT INTO bike VALUES(3,'CANYON AEROAD CF SLX 8.0 DI2',880,3049.9999999999999999,'Toray T700 and T800 carbon fiber');
+INSERT INTO bike VALUES(4,'GIANT TCR ADVANCED SL 0',750,9000.0,'Carbon CC');
+INSERT INTO bike VALUES(5,'Ibis',800,3598.9999999999999998,'Carbon CC');
+INSERT INTO bike VALUES(6,'Ibis ||',760,5000, 'carbon fiber');
+CREATE TABLE IF NOT EXISTS "cyclist" (
+    "id" int,
+    "heat" int,
+    "name" text,
+    "nation" text,
+    "result" real,
+    primary key("id")
+);
+INSERT INTO cyclist VALUES(1,4,'Bradley Wiggins','Great Britain','4:16.571');
+INSERT INTO cyclist VALUES(2,3,'Hayden Roulston','New Zealand','4:19.232');
+INSERT INTO cyclist VALUES(3,1,'Steven Burke','Great Britain','4:21.558');
+INSERT INTO cyclist VALUES(4,2,'Alexei Markov','Russia','4:22.308');
+INSERT INTO cyclist VALUES(5,1,'Volodymyr Dyudya','Ukraine','4:22.471');
+INSERT INTO cyclist VALUES(6,2,'Antonio Tauler','Spain','4:24.974');
+INSERT INTO cyclist VALUES(7,4,'Alexander Serov','Russia','4:25.391');
+INSERT INTO cyclist VALUES(8,3,'Taylor Phinney','United States','4:26.644');
+CREATE TABLE IF NOT EXISTS "cyclists_own_bikes" (
+    "cyclist_id" int,
+    "bike_id" int,
+    "purchase_year" int,
+    primary key("cyclist_id", "bike_id"),
+    foreign key("cyclist_id") references "cyclist"("id"),
+    foreign key("bike_id") references "bike"("id")
+);
+INSERT INTO cyclists_own_bikes VALUES(1,2,2011);
+INSERT INTO cyclists_own_bikes VALUES(1,3,2015);
+INSERT INTO cyclists_own_bikes VALUES(2,3,2017);
+INSERT INTO cyclists_own_bikes VALUES(2,5,2013);
+INSERT INTO cyclists_own_bikes VALUES(2,4,2018);
+INSERT INTO cyclists_own_bikes VALUES(3,4,2017);
+INSERT INTO cyclists_own_bikes VALUES(4,4,2017);
+INSERT INTO cyclists_own_bikes VALUES(5,5,2016);
+INSERT INTO cyclists_own_bikes VALUES(6,5,2016);
+INSERT INTO cyclists_own_bikes VALUES(7,5,2010);
+INSERT INTO cyclists_own_bikes VALUES(7,4,2011);
+INSERT INTO cyclists_own_bikes VALUES(7,2,2012);
+INSERT INTO cyclists_own_bikes VALUES(7,1,2013);
+INSERT INTO cyclists_own_bikes VALUES(7,3,2014);
+COMMIT;
+

test_database/{company_employee/company_employee.sqlite → book_press/book_press.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:86574c9edbecd80ded437d9439d6f81def0973816b1c8af8d007335e62565378
+oid sha256:c8748351b418fb213f3e4871471f8b923011323df6d341fb96796bb36f466acb
 size 28672

test_database/book_press/schema.sql

@@ -0,0 +1,67 @@
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "author" (
+"Author_ID" int,
+"Name" text,
+"Age" int,
+"Gender" text,
+PRIMARY KEY ("Author_ID")
+);
+
+
+INSERT INTO  "author" VALUES (1,"Derrick Kosinski",45,"Male");
+INSERT INTO  "author" VALUES (2,"Evelyn Smith",32,"Female");
+INSERT INTO  "author" VALUES (3,"Johnny Devenanzio",54,"Male");
+INSERT INTO  "author" VALUES (4,"Kenny Santucci",21,"Male");
+INSERT INTO  "author" VALUES (5,"Jenn Grijalva",19,"Female");
+INSERT INTO  "author" VALUES (6,"Paula Meronek",23,"Female");
+INSERT INTO  "author" VALUES (7,"Robin Hibbard",52,"Female");
+
+
+CREATE TABLE "press" (
+"Press_ID" int,
+"Name" text,
+"Month_Profits_billion" real,
+"Year_Profits_billion" real,
+PRIMARY KEY ("Press_ID")
+);
+
+
+INSERT INTO  "press" VALUES (1,"Accor","0.65","6.02");
+INSERT INTO  "press" VALUES (2,"Air Liquide","4.08","29.49");
+INSERT INTO  "press" VALUES (3,"Alstom","0.96","9.40");
+INSERT INTO  "press" VALUES (4,"ArcelorMittal","1.69","15.4");
+INSERT INTO  "press" VALUES (5,"STMicroelectronics","0.54","5.25");
+INSERT INTO  "press" VALUES (6,"Technip","1.18","9.24");
+INSERT INTO  "press" VALUES (7,"Total","11.96","86.94");
+INSERT INTO  "press" VALUES (8,"Unibail-Rodamco","2.31","16.80");
+INSERT INTO  "press" VALUES (9,"Vallourec","0.58","4.56");
+INSERT INTO  "press" VALUES (10,"Veolia Environnement","0.44","5.01");
+
+
+
+
+CREATE TABLE "book" (
+"Book_ID" int,
+"Title" text,
+"Book_Series" text,
+"Author_ID" int,
+"Press_ID" int,
+"Sale_Amount" text,
+"Release_date" text,
+PRIMARY KEY ("Book_ID"),
+FOREIGN KEY (`Author_ID`) REFERENCES `author`(`Author_ID`),
+FOREIGN KEY (`Press_ID`) REFERENCES `press`(`Press_ID`)
+);
+
+INSERT INTO  "book" VALUES (1,"Book Revue","LT",1,1,"1234","2016-01-05");
+INSERT INTO  "book" VALUES (2,"Baseball Bugs","LT",2,2,"1214","2016-02-02");
+INSERT INTO  "book" VALUES (3,"Holiday for Shoestrings","MM",3,3,"714","2016-02-23");
+INSERT INTO  "book" VALUES (4,"Quentin Quail","MM",4,4,"615","2016-03-02");
+INSERT INTO  "book" VALUES (5,"Baby Bottleneck","LT",5,5,"1256","2016-03-16");
+INSERT INTO  "book" VALUES (6,"Hare Remover","MM",5,4,"1014","2016-03-23");
+INSERT INTO  "book" VALUES (7,"Daffy Doodles","MM",1,9,"1307","2016-04-06");
+INSERT INTO  "book" VALUES (8,"Hollywood Canine Canteen","MM",1,2,"1114","2016-04-20");
+INSERT INTO  "book" VALUES (9,"Hush My Mouse","LT",2,3,"1258","2016-05-04");
+INSERT INTO  "book" VALUES (10,"Hair-Raising Hare","MM",5,2,"115","2016-05-25");
+

test_database/{candidate_poll/candidate_poll.sqlite → book_review/book_review.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7df58984f9d9796538716294ba0dda9f48a4a54907f03a3859285aa4b5cf8dc5
+oid sha256:ed22389124512c73025037cf2e5546e1225e78a6f5a9db052a3aa635b93fba31
 size 20480

test_database/book_review/schema.sql

@@ -0,0 +1,34 @@
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "book" (
+"Book_ID" int,
+"Title" text,
+"Type" text,
+"Pages" int,
+"Chapters" int,
+"Audio" text,
+"Release" text,
+PRIMARY KEY ("Book_ID")
+);
+
+CREATE TABLE "review" (
+"Review_ID" int,
+"Book_ID" int,
+"Rating" real,
+"Readers_in_Million" real,
+"Rank" int,
+PRIMARY KEY ("Review_ID"),
+FOREIGN KEY ("Book_ID") REFERENCES `book`("Book_ID")
+);
+
+INSERT INTO  "book" VALUES (1,"A Game of Thrones","Novel","704","73","33h 53m","August 1996");
+INSERT INTO  "book" VALUES (2,"A Clash of Kings","Novel","768","70","37h 17m","February 1999");
+INSERT INTO  "book" VALUES (3,"A Storm of Swords","Novel","992","82","47h 37m","November 2000");
+INSERT INTO  "book" VALUES (4,"A Feast for Crows","Novel","753","46","31h 10m","November 2005");
+INSERT INTO  "book" VALUES (5,"A Dance with Dragons","Poet","1056","73","48h 56m","July 2011");
+
+INSERT INTO  "review" VALUES (1,1,"6.6","3.3","16");
+INSERT INTO  "review" VALUES (2,3,"5.7","2.8","25");
+INSERT INTO  "review" VALUES (3,4,"5.8","2.6","26");
+INSERT INTO  "review" VALUES (4,5,"5.6","2.4","35");
+

test_database/book_review/schema_old.sql

@@ -0,0 +1,34 @@
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "book" (
+"Book_ID" int,
+"Title" text,
+"Type" text,
+"Pages" int,
+"Chapters" int,
+"Audio" text,
+"Release" text,
+PRIMARY KEY ("Book_ID")
+);
+
+CREATE TABLE "review" (
+"Review_ID" int,
+"Book_ID" int,
+"Rating" real,
+"Readers_in_Million" real,
+"Rank" int,
+PRIMARY KEY ("Review_ID"),
+FOREIGN KEY ("Book_ID") REFERENCES "book"("Book_ID")
+);
+
+INSERT INTO  "book" VALUES (1,"A Game of Thrones","Novel","704","73","33h 53m","August 1996");
+INSERT INTO  "book" VALUES (2,"A Clash of Kings","Novel","768","70","37h 17m","February 1999");
+INSERT INTO  "book" VALUES (3,"A Storm of Swords","Novel","992","82","47h 37m","November 2000");
+INSERT INTO  "book" VALUES (4,"A Feast for Crows","Novel","753","46","31h 10m","November 2005");
+INSERT INTO  "book" VALUES (5,"A Dance with Dragons","Poet","1056","73","48h 56m","July 2011");
+
+INSERT INTO  "review" VALUES (1,1,"6.6","3.3","16");
+INSERT INTO  "review" VALUES (2,3,"5.7","2.8","25");
+INSERT INTO  "review" VALUES (3,4,"5.8","2.6","26");
+INSERT INTO  "review" VALUES (4,5,"5.6","2.4","35");
+

test_database/browser_web/schema.sql

@@ -1,58 +0,0 @@
-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;
-

test_database/candidate_poll/schema.sql

@@ -1,42 +0,0 @@
-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");
-

test_database/car_1/annotation.json

@@ -1,62 +0,0 @@
-{
-    "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
-}

test_database/car_1/car_1.sql

@@ -1,52 +0,0 @@
-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)
-);
-
-

test_database/car_1/data_csv/README.CARS.TXT

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

test_database/car_1/data_csv/car-names.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4db9751bbee98a3943c8242dc08cb0ba7b4043e039de72ad2f24578863337bdd
-size 13468

test_database/car_1/data_csv/cars-data.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:95937d7f6535282015dded5894e7e1fa63f6627a2d9ef2049cee8e9ee7ae644b
-size 13071

test_database/car_1/data_csv/cars.desc

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

test_database/car_1/q.txt

@@ -1,27 +0,0 @@
-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.

test_database/cinema/schema.sql

@@ -1,60 +0,0 @@
-
-PRAGMA foreign_keys = ON;
-
-
-CREATE TABLE "film" (
-"Film_ID" int,
-"Rank_in_series" int,
-"Number_in_season" int,
-"Title" text,
-"Directed_by" text,
-"Original_air_date" text,
-"Production_code" text,
-PRIMARY KEY ("Film_ID")
-);
-
-CREATE TABLE "cinema" (
-"Cinema_ID" int,
-"Name" text,
-"Openning_year" int,
-"Capacity" int,
-"Location" text,
-PRIMARY KEY ("Cinema_ID"));
-
-INSERT INTO  "film" VALUES (1,"26","1","The Case of the Mystery Weekend","Bill Schreiner","September 21–25, 1992","50021–50025");
-INSERT INTO  "film" VALUES (2,"27","2","The Case of the Smart Dummy","Bill Schreiner","September 28–October 2, 1992","50231–50235");
-INSERT INTO  "film" VALUES (3,"28","3","The Case: Off the Record","Bill Schreiner","October 5–9, 1992","50011–50015");
-INSERT INTO  "film" VALUES (4,"29","4","The Case of the Bermuda Triangle","Jesus Salvador Treviño","October 12–16, 1992","50251–50255");
-INSERT INTO  "film" VALUES (5,"30","5","The Case of the Piggy Banker","Bill Schreiner","October 19–23, 1992","50241–50245");
-
-INSERT INTO  "cinema" VALUES (1,"Codling","2010","1100","County Wicklow");
-INSERT INTO  "cinema" VALUES (2,"Carrowleagh","2012","368","County Cork");
-INSERT INTO  "cinema" VALUES (3,"Dublin Array","2015","364","County Dublin");
-INSERT INTO  "cinema" VALUES (4,"Glenmore","2009","305","County Clare");
-INSERT INTO  "cinema" VALUES (5,"Glenough","2010","325","County Tipperary");
-INSERT INTO  "cinema" VALUES (6,"Gortahile","2010","208","County Laois");
-INSERT INTO  "cinema" VALUES (7,"Grouse Lodge","2011","203","County Tipperary");
-INSERT INTO  "cinema" VALUES (8,"Moneypoint","2011","225","County Clare");
-INSERT INTO  "cinema" VALUES (9,"Mount Callan","2011","908","County Clare");
-INSERT INTO  "cinema" VALUES (10,"Oriel","2013","330","County Louth");
-
-CREATE TABLE "schedule" (
-"Cinema_ID" int,
-"Film_ID" int,
-"Date" text,
-"Show_times_per_day" int,
-"Price" float,
-PRIMARY KEY ("Cinema_ID","Film_ID"),
-FOREIGN KEY (`Film_ID`) REFERENCES `film`(`Film_ID`),
-FOREIGN KEY (`Cinema_ID`) REFERENCES `cinema`(`Cinema_ID`)
-);
-
-
-INSERT INTO  "schedule" VALUES (1,1,"21 May",5,12.99);
-INSERT INTO  "schedule" VALUES (1,2,"21 May",3,12.99);
-INSERT INTO  "schedule" VALUES (1,3,"21 Jun",2,8.99);
-INSERT INTO  "schedule" VALUES (2,1,"11 July",5,9.99);
-INSERT INTO  "schedule" VALUES (6,5,"2 Aug",4,12.99);
-INSERT INTO  "schedule" VALUES (9,4,"20 May",5,9.99);
-INSERT INTO  "schedule" VALUES (10,1,"19 May",5,15.99);
-

test_database/{browser_web/browser_web.sqlite → club_leader/club_leader.sqlite}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ced1ee75f531e02adf66f387ced5997f416653adbcf519c037813aa69599f17a
+oid sha256:a863548152196d5ab4291c7393bc2fa814f020b0bbd7057a25e9ddaa7ab5e9cb
 size 28672

test_database/club_leader/schema.sql

@@ -0,0 +1,61 @@
+
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "member" (
+"Member_ID" int,
+"Name" text,
+"Nationality" text,
+"Age" int,
+PRIMARY KEY ("Member_ID")
+);
+
+CREATE TABLE "club" (
+"Club_ID" int,
+"Overall_Ranking" int,
+"Team_Leader" text,
+"Club_Name" text,
+PRIMARY KEY ("Club_ID")
+);
+
+INSERT INTO  "member" VALUES ("1984","Wally Lewis","Australia",23);
+INSERT INTO  "member" VALUES ("1985","Brett Kenny","Australia",19);
+INSERT INTO  "member" VALUES ("1986","Garry Jack","Australia",18);
+INSERT INTO  "member" VALUES ("1987","Hugh McGahan Peter Sterling","New Zealand Australia",24);
+INSERT INTO  "member" VALUES ("1988","Ellery Hanley","England",19);
+INSERT INTO  "member" VALUES ("1989","Mal Meninga","Australia",22);
+INSERT INTO  "member" VALUES ("1990","Garry Schofield","England",21);
+INSERT INTO  "member" VALUES ("1991","No award given","No award given",20);
+INSERT INTO  "member" VALUES ("1999","Andrew Johns","Australia",19);
+INSERT INTO  "member" VALUES ("2000","Brad Fittler","Australia",17);
+
+
+INSERT INTO  "club" VALUES ("1","5","Mack Mitchell","Houston");
+INSERT INTO  "club" VALUES ("3","57","Oscar Roan","SMU");
+INSERT INTO  "club" VALUES ("4","82","Tony Peters","Oklahoma");
+INSERT INTO  "club" VALUES ("5","109","John Zimba","Villanova");
+INSERT INTO  "club" VALUES ("2","119","Jim Cope","Ohio State");
+INSERT INTO  "club" VALUES ("6","150","Charles Miller","West Virginia");
+INSERT INTO  "club" VALUES ("16","154","Henry Hynoski","Temple");
+INSERT INTO  "club" VALUES ("7","161","Merle Wang","TCU");
+INSERT INTO  "club" VALUES ("8","186","Barry Santini","Purdue");
+INSERT INTO  "club" VALUES ("9","213","Larry Poole","Kent State");
+INSERT INTO  "club" VALUES ("19","215","Floyd Hogan","Arkansas");
+INSERT INTO  "club" VALUES ("10","238","Stan Lewis","Wayne");
+
+
+CREATE TABLE "club_leader" (
+"Club_ID" int,
+"Member_ID" int,
+"Year_Join" text,
+PRIMARY KEY ("Club_ID","Member_ID"),
+FOREIGN KEY ("Club_ID") REFERENCES `club`("Club_ID"),
+FOREIGN KEY ("Member_ID") REFERENCES `member`("Member_ID")
+);
+
+INSERT INTO  "club_leader" VALUES (1,1988,"2018");
+INSERT INTO  "club_leader" VALUES (8,1984,"2017");
+INSERT INTO  "club_leader" VALUES (6,1985,"2015");
+INSERT INTO  "club_leader" VALUES (4,1990,"2018");
+INSERT INTO  "club_leader" VALUES (10,1991,"2017");
+INSERT INTO  "club_leader" VALUES (6,1999,"2018");
+

test_database/club_leader/schema_old.sql

@@ -0,0 +1,61 @@
+
+PRAGMA foreign_keys = ON;
+
+CREATE TABLE "member" (
+"Member_ID" int,
+"Name" text,
+"Nationality" text,
+"Age" int,
+PRIMARY KEY ("Member_ID")
+);
+
+CREATE TABLE "club" (
+"Club_ID" int,
+"Overall_Ranking" int,
+"Team_Leader" text,
+"Club_Name" text,
+PRIMARY KEY ("Club_ID")
+);
+
+INSERT INTO  "member" VALUES ("1984","Wally Lewis","Australia",23);
+INSERT INTO  "member" VALUES ("1985","Brett Kenny","Australia",19);
+INSERT INTO  "member" VALUES ("1986","Garry Jack","Australia",18);
+INSERT INTO  "member" VALUES ("1987","Hugh McGahan Peter Sterling","New Zealand Australia",24);
+INSERT INTO  "member" VALUES ("1988","Ellery Hanley","England",19);
+INSERT INTO  "member" VALUES ("1989","Mal Meninga","Australia",22);
+INSERT INTO  "member" VALUES ("1990","Garry Schofield","England",21);
+INSERT INTO  "member" VALUES ("1991","No award given","No award given",20);
+INSERT INTO  "member" VALUES ("1999","Andrew Johns","Australia",19);
+INSERT INTO  "member" VALUES ("2000","Brad Fittler","Australia",17);
+
+
+INSERT INTO  "club" VALUES ("1","5","Mack Mitchell","Houston");
+INSERT INTO  "club" VALUES ("3","57","Oscar Roan","SMU");
+INSERT INTO  "club" VALUES ("4","82","Tony Peters","Oklahoma");
+INSERT INTO  "club" VALUES ("5","109","John Zimba","Villanova");
+INSERT INTO  "club" VALUES ("2","119","Jim Cope","Ohio State");
+INSERT INTO  "club" VALUES ("6","150","Charles Miller","West Virginia");
+INSERT INTO  "club" VALUES ("16","154","Henry Hynoski","Temple");
+INSERT INTO  "club" VALUES ("7","161","Merle Wang","TCU");
+INSERT INTO  "club" VALUES ("8","186","Barry Santini","Purdue");
+INSERT INTO  "club" VALUES ("9","213","Larry Poole","Kent State");
+INSERT INTO  "club" VALUES ("19","215","Floyd Hogan","Arkansas");
+INSERT INTO  "club" VALUES ("10","238","Stan Lewis","Wayne");
+
+
+CREATE TABLE "club_leader" (
+"Club_ID" int,
+"Member_ID" int,
+"Year_Join" text,
+PRIMARY KEY ("Club_ID","Member_ID"),
+FOREIGN KEY ("Club_ID") REFERENCES "club"("Club_ID"),
+FOREIGN KEY ("Member_ID") REFERENCES "member"("Member_ID")
+);
+
+INSERT INTO  "club_leader" VALUES (1,1988,"2018");
+INSERT INTO  "club_leader" VALUES (8,1984,"2017");
+INSERT INTO  "club_leader" VALUES (6,1985,"2015");
+INSERT INTO  "club_leader" VALUES (4,1990,"2018");
+INSERT INTO  "club_leader" VALUES (10,1991,"2017");
+INSERT INTO  "club_leader" VALUES (6,1999,"2018");
+

test_database/college_2/college_2.sqlite

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cb729920ad0b7f06d38a12f6f678307964acc7d3417af83d98c519c65c90d386
-size 2117632