context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28 values |
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CREATE TABLE Vehicle (id INT, name TEXT, is_autonomous BOOLEAN, is_electric BOOLEAN, highway_traffic_speed FLOAT); INSERT INTO Vehicle (id, name, is_autonomous, is_electric, highway_traffic_speed) VALUES (1, 'Model S', true, true, 120.3), (2, 'Camry', false, false, 112.5), (3, 'Bolt', true, true, 95.8), (4, 'Tesla', true, false, 130.0); | What are the names of the vehicles that are both autonomous and electric, and their highway traffic speed? | SELECT Vehicle.name, Vehicle.highway_traffic_speed FROM Vehicle WHERE is_autonomous = true AND is_electric = true; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA rural; CREATE TABLE rural.hospitals (id INT, hospital_name TEXT); | List all unique hospital names from the 'rural' schema. | SELECT DISTINCT hospital_name FROM rural.hospitals; | gretelai_synthetic_text_to_sql |
CREATE TABLE Events (ID INT, City VARCHAR(50), EventType VARCHAR(50), AttendeeCount INT); | Update the record for a concert in Los Angeles to have 50 attendees. | UPDATE Events SET AttendeeCount = 50 WHERE City = 'Los Angeles' AND EventType = 'Concert'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Policyholder (PolicyholderID INT, Name TEXT, DOB DATE); INSERT INTO Policyholder (PolicyholderID, Name, DOB) VALUES (1, 'john doe', '1980-05-05'), (2, 'jane smith', '1990-01-01'), (3, 'mike johnson', '1975-09-09'), (4, 'sara rodriguez', '1985-04-04'); | Update policyholder names to uppercase. | UPDATE Policyholder SET Name = UPPER(Name); | gretelai_synthetic_text_to_sql |
CREATE TABLE incidents (incident_id INT, incident_type VARCHAR(255), incident_date DATE); | What is the total number of traffic-related incidents and thefts? | SELECT 'Traffic incidents' AS incident_type, COUNT(*) AS count FROM incidents WHERE incident_type = 'Traffic incident' UNION ALL SELECT 'Thefts' AS incident_type, COUNT(*) AS count FROM incidents WHERE incident_type = 'Theft'; | gretelai_synthetic_text_to_sql |
CREATE TABLE restorative_justice_sentences (sentence_id INT, program_id INT, sentence_length INT, state VARCHAR(2)); INSERT INTO restorative_justice_sentences (sentence_id, program_id, sentence_length, state) VALUES (1, 1001, 18, 'CA'), (2, 1002, 24, 'CA'); | What is the maximum sentence length for offenders who participated in restorative justice programs in California? | SELECT MAX(sentence_length) FROM restorative_justice_sentences WHERE state = 'CA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Usage (id INT, ingredient VARCHAR(20), quantity INT, usage_date DATE); INSERT INTO Usage (id, ingredient, quantity, usage_date) VALUES (1, 'Cocoa', 10, '2022-01-01'), (2, 'Sugar', 15, '2022-01-02'); | What is the minimum quantity of a fair-trade ingredient used in a week? | SELECT ingredient, MIN(quantity) FROM Usage WHERE usage_date >= DATE_SUB(CURRENT_DATE, INTERVAL 7 DAY) AND ingredient IN ('Cocoa', 'Sugar', 'Coffee') GROUP BY ingredient; | gretelai_synthetic_text_to_sql |
CREATE TABLE Exploration (ExplorationID VARCHAR(10), Location VARCHAR(20), StartDate DATE, EndDate DATE); | Update 'Exploration' table and set 'EndDate' to '2022-12-31' for records where 'Location' is 'South China Sea' | UPDATE Exploration SET EndDate = '2022-12-31' WHERE Location = 'South China Sea'; | gretelai_synthetic_text_to_sql |
CREATE TABLE HabitatPreservation(Year INT, Habitat VARCHAR(20), Efforts INT); INSERT INTO HabitatPreservation VALUES (2017, 'Forest', 120), (2018, 'Forest', 150), (2019, 'Forest', 170), (2017, 'Wetland', 80), (2018, 'Wetland', 90), (2019, 'Wetland', 110); | Which habitats have seen the most preservation efforts in the last 5 years? | SELECT Habitat, SUM(Efforts) FROM HabitatPreservation WHERE Year >= 2017 GROUP BY Habitat ORDER BY SUM(Efforts) DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE military_innovation (id INT, region VARCHAR, project_count INT); | Which regions have the most military innovation projects? | SELECT region, SUM(project_count) AS total_projects FROM military_innovation GROUP BY region ORDER BY total_projects DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonationDate DATE, DonationAmount DECIMAL(10,2)); INSERT INTO Donations (DonationID, DonationDate, DonationAmount) VALUES (1, '2022-03-22', 100.00), (2, '2022-03-23', 200.00), (3, '2022-03-24', 150.00); | What is the average donation per day for the last 30 days? | SELECT AVG(DonationAmount) as AvgDonationPerDay FROM Donations WHERE DonationDate >= CURRENT_DATE - INTERVAL '30 days'; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name TEXT, age INT, donation FLOAT); INSERT INTO donors (id, name, age, donation) VALUES (1, 'John Doe', 35, 500.00); INSERT INTO donors (id, name, age, donation) VALUES (2, 'Jane Smith', 45, 750.00); | How many donors are there in the 'donors' table? | SELECT COUNT(*) FROM donors; | gretelai_synthetic_text_to_sql |
CREATE TABLE environmental_impact (site VARCHAR(255), score INT); INSERT INTO environmental_impact (site, score) VALUES ('Site A', 80), ('Site B', 70), ('Site C', 90); | Determine the environmental impact score for each mining site | SELECT ei.site, ei.score FROM environmental_impact ei; | gretelai_synthetic_text_to_sql |
CREATE TABLE ExplainableAI (model_name TEXT, confidence FLOAT, country TEXT); INSERT INTO ExplainableAI (model_name, confidence, country) VALUES ('ModelA', 0.85, 'USA'), ('ModelB', 0.92, 'USA'), ('ModelC', 0.78, 'USA'); | What is the average confidence score for explainable AI models in the US, grouped by state? | SELECT country, AVG(confidence) FROM ExplainableAI WHERE country = 'USA' GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE Military_Equipment_Sales (seller VARCHAR(255), equipment VARCHAR(255), year INT, quantity INT); INSERT INTO Military_Equipment_Sales (seller, equipment, year, quantity) VALUES ('Lockheed Martin', 'Tank', 2021, 150), ('Lockheed Martin', 'Humvee', 2021, 200); | What is the total number of military vehicles sold by 'Lockheed Martin' in '2021'? | SELECT SUM(quantity) FROM Military_Equipment_Sales WHERE seller = 'Lockheed Martin' AND year = 2021 AND equipment = 'Tank' OR equipment = 'Humvee'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Contracts (Month VARCHAR(7), Count INT); INSERT INTO Contracts (Month, Count) VALUES ('Jan-2021', 150), ('Feb-2021', 175), ('Mar-2021', 200), ('Apr-2021', 225), ('May-2021', 250), ('Jun-2021', 275), ('Jul-2021', 300), ('Aug-2021', 325), ('Sep-2021', 350), ('Oct-2021', 375), ('Nov-2021', 400), ('Dec-2021', 425); | What is the total number of defense contracts awarded per month? | SELECT STR_TO_DATE(Month, '%b-%Y') AS Month, SUM(Count) FROM Contracts GROUP BY Month; | gretelai_synthetic_text_to_sql |
CREATE TABLE MuseumStores (id INT, location VARCHAR(50), date DATE, revenue DECIMAL(5,2)); INSERT INTO MuseumStores (id, location, date, revenue) VALUES (1, 'Paris', '2022-01-01', 100.00), (2, 'Rome', '2022-01-02', 200.00), (3, 'Paris', '2022-04-03', 300.00); | What is the total revenue generated by museum stores in Paris and Rome in the last quarter? | SELECT location, SUM(revenue) FROM MuseumStores WHERE date >= DATEADD(quarter, -1, GETDATE()) AND location IN ('Paris', 'Rome') GROUP BY location; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotels (hotel_id INT, hotel_name VARCHAR(50), rating DECIMAL(2,1), PRIMARY KEY (hotel_id)); | Update the "rating" field in the "hotels" table for all records with a "hotel_name" of 'Grand Hotel' to be 4.8 | UPDATE hotels SET rating = 4.8 WHERE hotel_name = 'Grand Hotel'; | gretelai_synthetic_text_to_sql |
CREATE TABLE factories (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), co2_emission_per_year INT); | What is the average CO2 emission per garment for factories located in the 'Greater London' region? | SELECT AVG(co2_emission_per_year / quantity_manufactured) as avg_co2_emission_per_garment FROM factories WHERE location LIKE 'Greater London%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE policyholders (id INT, name TEXT, city TEXT, state TEXT, claim_amount FLOAT, coverage TEXT); INSERT INTO policyholders (id, name, city, state, claim_amount, coverage) VALUES (1, 'John Doe', 'New York', 'NY', 1200.00, 'Comprehensive'); INSERT INTO policyholders (id, name, city, state, claim_amount, coverage) VALUES (2, 'Jane Doe', 'Albany', 'NY', 1500.00, 'Liability'); INSERT INTO policyholders (id, name, city, state, claim_amount, coverage) VALUES (3, 'Bob Smith', 'Buffalo', 'NY', 900.00, 'Comprehensive'); | Find the average claim amount for policyholders in 'New York' who have comprehensive coverage. | SELECT AVG(claim_amount) FROM policyholders WHERE state = 'NY' AND coverage = 'Comprehensive'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ambulances (ambulance_id INT, county TEXT, state TEXT); | How many ambulances are available in each rural county of South Dakota? | SELECT county, COUNT(ambulance_id) AS ambulance_count FROM ambulances WHERE state = 'South Dakota' GROUP BY county; | gretelai_synthetic_text_to_sql |
CREATE TABLE clients (client_id INT, client_name TEXT, region TEXT, financial_capability_score FLOAT); | What is the average financial capability score of clients in the Asia-Pacific region? | SELECT AVG(clients.financial_capability_score) FROM clients WHERE clients.region = 'Asia-Pacific'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (id INT, species VARCHAR(50), ocean VARCHAR(50), conservation_status VARCHAR(50)); | Insert a new marine species 'Sperm Whale' into the Pacific Ocean with a conservation status of 'Vulnerable'. | INSERT INTO marine_species (species, ocean, conservation_status) VALUES ('Sperm Whale', 'Pacific', 'Vulnerable'); | gretelai_synthetic_text_to_sql |
CREATE TABLE ProfessionalDevelopment (TeacherID int, Date date, ProfessionalDevelopmentScore int); | Update the 'ProfessionalDevelopmentScore' field for a professional development record in the 'ProfessionalDevelopment' table | UPDATE ProfessionalDevelopment SET ProfessionalDevelopmentScore = 95 WHERE TeacherID = 5678 AND Date = '2022-10-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (tx_id INT, sc_id INT, transaction_volume DECIMAL(10,2), transaction_date DATE); CREATE TABLE smart_contracts (sc_id INT, name VARCHAR(255)); | What is the rank of each smart contract by transaction volume, and how many smart contracts are in the top 10% by transaction volume? | SELECT sc_id, name, RANK() OVER (ORDER BY transaction_volume DESC) as transaction_volume_rank FROM transactions t JOIN smart_contracts s ON t.sc_id = s.sc_id; SELECT COUNT(*) FROM (SELECT sc_id, name, RANK() OVER (ORDER BY transaction_volume DESC) as transaction_volume_rank FROM transactions t JOIN smart_contracts s ON t.sc_id = s.sc_id) WHERE transaction_volume_rank <= PERCENTILE_CONT(0.1) WITHIN GROUP (ORDER BY transaction_volume); | gretelai_synthetic_text_to_sql |
CREATE TABLE fare_distribution (route_id INT, trips_taken INT, fare_collected DECIMAL(5,2)); INSERT INTO fare_distribution (route_id, trips_taken, fare_collected) VALUES (1, 500, 1200.00), (2, 600, 1950.00), (3, 450, 1125.00); | Calculate the average fare per trip and number of trips per route | SELECT route_id, AVG(fare_collected / trips_taken) as average_fare_per_trip, AVG(trips_taken) as average_trips_per_route FROM fare_distribution GROUP BY route_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE funding (funding_id INT, company_id INT, funding_amount FLOAT); | Insert data into funding records table | INSERT INTO funding (funding_id, company_id, funding_amount) VALUES (1, 1, 50000), (2, 2, 75000), (3, 3, 100000), (4, 4, 150000), (5, 5, 200000); | gretelai_synthetic_text_to_sql |
CREATE TABLE healthcare_providers (provider_id INT, name TEXT, state TEXT, score INT); INSERT INTO healthcare_providers (provider_id, name, state, score) VALUES (1, 'Dr. Smith', 'CA', 90), (2, 'Dr. Johnson', 'CA', 85), (3, 'Dr. Rodriguez', 'TX', 95), (4, 'Dr. Lee', 'NY', 80), (5, 'Dr. Patel', 'CA', 99), (6, 'Dr. Kim', 'NY', 75); | What is the minimum and maximum cultural competency score for healthcare providers in each state? | SELECT state, MIN(score) AS min_score, MAX(score) AS max_score FROM healthcare_providers GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (well_id INT, well_name TEXT, location TEXT, gas_production FLOAT); INSERT INTO wells (well_id, well_name, location, gas_production) VALUES (1, 'Well A', 'Argentina', 1200.5), (2, 'Well B', 'Argentina', 1500.3), (3, 'Well C', 'Brazil', 1700.2), (4, 'Well D', 'Venezuela', 800.8), (5, 'Well E', 'Colombia', 900.7); | Which country had the highest natural gas production in South America in 2019? | SELECT location, SUM(gas_production) as total_gas_production FROM wells GROUP BY location ORDER BY total_gas_production DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (country_id INT, country_name VARCHAR(100));CREATE TABLE space_missions (mission_id INT, country_id INT, mission_name VARCHAR(100)); | What are the top 5 countries with the most space missions? | SELECT countries.country_name, COUNT(space_missions.mission_id) AS missions_count FROM countries INNER JOIN space_missions ON countries.country_id = space_missions.country_id GROUP BY countries.country_name ORDER BY missions_count DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE Attendance (ID INT, ParticipantName TEXT, Program TEXT, Age INT, Attended BOOLEAN); INSERT INTO Attendance (ID, ParticipantName, Program, Age, Attended) VALUES (1, 'Jane Doe', 'Art Class', 25, TRUE), (2, 'John Smith', 'Music Class', 30, FALSE), (3, 'Alice Johnson', 'Theater Class', 35, TRUE); | What is the attendance rate for each program by age group? | SELECT Program, Age, AVG(CASE WHEN Attended = TRUE THEN 1.0 ELSE 0.0 END) as AttendanceRate FROM Attendance GROUP BY Program, Age; | gretelai_synthetic_text_to_sql |
CREATE TABLE fairness_scores (model_name TEXT, sector TEXT, fairness_score FLOAT); INSERT INTO fairness_scores (model_name, sector, fairness_score) VALUES ('ModelA', 'Finance', 0.82), ('ModelB', 'Finance', 0.88), ('ModelC', 'Education', 0.93); | What is the minimum fairness score for models in the 'Finance' sector? | SELECT MIN(fairness_score) FROM fairness_scores WHERE sector = 'Finance'; | gretelai_synthetic_text_to_sql |
CREATE TABLE user_ratings (user_id INT, movie_title VARCHAR(50), rating INT, rating_date DATE); CREATE TABLE show_views (user_id INT, show_name VARCHAR(50), views_date DATE); | Show the number of users who have rated movies and watched shows in each quarter of 2020. | SELECT DATE_FORMAT(rating_date, '%Y-%m') AS quarter, COUNT(DISTINCT user_id) FROM user_ratings WHERE YEAR(rating_date) = 2020 AND MONTH(rating_date) IN (1, 2, 3) GROUP BY quarter UNION SELECT DATE_FORMAT(views_date, '%Y-%m') AS quarter, COUNT(DISTINCT user_id) FROM show_views WHERE YEAR(views_date) = 2020 AND MONTH(views_date) IN (1, 2, 3) GROUP BY quarter ORDER BY quarter; | gretelai_synthetic_text_to_sql |
CREATE TABLE MLB_Matches (MatchID INT, HomeTeam VARCHAR(50), AwayTeam VARCHAR(50), HomeTeamScore INT, AwayTeamScore INT); INSERT INTO MLB_Matches (MatchID, HomeTeam, AwayTeam, HomeTeamScore, AwayTeamScore) VALUES (1, 'New York Yankees', 'Boston Red Sox', 7, 7); | How many matches in the MLB have had a result of a 7-7 draw? | SELECT COUNT(*) FROM MLB_Matches WHERE HomeTeamScore = 7 AND AwayTeamScore = 7; | gretelai_synthetic_text_to_sql |
CREATE TABLE supplier_trends (supplier VARCHAR(25), element VARCHAR(2), quantity INT, quarter INT, year INT); INSERT INTO supplier_trends VALUES ('SupplierA', 'Eu', 500, 1, 2022), ('SupplierB', 'Eu', 300, 1, 2022), ('SupplierC', 'Eu', 700, 1, 2022); | What was the total quantity of Eu supplied by each supplier in Q1 2022, ordered by supplier name? | SELECT supplier, SUM(quantity) as total_quantity FROM supplier_trends WHERE element = 'Eu' AND quarter = 1 AND year = 2022 GROUP BY supplier ORDER BY supplier; | gretelai_synthetic_text_to_sql |
CREATE TABLE Service_Responses (City VARCHAR(20), Service VARCHAR(20), Response_Time INT); INSERT INTO Service_Responses (City, Service, Response_Time) VALUES ('CityC', 'Public Safety', 6); INSERT INTO Service_Responses (City, Service, Response_Time) VALUES ('CityC', 'Health Services', 8); | What is the average response time for public safety and health services in CityC? | SELECT City, AVG(CASE WHEN Service = 'Public Safety' THEN Response_Time ELSE 0 END) AS 'Public Safety Avg Response Time', AVG(CASE WHEN Service = 'Health Services' THEN Response_Time ELSE 0 END) AS 'Health Services Avg Response Time' FROM Service_Responses WHERE City = 'CityC' GROUP BY City; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, segment VARCHAR(20), price DECIMAL(5,2)); INSERT INTO products (product_id, segment, price) VALUES (1, 'Natural', 15.99), (2, 'Organic', 20.99), (3, 'Natural', 12.49); | What is the difference in price between the most expensive and least expensive products in the Natural segment? | SELECT t1.segment, t1.price - t2.price AS price_difference FROM (SELECT segment, MAX(price) AS price FROM products GROUP BY segment) t1 INNER JOIN (SELECT segment, MIN(price) AS price FROM products GROUP BY segment) t2 ON t1.segment = t2.segment; | gretelai_synthetic_text_to_sql |
CREATE TABLE veteran_employment (id INT, company VARCHAR(50), state VARCHAR(50), employment_date DATE, num_veterans INT); INSERT INTO veteran_employment (id, company, state, employment_date, num_veterans) VALUES (1, 'ABC', 'California', '2022-01-01', 100); INSERT INTO veteran_employment (id, company, state, employment_date, num_veterans) VALUES (2, 'XYZ', 'California', '2022-01-05', 150); | What is the average number of veterans employed by each company in California in Q1 2022? | SELECT AVG(num_veterans) FROM veteran_employment WHERE state = 'California' AND employment_date BETWEEN '2022-01-01' AND '2022-03-31' GROUP BY company; | gretelai_synthetic_text_to_sql |
CREATE TABLE peacekeeping_operations (id INT PRIMARY KEY, operation VARCHAR(255), year INT, region VARCHAR(255)); | How many peacekeeping operations were conducted between 2010 and 2020? | SELECT COUNT(*) as total_operations FROM peacekeeping_operations WHERE year BETWEEN 2010 AND 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE employees (id INT, name VARCHAR(50), department VARCHAR(50), salary FLOAT, employment_status VARCHAR(50)); INSERT INTO employees (id, name, department, salary, employment_status) VALUES (1, 'John Doe', 'IT', 75000.0, 'Full-time'), (2, 'Jane Smith', 'IT', 80000.0, 'Part-time'), (3, 'Alice Johnson', 'IT', 90000.0, 'Full-time'), (4, 'Bob Brown', 'HR', 70000.0, 'Full-time'), (5, 'Charlie Green', 'Finance', 85000.0, 'Full-time'); CREATE TABLE departments (id INT, name VARCHAR(50), manager VARCHAR(50)); INSERT INTO departments (id, name, manager) VALUES (1, 'IT', 'Alex Brown'), (2, 'HR', 'Alex Brown'), (3, 'Finance', ''); | What is the total number of employees in each department, including those without an assigned manager? | SELECT departments.name, COUNT(employees.id) FROM departments LEFT JOIN employees ON departments.name = employees.department GROUP BY departments.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE mobile_revenue(quarter INT, revenue FLOAT); INSERT INTO mobile_revenue(quarter, revenue) VALUES (1, 1500000), (2, 1800000), (3, 2250000), (4, 2500000); CREATE TABLE broadband_revenue(quarter INT, revenue FLOAT); INSERT INTO broadband_revenue(quarter, revenue) VALUES (1, 2000000), (2, 2750000), (3, 3250000), (4, 3500000); | What is the total revenue generated from mobile and broadband services in the first quarter of 2021? | SELECT SUM(revenue) FROM (SELECT revenue FROM mobile_revenue WHERE quarter = 1 UNION SELECT revenue FROM broadband_revenue WHERE quarter = 1); | gretelai_synthetic_text_to_sql |
CREATE TABLE visitors (id INT, visitor TEXT, event TEXT, category TEXT); INSERT INTO visitors (id, visitor, event, category) VALUES (1, 'John Doe', 'Art Exhibit', 'art'), (2, 'Jane Smith', 'Theatre Play', 'theatre'), (3, 'Michael Lee', 'Concert', 'music'); | What is the total number of visitors for each cultural event category, sorted by the number of visitors in descending order? | SELECT category, COUNT(DISTINCT visitor) as num_visitors FROM visitors GROUP BY category ORDER BY num_visitors DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE if not exists countries (id INT PRIMARY KEY, name VARCHAR(50), continent VARCHAR(50)); INSERT INTO countries (id, name, continent) VALUES (1, 'Argentina', 'South America'); INSERT INTO countries (id, name, continent) VALUES (2, 'Brazil', 'South America'); CREATE TABLE if not exists projects (id INT PRIMARY KEY, name VARCHAR(50), country_id INT, budget DECIMAL(10,2)); INSERT INTO projects (id, name, country_id, budget) VALUES (1, 'Disaster Response', 1, 50000.00); INSERT INTO projects (id, name, country_id, budget) VALUES (2, 'Community Development', 1, 70000.00); INSERT INTO projects (id, name, country_id, budget) VALUES (3, 'Refugee Support', 2, 60000.00); | What is the name of the projects and their budget in South America? | SELECT p.name, p.budget FROM projects p JOIN countries c ON p.country_id = c.id WHERE c.continent = 'South America'; | gretelai_synthetic_text_to_sql |
CREATE TABLE humanitarian_assistance (id INT PRIMARY KEY, organization VARCHAR(100), personnel INT); INSERT INTO humanitarian_assistance (id, organization, personnel) VALUES (1, 'Org 1', 1200), (2, 'Org 2', 1500), (3, 'Org 3', 1000); | What is the maximum number of humanitarian assistance personnel deployed by a single organization? | SELECT MAX(personnel) FROM humanitarian_assistance; | gretelai_synthetic_text_to_sql |
CREATE TABLE menus (menu_id INT, menu_name VARCHAR(50), type VARCHAR(20), price DECIMAL(5,2)); INSERT INTO menus (menu_id, menu_name, type, price) VALUES (1, 'Quinoa Salad', 'vegetarian', 9.99), (2, 'Margherita Pizza', 'non-vegetarian', 12.99), (3, 'Chickpea Curry', 'vegetarian', 10.99), (4, 'Beef Burger', 'non-vegetarian', 13.49), (5, 'Vegan Burger', 'vegan', 11.99), (6, 'Vegan Ice Cream', 'vegan', 5.99), (7, 'French Fries', 'vegetarian', 3.99), (8, 'Soda', 'non-vegetarian', 2.49), (9, 'Tofu Stir Fry', 'vegan', 12.99); | How many vegan menu items are there in total? | SELECT COUNT(*) FROM menus WHERE type = 'vegan'; | gretelai_synthetic_text_to_sql |
CREATE TABLE manufacturing (item_code VARCHAR(20), item_name VARCHAR(50), category VARCHAR(20), country VARCHAR(50), quantity INT, is_eco_friendly BOOLEAN); | What is the total quantity of eco-friendly clothing items manufactured in Italy in Q1 2021? | SELECT SUM(quantity) as total_quantity FROM manufacturing WHERE category = 'clothing' AND country = 'Italy' AND is_eco_friendly = TRUE AND manufacturing_date BETWEEN '2021-01-01' AND '2021-03-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE songs (id INT, title VARCHAR(100), release_year INT, genre VARCHAR(50), streams INT); INSERT INTO songs (id, title, release_year, genre, streams) VALUES (1, 'Shape of You', 2017, 'Pop', 2000000000); INSERT INTO songs (id, title, release_year, genre, streams) VALUES (2, 'Sicko Mode', 2018, 'Hip Hop', 1500000000); INSERT INTO songs (id, title, release_year, genre, streams) VALUES (3, 'Black Panther', 2018, 'Soundtrack', 1200000000); CREATE TABLE artists (id INT, name VARCHAR(100), age INT); | What is the maximum number of streams for a song released in 2018? | SELECT MAX(streams) FROM songs WHERE release_year = 2018; | gretelai_synthetic_text_to_sql |
CREATE TABLE travel_advisories (travel_advisory_id INT, destination VARCHAR(50), travel_advisory_level INT, updated_date DATE, PRIMARY KEY (travel_advisory_id)); | Update all records in the "travel_advisories" table with a "travel_advisory_level" of '3' to have an 'updated_date' of '2023-01-01' | UPDATE travel_advisories SET updated_date = '2023-01-01' WHERE travel_advisory_level = 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE art_collections (id INT, collection_name VARCHAR(255), city VARCHAR(255), value DECIMAL(10,2)); INSERT INTO art_collections (id, collection_name, city, value) VALUES (1, 'The Met Collection', 'New York', 50000000.00), (2, 'The Guggenheim Collection', 'New York', 20000000.00), (3, 'The MoMA Collection', 'New York', 30000000.00); | Calculate the total value of art collections in New York, NY. | SELECT SUM(value) FROM art_collections WHERE city = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Policy (PolicyID INT, PolicyType VARCHAR(50)); INSERT INTO Policy VALUES (1, 'Auto'), (2, 'Home'), (3, 'Life'); CREATE TABLE Claims (ClaimID INT, PolicyID INT, ClaimAmount DECIMAL(10,2)); INSERT INTO Claims VALUES (1, 1, 500.00), (2, 1, 200.00), (3, 2, 750.00), (4, 3, 15000.00), (5, 1, 300.00) | What is the average claim amount for policy type 'Auto'? | SELECT AVG(ClaimAmount) as AvgClaimAmount FROM Policy p INNER JOIN Claims c ON p.PolicyID = c.PolicyID WHERE p.PolicyType = 'Auto'; | gretelai_synthetic_text_to_sql |
CREATE TABLE warehouse_k(item_id INT, item_type VARCHAR(10), quantity INT);CREATE TABLE warehouse_l(item_id INT, item_type VARCHAR(10), quantity INT);INSERT INTO warehouse_k(item_id, item_type, quantity) VALUES (1, 'C', 200), (2, 'C', 300), (3, 'C', 50);INSERT INTO warehouse_l(item_id, item_type, quantity) VALUES (1, 'C', 150), (2, 'C', 250), (3, 'C', 40); | What is the total quantity of items with type 'C' in warehouse K and warehouse L? | SELECT quantity FROM warehouse_k WHERE item_type = 'C' UNION ALL SELECT quantity FROM warehouse_l WHERE item_type = 'C'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Agency (id INT PRIMARY KEY, name VARCHAR(100), state_id INT, area DECIMAL(10,2)); INSERT INTO Agency (id, name, state_id, area) VALUES (1, 'California Public Utilities Commission', 1, 50000); | What are the names and states of agencies with an area larger than the average state area, and whose names contain the word 'Commission'? | SELECT a.name, s.name AS state_name FROM Agency a INNER JOIN State s ON a.state_id = s.id WHERE s.area < (SELECT AVG(area) FROM State) AND a.name LIKE '%Commission%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT, region VARCHAR(20), contributions DECIMAL(10,2)); INSERT INTO donors (donor_id, region, contributions) VALUES (1, 'Asia', 50000.00), (2, 'Europe', 100000.00), (3, 'North America', 200000.00), (4, 'Asia', 75000.00), (5, 'Asia', 100000.00); | Who are the top 5 donors contributing to technology for social good projects in Asia? | SELECT donor_id, contributions FROM donors WHERE region = 'Asia' ORDER BY contributions DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE players (id INT, age INT, genre VARCHAR(20)); INSERT INTO players (id, age, genre) VALUES (1, 40, 'RPG'), (2, 35, 'RPG'), (3, 25, 'FPS'), (4, 50, 'RPG'); | Who are the top 3 oldest players in the 'RPG' genre? | SELECT * FROM (SELECT id, age, ROW_NUMBER() OVER (ORDER BY age DESC) AS rn FROM players WHERE genre = 'RPG') sub WHERE rn <= 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName TEXT, DonationAmount DECIMAL(10,2)); INSERT INTO Donors (DonorID, DonorName, DonationAmount) VALUES (1, 'John Doe', 500.00), (2, 'Jane Smith', 350.00); | What is the total amount donated by each donor in Q1 2021? | SELECT DonorName, SUM(DonationAmount) as TotalDonation FROM Donors WHERE DonationDate BETWEEN '2021-01-01' AND '2021-03-31' GROUP BY DonorName; | gretelai_synthetic_text_to_sql |
CREATE TABLE ports (port_id INT, port_name VARCHAR(20)); INSERT INTO ports (port_id, port_name) VALUES (1, 'LA'), (2, 'LB'), (3, 'HOU'); CREATE TABLE cargo (cargo_id INT, port_id INT, tonnage INT); INSERT INTO cargo (cargo_id, port_id, tonnage) VALUES (1, 1, 500000), (2, 1, 300000), (3, 2, 800000), (4, 3, 600000); | What is the total tonnage of cargo unloaded at port 'LB'? | SELECT SUM(tonnage) FROM cargo WHERE port_id = (SELECT port_id FROM ports WHERE port_name = 'LB'); | gretelai_synthetic_text_to_sql |
CREATE TABLE matches (match_id INT, home_team INT, away_team INT, home_team_score INT, away_team_score INT); CREATE TABLE teams (team_id INT, name VARCHAR(50), city VARCHAR(50)); | Show the total number of goals scored by each team in the 'matches' and 'teams' tables. | SELECT t.name, SUM(m.home_team_score + m.away_team_score) AS total_goals FROM teams t JOIN matches m ON t.team_id IN (m.home_team, m.away_team) GROUP BY t.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE company_data (company_id INT, company_name VARCHAR(50), company_region VARCHAR(20)); CREATE TABLE transactions (transaction_id INT, company_id INT, transaction_value FLOAT, transaction_date DATE); INSERT INTO company_data (company_id, company_name, company_region) VALUES (1, 'Ethical AI Co.', 'Asia-Pacific'); INSERT INTO transactions (transaction_id, company_id, transaction_value, transaction_date) VALUES (1, 1, 50.00, '2021-04-01'); | What is the daily transaction growth rate for ethical AI companies in the Asia-Pacific region, for Q2 2021? | SELECT ROW_NUMBER() OVER (ORDER BY transaction_date) as day, (LAG(SUM(transaction_value)) OVER (ORDER BY transaction_date) - SUM(transaction_value)) / ABS(LAG(SUM(transaction_value)) OVER (ORDER BY transaction_date)) as growth_rate FROM transactions INNER JOIN company_data ON transactions.company_id = company_data.company_id WHERE EXTRACT(MONTH FROM transaction_date) BETWEEN 4 AND 6 AND company_region = 'Asia-Pacific' AND company_name LIKE '%Ethical AI%' GROUP BY transaction_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE ImmigrationCases (CaseID INT, CaseType VARCHAR(20), AttorneyLastName VARCHAR(20), BillingAmount DECIMAL(10,2)); INSERT INTO ImmigrationCases (CaseID, CaseType, AttorneyLastName, BillingAmount) VALUES (1, 'Immigration', 'Garcia', 5000.00), (2, 'Immigration', 'Rodriguez', 3000.00), (3, 'Immigration', 'Garcia', 2000.00); | List all unique attorney last names who have billed for cases in the 'Immigration' case type, in descending order based on the number of cases they handled. | SELECT DISTINCT AttorneyLastName, COUNT(*) AS CaseCount FROM ImmigrationCases WHERE CaseType = 'Immigration' GROUP BY AttorneyLastName ORDER BY CaseCount DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers (subscriber_id INT, subscription_type VARCHAR(10), data_usage FLOAT, data_limit FLOAT, usage_date DATE); INSERT INTO subscribers (subscriber_id, subscription_type, data_usage, data_limit, usage_date) VALUES (1, 'postpaid', 3.5, 2.0, '2022-03-01'), (2, 'prepaid', 2.0, 1.5, '2022-03-01'), (3, 'postpaid', 4.0, 3.0, '2022-03-01'); | What is the percentage of mobile subscribers who have used more than 50% of their data limit in the current month, for each subscription type, ordered by subscription type and percentage? | SELECT subscription_type, AVG(CASE WHEN data_usage > 0.5 * data_limit THEN 1 ELSE 0 END) * 100 as pct_used_more_than_50_percent FROM subscribers WHERE usage_date >= LAST_DAY(CURRENT_DATE) AND usage_date < LAST_DAY(CURRENT_DATE) + INTERVAL 1 DAY GROUP BY subscription_type ORDER BY subscription_type, pct_used_more_than_50_percent DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE patient_info_2023 (patient_id INT, first_treatment_date DATE); INSERT INTO patient_info_2023 (patient_id, first_treatment_date) VALUES (5, '2023-02-03'), (6, '2023-01-15'), (7, '2023-06-28'), (8, NULL); CREATE TABLE therapy_sessions_2023 (patient_id INT, session_date DATE); INSERT INTO therapy_sessions_2023 (patient_id, session_date) VALUES (5, '2023-02-03'), (7, '2023-06-28'), (7, '2023-06-30'), (11, '2023-05-15'); | Update the patient's first_treatment_date to the earliest therapy session date if the current date is on or after '2023-06-01' | UPDATE patient_info_2023 JOIN (SELECT patient_id, MIN(session_date) AS min_session_date FROM therapy_sessions_2023 WHERE session_date < '2023-06-01' GROUP BY patient_id) AS earliest_sessions ON patient_info_2023.patient_id = earliest_sessions.patient_id SET patient_info_2023.first_treatment_date = earliest_sessions.min_session_date WHERE patient_info_2023.first_treatment_date IS NULL OR patient_info_2023.first_treatment_date > '2023-05-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE BAE_Timelines (id INT, corporation VARCHAR(20), region VARCHAR(20), project_name VARCHAR(20), start_date DATE, end_date DATE); INSERT INTO BAE_Timelines (id, corporation, region, project_name, start_date, end_date) VALUES (1, 'BAE Systems', 'Oceania', 'Project A', '2020-01-01', '2022-12-31'); | What are the defense project timelines for BAE Systems in Oceania? | SELECT project_name, start_date, end_date FROM BAE_Timelines WHERE corporation = 'BAE Systems' AND region = 'Oceania'; | gretelai_synthetic_text_to_sql |
CREATE TABLE local_businesses (id INT, name TEXT, country TEXT, hotel_name TEXT); INSERT INTO local_businesses (id, name, country, hotel_name) VALUES (1, 'Eco Shop', 'Italy', 'Eco Hotel Rome'); | How many local businesses in 'Italy' are associated with eco-friendly hotels? | SELECT COUNT(*) FROM local_businesses JOIN hotels ON local_businesses.hotel_name = hotels.name WHERE local_businesses.country = 'Italy' AND hotels.name LIKE '%eco%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, Name VARCHAR(50), TotalDonation DECIMAL(10,2)); INSERT INTO Donors (DonorID, Name, TotalDonation) VALUES (1, 'John Doe', 500.00), (2, 'Jane Smith', 350.00), (3, 'Mike Johnson', 200.00); | What is the percentage of total donations made by each donor, ordered by the percentage in descending order? | SELECT Name, 100.0 * SUM(TotalDonation) OVER (PARTITION BY NULL) / SUM(SUM(TotalDonation)) OVER () AS Percentage FROM Donors ORDER BY Percentage DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_adaptation (project_id INT, project_name VARCHAR(255), location VARCHAR(255), start_date DATE, end_date DATE, total_cost DECIMAL(10,2)); | Get the total cost of all climate adaptation projects in 'South America'. | SELECT SUM(total_cost) FROM climate_adaptation WHERE location = 'South America'; | gretelai_synthetic_text_to_sql |
CREATE TABLE NYCFireStations (Borough VARCHAR(255), Number INT); INSERT INTO NYCFireStations (Borough, Number) VALUES ('Manhattan', 32), ('Brooklyn', 45), ('Queens', 50), ('Bronx', 39), ('Staten Island', 11); | What is the total number of fire stations in each borough of New York City? | SELECT Borough, SUM(Number) as TotalFireStations FROM NYCFireStations GROUP BY Borough; | gretelai_synthetic_text_to_sql |
CREATE TABLE oceans (ocean_id INT, name VARCHAR(50)); CREATE TABLE species (species_id INT, name VARCHAR(50), ocean_id INT, avg_depth DECIMAL(5,2)); INSERT INTO oceans VALUES (1, 'Atlantic'), (2, 'Indian'), (3, 'Pacific'); INSERT INTO species VALUES (1, 'Clownfish', 2, 10), (2, 'Salmon', 1, 100), (3, 'Clownfish', 3, 15), (4, 'Dolphin', 1, 200), (5, 'Turtle', 3, 30), (6, 'Shark', 2, 250), (7, 'Shark', 1, 300), (8, 'Squid', 3, 40), (9, 'Dolphin', 2, 220), (10, 'Tuna', 1, 150); | Which marine species have a higher average depth in the Atlantic compared to the Indian Ocean? | SELECT s.name FROM species s WHERE s.ocean_id IN (1, 2) GROUP BY s.name HAVING AVG(s.avg_depth) > (SELECT AVG(s.avg_depth) FROM species s WHERE s.ocean_id = 3); | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (id VARCHAR(10), name VARCHAR(10), region VARCHAR(20)); INSERT INTO wells (id, name, region) VALUES ('W002', 'B', 'NorthSea'), ('W003', 'C', 'NorthSea'); CREATE TABLE production (well_id VARCHAR(10), date DATE, quantity INT); INSERT INTO production (well_id, date, quantity) VALUES ('W002', '2022-01-01', 150), ('W002', '2022-01-02', 180), ('W003', '2022-01-01', 50); | Which wells in the 'NorthSea' have had no production in the last month? | SELECT well_id FROM production WHERE well_id IN (SELECT id FROM wells WHERE region = 'NorthSea') AND date >= (CURRENT_DATE - INTERVAL '1 month') AND quantity = 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE dishes (id INT, name TEXT, type TEXT, price DECIMAL, cost DECIMAL); INSERT INTO dishes (id, name, type, price, cost) VALUES (1, 'Quinoa Salad', 'Vegan', 12.99, 5.50), (2, 'Chickpea Curry', 'Vegan', 10.99, 7.99), (3, 'Beef Burger', 'Non-Vegan', 15.99, 10.50), (4, 'Chicken Sandwich', 'Non-Vegan', 14.99, 9.50); | Which dish has the lowest cost? | SELECT name, cost FROM dishes WHERE cost = (SELECT MIN(cost) FROM dishes); | gretelai_synthetic_text_to_sql |
CREATE TABLE Warehouse (item VARCHAR(10), quantity INT); INSERT INTO Warehouse (item, quantity) VALUES ('A101', 50), ('B202', 75); | Display the warehouse stock for item 'B202' | SELECT item, quantity FROM Warehouse WHERE item = 'B202'; | gretelai_synthetic_text_to_sql |
CREATE TABLE district (did INT, district_name VARCHAR(255)); INSERT INTO district (did, district_name) VALUES (1, 'Central'), (2, 'North'), (3, 'South'); CREATE TABLE drills (drill_id INT, did INT, drill_date DATE); | How many disaster preparedness drills were conducted in the last quarter in the 'South' district? | SELECT COUNT(*) FROM drills WHERE did = 3 AND drill_date >= DATEADD(quarter, -1, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE Game_Library (game_id INT, game_name VARCHAR(50), player_id INT); INSERT INTO Game_Library (game_id, game_name, player_id) VALUES (1, 'Space Invaders', 1), (2, 'Star Wars', 2), (3, 'Space Ranger', 3); | How many games have players participated in that start with the word 'Space' in the game library? | SELECT COUNT(DISTINCT game_id) FROM Game_Library WHERE game_name LIKE 'Space%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Military_Innovation_Spending (id INT, country VARCHAR(50), year INT, spending INT); | What is the total spending on military innovation by the top 3 contributing countries in the past 5 years? | SELECT SUM(spending) as total_spending, country FROM Military_Innovation_Spending WHERE year BETWEEN (YEAR(CURRENT_DATE) - 5) AND YEAR(CURRENT_DATE) GROUP BY country ORDER BY total_spending DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Hotels (hotel_id INT, hotel_name VARCHAR(50), country VARCHAR(50), is_green_certified BOOLEAN, energy_consumption FLOAT); INSERT INTO Hotels (hotel_id, hotel_name, country, is_green_certified, energy_consumption) VALUES (1, 'GreenHotel Ottawa', 'Canada', true, 120.00), (2, 'EcoLodge Montreal', 'Canada', true, 150.00), (3, 'ClassicHotel Toronto', 'Canada', false, 200.00); | Show the average energy consumption of green-certified hotels in Canada. | SELECT AVG(energy_consumption) FROM Hotels WHERE country = 'Canada' AND is_green_certified = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE movie_releases (id INT, title VARCHAR(255), studio VARCHAR(255), release_date DATE); INSERT INTO movie_releases (id, title, studio, release_date) VALUES (1, 'Movie1', 'Studio1', '2020-01-01'), (2, 'Movie2', 'Studio2', '2020-02-01'), (3, 'Movie3', 'Studio1', '2020-03-01'); | How many movies were released by each studio in 2020? | SELECT studio, COUNT(*) as movie_count FROM movie_releases WHERE YEAR(release_date) = 2020 GROUP BY studio; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (patient_id INT, age INT, emergency_room_wait_time INT, location VARCHAR(255)); INSERT INTO patients (patient_id, age, emergency_room_wait_time, location) VALUES (12, 32, 60, 'rural Brazil'); INSERT INTO patients (patient_id, age, emergency_room_wait_time, location) VALUES (13, 50, 90, 'rural Brazil'); CREATE TABLE nurses (nurse_id INT, location VARCHAR(255)); INSERT INTO nurses (nurse_id, location) VALUES (120, 'rural Brazil'); INSERT INTO nurses (nurse_id, location) VALUES (121, 'rural Brazil'); | What is the average emergency room wait time for patients in rural Brazil, and how many nurses are available per patient in the emergency room? | SELECT AVG(emergency_room_wait_time) AS avg_wait_time, COUNT(nurses.nurse_id) / COUNT(DISTINCT patients.patient_id) AS nurses_per_patient FROM patients INNER JOIN nurses ON patients.location = nurses.location WHERE patients.location LIKE 'rural% Brazil'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Graduate_Students (Student_ID INT, First_Name VARCHAR(50), Last_Name VARCHAR(50), Gender VARCHAR(10), Enrollment_Status VARCHAR(20)); | Delete records in the 'Graduate_Students' table where the 'Gender' is 'Unknown' and 'Enrollment_Status' is 'Inactive' | DELETE FROM Graduate_Students WHERE Gender = 'Unknown' AND Enrollment_Status = 'Inactive'; | gretelai_synthetic_text_to_sql |
CREATE TABLE director (director_id INT, director_name VARCHAR(50), total_gross INT); INSERT INTO director (director_id, director_name, total_gross) VALUES (1, 'Director 1', 50000000), (2, 'Director 2', 70000000), (3, 'Director 3', 30000000); CREATE TABLE movie (movie_id INT, title VARCHAR(50), release_year INT, gross INT, director_id INT); INSERT INTO movie (movie_id, title, release_year, gross, director_id) VALUES (1, 'Movie 1', 2019, 10000000, 1), (2, 'Movie 2', 2016, 20000000, 1), (3, 'Movie 3', 2017, 15000000, 2); | Who are the top 3 directors with the highest total gross for movies released between 2015 and 2020? | SELECT director_name, SUM(gross) FROM movie JOIN director ON movie.director_id = director.director_id WHERE release_year BETWEEN 2015 AND 2020 GROUP BY director_name ORDER BY SUM(gross) DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE crime_incidents (id INT PRIMARY KEY, incident_date DATE, incident_type VARCHAR(255)); INSERT INTO crime_incidents (id, incident_date, incident_type) VALUES (1, '2010-01-02', 'Theft'), (2, '2009-12-31', 'Assault'), (3, '2010-01-05', 'Burglary'); | Update the incident_dates in the crime_incidents table for the 'Theft' incident type to be a month later | UPDATE crime_incidents SET incident_date = DATE_ADD(incident_date, INTERVAL 1 MONTH) WHERE incident_type = 'Theft'; | gretelai_synthetic_text_to_sql |
CREATE TABLE StudentAccommodations (studentID INT, accommodationType VARCHAR(50), cost FLOAT); | Display the number of students who received accommodations in the StudentAccommodations table by accommodation type. | SELECT accommodationType, COUNT(*) FROM StudentAccommodations GROUP BY accommodationType; | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_stock (species VARCHAR(50), biomass INT); INSERT INTO fish_stock (species, biomass) VALUES ('Tilapia', 500), ('Tilapia', 700), ('Salmon', 800); | What is the total number of fish in the fish_stock table? | SELECT COUNT(*) FROM fish_stock; | gretelai_synthetic_text_to_sql |
CREATE TABLE InvestmentsMax (id INT, investor VARCHAR(255), sector VARCHAR(255), amount DECIMAL(10,2)); | What is the maximum 'amount' invested by 'SustainableFund'? | SELECT MAX(amount) FROM InvestmentsMax WHERE investor = 'SustainableFund'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Workouts (WorkoutID INT, MemberID INT, WorkoutDate DATE, Duration INT); INSERT INTO Workouts (WorkoutID, MemberID, WorkoutDate, Duration) VALUES (1, 1, '2023-01-01', 60), (2, 2, '2023-01-02', 90), (3, 3, '2023-01-03', 75); | What is the average duration of workouts for members over 40 years old? | SELECT AVG(Duration) FROM Workouts INNER JOIN Members ON Workouts.MemberID = Members.MemberID WHERE Members.Age > 40; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID int, FirstName varchar(50), LastName varchar(50), Department varchar(50), Gender varchar(50), Salary decimal(10,2)); INSERT INTO Employees (EmployeeID, FirstName, LastName, Department, Gender, Salary) VALUES (1, 'John', 'Doe', 'IT', 'Male', 75000); INSERT INTO Employees (EmployeeID, FirstName, LastName, Department, Gender, Salary) VALUES (2, 'Jane', 'Doe', 'HR', 'Female', 80000); | What is the total salary paid by department? | SELECT Department, SUM(Salary) as TotalSalary FROM Employees GROUP BY Department; | gretelai_synthetic_text_to_sql |
CREATE TABLE military_sales (id INT PRIMARY KEY, region VARCHAR(20), year INT, equipment_name VARCHAR(30), quantity INT, value FLOAT); | Insert new records for 'Missile System' sales to 'Europe' in the year '2026' with the quantity of 30 and value of 25000000 | INSERT INTO military_sales (id, region, year, equipment_name, quantity, value) VALUES (4, 'Europe', 2026, 'Missile System', 30, 25000000); | gretelai_synthetic_text_to_sql |
CREATE TABLE community_outreach_coordinators (id INT, name VARCHAR(255));CREATE TABLE education_programs (id INT, coordinator_id INT, name VARCHAR(255)); INSERT INTO community_outreach_coordinators (id, name) VALUES (1, 'Alice'), (2, 'Brenda'), (3, 'Charlie'); INSERT INTO education_programs (id, coordinator_id, name) VALUES (1, 1, 'Wildlife Warriors'), (2, 1, 'Adopt an Animal'), (3, 2, 'Butterfly Conservation'), (4, 3, 'Endangered Species Protection'); | Count the number of educational programs for each community outreach coordinator | SELECT co.name AS coordinator_name, COUNT(e.id) AS program_count FROM community_outreach_coordinators co LEFT JOIN education_programs e ON co.id = e.coordinator_id GROUP BY co.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE spacecraft_temperatures (spacecraft_name TEXT, temperature FLOAT, mission_date DATE); | What is the average temperature (in Kelvin) per spacecraft per month, ranked in descending order? | SELECT spacecraft_name, DATE_TRUNC('month', mission_date) as mission_month, AVG(temperature) as avg_temperature, RANK() OVER (PARTITION BY spacecraft_name ORDER BY AVG(temperature) DESC) as temp_rank FROM spacecraft_temperatures GROUP BY spacecraft_name, mission_month ORDER BY spacecraft_name, temp_rank; | gretelai_synthetic_text_to_sql |
CREATE TABLE Auto (policyholder_id INT, car_make VARCHAR(20), car_model VARCHAR(20)); | Update car make to 'GM' for policyholders with policyholder_id 300, 301, and 302 in the 'Auto' table. | UPDATE Auto SET car_make = 'GM' WHERE policyholder_id IN (300, 301, 302); | gretelai_synthetic_text_to_sql |
CREATE TABLE raw_materials (id INT, chemical_id INT, cost FLOAT, date_purchased DATE); CREATE TABLE chemical_products (id INT, name VARCHAR(50)); | What is the total cost of all raw materials used in the production of chemical X in the past quarter? | SELECT SUM(cost) FROM raw_materials JOIN chemical_products ON raw_materials.chemical_id = chemical_products.id WHERE chemical_products.name = 'chemical X' AND date_purchased >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE rd_expenditure(company_name TEXT, expenditure INT, expenditure_year INT); INSERT INTO rd_expenditure(company_name, expenditure, expenditure_year) VALUES('CompanyX', 3000000, 2021); | What was the R&D expenditure for 'CompanyX' in 2021? | SELECT expenditure FROM rd_expenditure WHERE company_name = 'CompanyX' AND expenditure_year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE grain_production (farm_id INT, country VARCHAR(50), product VARCHAR(50), production INT); INSERT INTO grain_production (farm_id, country, product, production) VALUES (1, 'Tanzania', 'Maize', 500), (2, 'Tanzania', 'Rice', 300), (3, 'Malawi', 'Wheat', 400), (4, 'Zambia', 'Barley', 100); | What is the total production of grains in Tanzania and Malawi? | SELECT SUM(production) FROM grain_production WHERE country IN ('Tanzania', 'Malawi') AND product LIKE 'Grain%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE commercial_customers (customer_id INT, city VARCHAR(20), water_usage FLOAT); INSERT INTO commercial_customers (customer_id, city, water_usage) VALUES (1, 'Chicago', 3000), (2, 'Chicago', 4000); CREATE TABLE residential_customers (customer_id INT, city VARCHAR(20), water_usage FLOAT); INSERT INTO residential_customers (customer_id, city, water_usage) VALUES (1, 'Chicago', 2000), (2, 'Chicago', 2500); | What is the difference in water usage between commercial and residential customers in the city of Chicago? | SELECT SUM(commercial_customers.water_usage) - SUM(residential_customers.water_usage) FROM commercial_customers, residential_customers WHERE commercial_customers.city = 'Chicago' AND residential_customers.city = 'Chicago'; | gretelai_synthetic_text_to_sql |
CREATE TABLE NationalParks (ParkID int, ParkName varchar(255), State varchar(255)); INSERT INTO NationalParks (ParkID, ParkName, State) VALUES (1, 'Big Bend National Park', 'Texas'), (2, 'Guadalupe Mountains National Park', 'Texas'); | List the names of all national parks in the state of Texas. | SELECT ParkName FROM NationalParks WHERE State = 'Texas'; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (id INT, customer_id INT, transaction_date DATE, amount FLOAT); INSERT INTO transactions (id, customer_id, transaction_date, amount) VALUES (1, 1, '2022-01-01', 1000.00), (2, 2, '2022-01-02', 2000.00), (3, 1, '2022-01-03', 1500.00); | Identify the number of transactions and total transaction amount per day for the past week | SELECT DATE(transaction_date) AS transaction_date, COUNT(*) AS num_transactions, SUM(amount) AS total_amount FROM transactions WHERE transaction_date BETWEEN DATE_SUB(CURDATE(), INTERVAL 7 DAY) AND CURDATE() GROUP BY transaction_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE districts (id INT, name VARCHAR(255)); INSERT INTO districts (id, name) VALUES (4, 'Uptown'); CREATE TABLE emergency_incidents (id INT, district_id INT, incident_type VARCHAR(50), response_time INT); INSERT INTO emergency_incidents (id, district_id, incident_type, response_time) VALUES (1, 4, 'fire', 8), (2, 4, 'medical', 12), (3, 4, 'fire', 6); | Update the response time for all medical incidents in district 4 to 10 minutes | UPDATE emergency_incidents SET response_time = 10 WHERE district_id = 4 AND incident_type = 'medical'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accommodations (student_id INT, visual_impairment BOOLEAN, mobility_impairment BOOLEAN); | How many students require accommodations for both visual and mobility impairments? | SELECT COUNT(*) FROM Accommodations WHERE visual_impairment = TRUE AND mobility_impairment = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE satellites (id INT, country VARCHAR(255), result VARCHAR(10)); INSERT INTO satellites (id, country, result) VALUES (1, 'USA', 'successful'), (2, 'China', 'successful'), (3, 'India', 'unsuccessful'), (4, 'USA', 'successful'), (5, 'China', 'successful'); | What is the total number of satellites launched by each country, and how many of those were successful? | SELECT country, COUNT(*) FILTER (WHERE result = 'successful') as successful_launches, COUNT(*) as total_launches FROM satellites GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE startups(id INT, name TEXT, founders TEXT, founding_year INT, industry TEXT); INSERT INTO startups VALUES (1, 'StartupA', 'Aisha, Pedro', 2012, 'Fintech'); INSERT INTO startups VALUES (2, 'StartupB', 'Eve', 2015, 'Healthcare'); INSERT INTO startups VALUES (3, 'StartupC', 'Carlos', 2018, 'Tech'); CREATE TABLE investments(startup_id INT, round INT, funding INT); INSERT INTO investments VALUES (1, 1, 1000000); INSERT INTO investments VALUES (1, 2, 2000000); INSERT INTO investments VALUES (2, 1, 3000000); INSERT INTO investments VALUES (3, 1, 4000000); INSERT INTO investments VALUES (3, 2, 5000000); | What is the average founding year for startups founded by individuals who identify as Latinx in the fintech industry? | SELECT AVG(founding_year) FROM startups WHERE industry = 'Fintech' AND founders LIKE '%Pedro%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE moscow_buses (id INT, route_id VARCHAR(20), distance FLOAT, timestamp TIMESTAMP); | What is the average distance of public bus rides in Moscow? | SELECT AVG(distance) FROM moscow_buses WHERE route_id IS NOT NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accessible_Tech_Projects (ID INT, Project_Name VARCHAR(100), Location VARCHAR(50), Budget DECIMAL(10,2)); INSERT INTO Accessible_Tech_Projects (ID, Project_Name, Location, Budget) VALUES (1, 'Tech4All', 'Africa', 150000.00), (2, 'AI4Good', 'Africa', 200000.00), (3, 'EqualWeb', 'Europe', 120000.00); | What is the total number of accessible technology projects in Africa? | SELECT COUNT(*) FROM Accessible_Tech_Projects WHERE Location = 'Africa'; | gretelai_synthetic_text_to_sql |
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