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 game_sessions (user_id INT, game_name VARCHAR(10), login_date DATE); INSERT INTO game_sessions (user_id, game_name, login_date) VALUES (1, 'A', '2021-01-01'), (2, 'B', '2021-01-02'), (3, 'B', '2021-01-03'), (4, 'C', '2021-01-04'); | List all unique users who played game 'B' between January 1, 2021 and January 7, 2021 | SELECT DISTINCT user_id FROM game_sessions WHERE game_name = 'B' AND login_date BETWEEN '2021-01-01' AND '2021-01-07'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_life_sightings (sighting_id INTEGER, species TEXT, sighting_date DATE); INSERT INTO marine_life_sightings (sighting_id, species, sighting_date) VALUES (1, 'Blue Whale', '2022-01-01'), (2, 'Humpback Whale', '2022-01-02'), (3, 'Blue Whale', '2022-01-03'); | How many whale sightings were recorded in the 'marine_life_sightings' table for each type of whale? | SELECT species, COUNT(*) FROM marine_life_sightings WHERE species IN ('Blue Whale', 'Humpback Whale') GROUP BY species; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_farms_biomass (farm_id INT, species VARCHAR(20), biomass FLOAT); INSERT INTO marine_farms_biomass (farm_id, species, biomass) VALUES (1, 'Tuna', 1200.5), (2, 'Swordfish', 800.3), (3, 'Shrimp', 1500.2); | Find the percentage of total biomass for each species in marine farms. | SELECT species, SUM(biomass) total_biomass, 100.0 * SUM(biomass) / (SELECT SUM(biomass) FROM marine_farms_biomass) percentage FROM marine_farms_biomass GROUP BY species; | gretelai_synthetic_text_to_sql |
CREATE TABLE concerts (concert_id INT PRIMARY KEY, artist_name VARCHAR(100), concert_date DATE, location VARCHAR(100), tickets_sold INT, genre VARCHAR(50)); INSERT INTO concerts (concert_id, artist_name, concert_date, location, tickets_sold, genre) VALUES (1, 'Eminem', '2023-06-15', 'New York City', 15000, 'Hip-Hop'); INSERT INTO concerts (concert_id, artist_name, concert_date, location, tickets_sold, genre) VALUES (2, 'Kendrick Lamar', '2023-07-01', 'Los Angeles', 12000, 'Hip-Hop'); INSERT INTO concerts (concert_id, artist_name, concert_date, location, tickets_sold, genre) VALUES (3, 'Nas', '2023-08-10', 'Chicago', 10000, 'Hip-Hop'); | Find total tickets sold for all hip-hop concerts | SELECT SUM(tickets_sold) FROM concerts WHERE genre = 'Hip-Hop'; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name VARCHAR(50), continent VARCHAR(50), donation DECIMAL(10, 2)); | What is the maximum donation amount for donors from Africa? | SELECT MAX(donation) FROM donors WHERE continent = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE GovernmentEmployees (EmployeeID INT, Salary DECIMAL(10,2), State VARCHAR(100)); INSERT INTO GovernmentEmployees (EmployeeID, Salary, State) VALUES (1, 45000.00, 'Texas'), (2, 50000.00, 'Texas'), (3, 55000.00, 'Texas'), (4, 60000.00, 'Texas'), (5, 65000.00, 'Texas'); | What is the average salary of government employees in the state of Texas, and what is the mode salary? | SELECT AVG(Salary) as AverageSalary, MAX(Salary) as ModeSalary FROM GovernmentEmployees WHERE State = 'Texas' GROUP BY Salary HAVING COUNT(*) > 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE Stores (store_id INT, store_name VARCHAR(50), state VARCHAR(50)); INSERT INTO Stores (store_id, store_name, state) VALUES (1, 'Eco-Market', 'Utah'), (2, 'Green Vista', 'Arizona'); CREATE TABLE Inventory (inventory_id INT, product_id INT, product_name VARCHAR(50), store_id INT, last_sale_date DATE); INSERT INTO Inventory (inventory_id, product_id, product_name, store_id, last_sale_date) VALUES (1, 1, 'Almond Milk', 1, '2022-04-15'), (2, 2, 'Quinoa', 2, '2022-06-01'); | Delete records for products that have not been sold for the last 4 months in stores located in 'Utah' and 'Arizona' | DELETE FROM Inventory WHERE last_sale_date < DATE_SUB(CURRENT_DATE, INTERVAL 4 MONTH) AND store_id IN (SELECT store_id FROM Stores WHERE state IN ('Utah', 'Arizona')); | gretelai_synthetic_text_to_sql |
CREATE TABLE Readers (ReaderID INT, Age INT, Country VARCHAR(50), SubscriptionType VARCHAR(50)); INSERT INTO Readers (ReaderID, Age, Country, SubscriptionType) VALUES (1, 35, 'USA', 'Digital'), (2, 45, 'Canada', 'Print'), (3, 25, 'Mexico', 'Digital'); | What is the average age of readers who prefer digital subscriptions, grouped by their country of residence? | SELECT Country, AVG(Age) as AvgAge FROM Readers WHERE SubscriptionType = 'Digital' GROUP BY Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales (sale_id INT, product_type VARCHAR(50), country VARCHAR(50), revenue DECIMAL(10,2)); INSERT INTO sales (sale_id, product_type, country, revenue) VALUES (1, 'sustainable', 'France', 500.00), (2, 'non-sustainable', 'Nigeria', 400.00), (3, 'sustainable', 'Germany', 600.00), (4, 'sustainable', 'Kenya', 550.00), (5, 'non-sustainable', 'Spain', 450.00); | What is the total revenue generated from the sales of sustainable products in Europe and Africa for the last quarter? | SELECT SUM(sales.revenue) FROM sales WHERE sales.product_type = 'sustainable' AND sales.country IN ('Europe', 'Africa') AND sales.date BETWEEN '2022-01-01' AND '2022-03-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE drought_areas (id INT, area VARCHAR(50), event_date DATE, water_consumption FLOAT); INSERT INTO drought_areas (id, area, event_date, water_consumption) VALUES (1, 'Area1', '2020-01-01', 1200), (2, 'Area2', '2020-02-01', 1500), (3, 'Area3', '2020-03-01', 1800); | How many drought-affected areas were there in the year 2020 and what was the average water consumption in those areas? | SELECT area, AVG(water_consumption) as avg_water_consumption FROM drought_areas WHERE YEAR(event_date) = 2020 GROUP BY area; | gretelai_synthetic_text_to_sql |
CREATE TABLE clinical_trials (country TEXT, drug_class TEXT, trial_count INTEGER); | How many clinical trials were conducted in Asia for vaccines? | SELECT SUM(trial_count) FROM clinical_trials WHERE country = 'Asia' AND drug_class = 'vaccines'; | gretelai_synthetic_text_to_sql |
CREATE TABLE revenue_data (year INT, country VARCHAR(15), network VARCHAR(15), revenue FLOAT); INSERT INTO revenue_data (year, country, network, revenue) VALUES (2021, 'Japan', 'NTT Docomo', 15000000), (2021, 'Japan', 'Softbank', 12000000), (2021, 'Japan', 'KDDI', 13000000); | What is the total revenue generated by each mobile network in Japan for the year 2021? | SELECT network, SUM(revenue) as total_revenue FROM revenue_data WHERE country = 'Japan' AND year = 2021 GROUP BY network; | gretelai_synthetic_text_to_sql |
CREATE TABLE network_nodes (node_id INT, network VARCHAR(50), nodes_count INT); INSERT INTO network_nodes (node_id, network, nodes_count) VALUES (1, 'Algorand', 1234); | What is the number of nodes in the Algorand network? | SELECT nodes_count FROM network_nodes WHERE network = 'Algorand'; | gretelai_synthetic_text_to_sql |
CREATE TABLE crop_temperature (crop_type TEXT, temperature INTEGER, timestamp TIMESTAMP);CREATE TABLE crop_humidity (crop_type TEXT, humidity INTEGER, timestamp TIMESTAMP); | What is the minimum temperature and humidity for each crop type in the past month? | SELECT ct.crop_type, MIN(ct.temperature) as min_temp, MIN(ch.humidity) as min_humidity FROM crop_temperature ct JOIN crop_humidity ch ON ct.timestamp = ch.timestamp WHERE ct.timestamp BETWEEN DATEADD(month, -1, CURRENT_TIMESTAMP) AND CURRENT_TIMESTAMP GROUP BY ct.crop_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE Shipments (id INT, WarehouseId INT, Product VARCHAR(50), Quantity INT, Destination VARCHAR(50), ShippedDate DATE); INSERT INTO Shipments (id, WarehouseId, Product, Quantity, Destination, ShippedDate) VALUES (1, 1, 'Laptop', 50, 'New York', '2022-01-01'); INSERT INTO Shipments (id, WarehouseId, Product, Quantity, Destination, ShippedDate) VALUES (2, 1, 'Monitor', 75, 'Los Angeles', '2022-01-05'); INSERT INTO Shipments (id, WarehouseId, Product, Quantity, Destination, ShippedDate) VALUES (3, 2, 'Keyboard', 100, 'Paris', '2022-01-07'); | What is the total quantity of electronics shipped from each warehouse per country? | SELECT WarehouseId, Country, SUM(Quantity) AS TotalQuantity FROM (SELECT WarehouseId, Product, Quantity, Destination, SUBSTRING(Destination, 1, INSTR(Destination, ',') - 1) AS Country FROM Shipments) AS ShippedData GROUP BY WarehouseId, Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE DELIVERY (id INT, supplier_id INT, product_id INT, is_organic BOOLEAN, quantity INT); | What is the maximum quantity of a single organic product delivered in the DELIVERY table? | SELECT MAX(quantity) FROM DELIVERY WHERE is_organic = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE manufacturers (manufacturer_id INT, manufacturer_name VARCHAR(50), country VARCHAR(50), founding_date DATE); INSERT INTO manufacturers (manufacturer_id, manufacturer_name, country, founding_date) VALUES (1, 'ABC Chemicals', 'USA', '1950-01-01'), (2, 'XYZ Chemicals', 'Canada', '1980-01-01'), (3, 'DEF Chemicals', 'USA', '2000-01-01'), (4, 'LMN Chemicals', 'Mexico', '1990-01-01'); CREATE TABLE chemicals (chemical_id INT, chemical_type VARCHAR(50), manufacturer_id INT, weight FLOAT); INSERT INTO chemicals (chemical_id, chemical_type, manufacturer_id, weight) VALUES (1, 'Acid', 1, 150.5), (2, 'Alkali', 1, 200.3), (3, 'Solvent', 2, 120.7), (4, 'Solute', 3, 180.5), (5, 'Gas', 4, 250.9); | Identify the top 3 manufacturers with the highest total weight of chemicals produced, and rank them based on the date of their founding (earliest to latest) | SELECT manufacturer_id, manufacturer_name, SUM(weight) as total_weight, RANK() OVER (ORDER BY SUM(weight) DESC) as rank FROM chemicals JOIN manufacturers ON chemicals.manufacturer_id = manufacturers.manufacturer_id GROUP BY manufacturer_id, manufacturer_name ORDER BY rank ASC, founding_date ASC; | gretelai_synthetic_text_to_sql |
CREATE TABLE memberships (id INT, member_type VARCHAR(50), region VARCHAR(50)); CREATE TABLE workout_data (member_id INT, workout_type VARCHAR(50), duration INT, heart_rate_avg INT, calories_burned INT, workout_date DATE); | Which members in the North region have completed a workout of type 'Spin' with a duration of more than 60 minutes? | SELECT m.id FROM memberships m JOIN workout_data w ON m.id = w.member_id WHERE m.region = 'North' AND w.workout_type = 'Spin' AND w.duration > 60 GROUP BY m.id; | gretelai_synthetic_text_to_sql |
CREATE TABLE personnel_by_region(personnel_id INT, assignment VARCHAR(255), region VARCHAR(255)); INSERT INTO personnel_by_region(personnel_id, assignment, region) VALUES (1, 'Cybersecurity', 'Europe'), (2, 'Intelligence', 'Asia-Pacific'), (3, 'Logistics', 'North America'), (4, 'Cybersecurity', 'Europe'), (5, 'Cybersecurity', 'North America'); | What is the total number of military personnel assigned to cybersecurity operations in Europe? | SELECT COUNT(*) FROM personnel_by_region WHERE assignment = 'Cybersecurity' AND region = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE therapists (therapist_id INT, therapist_name TEXT, state TEXT); CREATE TABLE therapy_sessions (session_id INT, patient_age INT, therapist_id INT); INSERT INTO therapists (therapist_id, therapist_name, state) VALUES (1, 'Alice Johnson', 'California'); INSERT INTO therapy_sessions (session_id, patient_age, therapist_id) VALUES (1, 30, 1); | What is the average age of patients who have received therapy sessions in the state of California? | SELECT AVG(therapy_sessions.patient_age) FROM therapy_sessions JOIN therapists ON therapy_sessions.therapist_id = therapists.therapist_id WHERE therapists.state = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Vessel (id INT, name VARCHAR(50), type VARCHAR(50), length FLOAT); CREATE TABLE Captain (id INT, name VARCHAR(50), age INT, license_number VARCHAR(50), VesselId INT); CREATE TABLE Route (id INT, departure_port VARCHAR(50), arrival_port VARCHAR(50), distance FLOAT, VesselId INT); | Delete all routes associated with vessels that have a license_number of a captain who is under 30 years old. | DELETE FROM Route WHERE VesselId IN (SELECT VesselId FROM Captain WHERE age < 30); | gretelai_synthetic_text_to_sql |
CREATE TABLE Initiatives (id INT, name VARCHAR(255), plant_id INT, employees INT); INSERT INTO Initiatives (id, name, plant_id, employees) VALUES (4, 'Ethical Manufacturing', 7, 50); CREATE TABLE Plants (id INT, name VARCHAR(255)); INSERT INTO Plants (id, name) VALUES (7, 'Responsible Production'); | What is the number of employees working on ethical manufacturing initiatives at the 'Responsible Production' plant? | SELECT employees FROM Initiatives WHERE name = 'Ethical Manufacturing' AND plant_id = 7; | gretelai_synthetic_text_to_sql |
CREATE TABLE regions (region_id INT, region_name VARCHAR(50)); INSERT INTO regions (region_id, region_name) VALUES (1, 'Northeast'), (2, 'Southeast'), (3, 'Midwest'), (4, 'Southwest'), (5, 'West'); CREATE TABLE providers (provider_id INT, provider_name VARCHAR(50), region_id INT); INSERT INTO providers (provider_id, provider_name, region_id) VALUES (1, 'Dr. Smith', 1), (2, 'Dr. Johnson', 2); CREATE TABLE provider_patients (provider_id INT, patient_id INT, condition_id INT); CREATE TABLE mental_health_conditions (condition_id INT, condition_name VARCHAR(50)); INSERT INTO mental_health_conditions (condition_id, condition_name) VALUES (1, 'Anxiety'), (2, 'Depression'), (3, 'Bipolar Disorder'); | What is the average number of mental health conditions treated by providers in each region? | SELECT p.region_id, AVG(pp.condition_count) as avg_conditions FROM providers p JOIN (SELECT provider_id, COUNT(DISTINCT condition_id) as condition_count FROM provider_patients GROUP BY provider_id) pp ON p.provider_id = pp.provider_id GROUP BY p.region_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_prices (country VARCHAR(255) PRIMARY KEY, price_usd_per_ton FLOAT); | Delete records in the 'carbon_prices' table where the 'price_usd_per_ton' is greater than 50 | DELETE FROM carbon_prices WHERE price_usd_per_ton > 50; | gretelai_synthetic_text_to_sql |
CREATE TABLE community_engagement (engagement_id INT, engagement_type VARCHAR(10), total_shares INT); | Update the record in the 'community_engagement' table with an engagement ID of 7 to reflect a total of 150 social media shares | UPDATE community_engagement SET total_shares = 150 WHERE engagement_id = 7; | gretelai_synthetic_text_to_sql |
CREATE TABLE Policyholders (PolicyholderID INT, Age INT, PolicyType VARCHAR(20)); INSERT INTO Policyholders (PolicyholderID, Age, PolicyType) VALUES (1, 25, 'Auto'), (2, 32, 'Home'), (3, 19, 'Life'); | What is the total number of policies and their corresponding policy types for policyholders aged 30 or younger? | SELECT COUNT(*) as TotalPolicies, PolicyType FROM Policyholders WHERE Age <= 30 GROUP BY PolicyType; | gretelai_synthetic_text_to_sql |
CREATE TABLE DonorDisaster (DonorID INT, DisasterType VARCHAR(25), Amount DECIMAL(10,2)); INSERT INTO DonorDisaster (DonorID, DisasterType, Amount) VALUES (1, 'Earthquake', 100.00), (1, 'Flood', 50.00); | Find the total donations and number of donors for each disaster type. | SELECT DisasterType, SUM(Amount) as TotalDonations, COUNT(DISTINCT DonorID) as NumDonors FROM DonorDisaster GROUP BY DisasterType; | gretelai_synthetic_text_to_sql |
CREATE TABLE shariah_compliant_finance(customer_id INT, name VARCHAR(50), account_balance DECIMAL(10, 2)); INSERT INTO shariah_compliant_finance VALUES (1, 'Hassan Ahmed', 10000), (2, 'Aisha Bibi', 12000), (3, 'Muhammad Ali', 15000), (4, 'Fatima Khan', 11000); | Find the third highest account balance for Shariah-compliant finance customers, and identify the customer's name. | SELECT name, account_balance FROM (SELECT customer_id, name, account_balance, ROW_NUMBER() OVER (ORDER BY account_balance DESC) AS rn FROM shariah_compliant_finance) t WHERE rn = 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE dam_info (dam_id INT, dam_name VARCHAR(50)); CREATE TABLE dam_heights (dam_id INT, dam_height INT); INSERT INTO dam_info (dam_id, dam_name) VALUES (1, 'Hoover Dam'), (2, 'Grand Coulee Dam'), (3, 'Oroville Dam'); INSERT INTO dam_heights (dam_id, dam_height) VALUES (1, 726), (2, 550), (3, 770); | List all the dams along with their heights from the 'dam_info' and 'dam_heights' tables. | SELECT dam_info.dam_name, dam_heights.dam_height FROM dam_info INNER JOIN dam_heights ON dam_info.dam_id = dam_heights.dam_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE drugs (drug_id INT, drug_name TEXT); INSERT INTO drugs (drug_id, drug_name) VALUES (1001, 'Ibuprofen'), (1002, 'Paracetamol'), (1003, 'Aspirin'); CREATE TABLE sales (sale_id INT, drug_id INT, sale_date DATE, revenue FLOAT); INSERT INTO sales (sale_id, drug_id, sale_date, revenue) VALUES (1, 1001, '2020-01-05', 1500.0), (2, 1002, '2020-01-10', 2000.0), (3, 1003, '2020-01-15', 1200.0), (4, 1001, '2020-02-20', 1700.0), (5, 1002, '2020-03-25', 2200.0); | What are the total sales for each drug in Q1 2020? | SELECT drug_name, SUM(revenue) as total_sales FROM sales JOIN drugs ON sales.drug_id = drugs.drug_id WHERE sale_date BETWEEN '2020-01-01' AND '2020-03-31' GROUP BY drug_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE students (student_id INT PRIMARY KEY, name VARCHAR(50), department VARCHAR(50), grant_recipient BOOLEAN); INSERT INTO students (student_id, name, department, grant_recipient) VALUES (1, 'David', 'Humanities', TRUE); CREATE TABLE grants (grant_id INT PRIMARY KEY, student_id INT, amount FLOAT); INSERT INTO grants (grant_id, student_id) VALUES (1, 1); | How many research grants have been awarded to graduate students in the Humanities department? | SELECT COUNT(*) FROM grants g INNER JOIN students s ON g.student_id = s.student_id WHERE s.department = 'Humanities' AND s.grant_recipient = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT, donor_name TEXT, donation_amount DECIMAL, city_id INT); CREATE TABLE cities (city_id INT, city_name TEXT); | What is the total amount donated by each donor in the 'donors' table, joined with their corresponding city information from the 'cities' table? | SELECT donors.donor_name, SUM(donation_amount) FROM donors INNER JOIN cities ON donors.city_id = cities.city_id GROUP BY donor_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_treatment_plants (id INT, name TEXT, water_usage FLOAT); INSERT INTO water_treatment_plants (id, name, water_usage) VALUES (1, 'Plant A', 1000000), (2, 'Plant B', 1500000), (3, 'Plant C', 800000); | Which water treatment plants have water usage above the average? | SELECT name FROM water_treatment_plants WHERE water_usage > (SELECT AVG(water_usage) FROM water_treatment_plants); | gretelai_synthetic_text_to_sql |
CREATE TABLE broadband_speeds (location VARCHAR(20), speed FLOAT, country VARCHAR(20)); INSERT INTO broadband_speeds (location, speed, country) VALUES ('Madrid', 120.4, 'Spain'); INSERT INTO broadband_speeds (location, speed, country) VALUES ('Barcelona', 150.6, 'Spain'); | What is the average broadband speed in each country in Europe? | SELECT country, AVG(speed) FROM broadband_speeds GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_projects (project_name VARCHAR(255), project_type VARCHAR(255), city VARCHAR(255)); | What are the names and types of renewable energy projects in the city of Seattle? | SELECT project_name, project_type FROM renewable_projects WHERE city = 'Seattle'; | gretelai_synthetic_text_to_sql |
CREATE TABLE city_data (city VARCHAR(50), median_home_price FLOAT, first_time_buyer_friendly INT); INSERT INTO city_data (city, median_home_price, first_time_buyer_friendly) VALUES ('CityA', 200000, 1), ('CityB', 300000, 0), ('CityC', 150000, 1), ('CityD', 400000, 1), ('CityE', 250000, 0); | List the top 3 most affordable cities for first-time home buyers. | SELECT city, median_home_price FROM (SELECT city, median_home_price, RANK() OVER (ORDER BY median_home_price ASC) AS rank FROM city_data WHERE first_time_buyer_friendly = 1) AS subquery WHERE rank <= 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE donor_emails (id INT, donor_id INT, email VARCHAR(50)); INSERT INTO donor_emails (id, donor_id, email) VALUES (1, 1, 'johndoe'), (2, 2, 'janesmith'), (3, 3, 'alicej'); | Update the email addresses for donors with missing domain information ('@' symbol is missing). | UPDATE donor_emails SET email = CONCAT(email, '@example.org') WHERE email NOT LIKE '%@%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ElectricVehicles (Id INT, Make VARCHAR(50), Model VARCHAR(50), MaxSpeed FLOAT); INSERT INTO ElectricVehicles (Id, Make, Model, MaxSpeed) VALUES (1, 'Tesla', 'Model S', 261), (2, 'Tesla', 'Model 3', 225), (3, 'Tesla', 'Model X', 250), (4, 'Tesla', 'Model Y', 217); | What is the maximum speed of electric vehicles produced by Tesla? | SELECT MAX(MaxSpeed) FROM ElectricVehicles WHERE Make = 'Tesla' AND Model LIKE 'Model%' | gretelai_synthetic_text_to_sql |
CREATE TABLE WarehouseTemperature (id INT, temperature FLOAT, location VARCHAR(20)); INSERT INTO WarehouseTemperature (id, temperature, location) VALUES (1, 35, 'Asia'), (2, 20, 'Europe'); | What is the total number of pallets with a temperature above 30 degrees Celsius stored in warehouses located in Asia? | SELECT COUNT(*) FROM WarehouseTemperature WHERE location LIKE '%Asia%' AND temperature > 30; | gretelai_synthetic_text_to_sql |
CREATE TABLE animal_habitat (habitat_id INT, habitat_name VARCHAR(50), animal_name VARCHAR(50), acres FLOAT); INSERT INTO animal_habitat (habitat_id, habitat_name, animal_name, acres) VALUES (1, 'African Savannah', 'Lion', 5000.0), (2, 'Asian Rainforest', 'Tiger', 2000.0), (3, 'African Rainforest', 'Elephant', 3000.0); | How many animals are there in the 'animal_habitat' table? | SELECT COUNT(*) FROM animal_habitat; | gretelai_synthetic_text_to_sql |
CREATE TABLE energy_storage (state TEXT, num_projects INTEGER); INSERT INTO energy_storage (state, num_projects) VALUES ('California', 563), ('Texas', 357), ('New York', 256), ('Florida', 152), ('Illinois', 140), ('Pennsylvania', 137), ('Ohio', 128), ('North Carolina', 127), ('Michigan', 122), ('New Jersey', 118); | How many energy storage projects are there in California, Texas, and New York? | SELECT num_projects FROM energy_storage WHERE state IN ('California', 'Texas', 'New York') | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(50), country VARCHAR(50), ai_familiarity INT); INSERT INTO users (id, name, country, ai_familiarity) VALUES (1, 'John Doe', 'Canada', 3); INSERT INTO users (id, name, country, ai_familiarity) VALUES (2, 'Jane Smith', 'USA', 5); | Delete records from the "users" table where the country is "Canada" and the "ai_familiarity" score is less than 4 | DELETE FROM users WHERE country = 'Canada' AND ai_familiarity < 4; | gretelai_synthetic_text_to_sql |
CREATE TABLE artist (artist_id INT, artist_name VARCHAR(50), num_followers INT, primary_genre VARCHAR(30)); INSERT INTO artist (artist_id, artist_name, num_followers, primary_genre) VALUES (1, 'DJ Khalid', 3500000, 'Hip Hop'); INSERT INTO artist (artist_id, artist_name, num_followers, primary_genre) VALUES (2, 'Taylor Swift', 68000000, 'Pop'); INSERT INTO artist (artist_id, artist_name, num_followers, primary_genre) VALUES (5, 'Adele', 25000000, 'Pop'); INSERT INTO artist (artist_id, artist_name, num_followers, primary_genre) VALUES (6, 'Kendrick Lamar', 10000000, 'Hip Hop'); | What are the primary genres and the number of artists for each, for artists with more than 5 million followers? | SELECT primary_genre, COUNT(artist_id) as num_artists FROM artist WHERE num_followers > 5000000 GROUP BY primary_genre; | gretelai_synthetic_text_to_sql |
CREATE TABLE Games (GameID INT, GameName VARCHAR(100), Genre VARCHAR(50), AdoptionRevenue DECIMAL(10,2), Country VARCHAR(50)); INSERT INTO Games (GameID, GameName, Genre, AdoptionRevenue, Country) VALUES (1, 'Racing Game A', 'racing', 300.00, 'USA'), (2, 'RPG Game B', 'RPG', 400.00, 'Canada'), (3, 'Strategy Game C', 'strategy', 500.00, 'Mexico'); | What is the total revenue of games with a "racing" genre in North America? | SELECT SUM(AdoptionRevenue) FROM Games WHERE Genre = 'racing' AND Country = 'North America'; | gretelai_synthetic_text_to_sql |
CREATE TABLE communities_indigenous (community_id INT, community_name VARCHAR(100), region VARCHAR(50)); INSERT INTO communities_indigenous VALUES (1, 'Indigenous Australian STEM', 'Oceania'), (2, 'Maori AI Learners', 'Oceania'); CREATE TABLE university_programs (program_id INT, program_name VARCHAR(100), community_id INT); INSERT INTO university_programs VALUES (1, 'AI for Good', 1), (2, 'AI Ethics', 1), (3, 'AI Basics', 2); CREATE TABLE participation (participation_id INT, participant_id INT, program_id INT, hours DECIMAL(5,2)); INSERT INTO participation VALUES (1, 1, 1, 20.00), (2, 2, 1, 25.00), (3, 3, 2, 15.00); | What is the total number of hours spent by indigenous communities on AI training programs in universities in Oceania? | SELECT SUM(hours) FROM participation INNER JOIN university_programs ON participation.program_id = university_programs.program_id INNER JOIN communities_indigenous ON university_programs.community_id = communities_indigenous.community_id WHERE communities_indigenous.region = 'Oceania'; | gretelai_synthetic_text_to_sql |
CREATE TABLE HeritageSites (SiteID INT, SiteName VARCHAR(100), Country VARCHAR(50), Region VARCHAR(50), IsUNESCOWorldHeritageSite BOOLEAN, UNIQUE (SiteID)); | Provide the total number of heritage sites in the Asia-Pacific region, not including UNESCO World Heritage Sites. | SELECT COUNT(*) FROM HeritageSites WHERE Region = 'Asia-Pacific' AND IsUNESCOWorldHeritageSite = FALSE; | gretelai_synthetic_text_to_sql |
CREATE TABLE garment_manufacturing (garment_category VARCHAR(255), manufacturing_date DATE, co2_emissions INT); | Calculate the average CO2 emissions for each garment category in 2020. | SELECT garment_category, AVG(co2_emissions) FROM garment_manufacturing WHERE manufacturing_date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY garment_category; | gretelai_synthetic_text_to_sql |
CREATE TABLE AccessToJusticePetitions (id INT, petition_date DATE, petitions INT); INSERT INTO AccessToJusticePetitions (id, petition_date, petitions) VALUES (1, '2022-01-01', 1000), (2, '2022-02-01', 1500), (3, '2022-03-01', 1800), (4, '2022-04-01', 2000), (5, '2022-05-01', 2500); | What is the change in the number of access to justice petitions per month? | SELECT EXTRACT(MONTH FROM petition_date) as month, (LEAD(petitions) OVER (ORDER BY petition_date) - petitions) as change FROM AccessToJusticePetitions; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName TEXT, TotalDonation DECIMAL); | What is the total amount donated by each donor in descending order? | SELECT DonorName, SUM(TotalDonation) OVER (PARTITION BY DonorName ORDER BY SUM(TotalDonation) DESC) AS TotalDonation FROM Donors; | gretelai_synthetic_text_to_sql |
CREATE TABLE PlayerGameGenre (PlayerID INT, Age INT, GameGenre VARCHAR(30)); INSERT INTO PlayerGameGenre (PlayerID, Age, GameGenre) VALUES (1, 16, 'FPS'), (2, 20, 'RPG'), (3, 18, 'FPS'), (4, 25, 'Simulation'); | What is the most popular game genre among players aged 18 or above? | SELECT GameGenre, COUNT(*) as GameCount FROM PlayerGameGenre WHERE Age >= 18 GROUP BY GameGenre ORDER BY GameCount DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE policies (id INT, policy_name VARCHAR(255), last_updated_date DATE); INSERT INTO policies (id, policy_name, last_updated_date) VALUES (1, 'Access Control', '2022-01-01'), (2, 'Incident Response', '2022-01-15'), (3, 'Data Privacy', '2022-02-10'), (4, 'Network Security', '2022-03-05'); | Which policies have been updated in the last 30 days? Provide the output in the format: policy_name, last_updated_date. | SELECT policy_name, last_updated_date FROM policies WHERE last_updated_date >= DATE(NOW()) - INTERVAL 30 DAY; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name TEXT, country TEXT); CREATE TABLE donations (id INT, donor_id INT, organization_id INT); CREATE TABLE organizations (id INT, name TEXT, cause_area TEXT, country TEXT); CREATE TABLE countries (id INT, name TEXT, continent TEXT); | How many unique donors have made donations to organizations focused on human rights, categorized by continent? | SELECT c.continent, COUNT(DISTINCT d.id) as num_unique_donors FROM donors d INNER JOIN donations ON d.id = donations.donor_id INNER JOIN organizations o ON donations.organization_id = o.id INNER JOIN countries ON d.country = countries.name WHERE o.cause_area = 'human rights' GROUP BY c.continent; | gretelai_synthetic_text_to_sql |
CREATE TABLE peacekeeping_operations (operation_name VARCHAR(50), country VARCHAR(50), years_participated INT); INSERT INTO peacekeeping_operations (operation_name, country, years_participated) VALUES ('MINUSTAH', 'United States', 13), ('MONUSCO', 'United States', 8), ('UNMISS', 'United States', 10), ('UNAMID', 'United States', 7), ('UNFICYP', 'United States', 5); | In which peacekeeping operations did the US participate the most? | SELECT operation_name, SUM(years_participated) as total_years_participated FROM peacekeeping_operations WHERE country = 'United States' GROUP BY operation_name ORDER BY total_years_participated DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE mitigation (country VARCHAR(255), capacity INT, year INT); | What is the maximum 'renewable energy capacity' added by 'China' in a single 'year' from the 'mitigation' table? | SELECT MAX(capacity) FROM mitigation WHERE country = 'China' GROUP BY year; | gretelai_synthetic_text_to_sql |
CREATE TABLE graduate_students (student_id INT, name VARCHAR(50), country VARCHAR(50)); INSERT INTO graduate_students (student_id, name, country) VALUES (1, 'Alice', 'Egypt'), (2, 'Bob', 'Canada'), (3, 'Carlos', 'Mexico'), (4, 'Diana', 'South Africa'), (5, 'Eli', 'Nigeria'); CREATE TABLE academic_publications (publication_id INT, student_id INT, title VARCHAR(50)); INSERT INTO academic_publications (publication_id, student_id) VALUES (1, 1), (2, 1), (3, 3), (4, 4), (5, 4), (6, 4), (7, 4), (8, 5), (9, 5), (10, 5); | What is the number of academic publications per graduate student from Africa? | SELECT gs.country, COUNT(ap.publication_id) AS num_publications FROM graduate_students gs JOIN academic_publications ap ON gs.student_id = ap.student_id WHERE gs.country IN ('Egypt', 'South Africa', 'Nigeria') GROUP BY gs.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_offset_programs (id INT, name TEXT, start_date DATE, end_date DATE); INSERT INTO carbon_offset_programs (id, name, start_date, end_date) VALUES (1, 'Trees for the Future', '2020-01-01', '2022-12-31'); INSERT INTO carbon_offset_programs (id, name, start_date, end_date) VALUES (2, 'Clean Oceans', '2019-07-01', '2021-06-30'); INSERT INTO carbon_offset_programs (id, name, start_date, end_date) VALUES (3, 'Green Cities', '2021-01-01', '2023-12-31'); INSERT INTO carbon_offset_programs (id, name, start_date, end_date) VALUES (4, 'Eco Driving', '2018-04-01', '2022-03-31'); | Delete the carbon offset program with id 4 | DELETE FROM carbon_offset_programs WHERE id = 4; | gretelai_synthetic_text_to_sql |
CREATE TABLE production_costs (item_type VARCHAR(20), collection VARCHAR(20), cost NUMERIC(10,2), quantity INT); INSERT INTO production_costs (item_type, collection, cost, quantity) VALUES ('cashmere sweater', 'autumn 2021', 32.99, 100), ('cashmere scarf', 'autumn 2021', 35.99, 75), ('cotton t-shirt', 'autumn 2021', 12.99, 250), ('cotton hoodie', 'autumn 2021', 29.99, 150); | How many items were produced in the 'autumn 2021' collection with a production cost above 30? | SELECT COUNT(*) FROM production_costs WHERE collection = 'autumn 2021' AND cost > 30; | gretelai_synthetic_text_to_sql |
CREATE TABLE Music (song_id INT, title TEXT, genre TEXT); INSERT INTO Music (song_id, title, genre) VALUES (1, 'SongA', 'Rock'), (2, 'SongB', 'Jazz'), (3, 'SongC', 'Hip-Hop'), (4, 'SongD', 'Country'), (5, 'SongE', 'RnB'); | Update the music genre for 'SongE' to 'Pop' in the Music table. | UPDATE Music SET genre = 'Pop' WHERE title = 'SongE'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Artists (ArtistID INT PRIMARY KEY, Name VARCHAR(255), Nationality VARCHAR(255)); CREATE TABLE Artworks (ArtworkID INT PRIMARY KEY, Title VARCHAR(255), ArtistID INT, Year INT); CREATE TABLE Exhibitions (ExhibitionID INT PRIMARY KEY, Name VARCHAR(255), StartDate DATE, EndDate DATE, City VARCHAR(255)); CREATE TABLE ExhibitionArtworks (ExhibitionID INT, ArtworkID INT); | Which artworks were exhibited in both Paris and New York? | SELECT Artworks.Title FROM Artworks INNER JOIN ExhibitionArtworks ON Artworks.ArtworkID = ExhibitionArtworks.ArtworkID INNER JOIN Exhibitions ON ExhibitionArtworks.ExhibitionID = Exhibitions.ExhibitionID WHERE Exhibitions.City IN ('Paris', 'New York') GROUP BY Artworks.Title HAVING COUNT(DISTINCT Exhibitions.City) = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE trends (id INT, trend_name VARCHAR(50), region VARCHAR(50), forecast VARCHAR(50), popularity INT); | Select all records from trends table where region='Asia' and forecast='Spring' | SELECT * FROM trends WHERE region = 'Asia' AND forecast = 'Spring'; | gretelai_synthetic_text_to_sql |
CREATE TABLE schools (school_id INT, school_name TEXT, num_students INT); CREATE TABLE projects (project_id INT, project_name TEXT, school_id INT, student_id INT, num_projects INT); INSERT INTO schools (school_id, school_name, num_students) VALUES (1, 'Innovation School', 100), (2, 'Creativity School', 120), (3, 'Discovery School', 150); INSERT INTO projects (project_id, project_name, school_id, student_id, num_projects) VALUES (1, 'Open Source Software', 1, 1, 20), (2, 'Online Tutoring', 1, 2, 25), (3, 'Research Paper', 2, 1, 30), (4, 'Community Service', 2, 2, 22), (5, 'Art Portfolio', 3, 1, 35), (6, 'Science Experiment', 3, 2, 40); | What is the maximum number of open pedagogy projects completed by students in each school? | SELECT school_name, MAX(num_projects) as max_projects FROM schools JOIN projects ON schools.school_id = projects.school_id GROUP BY school_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales (product_id INT, region VARCHAR(255), quantity INT, ethical_source BOOLEAN); INSERT INTO sales (product_id, region, quantity, ethical_source) VALUES (1, 'North', 100, true), (2, 'South', 200, false), (3, 'East', 150, true); | What is the total quantity of ethically sourced products sold by region? | SELECT region, ethical_source, SUM(quantity) AS total_quantity FROM sales GROUP BY region, ethical_source; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonationDate DATE, DonationAmount DECIMAL(10,2), ProgramID INT); INSERT INTO Donations (DonationID, DonationDate, DonationAmount, ProgramID) VALUES (10, '2022-05-01', 550.00, 1), (11, '2022-05-15', 650.00, 1), (12, '2022-05-01', 750.00, 2), (13, '2022-05-15', 850.00, 2), (14, '2022-06-01', 950.00, 3); | What is the total donation amount per program in the last 3 months? | SELECT ProgramID, SUM(DonationAmount) OVER (PARTITION BY ProgramID ORDER BY DonationDate ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS TotalDonationInLast3Months FROM Donations; | gretelai_synthetic_text_to_sql |
CREATE TABLE ModelScores (model_id INT, score FLOAT, dev_region VARCHAR(255), model_year INT); INSERT INTO ModelScores (model_id, score, dev_region, model_year) VALUES (1, 8.5, 'Africa', 2020), (2, 9.2, 'Asia', 2021), (3, 8.8, 'Europe', 2022); | Find the average safety score of AI models created by African researchers since 2020. | SELECT AVG(score) FROM ModelScores WHERE dev_region = 'Africa' AND model_year >= 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE defense_contractors_3 (corp varchar(255), year int, sales int); INSERT INTO defense_contractors_3 (corp, year, sales) VALUES ('ABC Corp', 2019, 800000), ('ABC Corp', 2020, 900000), ('ABC Corp', 2021, 1000000); | What is the total military equipment sales revenue for 'ABC Corp' from 2019 to 2021? | SELECT SUM(sales) FROM defense_contractors_3 WHERE corp = 'ABC Corp' AND year BETWEEN 2019 AND 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE community_policing_interactions (id SERIAL PRIMARY KEY, neighborhood_id INTEGER, interaction_type VARCHAR(255), interaction_count INTEGER); CREATE TABLE neighborhoods (id SERIAL PRIMARY KEY, name VARCHAR(255), location POINT, radius INTEGER); INSERT INTO neighborhoods (name, location, radius) VALUES ('Downtown', '(40.7128, -74.0060)', 1); INSERT INTO community_policing_interactions (neighborhood_id, interaction_type, interaction_count) VALUES (1, 'Foot Patrol', 15), (1, 'Bike Patrol', 5), (2, 'Foot Patrol', 12); | Find the number of community policing interactions for each interaction type in the Downtown neighborhood | SELECT interaction_type, SUM(interaction_count) as total_interactions FROM community_policing_interactions cpi JOIN neighborhoods n ON n.id = cpi.neighborhood_id WHERE n.name = 'Downtown' GROUP BY interaction_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE conservation_initiatives (region VARCHAR(50), date DATE, initiative VARCHAR(50)); INSERT INTO conservation_initiatives (region, date, initiative) VALUES ('Sydney', '2017-01-01', 'Rainwater harvesting'), ('Sydney', '2016-01-01', 'Greywater reuse'), ('Sydney', '2015-01-01', 'Smart irrigation'); | Find the number of water conservation initiatives implemented in 'Sydney' before 2018 | SELECT COUNT(*) FROM conservation_initiatives WHERE region = 'Sydney' AND date < '2018-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, FirstName TEXT, LastName TEXT, Country TEXT); INSERT INTO Donors (DonorID, FirstName, LastName, Country) VALUES (1, 'John', 'Doe', 'USA'), (2, 'Jane', 'Smith', 'USA'); CREATE TABLE Donations (DonationID INT, DonorID INT, Amount DECIMAL); INSERT INTO Donations (DonationID, DonorID, Amount) VALUES (1, 1, 500), (2, 1, 750), (3, 2, 1000); | What is the total amount donated by each donor from the United States, including their contact information? | SELECT D.FirstName, D.LastName, D.Country, SUM(DON.Amount) AS TotalDonated FROM Donors D INNER JOIN Donations DON ON D.DonorID = DON.DonorID WHERE D.Country = 'USA' GROUP BY D.DonorID; | gretelai_synthetic_text_to_sql |
CREATE TABLE sports_team_performance (team_name VARCHAR(20), wins INT, losses INT); INSERT INTO sports_team_performance (team_name, wins, losses) VALUES ('Los Angeles Lakers', 55, 27), ('Boston Celtics', 48, 34); | Delete all records from the 'sports_team_performance' table where the 'team_name' is 'Los Angeles Lakers' | DELETE FROM sports_team_performance WHERE team_name = 'Los Angeles Lakers'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName TEXT, State TEXT, Country TEXT, TotalDonation DECIMAL); CREATE TABLE Donations (DonationID INT, DonorID INT, DonationDate DATE, DonationAmount DECIMAL); | List the top 5 donors by total donation amount in the year 2019, showing their total donation amount, state, and country. | SELECT D.DonorName, SUM(D.DonationAmount) as TotalDonation, D.State, D.Country FROM Donations D JOIN Donors DON ON D.DonorID = DON.DonorID WHERE YEAR(D.DonationDate) = 2019 GROUP BY D.DonorName, D.State, D.Country ORDER BY TotalDonation DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE UNESCO_SITES (id INT PRIMARY KEY, name VARCHAR(255), region VARCHAR(255), type VARCHAR(255)); INSERT INTO UNESCO_SITES (id, name, region, type) VALUES (1, 'Colosseum', 'Europe', 'Cultural'); | What are the names of UNESCO heritage sites in Europe and their types? | SELECT name, type FROM UNESCO_SITES WHERE region = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE astronauts (astronaut_id INT, name VARCHAR(255), gender VARCHAR(255), age INT, country VARCHAR(255), missions INT); INSERT INTO astronauts (astronaut_id, name, gender, age, country, missions) VALUES (1, 'Yuri Gagarin', 'Male', 41, 'Russia', 1); | What is the total number of missions for astronauts from Russia? | SELECT country, SUM(missions) as total_missions FROM astronauts WHERE country = 'Russia' GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE ReindeerData (reindeer_name VARCHAR(50), county VARCHAR(50), population INT); INSERT INTO ReindeerData (reindeer_name, county, population) VALUES ('Finnmark Reindeer', 'Finnmark County', 15000), ('Sami Reindeer', 'Finnmark County', 20000); | What is the total number of reindeer in Norway's Finnmark County? | SELECT county, SUM(population) FROM ReindeerData WHERE reindeer_name IN ('Finnmark Reindeer', 'Sami Reindeer') GROUP BY county; | gretelai_synthetic_text_to_sql |
CREATE TABLE Students (StudentID INT, Name VARCHAR(50), Disability VARCHAR(50)); CREATE TABLE StudentAccommodations (StudentID INT, AccommodationID INT, StartDate DATE, EndDate DATE); CREATE TABLE Accommodations (AccommodationID INT, Accommodation VARCHAR(100), Description TEXT); CREATE TABLE ExamResults (ExamID INT, StudentID INT, Score INT); | What is the average score for students who have received extended time accommodation? | SELECT AVG(er.Score) as AverageScore FROM ExamResults er JOIN Students s ON er.StudentID = s.StudentID JOIN StudentAccommodations sa ON s.StudentID = sa.StudentID JOIN Accommodations a ON sa.AccommodationID = a.AccommodationID WHERE a.Accommodation = 'Extended time'; | gretelai_synthetic_text_to_sql |
CREATE TABLE museums (id INT, name TEXT, city TEXT);CREATE TABLE museum_visitors (id INT, visitor_id INT, museum_id INT, country TEXT);CREATE TABLE visitors (id INT, name TEXT); | Which museum has the most international visitors in the last 6 months? | SELECT m.name, COUNT(mv.visitor_id) as num_visitors FROM museums m JOIN museum_visitors mv ON m.id = mv.museum_id JOIN visitors v ON mv.visitor_id = v.id WHERE v.country != 'USA' AND mv.visit_date >= DATEADD(month, -6, GETDATE()) GROUP BY m.name ORDER BY num_visitors DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE if NOT EXISTS tours (id INT, name TEXT, rating FLOAT, vegetarian_meal BOOLEAN); INSERT INTO tours (id, name, rating, vegetarian_meal) VALUES (1, 'Mountain Biking Adventure', 4.5, true), (2, 'Historic City Tour', 4.2, false); | What is the average rating of tours in Asia with a vegetarian meal option? | SELECT AVG(rating) FROM tours WHERE vegetarian_meal = true AND country = 'Asia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE user_calories (user_id INT, date DATE, calories INT, class VARCHAR(50)); INSERT INTO user_calories (user_id, date, calories, class) VALUES (1, '2022-01-01', 300, 'Zumba'), (1, '2022-01-02', 350, 'Zumba'), (2, '2022-01-01', 250, 'Yoga'), (2, '2022-01-02', 200, 'Yoga'), (1, '2022-01-03', 400, 'Zumba'); | Calculate the average calories burned per day for all users who participated in 'Zumba' classes. | SELECT AVG(calories) FROM user_calories WHERE class = 'Zumba'; | gretelai_synthetic_text_to_sql |
CREATE TABLE olympic_athletes (athlete_id INT, name VARCHAR(50), country VARCHAR(50), medals INT); INSERT INTO olympic_athletes (athlete_id, name, country, medals) VALUES (1, 'Usain Bolt', 'Jamaica', 8); | How many Olympic medals has Usain Bolt won? | SELECT medals FROM olympic_athletes WHERE name = 'Usain Bolt'; | gretelai_synthetic_text_to_sql |
CREATE TABLE equipment_sales (id INT, country VARCHAR(50), equipment_type VARCHAR(50), year INT, sales INT); INSERT INTO equipment_sales (id, country, equipment_type, year, sales) VALUES (1, 'USA', 'Tanks', 2018, 5000000), (2, 'USA', 'Aircraft', 2018, 12000000), (3, 'China', 'Tanks', 2018, 800000), (4, 'China', 'Aircraft', 2018, 1500000), (5, 'France', 'Tanks', 2018, 600000), (6, 'France', 'Aircraft', 2018, 1800000); | What is the total value of military equipment sales to each country in the current year? | SELECT country, SUM(sales) as total_sales FROM equipment_sales WHERE year = YEAR(CURRENT_TIMESTAMP) GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE property_co_ownership (id INT, property_id INT, co_owner_id INT, agreement_start_date DATE, agreement_end_date DATE); | Which properties in the 'property_co_ownership' table are co-owned by a person with id 5? | SELECT property_id FROM property_co_ownership WHERE co_owner_id = 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE Dams (ID INT, Name VARCHAR(50), Location VARCHAR(50), Length FLOAT, YearBuilt INT); INSERT INTO Dams (ID, Name, Location, Length, YearBuilt) VALUES (1, 'Hoover Dam', 'Nevada/Arizona border', 247.0, 1936); INSERT INTO Dams (ID, Name, Location, Length, YearBuilt) VALUES (2, 'Oroville Dam', 'Butte County, CA', 2302.0, 1968); | What is the name and ID of the longest dam in the 'Dams' table? | SELECT Name, ID FROM Dams WHERE Length = (SELECT MAX(Length) FROM Dams); | gretelai_synthetic_text_to_sql |
CREATE TABLE SustainableTrends (id INT, trend VARCHAR(255), sustainability_score INT); INSERT INTO SustainableTrends (id, trend, sustainability_score) VALUES (1, 'Organic Cotton T-Shirt', 90), (2, 'Recycled Polyester Hoodie', 80), (3, 'Bamboo Viscose Pants', 85); CREATE TABLE CustomerSizes (id INT, size VARCHAR(255), country VARCHAR(255), percentage DECIMAL(4,2)); INSERT INTO CustomerSizes (id, size, country, percentage) VALUES (1, 'XS', 'Australia', 5.00), (2, 'S', 'Australia', 10.00), (3, 'M', 'Australia', 15.00), (4, 'L', 'Australia', 20.00), (5, 'XL', 'Australia', 30.00); | What is the most popular sustainable fashion trend among customers of different sizes in Australia? | SELECT st.trend, c.size, MAX(c.percentage) AS popularity FROM SustainableTrends st CROSS JOIN CustomerSizes c WHERE c.country = 'Australia' GROUP BY st.trend, c.size; | gretelai_synthetic_text_to_sql |
CREATE TABLE Matches (MatchID int, PlayerID int, Game varchar(255), MatchResult varchar(255)); INSERT INTO Matches VALUES (1, 1, 'CS:GO', 'Win'), (2, 2, 'CS:GO', 'Loss'), (3, 1, 'Dota 2', 'Win'), (4, 3, 'Dota 2', 'Win'); | Which players have the highest number of wins in multiplayer matches? | SELECT PlayerID, COUNT(*) as Wins FROM Matches WHERE MatchResult = 'Win' GROUP BY PlayerID ORDER BY Wins DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Volunteers (VolunteerID int, Name varchar(50), Donation decimal(10,2)); INSERT INTO Volunteers (VolunteerID, Name, Donation) VALUES (1, 'John Doe', 100.00), (2, 'Jane Smith', 200.00), (3, 'Mike Johnson', 50.00); | Which volunteers have donated the most money? | SELECT Name, SUM(Donation) as TotalDonations FROM Volunteers GROUP BY Name ORDER BY TotalDonations DESC | gretelai_synthetic_text_to_sql |
CREATE TABLE Stores (id INT, name VARCHAR(255), region VARCHAR(255)); INSERT INTO Stores (id, name, region) VALUES (1, 'Store A', 'West'), (2, 'Store B', 'West'), (3, 'Store C', 'East'), (4, 'Store D', 'East'); CREATE TABLE Organic_Cotton_Sales (id INT, store_id INT, quarter INT, year INT, units INT); INSERT INTO Organic_Cotton_Sales (id, store_id, quarter, year, units) VALUES (1, 1, 3, 2021, 200), (2, 2, 3, 2021, 250), (3, 3, 3, 2021, 300), (4, 4, 3, 2021, 350); | How many units of organic cotton garments were sold by each store in the 'West' region in Q3 of 2021? | SELECT s.name, SUM(o.units) FROM Organic_Cotton_Sales o JOIN Stores s ON o.store_id = s.id WHERE o.quarter = 3 AND o.year = 2021 AND s.region = 'West' GROUP BY s.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE drug (drug_code CHAR(5), drug_name VARCHAR(100)); | Insert a new drug with a given code and name into the drug table | INSERT INTO drug (drug_code, drug_name) VALUES ('DR003', 'DrugC'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Departments (id INT, department_name VARCHAR(50), employee_id INT); CREATE TABLE Employees (id INT, salary DECIMAL(10, 2)); | Identify the departments with the highest and lowest number of employees | SELECT department_name, COUNT(*) AS employees_count FROM Departments JOIN Employees ON Departments.employee_id = Employees.id GROUP BY department_name ORDER BY employees_count DESC, department_name LIMIT 1; SELECT department_name, COUNT(*) AS employees_count FROM Departments JOIN Employees ON Departments.employee_id = Employees.id GROUP BY department_name ORDER BY employees_count ASC, department_name LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, donation_amount DECIMAL(10, 2), donation_date DATE); INSERT INTO donations (id, donation_amount, donation_date) VALUES (1, 50.00, '2021-01-01'); INSERT INTO donations (id, donation_amount, donation_date) VALUES (2, 100.00, '2021-02-01'); | What is the total donation amount per month in 2021? | SELECT DATE_FORMAT(donation_date, '%Y-%m') as month, SUM(donation_amount) as total_donations FROM donations WHERE donation_date >= '2021-01-01' AND donation_date < '2022-01-01' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE explainability_audits (id INT, model_id INT, explanation_score INT, created_at DATETIME); INSERT INTO explainability_audits (id, model_id, explanation_score, created_at) VALUES (1, 1, 7, '2021-01-01'); INSERT INTO explainability_audits (id, model_id, explanation_score, created_at) VALUES (2, 2, 8, '2021-01-02'); INSERT INTO explainability_audits (id, model_id, explanation_score, created_at) VALUES (3, 2, 8, '2021-01-03'); INSERT INTO explainability_audits (id, model_id, explanation_score, created_at) VALUES (4, 3, 9, '2021-01-04'); | What is the maximum explanation score for each model, and how many times does each model achieve that score? | SELECT model_id, MAX(explanation_score) as max_explanation_score, COUNT(*) as count FROM explainability_audits GROUP BY model_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE wildlife_habitats (id INT, name VARCHAR(50), area FLOAT, region VARCHAR(50)); INSERT INTO wildlife_habitats (id, name, area, region) VALUES (1, 'Habitat 1', 800.0, 'North America'), (2, 'Habitat 2', 600.0, 'South America'); | Which wildlife habitats in 'North America' have an area larger than 700? | SELECT name FROM wildlife_habitats WHERE area > 700 AND region = 'North America'; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_projects (id INT, project_name VARCHAR(100), country VARCHAR(50), capacity FLOAT); INSERT INTO renewable_projects (id, project_name, country, capacity) VALUES (1, 'Solar Farm Canada', 'Canada', 789.12), (2, 'Wind Farm Canada', 'Canada', 1500.78), (3, 'Hydro Plant Canada', 'Canada', 450.34); | How many renewable energy projects are in Canada with an installed capacity greater than 500? | SELECT COUNT(*) FROM renewable_projects WHERE country = 'Canada' AND capacity > 500; | gretelai_synthetic_text_to_sql |
CREATE TABLE VolunteerPrograms (VolunteerID INT, ProgramID INT, VolunteerDate DATE); INSERT INTO VolunteerPrograms (VolunteerID, ProgramID, VolunteerDate) VALUES (1, 1, '2020-01-01'), (2, 1, '2020-02-01'), (3, 2, '2020-03-01'); | How many volunteers were engaged in each program in 2020, sorted by the highest number of volunteers? | SELECT Programs.ProgramName, COUNT(DISTINCT VolunteerPrograms.VolunteerID) as VolunteerCount FROM Programs INNER JOIN VolunteerPrograms ON Programs.ProgramID = VolunteerPrograms.ProgramID WHERE YEAR(VolunteerPrograms.VolunteerDate) = 2020 GROUP BY Programs.ProgramName ORDER BY VolunteerCount DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(50), email VARCHAR(50), signup_date DATE, signup_source VARCHAR(20)); | List all users who signed up using email | SELECT * FROM users WHERE signup_source = 'email'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (species_id SERIAL PRIMARY KEY, species_name VARCHAR(50), ocean_name VARCHAR(50), sighting_date DATE); | Insert a new marine species 'Giant Squid' in the 'Pacific Ocean' and return the ID of the inserted record. | INSERT INTO marine_species (species_name, ocean_name, sighting_date) VALUES ('Giant Squid', 'Pacific Ocean', '2022-08-01') RETURNING species_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE DeepOceanExploration (id INT, name TEXT, latitude REAL, longitude REAL, depth REAL); INSERT INTO DeepOceanExploration (id, name, latitude, longitude, depth) VALUES (1, 'Station 1', 15.4948, -61.3704, 6000); INSERT INTO DeepOceanExploration (id, name, latitude, longitude, depth) VALUES (2, 'Station 2', 44.6419, -63.5742, 5500); | What is the minimum depth of all stations in the Deep Ocean Exploration database? | SELECT MIN(depth) FROM DeepOceanExploration; | gretelai_synthetic_text_to_sql |
CREATE TABLE clients (client_id INT, name VARCHAR(50), total_assets DECIMAL(10,2), primary_residence VARCHAR(50));CREATE TABLE transactions (transaction_id INT, client_id INT, transaction_date DATE); | What is the maximum total assets value for clients with a primary residence in California in Q4 2022? | SELECT MAX(total_assets) FROM clients c INNER JOIN transactions t ON c.client_id = t.client_id WHERE c.primary_residence = 'California' AND t.transaction_date BETWEEN '2022-10-01' AND '2022-12-31' | gretelai_synthetic_text_to_sql |
CREATE TABLE mlb_season (team_id INT, team_name VARCHAR(50), games_played INT, runs_home INT, runs_away INT); INSERT INTO mlb_season (team_id, team_name, games_played, runs_home, runs_away) VALUES (1, 'Los Angeles Dodgers', 162, 834, 653); | What is the difference in total runs scored between the home and away games for each team in the 2021 MLB season? | SELECT team_name, (runs_home - runs_away) as diff FROM mlb_season; | gretelai_synthetic_text_to_sql |
CREATE TABLE articles (id INT, title TEXT, category TEXT, likes INT); INSERT INTO articles (id, title, category, likes) VALUES (1, 'Climate Crisis Explained', 'climate_change', 1500); CREATE TABLE users (id INT, name TEXT, age INT); INSERT INTO users (id, name, age) VALUES (1, 'John Doe', 35), (2, 'Jane Smith', 42); | What is the average age of users who liked articles related to climate change? | SELECT AVG(age) FROM users JOIN (SELECT user_id FROM article_likes WHERE article_category = 'climate_change') AS liked_articles ON users.id = liked_articles.user_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE nhl_player_positions (id INT, name VARCHAR(100), position VARCHAR(50)); INSERT INTO nhl_player_positions (id, name, position) VALUES (1, 'Alex Ovechkin', 'Left Wing'), (2, 'Connor McDavid', 'Center'), (3, 'Sidney Crosby', 'Center'), (4, 'Patrick Kane', 'Right Wing'), (5, 'Victor Hedman', 'Defenseman'), (6, 'Andrei Vasilevskiy', 'Goalie'); | Count the number of players in each position group in the NHL. | SELECT position, COUNT(*) FROM nhl_player_positions GROUP BY position; | gretelai_synthetic_text_to_sql |
CREATE TABLE multimodal_trips (id INT, trips INT, city VARCHAR(50)); | What is the total number of multimodal trips taken in New York City? | SELECT SUM(trips) FROM multimodal_trips WHERE city = 'New York City'; | gretelai_synthetic_text_to_sql |
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