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 garment_info (garment_id INT, sustainability_rating DECIMAL(3, 2)); INSERT INTO garment_info (garment_id, sustainability_rating) VALUES (1001, 4.2), (1002, 3.5), (1003, 4.8), (1004, 2.9), (1005, 4.5), (1006, 3.7); CREATE TABLE garment_manufacturing (manufacturing_id INT, garment_id INT, country VARCHAR(255)); INSERT INTO garment_manufacturing (manufacturing_id, garment_id, country) VALUES (1, 1001, 'India'), (2, 1002, 'Vietnam'), (3, 1003, 'UK'), (4, 1004, 'China'), (5, 1005, 'Bangladesh'), (6, 1006, 'Indonesia'); | What is the average sustainability rating for garments manufactured in Asia? | SELECT AVG(g.sustainability_rating) AS avg_sustainability_rating FROM garment_info g INNER JOIN garment_manufacturing m ON g.garment_id = m.garment_id WHERE m.country IN ('India', 'Vietnam', 'China', 'Bangladesh', 'Indonesia'); | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, industry TEXT, founding_date DATE, founder_race TEXT);CREATE TABLE company_founders (company_id INT, founder_id INT);CREATE TABLE founders (id INT, race TEXT); | Identify the number of unique companies founded by a person who identifies as a person of color in the cleantech industry. | SELECT COUNT(DISTINCT companies.id) FROM companies INNER JOIN company_founders ON companies.id = company_founders.company_id INNER JOIN founders ON company_founders.founder_id = founders.id WHERE companies.industry = 'cleantech' AND founders.race = 'person of color'; | gretelai_synthetic_text_to_sql |
CREATE TABLE green_blogs (id INT, title TEXT, content TEXT, likes INT); | Get the average number of likes for posts containing the word "sustainability" in the "green_blogs" table. | SELECT AVG(likes) FROM green_blogs WHERE content LIKE '%sustainability%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE creators (id INT, underrepresented BOOLEAN, hours_of_content FLOAT); INSERT INTO creators (id, underrepresented, hours_of_content) VALUES (1, TRUE, 10.5), (2, FALSE, 15.2), (3, TRUE, 8.9); | What's the total number of hours of content produced by creators from underrepresented communities? | SELECT SUM(hours_of_content) FROM creators WHERE underrepresented = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE Sales (salesperson_id INT, salesperson_name TEXT, virtual_tours INT); INSERT INTO Sales (salesperson_id, salesperson_name, virtual_tours) VALUES (1, 'Samira Rodriguez', 12), (2, 'Hiroshi Nakamura', 17); | What is the average number of virtual tours per salesperson in the 'Sales' table? | SELECT AVG(virtual_tours) FROM Sales; | gretelai_synthetic_text_to_sql |
CREATE TABLE world_heritage_sites (site_id INT, name TEXT, location TEXT, rating FLOAT); INSERT INTO world_heritage_sites (site_id, name, location, rating) VALUES (1, 'Mount Fuji', 'Japan', 4.3), (2, 'Himeji Castle', 'Japan', 4.8); | Which UNESCO World Heritage sites in Japan have a rating higher than 4.5? | SELECT name FROM world_heritage_sites WHERE location = 'Japan' AND rating > 4.5; | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_biomass (id INT, farm_id INT, species TEXT, biomass INT, country TEXT, water_type TEXT); INSERT INTO fish_biomass (id, farm_id, species, biomass, country, water_type) VALUES (1, 1, 'Seabass', 2000, 'Greece', 'Marine'); INSERT INTO fish_biomass (id, farm_id, species, biomass, country, water_type) VALUES (2, 2, 'Seabream', 2500, 'Greece', 'Marine'); INSERT INTO fish_biomass (id, farm_id, species, biomass, country, water_type) VALUES (3, 3, 'Tilapia', 1500, 'Greece', 'Freshwater'); | What is the total biomass of fish in marine cages in Greece? | SELECT SUM(biomass) FROM fish_biomass WHERE country = 'Greece' AND water_type = 'Marine'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ad_funding (id INT, project VARCHAR(50), region VARCHAR(50), funding FLOAT); INSERT INTO ad_funding VALUES (1, 'Project Gamma', 'Europe', 6000000); INSERT INTO ad_funding VALUES (2, 'Project Delta', 'Asia', 5500000); | Get total funding for autonomous driving research projects in Europe | SELECT SUM(funding) FROM ad_funding WHERE region = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE agents (agent_id INT, region VARCHAR(20)); CREATE TABLE policyholders (policyholder_id INT, region VARCHAR(20)); CREATE TABLE policies (policy_id INT, agent_id INT, policyholder_id INT, issue_date DATE); INSERT INTO agents (agent_id, region) VALUES (1, 'Southeast'), (2, 'Southeast'), (3, 'Northwest'), (4, 'Northern'); INSERT INTO policyholders (policyholder_id, region) VALUES (1, 'Western'), (2, 'Western'), (3, 'Eastern'), (4, 'Northern'); | Insert a new policy record for agent 4, for a policyholder in the Northern region, for the month of March 2022, with a policy_id of 6. | INSERT INTO policies (policy_id, agent_id, policyholder_id, issue_date) VALUES (6, 4, 4, '2022-03-01'); | gretelai_synthetic_text_to_sql |
CREATE TABLE supply_chain (supplier_id INT, supplier_name TEXT); CREATE TABLE supplier_regions (region_id INT, supplier_id INT, region_name TEXT); | Show the number of suppliers in each region from the supply_chain and supplier_regions tables. | SELECT supplier_regions.region_name, COUNT(supply_chain.supplier_id) FROM supply_chain INNER JOIN supplier_regions ON supply_chain.supplier_id = supplier_regions.supplier_id GROUP BY supplier_regions.region_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Department VARCHAR(20), Salary DECIMAL(10,2)); INSERT INTO Employees (EmployeeID, Department, Salary) VALUES (1, 'IT', 70000.00), (2, 'Marketing', 55000.00), (3, 'Marketing', 58000.00), (4, 'HR', 60000.00), (5, 'HR', 62000.00), (6, 'Diversity & Inclusion', 75000.00); | Update the department of employee with ID 3 to 'Learning & Development'. | UPDATE Employees SET Department = 'Learning & Development' WHERE EmployeeID = 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE fiscal_years (year_id INT, year_start DATE, year_end DATE); INSERT INTO fiscal_years (year_id, year_start, year_end) VALUES (1, '2019-01-01', '2019-12-31'), (2, '2020-01-01', '2020-12-31'), (3, '2021-01-01', '2021-12-31'); CREATE TABLE budget_allocations (budget_id INT, district_id INT, department VARCHAR(50), amount INT, year_id INT); INSERT INTO budget_allocations (budget_id, district_id, department, amount, year_id) VALUES (1, 1, 'Public Transportation', 50000, 1), (2, 1, 'Education', 40000, 1), (3, 2, 'Public Transportation', 45000, 2), (4, 2, 'Healthcare', 55000, 2), (5, 3, 'Public Transportation', 30000, 3), (6, 3, 'Healthcare', 70000, 3); | What is the total budget allocated for public transportation in rural areas in the last 3 years? | SELECT SUM(amount) FROM budget_allocations WHERE department = 'Public Transportation' AND area_type = 'Rural' AND year_id IN (SELECT year_id FROM fiscal_years WHERE year_start >= DATEADD(year, -3, GETDATE())); | gretelai_synthetic_text_to_sql |
CREATE TABLE MentalHealthParity (Region VARCHAR(50), PayerType VARCHAR(50), Score DECIMAL(3,2)); INSERT INTO MentalHealthParity (Region, PayerType, Score) VALUES ('Northeast', 'Medicare', 0.75), ('Northeast', 'Medicaid', 0.78), ('Northeast', 'Private', 0.82), ('Midwest', 'Medicare', 0.72), ('Midwest', 'Medicaid', 0.76), ('Midwest', 'Private', 0.81), ('Southeast', 'Medicare', 0.77), ('Southeast', 'Medicaid', 0.79), ('Southeast', 'Private', 0.84), ('Southwest', 'Medicare', 0.73), ('Southwest', 'Medicaid', 0.75), ('Southwest', 'Private', 0.83), ('West', 'Medicare', 0.76), ('West', 'Medicaid', 0.78), ('West', 'Private', 0.85); | Identify the top 3 regions with the highest mental health parity scores, partitioned by payer type and ordered by the highest mental health parity score within each payer type. | SELECT Region, PayerType, Score, RANK() OVER (PARTITION BY PayerType ORDER BY Score DESC) as Rank FROM MentalHealthParity WHERE Rank <= 3 ORDER BY PayerType, Score DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE departments (id INT, name VARCHAR(50)); CREATE TABLE grants (id INT, department_id INT, amount INT); INSERT INTO departments VALUES (1, 'Psychology'), (2, 'Sociology'), (3, 'Anthropology'); INSERT INTO grants VALUES (1, 1, 5000), (2, 1, 7000), (3, 2, 6000), (4, 3, 4000); | Find the number of grants awarded to each department in the College of Social Sciences. | SELECT department_id, COUNT(*) AS grant_count FROM grants GROUP BY department_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE Artworks (artwork_id INT, title TEXT, creation_year INT, art_movement TEXT); INSERT INTO Artworks (artwork_id, title, creation_year, art_movement) VALUES (1, 'Impression, Sunrise', 1872, 'Impressionism'), (2, 'Water Lilies', 1900, 'Impressionism'); | What are the titles and creation years of all artworks with 'impressionism' in the title? | SELECT title, creation_year FROM Artworks WHERE art_movement LIKE '%impressionism%'; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA peace_operations;CREATE TABLE african_union_operations (operation_name VARCHAR(50), year INT, organization VARCHAR(50));INSERT INTO african_union_operations (operation_name, year, organization) VALUES ('Mali I', 2015, 'African Union'), ('Somalia II', 2016, 'African Union'), ('Darfur', 2017, 'African Union'), ('South Sudan', 2018, 'African Union'), ('Central African Republic', 2019, 'African Union'), ('Mali II', 2020, 'African Union'); | How many peacekeeping operations were conducted by the African Union between 2015 and 2020? | SELECT COUNT(*) FROM peace_operations.african_union_operations WHERE organization = 'African Union' AND year BETWEEN 2015 AND 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE investments (id INT, esg_factor VARCHAR(20)); INSERT INTO investments (id, esg_factor) VALUES (1, 'Carbon Emissions'), (2, 'Water Usage'); | Insert a new ESG factor for the given investment id. | INSERT INTO investments (id, esg_factor) VALUES (3, 'Biodiversity Impact'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Cases (CaseID int, ClientID int, Category varchar(50)); INSERT INTO Cases (CaseID, ClientID, Category) VALUES (201, 2, 'Family'); CREATE TABLE Clients (ClientID int, Age int, Gender varchar(10)); INSERT INTO Clients (ClientID, Age, Gender) VALUES (2, 32, 'Female'); | What is the average age of clients who won cases in the 'family' category? | SELECT AVG(C.Age) as AvgAge FROM Clients C INNER JOIN Cases CA ON C.ClientID = CA.ClientID INNER JOIN CaseOutcomes CO ON CA.CaseID = CO.CaseID WHERE CA.Category = 'Family' AND CO.Outcome = 'Won'; | gretelai_synthetic_text_to_sql |
CREATE TABLE EsportsEvents (EventID INT, Game VARCHAR(20), Spectators INT); INSERT INTO EsportsEvents (EventID, Game, Spectators) VALUES (1, 'Fighting', 5000); | What is the average number of spectators in fighting game esports events? | SELECT AVG(Spectators) FROM EsportsEvents WHERE Game = 'Fighting'; | gretelai_synthetic_text_to_sql |
CREATE TABLE member_demographics (member_id INT, age INT, gender VARCHAR(10), heart_rate INT); INSERT INTO member_demographics (member_id, age, gender, heart_rate) VALUES (1, 27, 'Female', 80), (2, 31, 'Male', 75), (3, 25, 'Male', 90), (4, 28, 'Female', 70), (5, 30, 'Male', 85); | How many male and female members are there in total? | SELECT gender, COUNT(*) FROM member_demographics GROUP BY gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteer_hours (id INT, volunteer_id INT, category VARCHAR(20), hours INT, hour_date DATE); INSERT INTO volunteer_hours (id, volunteer_id, category, hours, hour_date) VALUES (1, 1, 'Education', 5, '2021-01-05'), (2, 2, 'Health', 7, '2021-01-10'), (3, 3, 'Education', 6, '2021-02-15'), (4, 4, 'Arts & Culture', 3, '2021-03-01'), (5, 5, 'Health', 8, '2021-01-20'), (6, 6, 'Education', 9, '2021-02-25'), (7, 7, 'Arts & Culture', 4, '2021-03-10'); | What was the total number of volunteer hours in the 'Education' category in 2021? | SELECT SUM(hours) as total_volunteer_hours FROM volunteer_hours WHERE category = 'Education' AND YEAR(hour_date) = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE Eagle_Ford_Shale (well_id INT, company VARCHAR(255), production_bopd FLOAT); INSERT INTO Eagle_Ford_Shale (well_id, company, production_bopd) VALUES (1, 'Company X', 250), (2, 'Company Y', 300), (3, 'Company X', 350), (4, 'Company Z', 150); | What is the total production for wells in the Eagle Ford Shale owned by Company X? | SELECT SUM(production_bopd) FROM Eagle_Ford_Shale WHERE company = 'Company X'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (donor_id INT, donation_amount DECIMAL(10,2), donor_region VARCHAR(255), donation_date DATE); INSERT INTO Donors (donor_id, donation_amount, donor_region, donation_date) VALUES (1, 500, 'North', '2022-01-01'), (2, 350, 'South', '2022-02-01'), (3, 700, 'East', '2022-03-01'), (4, 280, 'West', '2022-04-01'), (5, 600, 'North', '2022-05-01'); | What was the average donation amount per donor by region for 2022? | SELECT donor_region, AVG(donation_amount) as avg_donation FROM Donors WHERE donation_date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY donor_region; | gretelai_synthetic_text_to_sql |
CREATE TABLE cultural_heritage (id INT, name TEXT, location TEXT, virtual_tour_id INT, rating INT); INSERT INTO cultural_heritage (id, name, location, virtual_tour_id, rating) VALUES (1, 'Acropolis', 'Greece', 1, 4); INSERT INTO cultural_heritage (id, name, location, virtual_tour_id, rating) VALUES (2, 'Machu Picchu', 'Peru', 2, 5); | What is the average virtual tour rating for each cultural heritage site? | SELECT virtual_tour_id, AVG(rating) as avg_rating FROM cultural_heritage GROUP BY virtual_tour_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE open_data_initiatives (initiative VARCHAR(50), num_datasets INT); INSERT INTO open_data_initiatives (initiative, num_datasets) VALUES ('Initiative A', 200), ('Initiative B', 150), ('Initiative C', 250); | What is the maximum number of datasets released in a single open data initiative? | SELECT MAX(num_datasets) FROM open_data_initiatives; | gretelai_synthetic_text_to_sql |
CREATE TABLE lifelong_learners (student_id INT, gender VARCHAR(10), enrolled_in_course BOOLEAN); INSERT INTO lifelong_learners (student_id, gender, enrolled_in_course) VALUES (1, 'Female', true), (2, 'Male', false), (3, 'Female', true), (4, 'Non-binary', true), (5, 'Male', true), (6, 'Female', false); | What is the percentage of lifelong learners by gender? | SELECT gender, (SUM(enrolled_in_course) * 100.0 / COUNT(*)) AS percentage FROM lifelong_learners GROUP BY gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_stock (species VARCHAR(255), harvest_date DATE, quantity INT); | What is the total quantity of fish harvested per species in 2022? | SELECT species, SUM(quantity) AS total_quantity FROM fish_stock WHERE harvest_date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY species; | gretelai_synthetic_text_to_sql |
CREATE TABLE SalesByWeek (SaleID INT, ProductCategory VARCHAR(255), SaleDate DATE); CREATE TABLE QuantitySold (QuantitySoldID INT, SaleID INT, Quantity INT); INSERT INTO SalesByWeek (SaleID, ProductCategory, SaleDate) VALUES (1, 'Flower', '2022-01-01'), (2, 'Concentrates', '2022-01-05'), (3, 'Edibles', '2022-01-10'); INSERT INTO QuantitySold (QuantitySoldID, SaleID, Quantity) VALUES (1, 1, 50), (2, 1, 25), (3, 2, 75), (4, 3, 100); | What is the total quantity of each product category sold in the last week? | SELECT ProductCategory, SUM(Quantity) AS TotalQuantitySold FROM SalesByWeek JOIN QuantitySold ON SalesByWeek.SaleID = QuantitySold.SaleID WHERE SaleDate >= DATEADD(WEEK, -1, GETDATE()) GROUP BY ProductCategory; | gretelai_synthetic_text_to_sql |
CREATE TABLE suppliers (id INT, name TEXT, country TEXT); INSERT INTO suppliers (id, name, country) VALUES (1, 'Supplier A', 'USA'), (2, 'Supplier B', 'Germany'), (3, 'Supplier C', 'France'), (4, 'Supplier D', 'Italy'); CREATE TABLE supplier_products (supplier_id INT, product TEXT); INSERT INTO supplier_products (supplier_id, product) VALUES (1, 'Product X'), (2, 'Product Y'), (3, 'Product Z'), (4, 'Product W'); CREATE TABLE retailer_products (retailer_id INT, product TEXT); INSERT INTO retailer_products (retailer_id, product) VALUES (1, 'Product X'), (1, 'Product Y'), (2, 'Product X'), (2, 'Product Z'), (3, 'Product Y'), (3, 'Product W'); CREATE TABLE retailers (id INT, name TEXT, country TEXT); INSERT INTO retailers (id, name, country) VALUES (1, 'Retailer A', 'USA'), (2, 'Retailer B', 'Germany'), (3, 'Retailer C', 'France'); | List the names of all suppliers that provide products to retailers located in both the US and Europe. | SELECT DISTINCT suppliers.name FROM suppliers INNER JOIN supplier_products ON suppliers.id = supplier_products.supplier_id INNER JOIN retailer_products ON supplier_products.product = retailer_products.product INNER JOIN retailers ON retailer_products.retailer_id = retailers.id WHERE retailers.country IN ('USA', 'Germany', 'France'); | gretelai_synthetic_text_to_sql |
CREATE TABLE projects (id INT, country VARCHAR(50), start_date DATE, end_date DATE, cost FLOAT); INSERT INTO projects (id, country, start_date, end_date, cost) VALUES (1, 'Colombia', '2015-01-01', '2017-12-31', 600000), (2, 'Colombia', '2016-01-01', '2018-12-31', 700000), (3, 'Colombia', '2018-01-01', '2019-12-31', 800000), (4, 'Colombia', '2019-01-01', '2020-12-31', 900000); | What is the total number of rural infrastructure projects in Colombia that were completed before 2018? | SELECT COUNT(*) FROM projects WHERE country = 'Colombia' AND (YEAR(end_date) < 2018 OR end_date IS NULL); | gretelai_synthetic_text_to_sql |
CREATE TABLE painters (name VARCHAR(255), paintings INT); INSERT INTO painters (name, paintings) VALUES ('Leonardo da Vinci', 7), ('Pablo Picasso', 5), ('Vincent van Gogh', 4); | What is the name of the artist who painted the most famous painting? | SELECT name FROM painters WHERE paintings = (SELECT MAX(paintings) FROM painters); | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, age INT, gender TEXT, state TEXT, condition TEXT); INSERT INTO patients (id, age, gender, state, condition) VALUES (1, 45, 'Male', 'New York', 'Depression'); INSERT INTO patients (id, age, gender, state, condition) VALUES (2, 50, 'Female', 'California', 'Anxiety'); | What is the average age of patients diagnosed with depression in New York? | SELECT AVG(age) FROM patients WHERE state = 'New York' AND condition = 'Depression'; | gretelai_synthetic_text_to_sql |
CREATE TABLE EmissionsData (Country VARCHAR(50), Year INT, CO2Emission DECIMAL(5,2), Population INT); INSERT INTO EmissionsData (Country, Year, CO2Emission, Population) VALUES ('China', 2020, 10.3, 1411000000), ('China', 2019, 9.6, 1409000000), ('India', 2020, 2.1, 1366000000), ('India', 2019, 1.9, 1352000000); | Find the average CO2 emission per capita for each country in 2020, and rank them. | SELECT Country, AVG(CO2Emission/Population) as AvgCO2PerCapita, RANK() OVER (ORDER BY AVG(CO2Emission/Population) DESC) as Rank FROM EmissionsData WHERE Year = 2020 GROUP BY Country HAVING COUNT(*) > 1 ORDER BY Rank; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name TEXT, state TEXT, donation_amount DECIMAL(10, 2), donation_date DATE); INSERT INTO donors (id, name, state, donation_amount, donation_date) VALUES (1, 'John Doe', 'California', 500.00, '2022-01-01'), (2, 'Jane Smith', 'Texas', 350.00, '2022-02-15'); | What is the total amount donated by each donor's state in the United States, summed up quarterly? | SELECT state, DATE_TRUNC('quarter', donation_date) AS donation_quarter, SUM(donation_amount) AS total_donation FROM donors GROUP BY state, donation_quarter; | gretelai_synthetic_text_to_sql |
CREATE TABLE mining_workforce (employee_id INT, country TEXT, gender TEXT); INSERT INTO mining_workforce (employee_id, country, gender) VALUES (1, 'Canada', 'Male'), (2, 'Canada', 'Female'), (3, 'Mexico', 'Male'), (4, 'Mexico', 'Male'), (5, 'Brazil', 'Female'), (6, 'Brazil', 'Male'), (7, 'USA', 'Female'), (8, 'USA', 'Male'), (9, 'Peru', 'Male'), (10, 'Peru', 'Female'); | What is the percentage of female workers in the mining industry by country, in descending order? | SELECT country, PERCENTAGE_RANK() OVER (ORDER BY COUNT(CASE WHEN gender = 'Female' THEN 1 END) DESC) AS female_percentage_rank FROM mining_workforce GROUP BY country ORDER BY female_percentage_rank DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE WasteTypes (waste_type_id INT PRIMARY KEY, name VARCHAR, description VARCHAR); CREATE TABLE Facilities (facility_id INT PRIMARY KEY, name VARCHAR, location VARCHAR, capacity INT, waste_type_id INT, FOREIGN KEY (waste_type_id) REFERENCES WasteTypes(waste_type_id)); | Add a new facility to the 'Facilities' table with the following details: facility_id = 1, name = 'Recycling Center 1', location = 'City A', capacity = 500, waste_type_id = 1 | INSERT INTO Facilities (facility_id, name, location, capacity, waste_type_id) VALUES (1, 'Recycling Center 1', 'City A', 500, 1); | gretelai_synthetic_text_to_sql |
CREATE TABLE songs (id INT, title VARCHAR(255), length FLOAT, genre VARCHAR(255), release_year INT); INSERT INTO songs (id, title, length, genre, release_year) VALUES (1, 'Song1', 200.5, 'Pop', 2011), (2, 'Song2', 180.3, 'Rock', 2008), (3, 'Song3', 220.0, 'Jazz', 1989), (4, 'Song4', 150.0, 'Jazz', 1920), (5, 'PopSong', 120.0, 'Pop', 2015); | What is the minimum length of a pop song released after 2010? | SELECT MIN(length) FROM songs WHERE genre = 'Pop' AND release_year > 2010; | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (id INT, name VARCHAR(255)); CREATE TABLE cargo (vessel_id INT, weight INT, timestamp TIMESTAMP); INSERT INTO vessels VALUES (1, 'Vessel A'), (2, 'Vessel B'), (3, 'Vessel C'); INSERT INTO cargo VALUES (1, 10000, '2021-01-01 10:00:00'), (1, 12000, '2021-01-15 12:00:00'), (3, 15000, '2020-01-03 08:00:00'); | Delete vessels with no cargo tracking records in the last year. | DELETE FROM vessels v WHERE id NOT IN (SELECT c.vessel_id FROM cargo c WHERE c.timestamp >= DATE_SUB(CURRENT_TIMESTAMP, INTERVAL 1 YEAR)); | gretelai_synthetic_text_to_sql |
CREATE TABLE ports_cargo_region (port_id INT, port_name TEXT, region TEXT, cargo_quantity INT); INSERT INTO ports_cargo_region VALUES (1, 'Port I', 'Africa', 2000), (2, 'Port J', 'Europe', 1800), (3, 'Port K', 'Asia Pacific', 2200); | What is the total quantity of cargo handled by ports in each region, excluding the African region? | SELECT ports_cargo_region.region, SUM(ports_cargo_region.cargo_quantity) FROM ports_cargo_region WHERE ports_cargo_region.region != 'Africa' GROUP BY ports_cargo_region.region; | gretelai_synthetic_text_to_sql |
CREATE TABLE clients (id INT, name TEXT, category TEXT, region TEXT); CREATE TABLE investments (id INT, client_id INT, product_code TEXT); INSERT INTO clients (id, name, category, region) VALUES (1, 'John Doe', 'Medium-Risk', 'East'), (2, 'Jane Smith', 'Low-Risk', 'West'), (3, 'Alice Johnson', 'High-Risk', 'North'), (4, 'Bob Brown', 'Medium-Risk', 'East'); INSERT INTO investments (id, client_id, product_code) VALUES (1, 1, 'AAPL'), (2, 1, 'GOOG'), (3, 2, 'MSFT'), (4, 4, 'FB'); | What is the number of investment products owned by clients in the 'Medium-Risk' category who live in the 'East' region? | SELECT COUNT(*) FROM clients c JOIN investments i ON c.id = i.client_id WHERE c.category = 'Medium-Risk' AND c.region = 'East'; | gretelai_synthetic_text_to_sql |
CREATE TABLE personnel (region VARCHAR(255), deployment_date DATE, personnel_count INT, personnel_type VARCHAR(255)); | What was the total number of peacekeeping personnel deployed in each region in the past year? | SELECT region, SUM(personnel_count) as total_personnel FROM personnel WHERE deployment_date BETWEEN DATE_SUB(CURDATE(), INTERVAL 1 YEAR) AND CURDATE() AND personnel_type = 'Peacekeeping' GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE sensor_data (sensor_id INTEGER, sensor_type TEXT, measurement_date DATE, measurement_value INTEGER);CREATE VIEW sensor_counts AS SELECT sensor_type, COUNT(*) as sensor_count FROM sensor_data WHERE measurement_date = CURRENT_DATE GROUP BY sensor_type; | How many sensors of each type are currently installed in the fields? | SELECT * FROM sensor_counts; | gretelai_synthetic_text_to_sql |
CREATE TABLE wages (worker_id INT, industry VARCHAR(20), wage DECIMAL(10,2));CREATE TABLE textile_industry (industry VARCHAR(20)); INSERT INTO textile_industry (industry) VALUES ('Textile - Apparel'), ('Textile - Home Furnishings'); | What is the average wage for workers in the textile industry in South America? | SELECT AVG(wage) FROM wages WHERE industry IN (SELECT industry FROM textile_industry) AND country IN (SELECT country FROM south_america); | gretelai_synthetic_text_to_sql |
CREATE TABLE faculty (id INT, name VARCHAR(50), department VARCHAR(50)); INSERT INTO faculty (id, name, department) VALUES (1, 'Alice', 'Computer Science'); INSERT INTO faculty (id, name, department) VALUES (2, 'Bob', 'Mathematics'); CREATE TABLE authorships (id INT, faculty_id INT, publication_id INT); INSERT INTO authorships (id, faculty_id, publication_id) VALUES (1, 1, 1); INSERT INTO authorships (id, faculty_id, publication_id) VALUES (2, 1, 2); CREATE TABLE publications (id INT, year INT, title VARCHAR(50)); INSERT INTO publications (id, year, title) VALUES (1, 2021, 'Artificial Intelligence'); INSERT INTO publications (id, year, title) VALUES (2, 2020, 'Machine Learning'); | What is the average number of publications per faculty member in the past year? | SELECT AVG(p.count) FROM (SELECT f.id, COUNT(a.id) AS count FROM authorships a JOIN faculty f ON a.faculty_id = f.id JOIN publications p ON a.publication_id = p.id WHERE p.year = 2021 GROUP BY f.id) p; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, department VARCHAR(255)); CREATE TABLE physicians (id INT, department VARCHAR(255)); INSERT INTO patients (id, department) VALUES (1, 'Department X'), (2, 'Department Y'); INSERT INTO physicians (id, department) VALUES (1, 'Department X'), (3, 'Department X'); | List the total number of patients and the number of unique physicians for each rural health department. | SELECT department, COUNT(DISTINCT id) AS unique_physicians, COUNT(p.id) AS total_patients FROM patients p JOIN physicians ph ON p.department = ph.department GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE TABLE RenewableGeneration (id INT, country VARCHAR(50), capacity FLOAT); INSERT INTO RenewableGeneration (id, country, capacity) VALUES (1, 'India', 180.5), (2, 'India', 195.2), (3, 'India', 210.7); | What is the total renewable energy generation capacity in India? | SELECT SUM(capacity) FROM RenewableGeneration WHERE country = 'India'; | gretelai_synthetic_text_to_sql |
CREATE TABLE games (id INT, name VARCHAR(50), genre VARCHAR(50), revenue FLOAT); INSERT INTO games (id, name, genre, revenue) VALUES (1, 'Game1', 'Gaming', 5000000), (2, 'Game2', 'Gaming', 7000000), (3, 'Game3', 'Simulation', 3000000); | What is the total revenue for each game in the 'gaming' category, ordered by revenue in descending order? | SELECT name, revenue FROM (SELECT name, revenue, ROW_NUMBER() OVER (ORDER BY revenue DESC) as rn FROM games WHERE genre = 'Gaming') sub WHERE rn != 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, age INT, diagnosis VARCHAR(20), residence VARCHAR(10)); INSERT INTO patients (id, age, diagnosis, residence) VALUES (1, 6, 'asthma', 'rural'), (2, 12, 'asthma', 'urban'), (3, 8, 'diabetes', 'rural'); | What is the prevalence of asthma among children in rural areas compared to urban areas? | SELECT (SELECT COUNT(*) FROM patients WHERE diagnosis = 'asthma' AND residence = 'rural') / (SELECT COUNT(*) FROM patients WHERE residence = 'rural') AS rural_asthma_prevalence, (SELECT COUNT(*) FROM patients WHERE diagnosis = 'asthma' AND residence = 'urban') / (SELECT COUNT(*) FROM patients WHERE residence = 'urban') AS urban_asthma_prevalence; | gretelai_synthetic_text_to_sql |
CREATE TABLE farmers_new (id INT, name VARCHAR(50), gender VARCHAR(50), location VARCHAR(50)); INSERT INTO farmers_new (id, name, gender, location) VALUES (1, 'Juana Garcia', 'Female', 'Veracruz'); INSERT INTO farmers_new (id, name, gender, location) VALUES (2, 'Carlos Hernandez', 'Male', 'Veracruz'); INSERT INTO farmers_new (id, name, gender, location) VALUES (3, 'Fatima Ahmed', 'Female', 'Cairo'); INSERT INTO farmers_new (id, name, gender, location) VALUES (4, 'Ahmed Ali', 'Male', 'Cairo'); | What is the total number of female and male farmers in the 'farmers_new' table? | SELECT SUM(CASE WHEN gender = 'Male' THEN 1 ELSE 0 END) AS total_males, SUM(CASE WHEN gender = 'Female' THEN 1 ELSE 0 END) AS total_females FROM farmers_new; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_pricing_annual (region VARCHAR(255), year INT, revenue FLOAT); | What is the total carbon pricing revenue (in USD) for each region from 2018 to 2020? | SELECT region, SUM(revenue) FROM carbon_pricing_annual WHERE year BETWEEN 2018 AND 2020 GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE CommunityCourts (CourtID INT, District VARCHAR(20)); CREATE TABLE CommunityCourtHearings (HearingID INT, CourtID INT, HearingDate DATE); INSERT INTO CommunityCourts (CourtID, District) VALUES (1, 'Downtown'), (2, 'Uptown'), (3, 'Midtown'); INSERT INTO CommunityCourtHearings (HearingID, CourtID, HearingDate) VALUES (1, 1, '2021-06-15'), (2, 1, '2021-06-25'), (3, 2, '2021-07-20'), (4, 3, '2021-08-12'), (5, 3, '2021-08-22'); | What is the earliest HearingDate for each CommunityCourt in descending order? | SELECT CourtID, MIN(HearingDate) as EarliestHearingDate FROM CommunityCourtHearings GROUP BY CourtID ORDER BY EarliestHearingDate DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Branches (branch_id INT, branch_name VARCHAR(255));CREATE TABLE Menu (dish_name VARCHAR(255), branch_id INT, dish_type VARCHAR(255), price DECIMAL(5,2));CREATE TABLE Sales (sale_date DATE, dish_name VARCHAR(255), quantity INT); | What is the total quantity of dishes sold by category in branch 7? | SELECT dish_type, SUM(quantity) as total_sales FROM Sales JOIN Menu ON Sales.dish_name = Menu.dish_name WHERE branch_id = 7 GROUP BY dish_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE Chemicals (ChemicalID INT PRIMARY KEY, ChemicalName VARCHAR(50), Department VARCHAR(50), QuantityInStock INT, ReorderLevel INT); INSERT INTO Chemicals (ChemicalID, ChemicalName, Department, QuantityInStock, ReorderLevel) VALUES (3, 'Benzene', 'Manufacturing', 250, 300); INSERT INTO Chemicals (ChemicalID, ChemicalName, Department, QuantityInStock, ReorderLevel) VALUES (4, 'Carbon Dioxide', 'Manufacturing', 400, 450); | Which chemicals in the Manufacturing department have a quantity in stock below the reorder level? | SELECT Chemicals.ChemicalName, Chemicals.Department, Chemicals.QuantityInStock, Chemicals.ReorderLevel FROM Chemicals WHERE Chemicals.Department = 'Manufacturing' AND Chemicals.QuantityInStock < Chemicals.ReorderLevel; | gretelai_synthetic_text_to_sql |
CREATE TABLE rural_development (country VARCHAR(255), year INT, num_projects INT); INSERT INTO rural_development (country, year, num_projects) VALUES ('Nepal', 2018, 10), ('Nepal', 2019, 12), ('Nepal', 2020, 15), ('Nepal', 2021, 18); | Delete all rural development projects in Nepal in 2018. | DELETE FROM rural_development WHERE country = 'Nepal' AND year = 2018; | gretelai_synthetic_text_to_sql |
CREATE TABLE regions (name VARCHAR(255)); INSERT INTO regions (name) VALUES ('West'), ('Midwest'); CREATE TABLE disaster_preparedness_kits (id INT, region VARCHAR(255), quantity INT, distributed INT); INSERT INTO disaster_preparedness_kits (id, region, quantity, distributed) VALUES (1, 'West', 500, 300), (2, 'Midwest', 700, 500); | What is the total number of disaster preparedness kits remaining in each region? | SELECT region, SUM(quantity - distributed) as total_kits_remaining FROM disaster_preparedness_kits GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE explainability_scores (id INT, model_id INT, score FLOAT); INSERT INTO explainability_scores (id, model_id, score) VALUES (1, 1, 0.75), (2, 2, 0.91), (3, 3, 0.68); CREATE TABLE models (id INT, name TEXT, country TEXT); INSERT INTO models (id, name, country) VALUES (1, 'ModelA', 'Africa'), (2, 'ModelB', 'Canada'), (3, 'ModelC', 'Africa'); | What is the minimum explainability score for models developed in Africa? | SELECT MIN(score) FROM explainability_scores JOIN models ON explainability_scores.model_id = models.id WHERE country = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE space_missions (id INT, mission_name VARCHAR(50), launch_date DATE, scheduled_date DATE); INSERT INTO space_missions VALUES (1, 'Artemis I', '2022-08-29', '2022-06-29'); INSERT INTO space_missions VALUES (2, 'Mars Science Laboratory', '2011-11-26', '2011-08-05'); | Which space missions had a launch delay of more than 60 days in the space_missions table? | SELECT mission_name, launch_date, scheduled_date, DATEDIFF(day, scheduled_date, launch_date) as delay_days FROM space_missions WHERE DATEDIFF(day, scheduled_date, launch_date) > 60; | gretelai_synthetic_text_to_sql |
CREATE TABLE FarmG (country VARCHAR(20), species VARCHAR(20), biomass FLOAT); INSERT INTO FarmG (country, species, biomass) VALUES ('Norway', 'Salmon', 450000); INSERT INTO FarmG (country, species, biomass) VALUES ('Norway', 'Trout', 120000); INSERT INTO FarmG (country, species, biomass) VALUES ('Scotland', 'Salmon', 320000); INSERT INTO FarmG (country, species, biomass) VALUES ('Scotland', 'Trout', 160000); INSERT INTO FarmG (country, species, biomass) VALUES ('Canada', 'Salmon', 200000); INSERT INTO FarmG (country, species, biomass) VALUES ('Canada', 'Trout', 260000); | Which countries have a total biomass of farmed salmon greater than 400,000? | SELECT country FROM FarmG WHERE species='Salmon' GROUP BY country HAVING SUM(biomass) > 400000; | gretelai_synthetic_text_to_sql |
CREATE TABLE sensor_details (sensor_id INT, sensor_location VARCHAR(50), operation_status VARCHAR(10)); | Get the number of IoT sensors in operation in California | SELECT COUNT(sensor_id) FROM sensor_details WHERE sensor_location = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE readers (id INT, name VARCHAR(50), age INT, country VARCHAR(50), news_preference VARCHAR(50)); INSERT INTO readers (id, name, age, country, news_preference) VALUES (1, 'John Doe', 35, 'Canada', 'Sports'), (2, 'Jane Smith', 28, 'Canada', 'Politics'), (3, 'Jim Brown', 45, 'United States', 'Sports'); | What is the total number of readers in each country, grouped by news preference? | SELECT country, news_preference, COUNT(*) AS total FROM readers GROUP BY country, news_preference; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT PRIMARY KEY, Age INT, Gender VARCHAR(50), Location VARCHAR(50)); | What is the total donation amount per organization located in South America for donors aged between 30 and 50? | SELECT O.OrgName, SUM(D.DonationAmount) as TotalDonationAmount FROM Donors D INNER JOIN Donations DON ON D.DonorID = DON.DonorID INNER JOIN Organizations O ON DON.OrgID = O.OrgID WHERE D.Age BETWEEN 30 AND 50 AND O.Location = 'South America' GROUP BY O.OrgName; | gretelai_synthetic_text_to_sql |
CREATE TABLE satellites (id INT, country VARCHAR(50), launch_date DATE, satellite_name VARCHAR(50)); | What is the total number of satellites launched by India and China? | SELECT SUM(country IN ('India', 'China')) FROM satellites; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA fitness; CREATE TABLE workouts (id INT, user_id INT, workout_type VARCHAR(50), duration INT, workout_date DATE); INSERT INTO workouts (id, user_id, workout_type, duration, workout_date) VALUES (1, 1, 'Strength Training', 90, '2022-09-20'); | What is the maximum duration of a single 'Strength Training' workout in the 'Australia' region? | SELECT MAX(duration) FROM fitness.workouts WHERE workout_type = 'Strength Training' AND region = 'Australia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE freight_forwarding (id INT, source_country VARCHAR(50), destination_country VARCHAR(50), delivery_time INT, ship_date DATE); INSERT INTO freight_forwarding (id, source_country, destination_country, delivery_time, ship_date) VALUES (4, 'South Korea', 'Germany', 10, '2023-01-02'); INSERT INTO freight_forwarding (id, source_country, destination_country, delivery_time, ship_date) VALUES (5, 'South Korea', 'Germany', 14, '2023-01-05'); INSERT INTO freight_forwarding (id, source_country, destination_country, delivery_time, ship_date) VALUES (6, 'South Korea', 'Germany', 12, '2023-01-10'); | What is the maximum delivery time for freight forwarding shipments from South Korea to Germany in January 2023? | SELECT MAX(delivery_time) FROM freight_forwarding WHERE source_country = 'South Korea' AND destination_country = 'Germany' AND ship_date >= '2023-01-01' AND ship_date < '2023-02-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE vehicles (id INT, city VARCHAR(20), type VARCHAR(20), is_electric BOOLEAN, daily_distance INT); INSERT INTO vehicles VALUES (1, 'paris', 'sedan', true, 55); INSERT INTO vehicles VALUES (2, 'paris', 'suv', true, 65); INSERT INTO vehicles VALUES (3, 'london', 'truck', false, 75); | What is the average distance traveled per day by electric vehicles in 'paris'? | SELECT AVG(daily_distance) FROM vehicles WHERE city = 'paris' AND is_electric = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE provider_service_areas (subscriber_id INT, provider VARCHAR(25)); | How many mobile customers are there in each network provider's service area? | SELECT provider, COUNT(*) FROM provider_service_areas GROUP BY provider; | gretelai_synthetic_text_to_sql |
CREATE TABLE ProjectCosts (ProjectID INT, Location VARCHAR(20), Year INT, Cost FLOAT); INSERT INTO ProjectCosts (ProjectID, Location, Year, Cost) VALUES (1, 'Alaska', 2021, 2000000); | What is the total cost of public works projects in Alaska that were completed in 2021? | SELECT SUM(Cost) FROM ProjectCosts WHERE Location = 'Alaska' AND Year = 2021 AND Completed = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE item_inventory (item_id INT, item_name VARCHAR(50), quantity INT, warehouse_id INT); | Delete records with a quantity of 0 from the item_inventory table | DELETE FROM item_inventory WHERE quantity = 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE astrophysics_research (research_id INT, topic VARCHAR(50), expenses INT); | What are the total research expenses for each astrophysics research topic? | SELECT topic, SUM(expenses) FROM astrophysics_research GROUP BY topic; | gretelai_synthetic_text_to_sql |
CREATE TABLE Farm (FarmID INT, FishSpecies VARCHAR(50), Capacity INT, Location VARCHAR(50)); INSERT INTO Farm (FarmID, FishSpecies, Capacity, Location) VALUES (1, 'Salmon', 5000, 'Norway'), (2, 'Tilapia', 3000, 'Indonesia'), (3, 'Carp', 4000, 'Canada'); CREATE TABLE Fish (FishID INT, FishSpecies VARCHAR(50), AvgWeight FLOAT); INSERT INTO Fish (FishID, FishSpecies, AvgWeight) VALUES (1, 'Salmon', 6.5), (2, 'Tilapia', 1.2), (3, 'Carp', 2.8), (4, 'Pangasius', 3.5); | What fish species are not being farmed in Canada? | SELECT Fish.FishSpecies FROM Fish LEFT JOIN Farm ON Fish.FishSpecies = Farm.FishSpecies WHERE Farm.Location IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE autonomous_vehicle_services (service_id INT, service_name TEXT, type TEXT, city TEXT, country TEXT); | Add a new autonomous shuttle service in the city of Tokyo | INSERT INTO autonomous_vehicle_services (service_id, service_name, type, city, country) VALUES (2001, 'Tokyo Sky Shuttle', 'autonomous shuttle', 'Tokyo', 'Japan'); | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, name VARCHAR(50), age INT, diagnosis_date DATE, country VARCHAR(30)); CREATE VIEW covid19_patients AS SELECT * FROM patients WHERE diagnosis = 'COVID-19'; | What is the average age of patients diagnosed with COVID-19 in 2021 in India? | SELECT AVG(age) FROM covid19_patients WHERE country = 'India' AND YEAR(diagnosis_date) = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE properties(id INT, city TEXT, affordability_rating INT); INSERT INTO properties(id, city, affordability_rating) VALUES (1, 'San Francisco', NULL); | Delete properties in San Francisco with no affordability ratings. | DELETE FROM properties WHERE city = 'San Francisco' AND affordability_rating IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE community_dev_indonesia (initiative VARCHAR(50), budget FLOAT, start_year INT); INSERT INTO community_dev_indonesia (initiative, budget, start_year) VALUES ('Microfinance Program', 2000000, 2010), ('Rural Healthcare Program', 5000000, 2010); | Identify the community development initiatives that have been implemented in Indonesia since 2010, and their respective budgets. | SELECT initiative, budget FROM community_dev_indonesia WHERE start_year <= 2010; | gretelai_synthetic_text_to_sql |
CREATE TABLE food_safety_inspections (restaurant_id INT, inspection_date DATE, violation_count INT); | Update the food_safety_inspections table, setting the violation_count to 0 where the inspection_date is '2023-01-18' | UPDATE food_safety_inspections SET violation_count = 0 WHERE inspection_date = '2023-01-18'; | gretelai_synthetic_text_to_sql |
CREATE TABLE urban_waste (waste_type TEXT, amount INTEGER, year INTEGER);CREATE TABLE rural_waste (waste_type TEXT, amount INTEGER, year INTEGER); | What are the total waste generation figures for urban and rural areas combined, for the year 2020? | SELECT SUM(amount) FROM urban_waste WHERE year = 2020 UNION ALL SELECT SUM(amount) FROM rural_waste WHERE year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE trips (id INT, city TEXT, year INT, trips INT); INSERT INTO trips (id, city, year, trips) VALUES (1, 'Sydney', 2019, 1000), (2, 'London', 2020, 1500), (3, 'Sydney', 2021, 800), (4, 'Paris', 2022, 1200); | What is the minimum number of public transportation trips taken in Sydney in the year 2021? | SELECT MIN(trips) FROM trips WHERE city = 'Sydney' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE production (id INT, element TEXT, location TEXT, year INT, quantity INT); INSERT INTO production (id, element, location, year, quantity) VALUES (1, 'dysprosium', 'South America', 2021, 300), (2, 'dysprosium', 'North America', 2021, 700); | What is the market share of dysprosium produced in South America in 2021? | SELECT (quantity / (SELECT SUM(quantity) FROM production WHERE element = 'dysprosium' AND year = 2021) * 100) AS market_share FROM production WHERE element = 'dysprosium' AND location = 'South America' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE aircraft_plants (plant_id INT, plant_name TEXT, country TEXT); INSERT INTO aircraft_plants (plant_id, plant_name, country) VALUES (1, 'Boeing Everett Factory', 'USA'), (2, 'Boeing Renton Factory', 'USA'), (3, 'Airbus Toulouse Factory', 'France'), (4, 'Comac Shanghai Factory', 'China'), (5, 'Irkut Kazan Factory', 'Russia'); | Which are the top 5 countries with the most aircraft manufacturing plants? | SELECT country, COUNT(*) as plant_count FROM aircraft_plants GROUP BY country ORDER BY plant_count DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE high_scores (player_id INT, game_id INT, score INT); INSERT INTO high_scores (player_id, game_id, score) VALUES (1, 1, 550), (2, 2, 480), (3, 1, 500); | List all players who achieved a high score of 500 or more in 'racing_game'. | SELECT player_id, game_id FROM high_scores WHERE score >= 500 AND game_id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE deep_sea_expeditions (expedition_name VARCHAR(255), ocean VARCHAR(255)); INSERT INTO deep_sea_expeditions (expedition_name, ocean) VALUES ('Expedition 1', 'Atlantic Ocean'), ('Expedition 2', 'Pacific Ocean'); | What is the total number of deep-sea expeditions in each ocean? | SELECT ocean, COUNT(*) as count FROM deep_sea_expeditions GROUP BY ocean; | gretelai_synthetic_text_to_sql |
CREATE VIEW field_rainfall AS SELECT fields.field_name, rainfall_data.rainfall, rainfall_data.measurement_date FROM fields JOIN rainfall_data ON fields.id = rainfall_data.field_id; | What is the total rainfall for each field in the 'field_rainfall' view for the year 2021? | SELECT field_name, SUM(rainfall) FROM field_rainfall WHERE YEAR(measurement_date) = 2021 GROUP BY field_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE movie_studios (id INT, name TEXT); CREATE TABLE movies (id INT, title TEXT, genre TEXT, studio_id INT, budget INT); INSERT INTO movie_studios (id, name) VALUES (1, 'Studio 1'), (2, 'Studio 2'), (3, 'Studio 3'), (4, 'Studio 4'); INSERT INTO movies (id, title, genre, studio_id, budget) VALUES (1, 'Movie A', 'Horror', 4, 5000000), (2, 'Movie B', 'Comedy', 1, 7000000), (3, 'Movie C', 'Action', 2, 6000000), (4, 'Movie D', 'Horror', 4, 8000000), (5, 'Movie E', 'Drama', 3, 9000000); | What is the total budget for all horror movies produced by Studio 4? | SELECT SUM(movies.budget) FROM movies JOIN movie_studios ON movies.studio_id = movie_studios.id WHERE movies.genre = 'Horror' AND movie_studios.name = 'Studio 4'; | gretelai_synthetic_text_to_sql |
CREATE TABLE organization (org_id INT, org_name VARCHAR(255)); CREATE TABLE donation (don_id INT, donor_id INT, org_id INT, donation_date DATE); | Determine the number of days between the earliest and latest donation date for each organization. | SELECT org_id, DATEDIFF(MAX(donation_date), MIN(donation_date)) AS days_between_earliest_and_latest_donation FROM donation GROUP BY org_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE events (event_id INT, event_type VARCHAR(50)); INSERT INTO events (event_id, event_type) VALUES (1, 'Dance'), (2, 'Theater'), (3, 'Music'); CREATE TABLE attendees (attendee_id INT, event_id INT, age INT); INSERT INTO attendees (attendee_id, event_id, age) VALUES (1, 1, 25), (2, 1, 30), (3, 2, 22), (4, 2, 28), (5, 2, 35), (6, 3, 50), (7, 3, 55), (8, 3, 60); | What is the average age of attendees for music events? | SELECT AVG(age) FROM attendees JOIN events ON attendees.event_id = events.event_id WHERE events.event_type = 'Music'; | gretelai_synthetic_text_to_sql |
CREATE TABLE player_demographics (player_id INT, player_name TEXT, age INT, country TEXT, game_type TEXT); INSERT INTO player_demographics (player_id, player_name, age, country, game_type) VALUES (1, 'John Doe', 25, 'United States', 'Single-Player'), (2, 'Jane Doe', 28, 'Canada', 'Multiplayer'), (3, 'Jim Smith', 31, 'United Kingdom', 'Single-Player'); CREATE TABLE countries (country_id INT, country TEXT); INSERT INTO countries (country_id, country) VALUES (1, 'United States'), (2, 'Canada'), (3, 'United Kingdom'); | What is the percentage of players who prefer single-player games, by country? | SELECT countries.country, (COUNT(player_demographics.player_id) FILTER (WHERE player_demographics.game_type = 'Single-Player') * 100.0 / COUNT(player_demographics.player_id)) AS percentage FROM player_demographics JOIN countries ON player_demographics.country = countries.country GROUP BY countries.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE member_data (member_id INT, age INT, gender VARCHAR(10)); CREATE TABLE workout_data (workout_id INT, member_id INT, workout_type VARCHAR(20), workout_date DATE); | Find the average age of members who did yoga workouts and zumba workouts. | SELECT AVG(member_data.age) as avg_age FROM member_data JOIN workout_data ON member_data.member_id = workout_data.member_id WHERE workout_data.workout_type IN ('yoga', 'zumba'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Contracts (id INT, contract_name VARCHAR(50), negotiation_date DATE); INSERT INTO Contracts (id, contract_name, negotiation_date) VALUES (1, 'Contract A', NULL), (2, 'Contract B', '2020-03-15'), (3, 'Contract C', NULL); | What are the names of all contracts that have not been negotiated yet? | SELECT contract_name FROM Contracts WHERE negotiation_date IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers (subscriber_id INT, data_usage FLOAT, region VARCHAR(20)); INSERT INTO subscribers (subscriber_id, data_usage, region) VALUES (1, 25.6, 'Northern'), (2, 32.8, 'Northeast'), (3, 18.9, 'Northern'); CREATE TABLE minimum_usage (min_usage FLOAT); INSERT INTO minimum_usage (min_usage) VALUES (50.0); | What is the minimum monthly data usage for broadband subscribers in the Northern region? | SELECT MIN(data_usage) FROM subscribers WHERE region = 'Northern'; | gretelai_synthetic_text_to_sql |
CREATE TABLE visitor_exhibition (visitor_id INT, exhibition_id INT, visit_date DATE); CREATE TABLE visitors (id INT, age INT, gender TEXT, country TEXT); CREATE TABLE exhibitions (id INT, name TEXT, start_date DATE, end_date DATE); | Delete records of visitors who have not visited any exhibition from the visitors table | DELETE FROM visitors WHERE id NOT IN (SELECT visitor_id FROM visitor_exhibition); | gretelai_synthetic_text_to_sql |
CREATE TABLE Crimes (id INT, city VARCHAR(20), date DATE, number_of_crimes INT); | What is the maximum number of crimes committed in a single day in New York City? | SELECT MAX(number_of_crimes) FROM Crimes WHERE city = 'New York City'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Game_Design (id INT PRIMARY KEY, game_id INT, genre VARCHAR(255), release_year INT, developer VARCHAR(255), platform VARCHAR(255)); INSERT INTO Game_Design (id, game_id, genre, release_year, developer) VALUES (1, 1001, 'RPG', 2018, 'CompanyA'); | Update the 'platform' for game with ID 1001 to 'PC' | UPDATE Game_Design SET platform = 'PC' WHERE id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE menu_items (item_id INT, item_name VARCHAR(50), west_coast_sales INT, east_coast_sales INT); INSERT INTO menu_items (item_id, item_name, west_coast_sales, east_coast_sales) VALUES (1, 'Cheeseburger', 300, 200), (2, 'Fried Chicken', 250, 270), (3, 'Veggie Burger', 180, 350); | Which menu items have higher sales in the West coast compared to the East coast? | SELECT item_name, west_coast_sales, east_coast_sales, (west_coast_sales - east_coast_sales) as sales_difference FROM menu_items ORDER BY sales_difference DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE PRODUCT ( id INT PRIMARY KEY, name TEXT, material TEXT, quantity INT, country TEXT, certifications TEXT ); INSERT INTO PRODUCT (id, name, material, quantity, country, certifications) VALUES (1, 'Organic Cotton Shirt', 'Organic Cotton', 30, 'USA', 'GOTS, Fair Trade'); INSERT INTO PRODUCT (id, name, material, quantity, country) VALUES (2, 'Recycled Poly Shoes', 'Recycled Polyester', 25, 'Germany'); INSERT INTO PRODUCT (id, name, material, quantity, country, certifications) VALUES (3, 'Bamboo T-Shirt', 'Bamboo', 15, 'China', 'OEKO-TEX'); | How many unique ethical certifications are there for all products in the PRODUCT table? | SELECT DISTINCT certifications FROM PRODUCT; | gretelai_synthetic_text_to_sql |
CREATE TABLE cricket_matches (team VARCHAR(50), match_date DATE, result VARCHAR(50)); | Display the number of days between the first and last matches for each team, and the difference between the total wins and losses, in the cricket_matches dataset. | SELECT team, DATEDIFF(MAX(match_date), MIN(match_date)) as days_between, SUM(CASE WHEN result = 'win' THEN 1 ELSE 0 END) - SUM(CASE WHEN result = 'loss' THEN 1 ELSE 0 END) as wins_minus_losses FROM cricket_matches GROUP BY team; | gretelai_synthetic_text_to_sql |
CREATE TABLE songs (song_id INT, title VARCHAR(255), genre VARCHAR(50), release_year INT, length FLOAT); INSERT INTO songs (song_id, title, genre, release_year, length) VALUES (1, 'Song1', 'Classical', 1995, 120.5), (2, 'Song2', 'Jazz', 1998, 210.3), (3, 'Song3', 'Rock', 1992, 180.7), (4, 'Song4', 'Classical', 1999, 200.0); | How many unique genres of songs were released before 2000? | SELECT COUNT(DISTINCT genre) FROM songs WHERE release_year < 2000; | gretelai_synthetic_text_to_sql |
CREATE TABLE Athletes (athlete_id INT, athlete_name VARCHAR(255), age INT, team VARCHAR(255)); CREATE VIEW WellbeingPrograms AS SELECT athlete_id, team FROM Programs WHERE program_type IN ('NBA', 'NFL'); | Which athletes in 'NBA' and 'NFL' wellbeing programs have the highest age? | SELECT Athletes.athlete_name, Athletes.age FROM Athletes INNER JOIN WellbeingPrograms ON Athletes.athlete_id = WellbeingPrograms.athlete_id WHERE (Athletes.team = 'NBA' OR Athletes.team = 'NFL') GROUP BY Athletes.athlete_name ORDER BY Athletes.age DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE Players (PlayerID INT, PlayerRegion VARCHAR(10), Wins INT, GameName VARCHAR(20)); INSERT INTO Players (PlayerID, PlayerRegion, Wins, GameName) VALUES (1, 'Europe', 25, 'Galactic Conquest'), (2, 'Asia', 30, 'Galactic Conquest'), (3, 'Europe', 35, 'Galactic Conquest'); | What is the maximum number of wins achieved by players from Europe who have played "Galactic Conquest"? | SELECT MAX(Wins) FROM Players WHERE PlayerRegion = 'Europe' AND GameName = 'Galactic Conquest'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species_ocean (species_name VARCHAR(50), ocean_name VARCHAR(50)); INSERT INTO marine_species_ocean (species_name, ocean_name) VALUES ('Salmon', 'Pacific'), ('Sea Otter', 'Pacific'), ('Bluefin Tuna', 'Atlantic'); | What are the names of the marine species that inhabit both the Atlantic and Pacific Oceans? | SELECT species_name FROM marine_species_ocean WHERE ocean_name IN ('Atlantic', 'Pacific') GROUP BY species_name HAVING COUNT(DISTINCT ocean_name) = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE policyholder_age (policyholder_id INT, policyholder_age INT); CREATE TABLE claims (claim_id INT, policy_id INT, claim_amount DECIMAL(10,2)); INSERT INTO policyholder_age VALUES (1, 35); INSERT INTO claims VALUES (1, 1, 500.00); | What is the average claim amount by policyholder age? | SELECT AVG(claim_amount) as avg_claim_amount FROM claims JOIN policies ON claims.policy_id = policies.policy_id JOIN policyholder_age ON policies.policyholder_id = policyholder_age.policyholder_id; | gretelai_synthetic_text_to_sql |
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