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CREATE TABLE accidents (id INT PRIMARY KEY, vehicle_make VARCHAR(255), accident_count INT);
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Delete all records in the 'accidents' table where the 'vehicle_make' is 'Tesla'
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DELETE FROM accidents WHERE vehicle_make = 'Tesla';
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpacecraftManufacturerCount (Manufacturer VARCHAR(50), TotalSpacecrafts INT); INSERT INTO SpacecraftManufacturerCount (Manufacturer, TotalSpacecrafts) VALUES ('Galactic Spacecraft Inc.', 100), ('Nebula Spacecrafts', 500), ('Cosmic Engineering', 350);
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What is the number of spacecrafts manufactured by each manufacturer?
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SELECT Manufacturer, COUNT(*) FROM SpacecraftManufacturerCount GROUP BY Manufacturer
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gretelai_synthetic_text_to_sql
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CREATE TABLE chemical_suppliers (id INT PRIMARY KEY, chemical_id INT, supplier_name VARCHAR(255), last_purchase_date DATE); CREATE TABLE chemicals (id INT PRIMARY KEY, hazard_level INT);
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What are the names of suppliers who have provided chemicals with a hazard level greater than 7 in the last 6 months?
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SELECT DISTINCT cs.supplier_name FROM chemical_suppliers cs JOIN chemicals c ON cs.chemical_id = c.id WHERE c.hazard_level > 7 AND cs.last_purchase_date > (CURRENT_DATE - INTERVAL '6 months');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Indian_Ocean_Pollution (pollutant TEXT, location TEXT, affected_species TEXT); INSERT INTO Indian_Ocean_Pollution (pollutant, location, affected_species) VALUES ('Microplastics', 'Arabian Sea', 'Omani Sardine, Whale Shark'), ('Plastic Waste', 'Bay of Bengal', 'Indian Oil Sardine, Bottlenose Dolphin');
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Which marine species are affected by plastic pollution in the Indian Ocean?
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SELECT affected_species FROM Indian_Ocean_Pollution WHERE pollutant = 'Microplastics' OR pollutant = 'Plastic Waste';
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gretelai_synthetic_text_to_sql
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CREATE TABLE consumptions (id INT, product VARCHAR(50), is_organic BOOLEAN, quantity INT); INSERT INTO consumptions (id, product, is_organic, quantity) VALUES (1, 'Beef', true, 1000), (2, 'Chicken', true, 800);
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What is the maximum quantity of organic meat consumed in Australia?
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SELECT MAX(quantity) FROM consumptions WHERE is_organic = true AND product LIKE '%Meat%' AND country = 'Australia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE GameSessions (PlayerID INT, GameGenre VARCHAR(255), SessionDuration FLOAT, SessionDate DATE); INSERT INTO GameSessions (PlayerID, GameGenre, SessionDuration, SessionDate) VALUES (1, 'RPG', 50.5, '2021-05-01'), (2, 'FPS', 130.3, '2021-07-10');
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Show the number of players who played more than 100 hours of a specific game genre in the last year.
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SELECT GameGenre, COUNT(PlayerID) as PlayersCount FROM GameSessions WHERE SessionDate BETWEEN DATEADD(year, -1, CURRENT_DATE) AND CURRENT_DATE AND SessionDuration > 100 GROUP BY GameGenre;
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gretelai_synthetic_text_to_sql
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CREATE TABLE programs (id INT, budget INT, program_type VARCHAR(20)); INSERT INTO programs (id, budget, program_type) VALUES (1, 120000, 'Education'), (2, 50000, 'Health'), (3, 80000, 'Arts');
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Delete any program records with a budget over $100,000 and a program type of 'Education'.
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DELETE FROM programs WHERE budget > 100000 AND program_type = 'Education';
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gretelai_synthetic_text_to_sql
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CREATE TABLE feedback (id INT, area TEXT, category TEXT, sentiment TEXT); INSERT INTO feedback (id, area, category, sentiment) VALUES (1, 'State A', 'road maintenance', 'positive'), (2, 'City B', 'road maintenance', 'negative'), (3, 'State A', 'road maintenance', 'positive');
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What is the percentage of positive citizen feedback on road maintenance?
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SELECT (COUNT(*) FILTER (WHERE sentiment = 'positive')) * 100.0 / COUNT(*) AS percentage FROM feedback WHERE category = 'road maintenance';
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA if not exists funding; USE funding; CREATE TABLE if not exists startup_funding (id INT, name VARCHAR(255), region VARCHAR(255), funding DECIMAL(10, 2)); INSERT INTO startup_funding (id, name, region, funding) VALUES (1, 'Startup A', 'Asia', 18000000.00), (2, 'Startup B', 'USA', 25000000.00), (3, 'Startup C', 'Europe', 10000000.00);
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What is the total funding for biotech startups in Asia?
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SELECT SUM(funding) FROM funding.startup_funding WHERE region = 'Asia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE mental_health_parity (id INT, violation_date DATE, location TEXT); INSERT INTO mental_health_parity (id, violation_date, location) VALUES (1, '2021-01-01', 'Japan'); INSERT INTO mental_health_parity (id, violation_date, location) VALUES (2, '2021-02-01', 'South Korea'); INSERT INTO mental_health_parity (id, violation_date, location) VALUES (3, '2021-03-01', 'Japan');
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What is the total number of mental health parity violations reported in Japan in 2021?
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SELECT COUNT(*) FROM mental_health_parity WHERE violation_date >= '2021-01-01' AND violation_date < '2022-01-01' AND location = 'Japan';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Buildings (id INT, name VARCHAR(100), state VARCHAR(50), seismic_retrofit BOOLEAN); INSERT INTO Buildings (id, name, state, seismic_retrofit) VALUES (1, 'City Hall', 'California', TRUE), (2, 'Library', 'California', FALSE), (3, 'Police Station', 'California', TRUE);
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What is the total number of seismic retrofits performed on buildings in California?
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SELECT COUNT(*) FROM Buildings WHERE state = 'California' AND seismic_retrofit = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE products (product_id INT, product_name TEXT, is_cruelty_free BOOLEAN); CREATE TABLE safety_records (record_id INT, product_id INT, violation_date DATE);
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Delete records of products that have never received a safety violation but are not cruelty-free certified.
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DELETE FROM products USING safety_records WHERE products.product_id = safety_records.product_id AND products.is_cruelty_free = FALSE AND safety_records.record_id IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Sustainable_Tourism (Destination VARCHAR(50), CO2_Emissions INT, Water_Usage INT); INSERT INTO Sustainable_Tourism (Destination, CO2_Emissions, Water_Usage) VALUES ('Bali', 120, 3500), ('Kyoto', 80, 2000), ('Rio de Janeiro', 150, 4000);
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Find all destinations with CO2 emissions below the average in the Sustainable_Tourism table.
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SELECT Destination FROM Sustainable_Tourism WHERE CO2_Emissions < (SELECT AVG(CO2_Emissions) FROM Sustainable_Tourism);
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gretelai_synthetic_text_to_sql
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CREATE TABLE shariah_loans (id INT, amount DECIMAL, date DATE); INSERT INTO shariah_loans (id, amount, date) VALUES (1, 5000, '2021-06-05'), (2, 7000, '2021-06-07'); CREATE TABLE socially_responsible_loans (id INT, amount DECIMAL, date DATE); INSERT INTO socially_responsible_loans (id, amount, date) VALUES (1, 3000, '2021-06-02'), (2, 4000, '2021-06-08');
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What is the sum of all Shariah-compliant and socially responsible loans issued in the month of June 2021?
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SELECT SUM(amount) FROM shariah_loans WHERE EXTRACT(MONTH FROM date) = 6 UNION ALL SELECT SUM(amount) FROM socially_responsible_loans WHERE EXTRACT(MONTH FROM date) = 6;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Donors (DonorID INT, Name TEXT, DonationAmount DECIMAL);
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Who is the top donor in terms of total donation amount?
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SELECT Name, SUM(DonationAmount) AS TotalDonation FROM Donors GROUP BY Name ORDER BY TotalDonation DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE intelligence_agencies (agency_id INT PRIMARY KEY, agency_name VARCHAR(255), director_name VARCHAR(255), director_start_date DATE, director_end_date DATE); INSERT INTO intelligence_agencies (agency_id, agency_name, director_name, director_start_date, director_end_date) VALUES (1, 'CIA', 'William Burns', '2021-03-19', 'NULL'), (2, 'FBI', 'Christopher Wray', '2017-08-02', 'NULL'), (3, 'NSA', 'Paul Nakasone', '2018-05-04', 'NULL'), (4, 'DHS', 'Alejandro Mayorkas', '2021-02-02', 'NULL');
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Who are the top 3 intelligence agency directors by tenure?
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SELECT director_name, DATEDIFF(day, director_start_date, director_end_date) AS tenure FROM intelligence_agencies ORDER BY tenure DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE menu (menu_id INT, restaurant_id INT, food_category TEXT, price DECIMAL(5,2), sustainability_score INT); CREATE TABLE restaurant (restaurant_id INT, name TEXT); INSERT INTO restaurant (restaurant_id, name) VALUES (1, 'Restaurant B'), (2, 'Restaurant C'); INSERT INTO menu (menu_id, restaurant_id, food_category, price, sustainability_score) VALUES (1, 1, 'Appetizers', 7.99, 80), (2, 1, 'Entrees', 14.99, 90), (3, 1, 'Desserts', 6.50, 70), (4, 2, 'Appetizers', 9.99, 95), (5, 2, 'Entrees', 19.99, 85), (6, 2, 'Desserts', 7.99, 75);
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List the top 3 sustainable menu items based on their sales and sustainability scores for a particular restaurant in Q2 2021.
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SELECT m.food_category, m.price, m.sustainability_score, SUM(m.price) AS total_sales FROM menu m JOIN restaurant r ON m.restaurant_id = r.restaurant_id WHERE r.name = 'Restaurant B' AND m.price > 0 AND EXTRACT(MONTH FROM m.order_date) BETWEEN 4 AND 6 AND EXTRACT(YEAR FROM m.order_date) = 2021 GROUP BY m.menu_id, m.food_category, m.price, m.sustainability_score ORDER BY total_sales DESC, m.sustainability_score DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE student_demographics (id INT PRIMARY KEY, name VARCHAR(255), age INT, gender VARCHAR(50), ethnicity VARCHAR(50)); CREATE TABLE disability_accommodations (id INT PRIMARY KEY, student_id INT, faculty_id INT, accommodation_type VARCHAR(50), start_date DATE, end_date DATE);
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Retrieve the name, age, and ethnicity of all students with disability accommodations
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SELECT student_demographics.name, student_demographics.age, student_demographics.ethnicity FROM student_demographics INNER JOIN disability_accommodations ON student_demographics.id = disability_accommodations.student_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Donations (DonationID int, DonorID int, DonationDate date, AmountDonated float); INSERT INTO Donations (DonationID, DonorID, DonationDate, AmountDonated) VALUES (1, 1, '2022-01-01', 5000.00), (2, 2, '2022-02-01', 7000.00), (3, 1, '2022-03-01', 8000.00), (4, 1, '2022-03-05', 3000.00);
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List the donors who have donated more than once in a single month, and the dates of their donations.
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SELECT DonorID, DonationDate FROM Donations D1 WHERE DonorID IN (SELECT DonorID FROM Donations D2 WHERE D1.DonorID = D2.DonorID AND MONTH(D1.DonationDate) = MONTH(D2.DonationDate) AND YEAR(D1.DonationDate) = YEAR(D2.DonationDate) AND D1.DonationID <> D2.DonationID);
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gretelai_synthetic_text_to_sql
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CREATE TABLE BlueOrigin (ID INT, Mission VARCHAR(50), LaunchDate DATE); INSERT INTO BlueOrigin (ID, Mission, LaunchDate) VALUES (1, 'New Shepard', '2022-08-01'), (2, 'New Glenn', '2023-02-15'), (3, 'Blue Moon', '2024-01-01');
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What is the next scheduled launch date for Blue Origin missions?
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SELECT Mission, LEAD(LaunchDate) OVER (ORDER BY LaunchDate) as NextLaunchDate FROM BlueOrigin;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE research_projects (project_id INT PRIMARY KEY, project_name VARCHAR(50), project_type VARCHAR(50));
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Delete all records from the 'research_projects' table where the 'project_type' is 'genomics'
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DELETE FROM research_projects WHERE project_type = 'genomics';
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gretelai_synthetic_text_to_sql
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CREATE TABLE return_data (return_id INT, item_id INT, return_date DATE); INSERT INTO return_data (return_id, item_id, return_date) VALUES (1, 1, '2022-01-01'), (2, 2, '2022-02-01'), (3, 3, '2022-03-01'), (4, 4, '2022-04-01'), (5, 5, '2022-05-01'); CREATE TABLE restock_data (restock_id INT, item_id INT, restock_date DATE); INSERT INTO restock_data (restock_id, item_id, restock_date) VALUES (1, 1, '2022-01-05'), (2, 2, '2022-02-03'), (3, 3, '2022-03-08'), (4, 4, '2022-04-10'), (5, 5, '2022-05-15');
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How many days on average does it take for a returned item to be restocked in the Tokyo warehouse?
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SELECT AVG(DATEDIFF(day, return_date, restock_date)) FROM return_data JOIN restock_data ON return_data.item_id = restock_data.item_id WHERE restock_data.restock_location = 'Tokyo';
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gretelai_synthetic_text_to_sql
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CREATE TABLE customer_usage (usage_id INT, customer_id INT, usage_date DATE, data_usage DECIMAL(5,2));
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Insert a new record in the customer_usage table for a customer with id 1001, who used 500 MB of data on 2023-03-01
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INSERT INTO customer_usage (usage_id, customer_id, usage_date, data_usage) VALUES ((SELECT MAX(usage_id) FROM customer_usage) + 1, 1001, '2023-03-01', 500.00);
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gretelai_synthetic_text_to_sql
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CREATE TABLE urban_farms (id INT, city VARCHAR(20), acreage DECIMAL(5,2)); INSERT INTO urban_farms (id, city, acreage) VALUES (1, 'NY', 1.25), (2, 'LA', 2.50), (3, 'NY', 1.75), (4, 'LA', 3.00);
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What is the average acreage of urban farms in New York and Los Angeles?
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SELECT AVG(acreage) FROM urban_farms WHERE city IN ('NY', 'LA');
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gretelai_synthetic_text_to_sql
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CREATE TABLE ai_projects_region (organization_name TEXT, region TEXT); INSERT INTO ai_projects_region (organization_name, region) VALUES ('TechCorp', 'Asia-Pacific'), ('InnoTech', 'North America'), ('GreenAI', 'Europe'), ('AIforGood', 'Africa'), ('Tech4Good', 'North America'); CREATE TABLE ai_projects_budget (organization_name TEXT, budget INTEGER); INSERT INTO ai_projects_budget (organization_name, budget) VALUES ('TechCorp', 1500000), ('InnoTech', 2000000), ('GreenAI', 1000000), ('AIforGood', 1200000), ('Tech4Good', 1800000);
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What is the total budget spent on AI projects by organizations in the top 3 regions with the most organizations working on AI projects?
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SELECT SUM(budget) FROM ai_projects_budget INNER JOIN ai_projects_region ON ai_projects_budget.organization_name = ai_projects_region.organization_name WHERE region IN (SELECT region FROM (SELECT region, COUNT(*) as organization_count FROM ai_projects_region GROUP BY region ORDER BY organization_count DESC LIMIT 3) subquery);
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gretelai_synthetic_text_to_sql
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CREATE TABLE patient_demographics (patient_id INT, age INT, gender VARCHAR(255), condition VARCHAR(255));
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What is the average age of patients who have received treatment for depression or anxiety in the patient_demographics table, grouped by their gender?
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SELECT gender, AVG(age) FROM patient_demographics WHERE condition IN ('depression', 'anxiety') GROUP BY gender;
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gretelai_synthetic_text_to_sql
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CREATE TABLE climate_finance (id INT PRIMARY KEY, project_id INT, year INT, region VARCHAR(255), sector VARCHAR(255), amount DECIMAL(10,2));
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What is the total amount of climate finance invested in renewable energy projects in Africa since 2010?
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SELECT SUM(amount) FROM climate_finance WHERE sector = 'Renewable Energy' AND year >= 2010 AND region = 'Africa';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Daily_Response(Day DATE, Response_Time INT); INSERT INTO Daily_Response VALUES ('2022-01-01', 2), ('2022-01-01', 5), ('2022-01-02', 3), ('2022-01-03', 4), ('2022-01-03', 6);
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What is the average response time to citizen complaints per day, with the fastest response time first?
|
SELECT Day, AVG(Response_Time) as Avg_Response_Time FROM Daily_Response GROUP BY Day ORDER BY Avg_Response_Time ASC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE renewable_energy_projects (id INT, name VARCHAR(50), city VARCHAR(50), state VARCHAR(50), country VARCHAR(50), energy_type VARCHAR(50), capacity_mw FLOAT, PRIMARY KEY (id));
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What is the total installed capacity and number of renewable energy projects for each energy type in a specific city and state, ordered by the total capacity in descending order?
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SELECT city, state, energy_type, SUM(capacity_mw) as total_capacity, COUNT(*) as project_count, ROW_NUMBER() OVER (ORDER BY SUM(capacity_mw) DESC) as ranking FROM renewable_energy_projects WHERE city = 'CityName' AND state = 'StateName' GROUP BY energy_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE RecyclingFacilities (RFID INT, Location VARCHAR(50), Type VARCHAR(50), Capacity INT); INSERT INTO RecyclingFacilities (RFID, Location, Type, Capacity) VALUES (9, 'Jakarta', 'E-waste', 6000); INSERT INTO RecyclingFacilities (RFID, Location, Type, Capacity) VALUES (10, 'Jakarta', 'Glass', 7000); INSERT INTO RecyclingFacilities (RFID, Location, Type, Capacity) VALUES (11, 'Nairobi', 'E-waste', 8000); INSERT INTO RecyclingFacilities (RFID, Location, Type, Capacity) VALUES (12, 'Nairobi', 'Glass', 9000);
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Which recycling facilities can handle e-waste and glass in Jakarta and Nairobi?
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SELECT R.Location, R.Type FROM RecyclingFacilities R WHERE R.Location IN ('Jakarta', 'Nairobi') AND R.Type IN ('E-waste', 'Glass') GROUP BY R.Location, R.Type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE BusRoutes (RouteID INT, District VARCHAR(20), Fare DECIMAL(5,2)); INSERT INTO BusRoutes (RouteID, District, Fare) VALUES (1, 'North', 1.50), (2, 'South', 2.00), (3, 'East', 1.25), (4, 'North', 2.50), (5, 'West', 1.75);
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Find the maximum fare for bus routes serving the 'North' district.
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SELECT MAX(Fare) FROM BusRoutes WHERE District = 'North';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Countries (CountryID INT, CountryName VARCHAR(50));CREATE TABLE Products (ProductID INT, ProductName VARCHAR(50), ProductType VARCHAR(50), QuantitySold INT); INSERT INTO Countries VALUES (1, 'USA'), (2, 'Canada'); INSERT INTO Products VALUES (1, 'Chicken', 'Meat', 100), (2, 'Beef', 'Meat', 150), (3, 'Fish', 'Meat', 200), (4, 'Soy Milk', 'Dairy', 50);
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What is the maximum quantity of each type of meat product sold in each country?
|
SELECT c.CountryName, p.ProductType, MAX(p.QuantitySold) as MaxQuantitySold FROM Countries c JOIN Products p ON c.CountryID = 1 GROUP BY c.CountryName, p.ProductType;
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gretelai_synthetic_text_to_sql
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CREATE TABLE location (id INT, name TEXT, country TEXT); INSERT INTO location (id, name, country) VALUES (1, 'Operation A', 'Country G'); INSERT INTO location (id, name, country) VALUES (2, 'Operation B', 'Country H');
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How many mining operations are located in Country G?
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SELECT COUNT(*) FROM location WHERE country = 'Country G';
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gretelai_synthetic_text_to_sql
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CREATE TABLE rural_infrastructure_count (id INT, name VARCHAR(255)); INSERT INTO rural_infrastructure_count (id, name) VALUES (1, 'Water Supply System'), (2, 'Solar Farm'), (3, 'School'); CREATE TABLE community_initiatives_count (id INT, name VARCHAR(255)); INSERT INTO community_initiatives_count (id, name) VALUES (1, 'Youth Skills Training'), (2, 'Women Empowerment Program');
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Find the total number of rural infrastructure projects and community development initiatives in 'RuralDev' database.
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SELECT COUNT(*) FROM rural_infrastructure_count; SELECT COUNT(*) FROM community_initiatives_count;
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA fitness; CREATE TABLE membership (member_id INT, demographic_segment VARCHAR(20)); CREATE TABLE revenue (member_id INT, revenue DECIMAL(10,2), transaction_date DATE); INSERT INTO membership (member_id, demographic_segment) VALUES (1, 'Young Adults'), (2, 'Seniors'); INSERT INTO revenue (member_id, revenue, transaction_date) VALUES (1, 500, '2020-01-01'), (1, 600, '2020-02-01'), (2, 300, '2020-01-01');
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What is the total revenue generated from members in the "Young Adults" demographic segment for the year 2020?
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SELECT SUM(revenue) FROM revenue INNER JOIN membership ON revenue.member_id = membership.member_id WHERE membership.demographic_segment = 'Young Adults' AND YEAR(transaction_date) = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE asia_pacific_archaeology (site_id INT, radiocarbon_dating BOOLEAN);
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Count of sites in 'asia_pacific_archaeology' with 'radiocarbon_dating'?
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SELECT COUNT(*) FROM asia_pacific_archaeology WHERE radiocarbon_dating = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE healthcare_workers (id INT, name VARCHAR(50), age INT, gender VARCHAR(10), location VARCHAR(50)); INSERT INTO healthcare_workers (id, name, age, gender, location) VALUES (1, 'John Doe', 35, 'Male', 'New York'); INSERT INTO healthcare_workers (id, name, age, gender, location) VALUES (2, 'Jane Smith', 32, 'Female', 'California');
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List the names and locations of all female healthcare workers.
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SELECT name, location FROM healthcare_workers WHERE gender = 'Female';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Ethical_AI_Region (region VARCHAR(255), initiative VARCHAR(255), budget INT); INSERT INTO Ethical_AI_Region (region, initiative, budget) VALUES ('Asia', 'Transparency', 500000), ('Africa', 'Accountability', 300000), ('South America', 'Fairness', 200000), ('Europe', 'Explainability', 400000), ('North America', 'Privacy', 600000);
|
What is the distribution of ethical AI initiatives by region and budget?
|
SELECT region, initiative, AVG(budget) as avg_budget FROM Ethical_AI_Region GROUP BY region, initiative;
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gretelai_synthetic_text_to_sql
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CREATE TABLE carbon_offset_projects (id INT, project_name VARCHAR(100), region VARCHAR(50), carbon_offset FLOAT);
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Calculate the average carbon offset per project in the 'Europe' region
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SELECT AVG(carbon_offset) FROM carbon_offset_projects WHERE region = 'Europe';
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gretelai_synthetic_text_to_sql
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CREATE TABLE production (id INT, mine_id INT, year INT, product TEXT, production_volume INT); INSERT INTO production (id, mine_id, year, product, production_volume) VALUES (1, 1, 2020, 'Rare Earth Elements', 5000);
|
What is the total production volume of rare earth elements in China for the year 2020?
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SELECT SUM(production_volume) FROM production WHERE year = 2020 AND product = 'Rare Earth Elements' AND mine_id IN (SELECT id FROM mines WHERE location = 'China');
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gretelai_synthetic_text_to_sql
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CREATE TABLE students (student_id INT, name VARCHAR(255), major VARCHAR(255), gpa DECIMAL(3,2));
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Add a new student named "Jamie" with a major in "Computer Science" and a GPA of 3.8 to the "students" table.
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INSERT INTO students (name, major, gpa) VALUES ('Jamie', 'Computer Science', 3.8);
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gretelai_synthetic_text_to_sql
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CREATE TABLE orders_summary (menu_id INT, quantity INT); INSERT INTO orders_summary (menu_id, quantity) VALUES (1, 100), (2, 90), (3, 80), (4, 70), (5, 60);
|
Identify menu items ordered less frequently than 10% of the most ordered item.
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SELECT m.menu_name FROM menus m JOIN orders_summary os ON m.menu_id = os.menu_id WHERE os.quantity < (SELECT 0.1 * quantity FROM orders_summary WHERE quantity = (SELECT MAX(quantity) FROM orders_summary));
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gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthParity (ID INT, Violation VARCHAR(255), State VARCHAR(255), Date DATE); INSERT INTO MentalHealthParity VALUES (1, 'Non-compliance with mental health coverage', 'California', '2022-01-15'); INSERT INTO MentalHealthParity VALUES (2, 'Lack of mental health coverage parity', 'California', '2022-02-28');
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List all mental health parity violations in California in the past month.
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SELECT * FROM MentalHealthParity WHERE State = 'California' AND Date >= DATEADD(month, -1, GETDATE());
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gretelai_synthetic_text_to_sql
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CREATE TABLE military_innovation (id INT, country VARCHAR(50), patent VARCHAR(50), date DATE); INSERT INTO military_innovation (id, country, patent, date) VALUES (1, 'USA', 'Stealth Technology', '2015-01-01'); INSERT INTO military_innovation (id, country, patent, date) VALUES (2, 'China', 'Drone Technology', '2018-05-23'); INSERT INTO military_innovation (id, country, patent, date) VALUES (3, 'Russia', 'Cyber Warfare', '2016-12-12'); INSERT INTO military_innovation (id, country, patent, date) VALUES (4, 'France', 'AI in Military', '2017-07-04');
|
What are the top 5 countries with the highest number of military innovation patents since 2010?
|
SELECT country, COUNT(*) as patents_since_2010 FROM military_innovation WHERE date >= '2010-01-01' GROUP BY country ORDER BY patents_since_2010 DESC LIMIT 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE vessel (id INT, type VARCHAR(50), name VARCHAR(50));CREATE TABLE incident (id INT, vessel_id INT, incident_date DATE, incident_type VARCHAR(50));
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Which container vessels have had the most collisions in the past 3 years?
|
SELECT v.name, COUNT(i.id) as collision_count FROM vessel v INNER JOIN incident i ON v.id = i.vessel_id WHERE v.type = 'container' AND i.incident_type = 'collision' AND i.incident_date >= DATE(NOW(), INTERVAL -3 YEAR) GROUP BY v.name ORDER BY collision_count DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE community_development (government VARCHAR(50), half INT, expenditure FLOAT); INSERT INTO community_development (government, half, expenditure) VALUES ('US Federal Government', 1, 2000000), ('US State Government', 1, 1500000), ('US Local Government', 1, 1000000), ('German Federal Government', 1, 1200000), ('German State Government', 1, 800000);
|
What was the total community development expenditure by the US government in H1 2016?
|
SELECT SUM(expenditure) as total_expenditure FROM community_development WHERE government = 'US Federal Government' AND half = 1;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE community_health_workers (id INT, age INT, cultural_competency VARCHAR(20)); INSERT INTO community_health_workers (id, age, cultural_competency) VALUES (1, 35, 'High'), (2, 40, 'Medium'), (3, 30, 'Low'), (4, 45, 'High'), (5, 50, 'High');
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What is the average age of community health workers with high cultural competency?
|
SELECT AVG(age) FROM community_health_workers WHERE cultural_competency = 'High';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Inventory (id INT, warehouse_id INT, pallets INT); INSERT INTO Inventory (id, warehouse_id, pallets) VALUES (1, 1, 100), (2, 1, 200), (3, 2, 150); CREATE TABLE Warehouses (id INT, name VARCHAR(50), city VARCHAR(50), country VARCHAR(50)); INSERT INTO Warehouses (id, name, city, country) VALUES (1, 'Warehouse A', 'City A', 'Country A'), (2, 'Warehouse B', 'City B', 'Country B');
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How many pallets are stored in the warehouse with the most pallets?
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SELECT SUM(i.pallets) FROM Inventory i JOIN (SELECT MAX(total_pallets) AS max_pallets FROM (SELECT w.id, SUM(i.pallets) AS total_pallets FROM Inventory i JOIN Warehouses w ON i.warehouse_id = w.id GROUP BY w.id) subquery) subquery2 ON i.pallets = subquery2.max_pallets;
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gretelai_synthetic_text_to_sql
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CREATE TABLE waste_generation(year INT, state VARCHAR(20), material VARCHAR(20), amount INT); INSERT INTO waste_generation VALUES (2018, 'California', 'Plastic', 5000), (2018, 'California', 'Paper', 8000), (2019, 'California', 'Plastic', 5500), (2019, 'California', 'Paper', 8500), (2020, 'California', 'Plastic', 6000), (2020, 'California', 'Paper', 9000);
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What is the total waste generation by material type in 2020 for California?
|
SELECT SUM(amount) as total_waste, material FROM waste_generation WHERE year = 2020 AND state = 'California' GROUP BY material;
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gretelai_synthetic_text_to_sql
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CREATE TABLE hotel_virtual_tours (hotel_id INT, city VARCHAR(50), rating FLOAT); INSERT INTO hotel_virtual_tours (hotel_id, city, rating) VALUES (1, 'Paris', 4.6), (2, 'Paris', 4.5), (3, 'Rome', 4.4), (4, 'Rome', 4.3);
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What is the difference in average rating between hotel virtual tours in Paris and Rome?
|
SELECT city, AVG(rating) as avg_rating FROM hotel_virtual_tours GROUP BY city; SELECT (PARIS_AVG_RATING - ROME_AVG_RATING) as rating_difference;
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gretelai_synthetic_text_to_sql
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CREATE TABLE indian_ocean_research_stations (id INT, country TEXT, num_stations INT); INSERT INTO indian_ocean_research_stations (id, country, num_stations) VALUES (1, 'India', 15), (2, 'Indonesia', 20);
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What is the maximum number of marine research stations in the Indian Ocean?
|
SELECT MAX(num_stations) FROM indian_ocean_research_stations;
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gretelai_synthetic_text_to_sql
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SELECT * FROM NewHiresByQuarter;
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Query the NewHiresByQuarter view
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SELECT * FROM NewHiresByQuarter;
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gretelai_synthetic_text_to_sql
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CREATE TABLE content_categories (id INT, content_category VARCHAR(255)); CREATE TABLE posts_extended (id INT, content_category_id INT, content TEXT); INSERT INTO content_categories (id, content_category) VALUES (1, 'AI'), (2, 'Data Science'), (3, 'Machine Learning'); INSERT INTO posts_extended (id, content_category_id, content) VALUES (1, 1, 'Hello'), (2, 1, 'World'), (3, 2, 'AI');
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What is the total number of posts in each content category?
|
SELECT content_categories.content_category, COUNT(posts_extended.id) FROM content_categories JOIN posts_extended ON posts_extended.content_category_id = content_categories.id GROUP BY content_categories.content_category;
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gretelai_synthetic_text_to_sql
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CREATE TABLE teams (team_id INT, team_name VARCHAR(50)); INSERT INTO teams (team_id, team_name) VALUES (1, 'TeamA'), (2, 'TeamB'); CREATE TABLE ticket_sales (team_id INT, ticket_type VARCHAR(50), price DECIMAL(5,2)); INSERT INTO ticket_sales (team_id, ticket_type, price) VALUES (1, 'VIP', 100.00), (1, 'Regular', 60.00), (2, 'VIP', 120.00), (2, 'Regular', 70.00);
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What is the average ticket price by team and ticket type?
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SELECT t.team_name, ticket_type, AVG(ticket_sales.price) as avg_price FROM ticket_sales JOIN teams ON ticket_sales.team_id = teams.team_id GROUP BY t.team_name, ticket_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE projects (id INT, name VARCHAR(50), budget INT, completion_date DATE, planned_completion_date DATE);
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What is the success rate of rural infrastructure projects, defined as the percentage of projects that were completed on time and within budget, in the last 3 years?
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SELECT 100.0 * AVG(CASE WHEN budget = actual_spent AND completion_date <= planned_completion_date THEN 1 ELSE 0 END) as success_rate FROM (SELECT id, budget, completion_date, planned_completion_date, SUM(cost) as actual_spent FROM projects WHERE date(completion_date) >= date('now','-3 years') GROUP BY id) subquery;
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gretelai_synthetic_text_to_sql
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CREATE TABLE mine_productivity (mine_name TEXT, extraction_tons INTEGER, workforce_size INTEGER, productivity_tons_per_worker FLOAT, location TEXT); INSERT INTO mine_productivity (mine_name, extraction_tons, workforce_size, productivity_tons_per_worker, location) VALUES ('Golden Ridge Mine', 3500, 200, 17.5, 'North America'), ('Silver Peak Mine', 2800, 150, 18.67, 'North America'), ('Emerald Paradise Mine', 2200, 250, 8.8, 'Asia'), ('Ruby Desert Mine', 4500, 300, 15, 'Africa');
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What is the maximum productivity for mines located in 'Africa'?
|
SELECT MAX(productivity_tons_per_worker) as max_productivity FROM mine_productivity WHERE location = 'Africa';
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gretelai_synthetic_text_to_sql
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CREATE TABLE workforce (id INT PRIMARY KEY, name VARCHAR(50), gender VARCHAR(50), role VARCHAR(50)); INSERT INTO workforce (id, name, gender, role) VALUES (1, 'John Doe', 'Male', 'Miner'), (2, 'Jane Smith', 'Female', 'Engineer'), (3, 'Alberto Garcia', 'Male', 'Manager'), (4, 'Sandra Rodriguez', 'Female', 'Miner'), (5, 'David Kim', 'Male', 'Engineer');
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What's the total number of workers in the mining industry, categorized by their gender?
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SELECT gender, COUNT(*) as total_workers FROM workforce GROUP BY gender;
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gretelai_synthetic_text_to_sql
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CREATE TABLE EsportsEvents (EventID INT, City VARCHAR(50), Country VARCHAR(50), Year INT); INSERT INTO EsportsEvents (EventID, City, Country, Year) VALUES (1, 'Los Angeles', 'USA', 2019), (2, 'Paris', 'France', 2019), (3, 'Tokyo', 'Japan', 2020), (4, 'Seoul', 'South Korea', 2018);
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How many esports events were held in Tokyo, Japan in 2020?
|
SELECT COUNT(*) FROM EsportsEvents WHERE City = 'Tokyo' AND Year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cuisine (id INT, name VARCHAR(255)); INSERT INTO cuisine (id, name) VALUES (1, 'Asian'), (2, 'Italian'), (3, 'Mexican'); CREATE TABLE dishes (id INT, name VARCHAR(255), cuisine_id INT, calories INT); INSERT INTO dishes (id, name, cuisine_id, calories) VALUES (1, 'Pad Thai', 1, 600), (2, 'Fried Rice', 1, 700), (3, 'Pizza', 2, 1200), (4, 'Tacos', 3, 800);
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What is the average calorie count for dishes in the Asian cuisine category?
|
SELECT AVG(calories) FROM dishes WHERE cuisine_id = (SELECT id FROM cuisine WHERE name = 'Asian');
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gretelai_synthetic_text_to_sql
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CREATE TABLE employee (id INT, name VARCHAR(50), department VARCHAR(20), hire_date DATE);CREATE VIEW experienced_employees_by_dept AS SELECT department, id, name, DATEDIFF(CURDATE(), hire_date) as work_experience FROM employee WHERE department IN ('Manufacturing', 'Design');
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Identify the most experienced employees in each department.
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SELECT department, id, name, work_experience, RANK() OVER (PARTITION BY department ORDER BY work_experience DESC) as experience_rank FROM experienced_employees_by_dept WHERE experience_rank = 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE suppliers (id INT, name VARCHAR(255), country VARCHAR(255)); CREATE TABLE products (id INT, name VARCHAR(255), organic BOOLEAN, weight FLOAT, supplier_id INT);
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Find the total weight of organic products supplied by the top 2 suppliers.
|
SELECT s.name, SUM(p.weight) FROM suppliers s INNER JOIN products p ON s.id = p.supplier_id WHERE p.organic = 't' GROUP BY s.name ORDER BY SUM(p.weight) DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE water (country VARCHAR(255), region VARCHAR(255), access INT); INSERT INTO water (country, region, access) VALUES ('Country A', 'Latin America', 500000), ('Country B', 'Latin America', 600000);
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How many people have access to clean water in Latin America?
|
SELECT SUM(access) FROM water WHERE region = 'Latin America';
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gretelai_synthetic_text_to_sql
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CREATE TABLE wind_farms (id INT, name TEXT, region TEXT, capacity_mw FLOAT); INSERT INTO wind_farms (id, name, region, capacity_mw) VALUES (1, 'Windfarm A', 'west', 150.5); INSERT INTO wind_farms (id, name, region, capacity_mw) VALUES (2, 'Windfarm B', 'east', 120.2); CREATE TABLE solar_power_plants (id INT, name TEXT, region TEXT, capacity_mw FLOAT); INSERT INTO solar_power_plants (id, name, region, capacity_mw) VALUES (1, 'Solar Plant A', 'north', 125.8); INSERT INTO solar_power_plants (id, name, region, capacity_mw) VALUES (2, 'Solar Plant B', 'south', 180.3);
|
Which renewable energy projects have a capacity greater than 150 MW?
|
SELECT name, capacity_mw FROM wind_farms WHERE capacity_mw > 150 UNION ALL SELECT name, capacity_mw FROM solar_power_plants WHERE capacity_mw > 150;
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gretelai_synthetic_text_to_sql
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CREATE TABLE dams (dam_name TEXT, dam_year INT, dam_state TEXT); INSERT INTO dams (dam_name, dam_year, dam_state) VALUES ('D1', 2015, 'Texas'), ('D2', 2018, 'Texas'), ('D3', 2008, 'Texas'), ('D4', 2012, 'Texas'), ('D5', 2020, 'Texas');
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How many dams were built in Texas between 2010 and 2020?
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SELECT COUNT(*) FROM dams WHERE dam_year BETWEEN 2010 AND 2020 AND dam_state = 'Texas';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vulnerabilities (id INT, sector VARCHAR(255), severity FLOAT); INSERT INTO vulnerabilities (id, sector, severity) VALUES (1, 'healthcare', 7.5), (2, 'finance', 5.2), (3, 'healthcare', 8.1);
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What is the average severity score of vulnerabilities detected in the healthcare sector?
|
SELECT AVG(severity) FROM vulnerabilities WHERE sector = 'healthcare';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE programs (id INT, name VARCHAR(50), location VARCHAR(50), type VARCHAR(50), start_date DATE, end_date DATE);
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Insert a new restorative justice program into the 'programs' table
|
INSERT INTO programs (id, name, location, type, start_date, end_date) VALUES (103, 'Victim-Offender Mediation', 'San Francisco, CA', 'Restorative Justice', '2023-01-01', '2023-12-31');
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gretelai_synthetic_text_to_sql
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CREATE TABLE ArtSales (SaleID INT, SaleDate DATE, Revenue INT); INSERT INTO ArtSales (SaleID, SaleDate, Revenue) VALUES (1, '2022-01-01', 1000), (2, '2022-02-01', 2000), (3, '2022-03-01', 3000), (4, '2022-04-01', 1500), (5, '2022-05-01', 2500), (6, '2022-06-01', 3500), (7, '2022-07-01', 1700), (8, '2022-08-01', 2700), (9, '2022-09-01', 3700), (10, '2022-10-01', 2200), (11, '2022-11-01', 3200), (12, '2022-12-01', 4200);
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What is the total revenue generated from art sales in each quarter?
|
SELECT QUARTER(SaleDate) as Quarter, SUM(Revenue) as TotalRevenue FROM ArtSales GROUP BY Quarter;
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gretelai_synthetic_text_to_sql
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CREATE TABLE startup_founders (id INT PRIMARY KEY, name VARCHAR(255), sexual_orientation VARCHAR(50), industry VARCHAR(255), total_funding FLOAT);
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What is the total funding for startups founded by a person from the LGBTQ+ community?
|
SELECT SUM(total_funding) FROM startup_founders WHERE sexual_orientation = 'LGBTQ+';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE nyc_real_estate(id INT, borough VARCHAR(50), green_roof BOOLEAN); INSERT INTO nyc_real_estate VALUES (1, 'Manhattan', true);
|
How many properties are there in each borough of NYC that have green roofs?
|
SELECT borough, COUNT(*) FROM nyc_real_estate WHERE green_roof = true GROUP BY borough;
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gretelai_synthetic_text_to_sql
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CREATE TABLE users (id INT, name TEXT, time_spent_reading INT); CREATE TABLE user_activity (user_id INT, article_id INT, start_time DATETIME, end_time DATETIME); CREATE TABLE articles (id INT, title TEXT, category TEXT);
|
Who are the top 5 users who spent the most time reading articles about 'politics'?
|
SELECT name FROM (SELECT user_id, SUM(TIMESTAMPDIFF(MINUTE, start_time, end_time)) AS time_spent_reading FROM user_activity JOIN articles ON user_activity.article_id = articles.id WHERE articles.category = 'politics' GROUP BY user_id ORDER BY time_spent_reading DESC LIMIT 5) AS subquery JOIN users ON subquery.user_id = users.id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE peacekeeping_ops (id INT, country VARCHAR(50), region VARCHAR(50)); INSERT INTO peacekeeping_ops (id, country, region) VALUES (1, 'Nigeria', 'Africa'), (2, 'Ukraine', 'Europe'), (3, 'Iraq', 'Middle East');
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Display the "country" and "region" columns from the "peacekeeping_ops" table, showing only records where the "region" column is 'Europe'
|
SELECT country, region FROM peacekeeping_ops WHERE region = 'Europe';
|
gretelai_synthetic_text_to_sql
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CREATE VIEW green_certified_properties AS SELECT * FROM properties WHERE has_green_certification = TRUE;
|
What is the total number of properties with a green certification in the green_certified_properties view?
|
SELECT COUNT(*) FROM green_certified_properties;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Clients (ClientID int, Age int, Gender varchar(10), Region varchar(50)); INSERT INTO Clients (ClientID, Age, Gender, Region) VALUES (11, 35, 'Female', 'Asia'); CREATE TABLE Cases (CaseID int, ClientID int, Category varchar(50)); INSERT INTO Cases (CaseID, ClientID, Category) VALUES (1101, 11, 'Civil Law');
|
What is the total number of clients from 'Asia' who have had 'civil law' cases?
|
SELECT COUNT(DISTINCT C.ClientID) as TotalClients FROM Clients C INNER JOIN Cases CA ON C.ClientID = CA.ClientID WHERE C.Region = 'Asia' AND CA.Category = 'Civil Law';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE manufacturing_emissions (emission_id INT, product_id INT, co2_emissions FLOAT, emission_date DATE);
|
What is the total CO2 emissions from manufacturing cosmetics in the last 12 months?
|
SELECT SUM(co2_emissions) FROM manufacturing_emissions WHERE emission_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) AND CURRENT_DATE;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE climate_finance_2019 (recipient_name TEXT, funding_year INTEGER); INSERT INTO climate_finance_2019 (recipient_name, funding_year) VALUES ('Recipient A', 2019), ('Recipient B', 2019), ('Recipient A', 2020); CREATE TABLE climate_finance_2020 (recipient_name TEXT, funding_year INTEGER); INSERT INTO climate_finance_2020 (recipient_name, funding_year) VALUES ('Recipient A', 2020), ('Recipient C', 2020);
|
Display the names of all climate finance recipients who received funding in both 2019 and 2020.
|
SELECT recipient_name FROM climate_finance_2019 WHERE funding_year = 2019 INTERSECT SELECT recipient_name FROM climate_finance_2020 WHERE funding_year = 2020;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE artworks (artwork_id INT, artwork_name TEXT, artist_name TEXT, country TEXT); CREATE TABLE country_continent (country TEXT, continent TEXT);
|
What is the number of artworks in the artworks table, grouped by country, excluding those from the United States?
|
SELECT country, COUNT(artwork_id) FROM artworks JOIN country_continent ON artworks.country = country_continent.country WHERE country != 'United States' GROUP BY country;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE clients (client_id INT, name VARCHAR(50), region VARCHAR(50)); INSERT INTO clients VALUES (1, 'John Doe', 'Latin America'), (2, 'Jane Smith', 'North America'), (3, 'Alice Johnson', 'Latin America'); CREATE TABLE transactions (transaction_id INT, client_id INT, transaction_date DATE, transaction_amount DECIMAL(10,2)); INSERT INTO transactions VALUES (1, 1, '2022-04-01', 100.00), (2, 1, '2022-05-01', 200.00), (3, 2, '2022-04-15', 150.00), (4, 3, '2022-05-01', 50.00);
|
What is the average transaction amount by client in the Latin America region in Q2 2022?
|
SELECT c.region, AVG(t.transaction_amount) FROM clients c JOIN transactions t ON c.client_id = t.client_id WHERE c.region = 'Latin America' AND t.transaction_date BETWEEN '2022-04-01' AND '2022-06-30' GROUP BY c.region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tokyo_art(id INT, museum VARCHAR(30), section VARCHAR(30), value INT); INSERT INTO tokyo_art VALUES (1, 'Tokyo National Museum', 'Modern Art', 1000000); INSERT INTO tokyo_art VALUES (2, 'Mori Art Museum', 'Modern Art', 2000000);
|
What is the total value of artworks in the modern art section of the museums in Tokyo?
|
SELECT SUM(value) FROM tokyo_art WHERE museum IN (SELECT museum FROM tokyo_art WHERE section = 'Modern Art') AND section = 'Modern Art';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE subway_trips (trip_id INT, trip_date DATE, station_id INT); CREATE TABLE subway_stations (station_id INT, station_name VARCHAR(255), city VARCHAR(255));
|
How many subway trips were taken in Berlin in the last week?
|
SELECT COUNT(*) FROM subway_trips JOIN subway_stations ON subway_trips.station_id = subway_stations.station_id WHERE subway_stations.city = 'Berlin' AND subway_trips.trip_date >= DATEADD(WEEK, -1, GETDATE());
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gretelai_synthetic_text_to_sql
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CREATE TABLE healthcare_facilities (facility_id INT, country VARCHAR(20), num_beds INT); INSERT INTO healthcare_facilities (facility_id, country, num_beds) VALUES (1, 'Brazil', 50), (2, 'Mexico', 75);
|
Calculate the average number of hospital beds per rural healthcare facility in Brazil and Mexico.
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SELECT AVG(num_beds) FROM healthcare_facilities WHERE country IN ('Brazil', 'Mexico');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE fan_demographics (fan_id INT, gender VARCHAR(255), team_id INT); INSERT INTO fan_demographics (fan_id, gender, team_id) VALUES (1, 'Male', 1), (2, 'Female', 2), (3, 'Male', 1), (4, 'Male', 3), (5, 'Female', 2); CREATE TABLE teams (team_id INT, team_name VARCHAR(255)); INSERT INTO teams (team_id, team_name) VALUES (1, 'Knicks'), (2, 'Lakers'), (3, 'Chelsea');
|
What is the distribution of fans by gender for each team?
|
SELECT t.team_name, f.gender, COUNT(f.fan_id) fan_count FROM fan_demographics f JOIN teams t ON f.team_id = t.team_id GROUP BY t.team_name, f.gender;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE sustainable_projects (id INT, project_name TEXT, state TEXT, completion_year INT, is_sustainable BOOLEAN); INSERT INTO sustainable_projects (id, project_name, state, completion_year, is_sustainable) VALUES (1, 'Solar Park', 'New York', 2021, true), (2, 'Wind Farm', 'California', 2020, true), (3, 'Green Apartments', 'New York', 2021, true), (4, 'Eco-Hotel', 'Florida', 2020, false);
|
How many sustainable building projects were completed in New York in 2021?
|
SELECT COUNT(*) FROM sustainable_projects WHERE state = 'New York' AND completion_year = 2021 AND is_sustainable = true;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE department (name VARCHAR(255)); CREATE TABLE employee (id INT, name VARCHAR(255), gender VARCHAR(50), ethnicity VARCHAR(50), department_id INT);
|
Find the number of employees of different genders and ethnicities in each department of the company.
|
SELECT department.name AS department, gender, ethnicity, COUNT(*) AS employee_count FROM department INNER JOIN employee ON department.id = employee.department_id GROUP BY department.name, gender, ethnicity;
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gretelai_synthetic_text_to_sql
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CREATE TABLE species_timber_2 (species_id INT, species_name VARCHAR(50), year INT, volume INT); INSERT INTO species_timber_2 (species_id, species_name, year, volume) VALUES (1, 'Oak', 2018, 1000), (2, 'Pine', 2018, 2000), (3, 'Maple', 2018, 3000), (4, 'Birch', 2018, 4000), (1, 'Oak', 2019, 900), (2, 'Pine', 2019, 2200), (3, 'Maple', 2019, 3300), (4, 'Birch', 2019, 4200);
|
Identify the species with a decrease in timber production between 2018 and 2019, and order them by the largest decrease first.
|
SELECT species_name, (LAG(volume, 1) OVER (PARTITION BY species_name ORDER BY year)) - volume AS volume_decrease FROM species_timber_2 WHERE year = 2019 GROUP BY species_name, volume ORDER BY volume_decrease DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE user_activity (user_id INT, activity_type VARCHAR(50), hobby VARCHAR(50)); INSERT INTO user_activity (user_id, activity_type, hobby) VALUES (1, 'followed_account', 'yoga'), (2, 'engaged_post', 'cooking'), (3, 'followed_account', 'hiking'), (4, 'engaged_post', 'painting'), (5, 'followed_account', 'meditation'), (6, 'engaged_post', 'gardening');
|
What are the unique hobbies of users who have followed accounts about mental health advocacy but have not engaged with posts about mindfulness.
|
SELECT hobby FROM user_activity WHERE activity_type = 'followed_account' AND user_id NOT IN (SELECT user_id FROM user_activity WHERE activity_type = 'engaged_post' AND post_topic = 'mindfulness');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE movies (id INT PRIMARY KEY, title VARCHAR(100), release_year INT, genre VARCHAR(50), production_budget INT);
|
Update the production budget of all movies released in 2010 by 15%
|
UPDATE movies SET production_budget = production_budget * 1.15 WHERE release_year = 2010;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE offenses (id INT, victim_id INT, offense_type VARCHAR(50), date_of_offense DATE);
|
Add a new offense record into the "offenses" table
|
INSERT INTO offenses (id, victim_id, offense_type, date_of_offense) VALUES (2003, 1002, 'Assault', '2021-09-25');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Companies (CompanyID INT, CompanyName VARCHAR(50), LaborProductivity DECIMAL(5,2)); INSERT INTO Companies (CompanyID, CompanyName, LaborProductivity) VALUES (1, 'ABC Mining', 15.5), (2, 'XYZ Excavations', 12.3), (3, 'MNO Drilling', 18.7), (4, 'PQR Quarrying', 10.1);
|
What are the names of mining companies with the highest and lowest labor productivity?
|
SELECT CompanyName FROM Companies WHERE LaborProductivity = (SELECT MAX(LaborProductivity) FROM Companies) OR LaborProductivity = (SELECT MIN(LaborProductivity) FROM Companies);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE restaurant_inspections (restaurant_name VARCHAR(255), location VARCHAR(255), score INTEGER, inspection_date DATE); INSERT INTO restaurant_inspections (restaurant_name, location, score, inspection_date) VALUES ('Restaurant A', 'New York', 90, '2021-01-01'), ('Restaurant B', 'New York', 85, '2021-02-01');
|
What was the average food safety score for restaurants in New York in 2021?
|
SELECT AVG(score) FROM restaurant_inspections WHERE location = 'New York' AND YEAR(inspection_date) = 2021;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE users (id INT, name VARCHAR(50), gender VARCHAR(10), age INT, location VARCHAR(50), posts INT); CREATE TABLE posts (id INT, user_id INT, content TEXT, timestamp TIMESTAMP);
|
What is the average number of posts per day for users over 40 years old in the 'social_media' database?
|
SELECT AVG(COUNT(posts.id)/86400) AS avg_posts_per_day FROM posts JOIN users ON posts.user_id = users.id WHERE users.age > 40;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE well_production (well_name VARCHAR(20), production_qty FLOAT, production_date DATE); INSERT INTO well_production (well_name, production_qty, production_date) VALUES ('Well A', 1000, '2020-01-01'); INSERT INTO well_production (well_name, production_qty, production_date) VALUES ('Well B', 1500, '2020-01-01'); INSERT INTO well_production (well_name, production_qty, production_date) VALUES ('Well C', 1200, '2020-01-01');
|
List the top 3 producing wells in the North Sea, partitioned by year.
|
SELECT well_name, production_qty, production_date, RANK() OVER (PARTITION BY EXTRACT(YEAR FROM production_date) ORDER BY production_qty DESC) as rank FROM well_production WHERE well_name LIKE 'Well%' AND production_date BETWEEN '2020-01-01' AND '2021-12-31' AND location = 'North Sea' ORDER BY production_date, rank;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE music_genres (genre_id INT, genre VARCHAR(255)); CREATE TABLE platforms (platform_id INT, platform_name VARCHAR(255)); CREATE TABLE revenue (genre_id INT, platform_id INT, revenue INT, year INT); INSERT INTO music_genres (genre_id, genre) VALUES (1, 'Latin'); INSERT INTO platforms (platform_id, platform_name) VALUES (1, 'Spotify'); INSERT INTO revenue (genre_id, platform_id, revenue, year) VALUES (1, 1, 1000000, 2015);
|
What is the total revenue for Latin music on streaming platforms since 2015?
|
SELECT SUM(revenue) FROM revenue JOIN music_genres ON revenue.genre_id = music_genres.genre_id JOIN platforms ON revenue.platform_id = platforms.platform_id WHERE music_genres.genre = 'Latin' AND revenue.year >= 2015;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Accommodations (ID INT, Type VARCHAR(50), Cost FLOAT, Disability VARCHAR(50), Region VARCHAR(50)); INSERT INTO Accommodations (ID, Type, Cost, Disability, Region) VALUES (1, 'Wheelchair Accessibility', 2000.0, 'Physical Disability', 'Southwest'), (2, 'Adaptive Equipment', 2500.0, 'Physical Disability', 'Southwest'), (3, 'Sign Language Interpretation', 1500.0, 'Physical Disability', 'Southwest');
|
What is the maximum budget for accommodations for students with physical disabilities in the Southwest?
|
SELECT MAX(Cost) FROM Accommodations WHERE Disability = 'Physical Disability' AND Region = 'Southwest';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE vehicle_types (vehicle_type_id INT, vehicle_type VARCHAR(255)); CREATE TABLE maintenance_requests (request_id INT, vehicle_type_id INT, request_date DATE);
|
How many maintenance requests have been submitted for each vehicle type?
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SELECT vt.vehicle_type, COUNT(mr.request_id) as num_requests FROM vehicle_types vt INNER JOIN maintenance_requests mr ON vt.vehicle_type_id = mr.vehicle_type_id GROUP BY vt.vehicle_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Volunteers (VolunteerID INT, VolunteerName TEXT); INSERT INTO Volunteers (VolunteerID, VolunteerName) VALUES (1, 'Alice'), (2, 'Bob'); CREATE TABLE Assignments (AssignmentID INT, VolunteerID INT, ProjectID INT, ProjectCountry TEXT); INSERT INTO Assignments (AssignmentID, VolunteerID, ProjectID, ProjectCountry) VALUES (1, 1, 1, 'Japan'), (2, 2, 2, 'China');
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List all volunteers who have not been assigned to a project in Asia.
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SELECT Volunteers.VolunteerName FROM Volunteers LEFT JOIN Assignments ON Volunteers.VolunteerID = Assignments.VolunteerID WHERE Assignments.ProjectCountry IS NULL OR Assignments.ProjectCountry != 'Asia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE marine_species (id INT PRIMARY KEY, name VARCHAR(255), conservation_status VARCHAR(255)); INSERT INTO marine_species (id, name, conservation_status) VALUES (1, 'Whale Shark', 'Endangered'); CREATE TABLE oceanography (id INT PRIMARY KEY, species_id INT, sea_surface_temperature INT); INSERT INTO oceanography (id, species_id, sea_surface_temperature) VALUES (1, 1, 30);
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Update the conservation status of the species with the highest sea surface temperature to 'Critically Endangered'.
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UPDATE marine_species m SET m.conservation_status = 'Critically Endangered' FROM oceanography o WHERE m.id = o.species_id AND o.sea_surface_temperature = (SELECT MAX(sea_surface_temperature) FROM oceanography);
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gretelai_synthetic_text_to_sql
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CREATE TABLE prescriptions (id INT PRIMARY KEY, patient_id INT, drug VARCHAR(50), country VARCHAR(50), prescription_date DATE);
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Which antidepressants are most commonly prescribed in Australia?
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SELECT drug FROM prescriptions WHERE country = 'Australia' AND drug LIKE '%antidepressant%' GROUP BY drug ORDER BY COUNT(*) DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Student (StudentID INT, Name VARCHAR(20), District VARCHAR(20));
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Insert a new student 'Pascale' from 'RainbowSchool' district into the 'Student' table.
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INSERT INTO Student (StudentID, Name, District) VALUES (3, 'Pascale', 'RainbowSchool');
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gretelai_synthetic_text_to_sql
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CREATE TABLE ota_bookings (booking_id INT, ota_name TEXT, region TEXT, booking_amount DECIMAL(10,2)); INSERT INTO ota_bookings (booking_id, ota_name, region, booking_amount) VALUES (1, 'Booking.com', 'APAC', 200.50), (2, 'Expedia', 'NA', 150.25), (3, 'Agoda', 'APAC', 300.00);
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What is the total revenue of OTA bookings from APAC region in 2021?
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SELECT SUM(booking_amount) FROM ota_bookings WHERE region = 'APAC' AND YEAR(booking_date) = 2021;
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gretelai_synthetic_text_to_sql
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CREATE TABLE News (news_id INT, title TEXT, category TEXT); INSERT INTO News (news_id, title, category) VALUES (1, 'Article1', 'Politics'), (2, 'Article2', 'Sports'), (3, 'Article3', 'Politics'); CREATE TABLE Categories (category_id INT, category_name TEXT); INSERT INTO Categories (category_id, category_name) VALUES (1, 'Politics'), (2, 'Sports'), (3, 'Culture');
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How many news articles are there in each news category?
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SELECT c.category_name, COUNT(n.news_id) as num_articles FROM News n INNER JOIN Categories c ON n.category = c.category_name GROUP BY c.category_name;
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gretelai_synthetic_text_to_sql
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