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6c066c1a4a
* test: migrate join tests Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * chore: update test results after rebasing main branch Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: unstable query sort results and natural_join test Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: count(*) with joining Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: unstable query sort results and style Signed-off-by: Dennis Zhuang <killme2008@gmail.com> --------- Signed-off-by: Dennis Zhuang <killme2008@gmail.com>
95 lines
3.1 KiB
SQL
95 lines
3.1 KiB
SQL
-- Migrated from DuckDB test: test/sql/join/iejoin/ inequality join tests
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-- Tests inequality join conditions
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CREATE TABLE time_events(event_id INTEGER, event_time TIMESTAMP, event_type VARCHAR, ts TIMESTAMP TIME INDEX);
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CREATE TABLE time_windows(window_id INTEGER, start_time TIMESTAMP, end_time TIMESTAMP, window_name VARCHAR, ts TIMESTAMP TIME INDEX);
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INSERT INTO time_events VALUES
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(1, '2023-01-01 10:15:00', 'login', 1000),
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(2, '2023-01-01 10:30:00', 'purchase', 2000),
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(3, '2023-01-01 10:45:00', 'logout', 3000),
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(4, '2023-01-01 11:05:00', 'login', 4000),
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(5, '2023-01-01 11:20:00', 'view', 5000),
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(6, '2023-01-01 11:35:00', 'purchase', 6000);
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INSERT INTO time_windows VALUES
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(1, '2023-01-01 10:00:00', '2023-01-01 10:30:00', 'Morning Early', 1000),
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(2, '2023-01-01 10:30:00', '2023-01-01 11:00:00', 'Morning Late', 2000),
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(3, '2023-01-01 11:00:00', '2023-01-01 11:30:00', 'Noon Early', 3000),
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(4, '2023-01-01 11:30:00', '2023-01-01 12:00:00', 'Noon Late', 4000);
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-- Range join: events within time windows
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SELECT
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e.event_id, e.event_time, e.event_type, w.window_name
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FROM time_events e
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INNER JOIN time_windows w
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ON e.event_time >= w.start_time AND e.event_time < w.end_time
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ORDER BY e.event_time;
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-- Inequality join with additional conditions
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SELECT
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e.event_id, e.event_type, w.window_name
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FROM time_events e
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INNER JOIN time_windows w
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ON e.event_time >= w.start_time
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AND e.event_time < w.end_time
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AND e.event_type = 'purchase'
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ORDER BY e.event_time;
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-- Cross-time analysis with inequality joins
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SELECT
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e1.event_id as first_event, e2.event_id as second_event,
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e1.event_type as first_type, e2.event_type as second_type,
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e2.event_time - e1.event_time as time_diff
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FROM time_events e1
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INNER JOIN time_events e2
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ON e1.event_time < e2.event_time
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AND e2.event_time - e1.event_time <= INTERVAL '30 minutes'
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ORDER BY e1.event_time, e2.event_time;
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CREATE TABLE price_history(item_id INTEGER, price DOUBLE, effective_date DATE, ts TIMESTAMP TIME INDEX);
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CREATE TABLE orders_ineq(order_id INTEGER, item_id INTEGER, order_date DATE, ts TIMESTAMP TIME INDEX);
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INSERT INTO price_history VALUES
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(1, 100.00, '2023-01-01', 1000), (1, 110.00, '2023-01-15', 2000),
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(2, 50.00, '2023-01-01', 3000), (2, 55.00, '2023-01-20', 4000);
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INSERT INTO orders_ineq VALUES
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(1, 1, '2023-01-10', 1000), (2, 1, '2023-01-20', 2000),
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(3, 2, '2023-01-05', 3000), (4, 2, '2023-01-25', 4000);
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-- Historical price lookup with inequality join
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SELECT
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o.order_id, o.order_date, p.price, p.effective_date
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FROM orders_ineq o
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INNER JOIN price_history p
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ON o.item_id = p.item_id
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AND o.order_date >= p.effective_date
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ORDER BY o.order_id;
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-- Latest price before order date
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SELECT
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o.order_id, o.order_date, latest_price.price
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FROM orders_ineq o
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INNER JOIN (
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SELECT
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item_id,
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price,
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effective_date,
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ROW_NUMBER() OVER (PARTITION BY item_id ORDER BY effective_date DESC) as rn
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FROM price_history
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) latest_price
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ON o.item_id = latest_price.item_id
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AND o.order_date >= latest_price.effective_date
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AND latest_price.rn = 1
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ORDER BY o.order_id;
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DROP TABLE time_events;
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DROP TABLE time_windows;
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DROP TABLE price_history;
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DROP TABLE orders_ineq;
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