mirror of https://github.com/citusdata/citus.git
1349 lines
38 KiB
PL/PgSQL
1349 lines
38 KiB
PL/PgSQL
--
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-- multi subquery behavioral analytics queries aims to expand existing subquery pushdown
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-- regression tests to cover more cases
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-- the tables that are used depends to multi_insert_select_behavioral_analytics_create_table.sql
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--
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-- We don't need shard id sequence here, so commented out to prevent conflicts with concurrent tests
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-- ALTER SEQUENCE pg_catalog.pg_dist_shardid_seq RESTART 1430000;
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-- ALTER SEQUENCE pg_catalog.pg_dist_jobid_seq RESTART 1430000;
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SET citus.enable_router_execution TO FALSE;
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------------------------------------
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-- Vanilla funnel query
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------------------------------------
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SELECT user_id, array_length(events_table, 1)
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FROM (
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SELECT user_id, array_agg(event ORDER BY time) AS events_table
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FROM (
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SELECT u.user_id, e.event_type::text AS event, e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (100, 101, 102)
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) t
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GROUP BY user_id
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) q
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ORDER BY 2 DESC, 1;
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------------------------------------
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-- Funnel grouped by whether or not a user has done an event
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-- This has multiple subqueries joinin at the top level
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------------------------------------
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SELECT user_id, sum(array_length(events_table, 1)), length(hasdone_event), hasdone_event
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FROM (
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SELECT
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t1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(hasdone_event, 'Has not done event') AS hasdone_event
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FROM (
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(
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SELECT u.user_id, 'step=>1'::text AS event, e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (100, 101, 102)
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)
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UNION
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(
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SELECT u.user_id, 'step=>2'::text AS event, e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (103, 104, 105)
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)
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) t1 LEFT JOIN (
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SELECT DISTINCT user_id,
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'Has done event'::TEXT AS hasdone_event
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FROM events_table AS e
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WHERE e.user_id >= 10
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AND e.user_id <= 25
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AND e.event_type IN (106, 107, 108)
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) t2 ON (t1.user_id = t2.user_id)
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GROUP BY t1.user_id, hasdone_event
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) t GROUP BY user_id, hasdone_event
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ORDER BY user_id;
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-- same query but multiple joins are one level below, returns count of row instead of actual rows
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SELECT count(*)
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FROM (
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SELECT user_id, sum(array_length(events_table, 1)), length(hasdone_event), hasdone_event
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FROM (
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SELECT
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t1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(hasdone_event, 'Has not done event') AS hasdone_event
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FROM (
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(
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SELECT u.user_id, 'step=>1'::text AS event, e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (100, 101, 102)
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)
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UNION
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(
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SELECT u.user_id, 'step=>2'::text AS event, e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (103, 104, 105)
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)
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) t1 LEFT JOIN (
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SELECT DISTINCT user_id,
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'Has done event'::TEXT AS hasdone_event
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FROM events_table AS e
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WHERE e.user_id >= 10
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AND e.user_id <= 25
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AND e.event_type IN (106, 107, 108)
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) t2 ON (t1.user_id = t2.user_id)
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GROUP BY t1.user_id, hasdone_event
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) t GROUP BY user_id, hasdone_event
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ORDER BY user_id) u;
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-- Same queries written without unions
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SELECT user_id, sum(array_length(events_table, 1)), length(hasdone_event), hasdone_event
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FROM (
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SELECT
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t1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(hasdone_event, 'Has not done event') AS hasdone_event
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FROM (
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SELECT
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u.user_id,
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CASE WHEN e.event_type IN (100, 101, 102) THEN 'step=>1'::text else 'step==>2'::text END AS event,
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e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (100, 101, 102, 103, 104, 105)
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GROUP BY 1,2,3
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) t1 LEFT JOIN (
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SELECT DISTINCT user_id,
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'Has done event'::TEXT AS hasdone_event
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FROM events_table AS e
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WHERE e.user_id >= 10
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AND e.user_id <= 25
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AND e.event_type IN (106, 107, 108)
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) t2 ON (t1.user_id = t2.user_id)
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GROUP BY t1.user_id, hasdone_event
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) t GROUP BY user_id, hasdone_event
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ORDER BY user_id;
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-- same query but multiple joins are one level below, returns count of row instead of actual rows
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SELECT count(*)
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FROM (
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SELECT user_id, sum(array_length(events_table, 1)), length(hasdone_event), hasdone_event
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FROM (
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SELECT
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t1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(hasdone_event, 'Has not done event') AS hasdone_event
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FROM (
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SELECT
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u.user_id,
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CASE WHEN e.event_type in (100, 101, 102) then 'step=>1'::text else 'step==>2'::text END AS event,
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e.time
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FROM users_table AS u,
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events_table AS e
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WHERE u.user_id = e.user_id
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AND u.user_id >= 10
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AND u.user_id <= 25
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AND e.event_type IN (100, 101, 102, 103, 104, 105)
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GROUP BY 1,2,3
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) t1 LEFT JOIN (
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SELECT DISTINCT user_id,
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'Has done event'::TEXT AS hasdone_event
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FROM events_table AS e
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WHERE e.user_id >= 10
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AND e.user_id <= 25
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AND e.event_type IN (106, 107, 108)
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) t2 ON (t1.user_id = t2.user_id)
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GROUP BY t1.user_id, hasdone_event
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) t GROUP BY user_id, hasdone_event
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ORDER BY user_id) u;
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------------------------------------
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-- Funnel, grouped by the number of times a user has done an event
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------------------------------------
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SELECT
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user_id,
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avg(array_length(events_table, 1)) AS event_average,
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count_pay
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FROM (
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SELECT
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subquery_1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(count_pay, 0) AS count_pay
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FROM
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(
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(SELECT
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users_table.user_id,
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'action=>1'AS event,
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events_table.time
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FROM
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users_table,
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events_table
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WHERE
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users_table.user_id = events_table.user_id AND
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users_table.user_id >= 10 AND
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users_table.user_id <= 70 AND
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events_table.event_type > 10 AND events_table.event_type < 12
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)
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UNION
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(SELECT
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users_table.user_id,
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'action=>2'AS event,
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events_table.time
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FROM
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users_table,
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events_table
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WHERE
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users_table.user_id = events_table.user_id AND
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users_table.user_id >= 10 AND
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users_table.user_id <= 70 AND
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events_table.event_type > 12 AND events_table.event_type < 14
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)
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) AS subquery_1
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LEFT JOIN
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(SELECT
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user_id,
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COUNT(*) AS count_pay
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FROM
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users_table
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WHERE
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user_id >= 10 AND
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user_id <= 70 AND
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users_table.value_1 > 15 AND users_table.value_1 < 17
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GROUP BY
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user_id
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HAVING
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COUNT(*) > 1) AS subquery_2
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ON
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subquery_1.user_id = subquery_2.user_id
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GROUP BY
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subquery_1.user_id,
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count_pay) AS subquery_top
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WHERE
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array_ndims(events_table) > 0
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GROUP BY
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count_pay, user_id
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ORDER BY
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event_average DESC, count_pay DESC, user_id DESC;
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SELECT
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user_id,
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avg(array_length(events_table, 1)) AS event_average,
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count_pay
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FROM (
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SELECT
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subquery_1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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COALESCE(count_pay, 0) AS count_pay
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FROM
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(
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(SELECT
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users_table.user_id,
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'action=>1'AS event,
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events_table.time
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FROM
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users_table,
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events_table
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WHERE
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users_table.user_id = events_table.user_id AND
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users_table.user_id >= 10 AND
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users_table.user_id <= 70 AND
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events_table.event_type > 10 AND events_table.event_type < 12
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)
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UNION
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(SELECT
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users_table.user_id,
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'action=>2'AS event,
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events_table.time
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FROM
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users_table,
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events_table
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WHERE
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users_table.user_id = events_table.user_id AND
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users_table.user_id >= 10 AND
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users_table.user_id <= 70 AND
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events_table.event_type > 12 AND events_table.event_type < 14
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)
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) AS subquery_1
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LEFT JOIN
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(SELECT
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user_id,
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COUNT(*) AS count_pay
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FROM
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users_table
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WHERE
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user_id >= 10 AND
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user_id <= 70 AND
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users_table.value_1 > 15 AND users_table.value_1 < 17
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GROUP BY
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user_id
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HAVING
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COUNT(*) > 1) AS subquery_2
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ON
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subquery_1.user_id = subquery_2.user_id
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GROUP BY
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subquery_1.user_id,
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count_pay) AS subquery_top
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WHERE
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array_ndims(events_table) > 0
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GROUP BY
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count_pay, user_id
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HAVING
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avg(array_length(events_table, 1)) > 0
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ORDER BY
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event_average DESC, count_pay DESC, user_id DESC;
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-- Same queries rewritten without using unions
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SELECT
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user_id,
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avg(array_length(events_table, 1)) AS event_average,
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count_pay
|
||
FROM (
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||
SELECT
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||
subquery_1.user_id,
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array_agg(event ORDER BY time) AS events_table,
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||
COALESCE(count_pay, 0) AS count_pay
|
||
FROM
|
||
(
|
||
SELECT
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||
users_table.user_id,
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CASE WHEN events_table.event_type > 10 AND events_table.event_type < 12 THEN 'action=>1' ELSE 'action=>2' END AS event,
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||
events_table.time
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||
FROM
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||
users_table,
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events_table
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||
WHERE
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||
users_table.user_id = events_table.user_id AND
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users_table.user_id >= 10 AND
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users_table.user_id <= 70 AND
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(events_table.event_type > 10 AND events_table.event_type < 12
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||
OR
|
||
events_table.event_type > 12 AND events_table.event_type < 14)
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||
GROUP BY 1, 2, 3
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||
) AS subquery_1
|
||
LEFT JOIN
|
||
(SELECT
|
||
user_id,
|
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COUNT(*) AS count_pay
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
user_id >= 10 AND
|
||
user_id <= 70 AND
|
||
users_table.value_1 > 15 AND users_table.value_1 < 17
|
||
GROUP BY
|
||
user_id
|
||
HAVING
|
||
COUNT(*) > 1) AS subquery_2
|
||
ON
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||
subquery_1.user_id = subquery_2.user_id
|
||
GROUP BY
|
||
subquery_1.user_id,
|
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count_pay) AS subquery_top
|
||
WHERE
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||
array_ndims(events_table) > 0
|
||
GROUP BY
|
||
count_pay, user_id
|
||
ORDER BY
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event_average DESC, count_pay DESC, user_id DESC;
|
||
|
||
SELECT
|
||
user_id,
|
||
avg(array_length(events_table, 1)) AS event_average,
|
||
count_pay
|
||
FROM (
|
||
SELECT
|
||
subquery_1.user_id,
|
||
array_agg(event ORDER BY time) AS events_table,
|
||
COALESCE(count_pay, 0) AS count_pay
|
||
FROM
|
||
(
|
||
SELECT
|
||
users_table.user_id,
|
||
CASE WHEN events_table.event_type > 10 AND events_table.event_type < 12 THEN 'action=>1' ELSE 'action=>2' END AS event,
|
||
events_table.time
|
||
FROM
|
||
users_table,
|
||
events_table
|
||
WHERE
|
||
users_table.user_id = events_table.user_id AND
|
||
users_table.user_id >= 10 AND
|
||
users_table.user_id <= 70 AND
|
||
(events_table.event_type > 10 AND events_table.event_type < 12
|
||
OR
|
||
events_table.event_type > 12 AND events_table.event_type < 14)
|
||
GROUP BY 1, 2, 3
|
||
) AS subquery_1
|
||
LEFT JOIN
|
||
(SELECT
|
||
user_id,
|
||
COUNT(*) AS count_pay
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
user_id >= 10 AND
|
||
user_id <= 70 AND
|
||
users_table.value_1 > 15 AND users_table.value_1 < 17
|
||
GROUP BY
|
||
user_id
|
||
HAVING
|
||
COUNT(*) > 1) AS subquery_2
|
||
ON
|
||
subquery_1.user_id = subquery_2.user_id
|
||
GROUP BY
|
||
subquery_1.user_id,
|
||
count_pay) AS subquery_top
|
||
WHERE
|
||
array_ndims(events_table) > 0
|
||
GROUP BY
|
||
count_pay, user_id
|
||
HAVING
|
||
avg(array_length(events_table, 1)) > 0
|
||
ORDER BY
|
||
event_average DESC, count_pay DESC, user_id DESC;
|
||
|
||
------------------------------------
|
||
-- Most recently seen users_table events_table
|
||
------------------------------------
|
||
-- Note that we don't use ORDER BY/LIMIT yet
|
||
------------------------------------
|
||
SELECT
|
||
user_id,
|
||
user_lastseen,
|
||
array_length(event_array, 1)
|
||
FROM (
|
||
SELECT
|
||
user_id,
|
||
max(u.time) as user_lastseen,
|
||
array_agg(event_type ORDER BY u.time) AS event_array
|
||
FROM (
|
||
SELECT user_id, time
|
||
FROM users_table
|
||
WHERE
|
||
user_id >= 10 AND
|
||
user_id <= 70 AND
|
||
users_table.value_1 > 10 AND users_table.value_1 < 12
|
||
) u LEFT JOIN LATERAL (
|
||
SELECT event_type, time
|
||
FROM events_table
|
||
WHERE user_id = u.user_id AND
|
||
events_table.event_type > 10 AND events_table.event_type < 12
|
||
) t ON true
|
||
GROUP BY user_id
|
||
) AS shard_union
|
||
ORDER BY user_lastseen DESC, user_id;
|
||
|
||
------------------------------------
|
||
-- Count the number of distinct users_table who are in segment X and Y and Z
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT DISTINCT user_id
|
||
FROM users_table
|
||
WHERE user_id IN (SELECT user_id FROM users_table WHERE value_1 >= 10 AND value_1 <= 20)
|
||
AND user_id IN (SELECT user_id FROM users_table WHERE value_1 >= 30 AND value_1 <= 40)
|
||
AND user_id IN (SELECT user_id FROM users_table WHERE value_1 >= 50 AND value_1 <= 60);
|
||
|
||
------------------------------------
|
||
-- Find customers who have done X, and satisfy other customer specific criteria
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id, value_2 FROM users_table WHERE
|
||
value_1 > 101 AND value_1 < 110
|
||
AND value_2 >= 5
|
||
AND EXISTS (SELECT user_id FROM events_table WHERE event_type>101 AND event_type < 110 AND value_3 > 100 AND user_id=users_table.user_id);
|
||
|
||
------------------------------------
|
||
-- Customers who haven’t done X, and satisfy other customer specific criteria
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id, value_2 FROM users_table WHERE
|
||
value_1 = 101
|
||
AND value_2 >= 5
|
||
AND NOT EXISTS (SELECT user_id FROM events_table WHERE event_type=101 AND value_3 > 100 AND user_id=users_table.user_id);
|
||
|
||
------------------------------------
|
||
-- Customers who have done X and Y, and satisfy other customer specific criteria
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id, value_2 FROM users_table WHERE
|
||
value_1 > 100
|
||
AND value_2 >= 5
|
||
AND EXISTS (SELECT user_id FROM events_table WHERE event_type!=100 AND value_3 > 100 AND user_id=users_table.user_id)
|
||
AND EXISTS (SELECT user_id FROM events_table WHERE event_type=101 AND value_3 > 100 AND user_id=users_table.user_id);
|
||
|
||
------------------------------------
|
||
-- Customers who have done X and haven’t done Y, and satisfy other customer specific criteria
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id, value_2 FROM users_table WHERE
|
||
value_2 >= 5
|
||
AND EXISTS (SELECT user_id FROM events_table WHERE event_type > 100 AND event_type <= 300 AND value_3 > 100 AND user_id=users_table.user_id)
|
||
AND NOT EXISTS (SELECT user_id FROM events_table WHERE event_type > 300 AND event_type <= 350 AND value_3 > 100 AND user_id=users_table.user_id);
|
||
|
||
------------------------------------
|
||
-- Customers who have done X more than 2 times, and satisfy other customer specific criteria
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id,
|
||
value_2
|
||
FROM users_table
|
||
WHERE value_1 > 100
|
||
AND value_1 < 124
|
||
AND value_2 >= 5
|
||
AND EXISTS (SELECT user_id
|
||
FROM events_table
|
||
WHERE event_type > 100
|
||
AND event_type < 124
|
||
AND value_3 > 100
|
||
AND user_id = users_table.user_id
|
||
GROUP BY user_id
|
||
HAVING Count(*) > 2);
|
||
|
||
------------------------------------
|
||
-- Find me all users_table who logged in more than once
|
||
------------------------------------
|
||
SELECT user_id, value_1 from
|
||
(
|
||
SELECT user_id, value_1 From users_table
|
||
WHERE value_2 > 100 and user_id = 15 GROUP BY value_1, user_id HAVING count(*) > 1
|
||
) AS a
|
||
ORDER BY user_id ASC, value_1 ASC;
|
||
|
||
-- same query with additional filter to make it not router plannable
|
||
SELECT user_id, value_1 from
|
||
(
|
||
SELECT user_id, value_1 From users_table
|
||
WHERE value_2 > 100 and (user_id = 15 OR user_id = 16) GROUP BY value_1, user_id HAVING count(*) > 1
|
||
) AS a
|
||
ORDER BY user_id ASC, value_1 ASC;
|
||
|
||
------------------------------------
|
||
-- Find me all users_table who has done some event and has filters
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id
|
||
FROM events_table
|
||
WHERE
|
||
event_type = 16 AND value_2 > 50
|
||
AND user_id IN
|
||
(SELECT user_id
|
||
FROM users_table
|
||
WHERE
|
||
value_1 = 15 AND value_2 > 25);
|
||
|
||
------------------------------------
|
||
-- Which events_table did people who has done some specific events_table
|
||
-- This query will be supported when we have subqueries in where clauses.
|
||
------------------------------------
|
||
SELECT user_id, event_type FROM events_table
|
||
WHERE user_id in (SELECT user_id from events_table WHERE event_type > 500 and event_type < 505)
|
||
GROUP BY user_id, event_type;
|
||
|
||
------------------------------------
|
||
-- Find me all the users_table who has done some event more than three times
|
||
------------------------------------
|
||
SELECT user_id FROM
|
||
(
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
events_table
|
||
WHERE event_type = 901
|
||
GROUP BY user_id HAVING count(*) > 3
|
||
) AS a
|
||
ORDER BY user_id;
|
||
|
||
------------------------------------
|
||
-- Find my assets that have the highest probability and fetch their metadata
|
||
------------------------------------
|
||
CREATE TEMP TABLE assets AS
|
||
SELECT
|
||
users_table.user_id, users_table.value_1, prob
|
||
FROM
|
||
users_table
|
||
JOIN
|
||
(SELECT
|
||
ma.user_id, (GREATEST(coalesce(ma.value_4 / 250, 0.0) + GREATEST(1.0))) / 2 AS prob
|
||
FROM
|
||
users_table AS ma, events_table as short_list
|
||
WHERE
|
||
short_list.user_id = ma.user_id and ma.value_1 < 50 and short_list.event_type < 50
|
||
) temp
|
||
ON users_table.user_id = temp.user_id
|
||
WHERE users_table.value_1 < 50;
|
||
|
||
-- get some statistics from the aggregated results to ensure the results are correct
|
||
SELECT count(*), count(DISTINCT user_id), avg(user_id) FROM assets;
|
||
|
||
DROP TABLE assets;
|
||
|
||
-- count number of distinct users who have value_1 equal to 5 or 13 but not 3
|
||
-- original query that fails
|
||
SELECT count(*) FROM
|
||
(
|
||
SELECT user_id
|
||
FROM users_table
|
||
WHERE (value_1 = '5'
|
||
OR value_1 = '13')
|
||
AND user_id NOT IN (select user_id from users_table where value_1 = '3')
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) = 2
|
||
) as foo;
|
||
|
||
-- previous push down query
|
||
SELECT subquery_count FROM
|
||
(SELECT count(*) as subquery_count FROM
|
||
(SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '5' OR value_1 = '13')
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) = 2) as a
|
||
LEFT JOIN
|
||
(SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '3')
|
||
GROUP BY user_id) as b on a.user_id = b.user_id WHERE b.user_id IS NULL
|
||
GROUP BY a.user_id) AS inner_subquery;
|
||
|
||
-- new pushdown query without single range table entry at top requirement
|
||
SELECT count(*) as subquery_count
|
||
FROM (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '5' OR value_1 = '13')
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) = 2
|
||
) as a
|
||
LEFT JOIN (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '3')
|
||
GROUP BY user_id) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NULL
|
||
GROUP BY a.user_id;
|
||
|
||
-- multi-subquery-join
|
||
-- The first query has filters on partion column to make it router plannable
|
||
-- but it is processed by logical planner since we disabled router execution
|
||
SELECT
|
||
e1.user_id,
|
||
sum(view_homepage) AS viewed_homepage,
|
||
sum(use_demo) AS use_demo,
|
||
sum(enter_credit_card) AS entered_credit_card,
|
||
sum(submit_card_info) as submit_card_info,
|
||
sum(see_bought_screen) as see_bought_screen
|
||
FROM (
|
||
-- Get the first time each user viewed the homepage.
|
||
SELECT
|
||
user_id,
|
||
1 AS view_homepage,
|
||
min(time) AS view_homepage_time
|
||
FROM events_table
|
||
WHERE user_id = 1 and
|
||
event_type IN (10, 20, 30, 40, 50, 60, 70, 80, 90)
|
||
GROUP BY user_id
|
||
) e1 LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS use_demo,
|
||
time AS use_demo_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e1.user_id AND user_id = 1 and
|
||
event_type IN (11, 21, 31, 41, 51, 61, 71, 81, 91)
|
||
ORDER BY time
|
||
LIMIT 1
|
||
) e2 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS enter_credit_card,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e2.user_id AND user_id = 1 and
|
||
event_type IN (12, 22, 32, 42, 52, 62, 72, 82, 92)
|
||
ORDER BY time
|
||
LIMIT 1
|
||
) e3 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS submit_card_info,
|
||
user_id,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e3.user_id AND user_id = 1 and
|
||
event_type IN (13, 23, 33, 43, 53, 63, 73, 83, 93)
|
||
ORDER BY time
|
||
LIMIT 1
|
||
) e4 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS see_bought_screen
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e4.user_id AND user_id = 1 and
|
||
event_type IN (14, 24, 34, 44, 54, 64, 74, 84, 94)
|
||
ORDER BY time
|
||
LIMIT 1
|
||
) e5 ON true
|
||
where e1.user_id = 1
|
||
group by e1.user_id
|
||
limit 1;
|
||
|
||
-- Same query without all limitations
|
||
SELECT
|
||
e1.user_id,
|
||
sum(view_homepage) AS viewed_homepage,
|
||
sum(use_demo) AS use_demo,
|
||
sum(enter_credit_card) AS entered_credit_card,
|
||
sum(submit_card_info) as submit_card_info,
|
||
sum(see_bought_screen) as see_bought_screen
|
||
FROM (
|
||
-- Get the first time each user viewed the homepage.
|
||
SELECT
|
||
user_id,
|
||
1 AS view_homepage,
|
||
min(time) AS view_homepage_time
|
||
FROM events_table
|
||
WHERE
|
||
event_type IN (10, 20, 30, 40, 50, 60, 70, 80, 90)
|
||
GROUP BY user_id
|
||
) e1 LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS use_demo,
|
||
time AS use_demo_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e1.user_id AND
|
||
event_type IN (11, 21, 31, 41, 51, 61, 71, 81, 91)
|
||
ORDER BY time
|
||
) e2 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS enter_credit_card,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e2.user_id AND
|
||
event_type IN (12, 22, 32, 42, 52, 62, 72, 82, 92)
|
||
ORDER BY time
|
||
) e3 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS submit_card_info,
|
||
user_id,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e3.user_id AND
|
||
event_type IN (13, 23, 33, 43, 53, 63, 73, 83, 93)
|
||
ORDER BY time
|
||
) e4 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS see_bought_screen
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e4.user_id AND
|
||
event_type IN (14, 24, 34, 44, 54, 64, 74, 84, 94)
|
||
ORDER BY time
|
||
) e5 ON true
|
||
GROUP BY e1.user_id
|
||
ORDER BY 6 DESC NULLS LAST, 5 DESC NULLS LAST, 4 DESC NULLS LAST, 3 DESC NULLS LAST, 2 DESC NULLS LAST, 1
|
||
LIMIT 15;
|
||
|
||
-- Same query without all limitations but uses having() to show only those submitted their credit card info
|
||
SELECT
|
||
e1.user_id,
|
||
sum(view_homepage) AS viewed_homepage,
|
||
sum(use_demo) AS use_demo,
|
||
sum(enter_credit_card) AS entered_credit_card,
|
||
sum(submit_card_info) as submit_card_info,
|
||
sum(see_bought_screen) as see_bought_screen
|
||
FROM (
|
||
-- Get the first time each user viewed the homepage.
|
||
SELECT
|
||
user_id,
|
||
1 AS view_homepage,
|
||
min(time) AS view_homepage_time
|
||
FROM events_table
|
||
WHERE
|
||
event_type IN (10, 20, 30, 40, 50, 60, 70, 80, 90)
|
||
GROUP BY user_id
|
||
) e1 LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS use_demo,
|
||
time AS use_demo_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e1.user_id AND
|
||
event_type IN (11, 21, 31, 41, 51, 61, 71, 81, 91)
|
||
ORDER BY time
|
||
) e2 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
user_id,
|
||
1 AS enter_credit_card,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e2.user_id AND
|
||
event_type IN (12, 22, 32, 42, 52, 62, 72, 82, 92)
|
||
ORDER BY time
|
||
) e3 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS submit_card_info,
|
||
user_id,
|
||
time AS enter_credit_card_time
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e3.user_id AND
|
||
event_type IN (13, 23, 33, 43, 53, 63, 73, 83, 93)
|
||
ORDER BY time
|
||
) e4 ON true LEFT JOIN LATERAL (
|
||
SELECT
|
||
1 AS see_bought_screen
|
||
FROM events_table
|
||
WHERE
|
||
user_id = e4.user_id AND
|
||
event_type IN (14, 24, 34, 44, 54, 64, 74, 84, 94)
|
||
ORDER BY time
|
||
) e5 ON true
|
||
group by e1.user_id
|
||
HAVING sum(submit_card_info) > 0
|
||
ORDER BY 6 DESC NULLS LAST, 5 DESC NULLS LAST, 4 DESC NULLS LAST, 3 DESC NULLS LAST, 2 DESC NULLS LAST, 1
|
||
LIMIT 15;
|
||
|
||
-- Explain analyze on this query fails due to #756
|
||
-- avg expression used on order by
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg
|
||
FROM (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN (
|
||
SELECT
|
||
user_id, value_2, value_3
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 > 3)) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NOT NULL
|
||
GROUP BY a.user_id
|
||
ORDER BY avg(b.value_3), 2, 1
|
||
LIMIT 5;
|
||
|
||
-- add having
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg
|
||
FROM (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN (
|
||
SELECT
|
||
user_id, value_2, value_3
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 > 3)) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NOT NULL
|
||
GROUP BY a.user_id
|
||
HAVING sum(b.value_3) > 50000
|
||
ORDER BY avg(b.value_3), 2, 1
|
||
LIMIT 5;
|
||
|
||
-- avg on the value_3 is not a resjunk
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg, avg(b.value_3)
|
||
FROM
|
||
(SELECT user_id
|
||
FROM users_table
|
||
WHERE (value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN
|
||
(SELECT user_id, value_2, value_3
|
||
FROM users_table
|
||
WHERE (value_1 > 3)
|
||
) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NOT NULL
|
||
GROUP BY a.user_id
|
||
ORDER BY avg(b.value_3) DESC, 2, 1
|
||
LIMIT 5;
|
||
|
||
-- a powerful query structure that analyzes users/events
|
||
-- using (relation JOIN subquery JOIN relation)
|
||
SELECT u.user_id, sub.value_2, sub.value_3, COUNT(e2.user_id) counts
|
||
FROM
|
||
users_table u
|
||
LEFT OUTER JOIN LATERAL
|
||
(SELECT *
|
||
FROM events_table e1
|
||
WHERE e1.user_id = u.user_id
|
||
ORDER BY e1.value_3 DESC
|
||
LIMIT 1
|
||
) sub
|
||
ON true
|
||
LEFT OUTER JOIN events_table e2
|
||
ON e2.user_id = sub.user_id
|
||
WHERE e2.value_2 > 10 and e2.value_2 < 50 AND u.value_2 > 10 and u.value_2 < 50
|
||
GROUP BY u.user_id, sub.value_2, sub.value_3
|
||
ORDER BY 4 DESC, 1 DESC, 2 ASC, 3 ASC
|
||
LIMIT 10;
|
||
|
||
-- distinct users joined with events
|
||
SELECT
|
||
avg(events_table.event_type) as avg_type,
|
||
count(*) as users_count
|
||
FROM events_table
|
||
JOIN
|
||
(SELECT DISTINCT user_id
|
||
FROM users_table
|
||
) as distinct_users
|
||
ON distinct_users.user_id = events_table.user_id
|
||
GROUP BY distinct_users.user_id
|
||
ORDER BY users_count desc, avg_type DESC
|
||
LIMIT 5;
|
||
|
||
-- reduce the data set, aggregate and join
|
||
SELECT
|
||
events_table.event_type,
|
||
users_count.ct
|
||
FROM events_table
|
||
JOIN
|
||
(SELECT distinct_users.user_id, count(1) as ct
|
||
FROM
|
||
(SELECT user_id
|
||
FROM users_table
|
||
) as distinct_users
|
||
GROUP BY distinct_users.user_id
|
||
) as users_count
|
||
ON users_count.user_id = events_table.user_id
|
||
ORDER BY users_count.ct desc, event_type DESC
|
||
LIMIT 5;
|
||
|
||
--- now, test (subquery JOIN subquery)
|
||
SELECT n1.user_id, count_1, total_count
|
||
FROM
|
||
(SELECT user_id, count(1) as count_1
|
||
FROM users_table
|
||
GROUP BY user_id
|
||
) n1
|
||
INNER JOIN
|
||
(SELECT user_id, count(1) as total_count
|
||
FROM events_table
|
||
GROUP BY user_id, event_type
|
||
) n2
|
||
ON (n2.user_id = n1.user_id)
|
||
ORDER BY total_count DESC, count_1 DESC, 1 DESC
|
||
LIMIT 10;
|
||
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg
|
||
FROM
|
||
(SELECT user_id
|
||
FROM users_table
|
||
WHERE (value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN
|
||
(SELECT DISTINCT ON (user_id) user_id, value_2, value_3
|
||
FROM users_table
|
||
WHERE (value_1 > 3)
|
||
ORDER BY 1,2,3
|
||
) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NOT NULL
|
||
GROUP BY a.user_id
|
||
ORDER BY avg(b.value_3), 2, 1
|
||
LIMIT 5;
|
||
|
||
-- distinct clause must include partition column
|
||
-- when used in target list
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg
|
||
FROM
|
||
(SELECT user_id
|
||
FROM users_table
|
||
WHERE (value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN
|
||
(SELECT DISTINCT ON (value_2) value_2 , user_id, value_3
|
||
FROM users_table
|
||
WHERE (value_1 > 3)
|
||
ORDER BY 1,2,3
|
||
) AS b
|
||
USING (user_id)
|
||
GROUP BY user_id;
|
||
|
||
SELECT a.user_id, avg(b.value_2) as subquery_avg
|
||
FROM
|
||
(SELECT user_id
|
||
FROM users_table
|
||
WHERE (value_1 > 5)
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) > 88
|
||
) as a
|
||
LEFT JOIN
|
||
(SELECT DISTINCT ON (value_2, user_id) value_2 , user_id, value_3
|
||
FROM users_table
|
||
WHERE (value_1 > 3)
|
||
ORDER BY 1,2,3
|
||
) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NOT NULL
|
||
GROUP BY a.user_id
|
||
ORDER BY avg(b.value_3), 2, 1
|
||
LIMIT 5;
|
||
|
||
SELECT user_id, event_type
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT event_type, user_id as a_user_id FROM events_table) AS a
|
||
JOIN
|
||
(SELECT
|
||
ma.user_id AS user_id, ma.value_2 AS value_2,
|
||
(GREATEST(coalesce((ma.value_3 * ma.value_2 ) / 20, 0.0) + GREATEST(1.0))) / 2 AS prob
|
||
FROM users_table AS ma
|
||
WHERE (ma.value_2 > 100)
|
||
ORDER BY prob DESC, user_id DESC
|
||
LIMIT 10
|
||
) AS ma
|
||
ON (a.a_user_id = ma.user_id)
|
||
) AS inner_sub
|
||
ORDER BY prob DESC, user_id DESC
|
||
LIMIT 10
|
||
) AS outer_sub
|
||
ORDER BY prob DESC, event_type DESC, user_id DESC
|
||
LIMIT 10;
|
||
|
||
-- very similar query but produces different result due to
|
||
-- ordering difference in the previous one's inner query
|
||
SELECT user_id, event_type
|
||
FROM
|
||
(SELECT event_type, user_id as a_user_id FROM events_table) AS a
|
||
JOIN
|
||
(SELECT
|
||
ma.user_id AS user_id, ma.value_2 AS value_2,
|
||
(GREATEST(coalesce((ma.value_3 * ma.value_2 ) / 20, 0.0) + GREATEST(1.0))) / 2 AS prob
|
||
FROM users_table AS ma
|
||
WHERE (ma.value_2 > 100)
|
||
ORDER BY prob DESC, user_id DESC
|
||
LIMIT 10
|
||
) AS ma
|
||
ON (a.a_user_id = ma.user_id)
|
||
ORDER BY prob DESC, event_type DESC, user_id DESC
|
||
LIMIT 10;
|
||
|
||
-- now they produce the same result when ordering fixed in 'outer_sub'
|
||
SELECT user_id, event_type
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT event_type, user_id as a_user_id FROM events_table) AS a
|
||
JOIN
|
||
(SELECT
|
||
ma.user_id AS user_id, ma.value_2 AS value_2,
|
||
(GREATEST(coalesce((ma.value_3 * ma.value_2 ) / 20, 0.0) + GREATEST(1.0))) / 2 AS prob
|
||
FROM users_table AS ma
|
||
WHERE (ma.value_2 > 100)
|
||
ORDER BY prob DESC, user_id DESC
|
||
LIMIT 10
|
||
) AS ma
|
||
ON (a.a_user_id = ma.user_id)
|
||
) AS inner_sub
|
||
ORDER BY prob DESC, event_type DESC, user_id DESC
|
||
LIMIT 10
|
||
) AS outer_sub
|
||
ORDER BY prob DESC, event_type DESC, user_id DESC
|
||
LIMIT 10;
|
||
|
||
-- this is one complex join query derived from a user's production query
|
||
-- first declare the function on workers on master
|
||
-- With array_index:
|
||
SELECT * FROM run_command_on_workers('CREATE OR REPLACE FUNCTION array_index(ANYARRAY, ANYELEMENT)
|
||
RETURNS INT AS $$
|
||
SELECT i
|
||
FROM (SELECT generate_series(array_lower($1, 1), array_upper($1, 1))) g(i)
|
||
WHERE $1 [i] = $2
|
||
LIMIT 1;
|
||
$$ LANGUAGE sql')
|
||
ORDER BY 1,2;
|
||
|
||
CREATE OR REPLACE FUNCTION array_index(ANYARRAY, ANYELEMENT)
|
||
RETURNS INT AS $$
|
||
SELECT i
|
||
FROM (SELECT generate_series(array_lower($1, 1), array_upper($1, 1))) g(i)
|
||
WHERE $1 [i] = $2
|
||
LIMIT 1;
|
||
$$ LANGUAGE sql;
|
||
|
||
SELECT *
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT
|
||
user_id AS user_id_e,
|
||
event_type as event_type_e
|
||
FROM
|
||
events_table
|
||
) AS ma_e
|
||
JOIN
|
||
(SELECT
|
||
value_2,
|
||
value_3,
|
||
user_id
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT user_id_p AS user_id
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT user_id AS user_id_p
|
||
FROM events_table
|
||
WHERE (event_type IN (1, 2, 3, 4, 5))
|
||
) AS ma_p
|
||
JOIN
|
||
(SELECT user_id AS user_id_a
|
||
FROM users_table
|
||
WHERE (value_2 % 5 = 1)
|
||
) AS a
|
||
ON (a.user_id_a = ma_p.user_id_p)
|
||
)
|
||
) AS a_ma_p
|
||
) AS inner_filter_q
|
||
JOIN
|
||
(SELECT
|
||
value_2,
|
||
value_3,
|
||
user_id AS user_id_ck
|
||
FROM events_table
|
||
WHERE event_type = ANY(ARRAY [10, 11, 12])
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id_ck DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10
|
||
) AS ma_ck
|
||
ON (ma_ck.user_id_ck = inner_filter_q.user_id)
|
||
) AS inner_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id_ck DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10
|
||
) AS outer_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10) AS inner_search_q
|
||
ON (ma_e.user_id_e = inner_search_q.user_id)
|
||
) AS outer_inner_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC,
|
||
event_type_e DESC
|
||
LIMIT 10) AS outer_outer_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC,
|
||
event_type_e DESC
|
||
LIMIT 10;
|
||
|
||
-- top level select * is removed now there is
|
||
-- a join at top level.
|
||
SELECT *
|
||
FROM
|
||
(
|
||
(SELECT
|
||
user_id AS user_id_e,
|
||
event_type as event_type_e
|
||
FROM
|
||
events_table
|
||
) AS ma_e
|
||
JOIN
|
||
(SELECT
|
||
value_2,
|
||
value_3,
|
||
user_id
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT user_id_p AS user_id
|
||
FROM
|
||
(SELECT *
|
||
FROM
|
||
(
|
||
(SELECT user_id AS user_id_p
|
||
FROM events_table
|
||
WHERE (event_type IN (1, 2, 3, 4, 5))
|
||
) AS ma_p
|
||
JOIN
|
||
(SELECT user_id AS user_id_a
|
||
FROM users_table
|
||
WHERE (value_2 % 5 = 1)
|
||
) AS a
|
||
ON (a.user_id_a = ma_p.user_id_p)
|
||
)
|
||
) AS a_ma_p
|
||
) AS inner_filter_q
|
||
JOIN
|
||
(SELECT
|
||
value_2,
|
||
value_3,
|
||
user_id AS user_id_ck
|
||
FROM events_table
|
||
WHERE event_type = ANY(ARRAY [10, 11, 12])
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id_ck DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10
|
||
) AS ma_ck
|
||
ON (ma_ck.user_id_ck = inner_filter_q.user_id)
|
||
) AS inner_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id_ck DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10
|
||
) AS outer_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC
|
||
LIMIT 10) AS inner_search_q
|
||
ON (ma_e.user_id_e = inner_search_q.user_id)
|
||
) AS outer_inner_sub_q
|
||
ORDER BY
|
||
value_3 ASC,
|
||
user_id DESC,
|
||
array_index(ARRAY [1, 2, 3], (value_2 % 3)) ASC,
|
||
event_type_e DESC
|
||
LIMIT 10;
|
||
|
||
|
||
-- drop created functions
|
||
SELECT * FROM run_command_on_workers('DROP FUNCTION array_index(ANYARRAY, ANYELEMENT)')
|
||
ORDER BY 1,2;
|
||
DROP FUNCTION array_index(ANYARRAY, ANYELEMENT);
|
||
|
||
-- a not supported query due to constant range table entry
|
||
SELECT count(*) as subquery_count
|
||
FROM (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '5' OR value_1 = '13')
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) = 2
|
||
) as a
|
||
LEFT JOIN (
|
||
SELECT
|
||
1 as user_id
|
||
) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NULL
|
||
GROUP BY a.user_id;
|
||
|
||
-- same with INNER JOIN
|
||
SELECT count(*) as subquery_count
|
||
FROM (
|
||
SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '5' OR value_1 = '13')
|
||
GROUP BY user_id
|
||
HAVING count(distinct value_1) = 2
|
||
) as a
|
||
INNER JOIN (
|
||
SELECT
|
||
1 as user_id
|
||
) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NULL
|
||
GROUP BY a.user_id;
|
||
|
||
-- this is slightly different, we use RTE_VALUEs here
|
||
SELECT Count(*) AS subquery_count
|
||
FROM (SELECT
|
||
user_id
|
||
FROM
|
||
users_table
|
||
WHERE
|
||
(value_1 = '5' OR value_1 = '13' )
|
||
GROUP BY
|
||
user_id
|
||
HAVING
|
||
Count(DISTINCT value_1) = 2) AS a
|
||
INNER JOIN
|
||
(SELECT
|
||
*
|
||
FROM
|
||
(VALUES (1, 'one'), (2, 'two'), (3, 'three')) AS t (user_id, letter)) AS b
|
||
ON a.user_id = b.user_id
|
||
WHERE b.user_id IS NULL
|
||
GROUP BY a.user_id;
|
||
|
||
SET citus.enable_router_execution TO TRUE;
|