mirror of https://github.com/citusdata/citus.git
222 lines
8.7 KiB
Plaintext
222 lines
8.7 KiB
Plaintext
--
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-- MULTI_HAVING_PUSHDOWN
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--
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SET citus.next_shard_id TO 590000;
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CREATE TABLE lineitem_hash (LIKE lineitem);
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SELECT create_distributed_table('lineitem_hash', 'l_orderkey', 'hash');
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create_distributed_table
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---------------------------------------------------------------------
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(1 row)
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CREATE TABLE orders_hash (LIKE orders);
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SELECT create_distributed_table('orders_hash', 'o_orderkey', 'hash');
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create_distributed_table
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---------------------------------------------------------------------
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(1 row)
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-- push down when table is distributed by hash and grouped by partition column
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EXPLAIN (COSTS FALSE)
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SELECT l_orderkey, sum(l_extendedprice * l_discount) as revenue
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FROM lineitem_hash
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GROUP BY l_orderkey HAVING sum(l_quantity) > 24
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ORDER BY 2 DESC, 1 ASC LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: remote_scan.revenue DESC, remote_scan.l_orderkey
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-> Custom Scan (Citus Adaptive)
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Task Count: 4
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Tasks Shown: One of 4
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> Limit
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-> Sort
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Sort Key: (sum((l_extendedprice * l_discount))) DESC, l_orderkey
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-> HashAggregate
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Group Key: l_orderkey
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Filter: (sum(l_quantity) > '24'::numeric)
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-> Seq Scan on lineitem_hash_590000 lineitem_hash
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(15 rows)
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-- but don't push down when table is distributed by append
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EXPLAIN (COSTS FALSE)
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SELECT l_orderkey, sum(l_extendedprice * l_discount) as revenue
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FROM lineitem
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GROUP BY l_orderkey HAVING sum(l_quantity) > 24
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ORDER BY 2 DESC, 1 ASC LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: (sum(remote_scan.revenue)) DESC, remote_scan.l_orderkey
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-> HashAggregate
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Group Key: remote_scan.l_orderkey
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Filter: (sum(remote_scan.worker_column_3) > '24'::numeric)
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-> Custom Scan (Citus Adaptive)
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Task Count: 2
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Tasks Shown: One of 2
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> HashAggregate
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Group Key: l_orderkey
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-> Seq Scan on lineitem_290000 lineitem
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(14 rows)
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-- and don't push down when not grouped by partition column
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EXPLAIN (COSTS FALSE)
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SELECT l_shipmode, sum(l_extendedprice * l_discount) as revenue
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FROM lineitem_hash
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GROUP BY l_shipmode HAVING sum(l_quantity) > 24
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ORDER BY 2 DESC, 1 ASC LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: (sum(remote_scan.revenue)) DESC, remote_scan.l_shipmode
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-> HashAggregate
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Group Key: remote_scan.l_shipmode
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Filter: (sum(remote_scan.worker_column_3) > '24'::numeric)
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-> Custom Scan (Citus Adaptive)
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Task Count: 4
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Tasks Shown: One of 4
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> HashAggregate
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Group Key: l_shipmode
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-> Seq Scan on lineitem_hash_590000 lineitem_hash
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(14 rows)
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-- push down if grouped by multiple rows one of which is partition column
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EXPLAIN (COSTS FALSE)
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SELECT l_shipmode, l_orderkey, sum(l_extendedprice * l_discount) as revenue
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FROM lineitem_hash
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GROUP BY l_shipmode, l_orderkey HAVING sum(l_quantity) > 24
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ORDER BY 3 DESC, 1, 2 LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: remote_scan.revenue DESC, remote_scan.l_shipmode, remote_scan.l_orderkey
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-> Custom Scan (Citus Adaptive)
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Task Count: 4
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Tasks Shown: One of 4
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> Limit
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-> Sort
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Sort Key: (sum((l_extendedprice * l_discount))) DESC, l_shipmode, l_orderkey
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-> HashAggregate
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Group Key: l_shipmode, l_orderkey
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Filter: (sum(l_quantity) > '24'::numeric)
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-> Seq Scan on lineitem_hash_590000 lineitem_hash
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(15 rows)
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-- couple more checks with joins
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EXPLAIN (COSTS FALSE)
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SELECT sum(l_extendedprice * l_discount) as revenue
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FROM lineitem_hash, orders_hash
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WHERE o_orderkey = l_orderkey
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GROUP BY l_orderkey, o_orderkey, l_shipmode HAVING sum(l_quantity) > 24
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ORDER BY 1 DESC LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: remote_scan.revenue DESC
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-> Custom Scan (Citus Adaptive)
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Task Count: 4
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Tasks Shown: One of 4
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> Limit
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-> Sort
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Sort Key: (sum((lineitem_hash.l_extendedprice * lineitem_hash.l_discount))) DESC
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-> HashAggregate
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Group Key: lineitem_hash.l_orderkey, orders_hash.o_orderkey, lineitem_hash.l_shipmode
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Filter: (sum(lineitem_hash.l_quantity) > '24'::numeric)
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-> Hash Join
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Hash Cond: (orders_hash.o_orderkey = lineitem_hash.l_orderkey)
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-> Seq Scan on orders_hash_590004 orders_hash
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-> Hash
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-> Seq Scan on lineitem_hash_590000 lineitem_hash
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(19 rows)
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EXPLAIN (COSTS FALSE)
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SELECT sum(l_extendedprice * l_discount) as revenue
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FROM lineitem_hash, orders_hash
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WHERE o_orderkey = l_orderkey
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GROUP BY l_shipmode, o_clerk HAVING sum(l_quantity) > 24
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ORDER BY 1 DESC LIMIT 3;
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QUERY PLAN
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---------------------------------------------------------------------
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Limit
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-> Sort
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Sort Key: (sum(remote_scan.revenue)) DESC
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-> HashAggregate
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Group Key: remote_scan.worker_column_2, remote_scan.worker_column_3
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Filter: (sum(remote_scan.worker_column_4) > '24'::numeric)
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-> Custom Scan (Citus Adaptive)
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Task Count: 4
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Tasks Shown: One of 4
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-> Task
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Node: host=localhost port=xxxxx dbname=regression
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-> HashAggregate
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Group Key: lineitem_hash.l_shipmode, orders_hash.o_clerk
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-> Hash Join
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Hash Cond: (orders_hash.o_orderkey = lineitem_hash.l_orderkey)
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-> Seq Scan on orders_hash_590004 orders_hash
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-> Hash
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-> Seq Scan on lineitem_hash_590000 lineitem_hash
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(18 rows)
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DROP TABLE lineitem_hash;
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DROP TABLE orders_hash;
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SELECT max(value_1)
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FROM users_table
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GROUP BY user_id
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HAVING max(value_2) > 4 AND min(value_2) < 1
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ORDER BY 1;
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max
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---------------------------------------------------------------------
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4
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5
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5
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(3 rows)
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SELECT max(value_1)
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FROM users_table
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GROUP BY user_id
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HAVING max(value_2) > 4 AND min(value_2) < 1 OR count(*) > 10
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ORDER BY 1;
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max
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---------------------------------------------------------------------
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4
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5
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5
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5
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(4 rows)
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SELECT max(value_1)
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FROM users_table
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GROUP BY user_id
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HAVING max(value_2) > 4 AND min(value_2) < 1 AND count(*) > 20
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ORDER BY 1;
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max
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---------------------------------------------------------------------
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5
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5
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(2 rows)
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SELECT max(value_1)
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FROM users_table
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GROUP BY user_id
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HAVING max(value_2) > 0 AND count(*) FILTER (WHERE value_3=2) > 3 AND min(value_2) IN (0,1,2,3);
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max
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---------------------------------------------------------------------
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5
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(1 row)
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