citus/src/test/regress/expected/multi_having_pushdown.out

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