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Posted to commits@cloudberry.apache.org by ch...@apache.org on 2025/12/20 15:24:55 UTC
(cloudberry) branch cbdb-postgres-merge updated: Fix error in create_partial_grouping_paths
This is an automated email from the ASF dual-hosted git repository.
chenjinbao1989 pushed a commit to branch cbdb-postgres-merge
in repository https://gitbox.apache.org/repos/asf/cloudberry.git
The following commit(s) were added to refs/heads/cbdb-postgres-merge by this push:
new 330736e0fae Fix error in create_partial_grouping_paths
330736e0fae is described below
commit 330736e0fae687e703f76c6506f1b2ac60c861c4
Author: Jinbao Chen <ch...@gmail.com>
AuthorDate: Sat Dec 20 23:24:43 2025 +0800
Fix error in create_partial_grouping_paths
---
src/backend/optimizer/plan/planner.c | 31 +++---
src/test/regress/expected/select_parallel.out | 132 ++++++++++++++------------
2 files changed, 86 insertions(+), 77 deletions(-)
diff --git a/src/backend/optimizer/plan/planner.c b/src/backend/optimizer/plan/planner.c
index d9184c897f0..527a4136e69 100644
--- a/src/backend/optimizer/plan/planner.c
+++ b/src/backend/optimizer/plan/planner.c
@@ -8883,21 +8883,6 @@ create_partial_grouping_paths(PlannerInfo *root,
root->group_pathkeys,
-1.0);
- //if (parse->hasAggs)
- {
- add_partial_path(partially_grouped_rel, (Path *)
- create_agg_path(root,
- partially_grouped_rel,
- path,
- partially_grouped_rel->reltarget,
- parse->groupClause ? AGG_SORTED : AGG_PLAIN,
- AGGSPLIT_INITIAL_SERIAL,
- false,
- root->processed_groupClause,
- NIL,
- agg_partial_costs,
- dNumPartialPartialGroups));
- }
/* Group nodes are not used in GPDB */
#if 0
else
@@ -8911,6 +8896,22 @@ create_partial_grouping_paths(PlannerInfo *root,
#endif
}
+ //if (parse->hasAggs)
+ {
+ add_partial_path(partially_grouped_rel, (Path *)
+ create_agg_path(root,
+ partially_grouped_rel,
+ path,
+ partially_grouped_rel->reltarget,
+ parse->groupClause ? AGG_SORTED : AGG_PLAIN,
+ AGGSPLIT_INITIAL_SERIAL,
+ false,
+ root->processed_groupClause,
+ NIL,
+ agg_partial_costs,
+ dNumPartialPartialGroups));
+ }
+
/*
* Now we may consider incremental sort on this path, but only
* when the path is not already sorted and when incremental sort
diff --git a/src/test/regress/expected/select_parallel.out b/src/test/regress/expected/select_parallel.out
index e2117df4bd3..697ed067121 100644
--- a/src/test/regress/expected/select_parallel.out
+++ b/src/test/regress/expected/select_parallel.out
@@ -15,19 +15,20 @@ set max_parallel_workers_per_gather=4;
-- Parallel Append with partial-subplans
explain (costs off)
select round(avg(aa)), sum(aa) from a_star;
- QUERY PLAN
-------------------------------------------------
- Aggregate
+ QUERY PLAN
+-----------------------------------------------------
+ Finalize Aggregate
-> Gather Motion 9:1 (slice1; segments: 9)
- -> Parallel Append
- -> Seq Scan on d_star a_star_4
- -> Seq Scan on f_star a_star_6
- -> Seq Scan on e_star a_star_5
- -> Seq Scan on b_star a_star_2
- -> Seq Scan on c_star a_star_3
- -> Seq Scan on a_star a_star_1
+ -> Partial Aggregate
+ -> Parallel Append
+ -> Seq Scan on d_star a_star_4
+ -> Seq Scan on f_star a_star_6
+ -> Seq Scan on e_star a_star_5
+ -> Seq Scan on b_star a_star_2
+ -> Seq Scan on c_star a_star_3
+ -> Seq Scan on a_star a_star_1
Optimizer: Postgres query optimizer
-(10 rows)
+(11 rows)
select round(avg(aa)), sum(aa) from a_star a1;
round | sum
@@ -40,19 +41,20 @@ alter table c_star set (parallel_workers = 0);
alter table d_star set (parallel_workers = 0);
explain (costs off)
select round(avg(aa)), sum(aa) from a_star;
- QUERY PLAN
-------------------------------------------------
- Aggregate
+ QUERY PLAN
+-----------------------------------------------------
+ Finalize Aggregate
-> Gather Motion 9:1 (slice1; segments: 9)
- -> Parallel Append
- -> Seq Scan on d_star a_star_4
- -> Seq Scan on f_star a_star_6
- -> Seq Scan on e_star a_star_5
- -> Seq Scan on b_star a_star_2
- -> Seq Scan on c_star a_star_3
- -> Seq Scan on a_star a_star_1
+ -> Partial Aggregate
+ -> Parallel Append
+ -> Seq Scan on d_star a_star_4
+ -> Seq Scan on f_star a_star_6
+ -> Seq Scan on e_star a_star_5
+ -> Seq Scan on b_star a_star_2
+ -> Seq Scan on c_star a_star_3
+ -> Seq Scan on a_star a_star_1
Optimizer: Postgres query optimizer
-(10 rows)
+(11 rows)
select round(avg(aa)), sum(aa) from a_star a2;
round | sum
@@ -67,19 +69,20 @@ alter table e_star set (parallel_workers = 0);
alter table f_star set (parallel_workers = 0);
explain (costs off)
select round(avg(aa)), sum(aa) from a_star;
- QUERY PLAN
-------------------------------------------------
- Aggregate
+ QUERY PLAN
+-----------------------------------------------------
+ Finalize Aggregate
-> Gather Motion 9:1 (slice1; segments: 9)
- -> Parallel Append
- -> Seq Scan on d_star a_star_4
- -> Seq Scan on f_star a_star_6
- -> Seq Scan on e_star a_star_5
- -> Seq Scan on b_star a_star_2
- -> Seq Scan on c_star a_star_3
- -> Seq Scan on a_star a_star_1
+ -> Partial Aggregate
+ -> Parallel Append
+ -> Seq Scan on d_star a_star_4
+ -> Seq Scan on f_star a_star_6
+ -> Seq Scan on e_star a_star_5
+ -> Seq Scan on b_star a_star_2
+ -> Seq Scan on c_star a_star_3
+ -> Seq Scan on a_star a_star_1
Optimizer: Postgres query optimizer
-(10 rows)
+(11 rows)
select round(avg(aa)), sum(aa) from a_star a3;
round | sum
@@ -167,14 +170,15 @@ drop table part_pa_test;
set parallel_leader_participation = off;
explain (costs off)
select count(*) from tenk1 where stringu1 = 'GRAAAA';
- QUERY PLAN
----------------------------------------------------
- Aggregate
+ QUERY PLAN
+---------------------------------------------------------
+ Finalize Aggregate
-> Gather Motion 12:1 (slice1; segments: 12)
- -> Parallel Seq Scan on tenk1
- Filter: (stringu1 = 'GRAAAA'::name)
+ -> Partial Aggregate
+ -> Parallel Seq Scan on tenk1
+ Filter: (stringu1 = 'GRAAAA'::name)
Optimizer: Postgres query optimizer
-(5 rows)
+(6 rows)
select count(*) from tenk1 where stringu1 = 'GRAAAA';
count
@@ -187,14 +191,15 @@ select count(*) from tenk1 where stringu1 = 'GRAAAA';
set max_parallel_workers = 0;
explain (costs off)
select count(*) from tenk1 where stringu1 = 'GRAAAA';
- QUERY PLAN
----------------------------------------------------
- Aggregate
+ QUERY PLAN
+---------------------------------------------------------
+ Finalize Aggregate
-> Gather Motion 12:1 (slice1; segments: 12)
- -> Parallel Seq Scan on tenk1
- Filter: (stringu1 = 'GRAAAA'::name)
+ -> Partial Aggregate
+ -> Parallel Seq Scan on tenk1
+ Filter: (stringu1 = 'GRAAAA'::name)
Optimizer: Postgres query optimizer
-(5 rows)
+(6 rows)
select count(*) from tenk1 where stringu1 = 'GRAAAA';
count
@@ -1212,24 +1217,27 @@ EXPLAIN (VERBOSE, COSTS OFF)
SELECT unnest(ARRAY[]::integer[]) + 1 AS pathkey
FROM tenk1 t1 JOIN tenk1 t2 ON TRUE
ORDER BY pathkey;
- QUERY PLAN
------------------------------------------------------------------------------------------------------
- Sort
+ QUERY PLAN
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+ Gather Motion 6:1 (slice1; segments: 6)
Output: (((unnest('{}'::integer[])) + 1))
- Sort Key: (((unnest('{}'::integer[])) + 1))
- -> Result
- Output: ((unnest('{}'::integer[])) + 1)
- -> ProjectSet
- Output: unnest('{}'::integer[])
- -> Nested Loop
- -> Gather
- Workers Planned: 4
- -> Parallel Index Only Scan using tenk1_hundred on public.tenk1 t1
- -> Materialize
- -> Gather
- Workers Planned: 4
- -> Parallel Index Only Scan using tenk1_hundred on public.tenk1 t2
-(15 rows)
+ Merge Key: (((unnest('{}'::integer[])) + 1))
+ -> Sort
+ Output: (((unnest('{}'::integer[])) + 1))
+ Sort Key: (((unnest('{}'::integer[])) + 1))
+ -> Result
+ Output: ((unnest('{}'::integer[])) + 1)
+ -> ProjectSet
+ Output: unnest('{}'::integer[])
+ -> Nested Loop
+ -> Parallel Seq Scan on public.tenk1 t1
+ Output: t1.unique1, t1.unique2, t1.two, t1.four, t1.ten, t1.twenty, t1.hundred, t1.thousand, t1.twothousand, t1.fivethous, t1.tenthous, t1.odd, t1.even, t1.stringu1, t1.stringu2, t1.string4
+ -> Materialize
+ -> Broadcast Motion 3:6 (slice2; segments: 3)
+ -> Seq Scan on public.tenk1 t2
+ Settings: enable_parallel = 'on', optimizer = 'off', parallel_setup_cost = '0', parallel_tuple_cost = '0', min_parallel_table_scan_size = '0'
+ Optimizer: Postgres query optimizer
+(18 rows)
-- test passing expanded-value representations to workers
CREATE FUNCTION make_some_array(int,int) returns int[] as
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