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Mostly-cosmetic adjustments to estimate_multivariate_bucketsize().
- aadf7db66ef5 19 (unreleased) cited
Consider fractional paths in generate_orderedappend_paths
- 6b94e7a6da2f 15.0 cited

MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2024-06-18T16:45:09Z

Hi.

Now when planner finds suitable pathkeys in 
generate_orderedappend_paths(), it uses them, even if explicit sort of 
the cheapest child path could be more efficient.

We encountered this issue on partitioned table with two indexes, where 
one is suitable for sorting, and another is good for selecting data. 
MergeAppend was generated
with subpaths doing index scan on suitably ordered index and filtering a 
lot of data.
The suggested fix allows MergeAppend to consider sorting on cheapest 
childrel total path as an alternative.

-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Bruce Momjian <bruce@momjian.us> — 2024-10-17T00:03:09Z

Is this still being considered?

---------------------------------------------------------------------------

On Tue, Jun 18, 2024 at 07:45:09PM +0300, Alexander Pyhalov wrote:
> Hi.
> 
> Now when planner finds suitable pathkeys in generate_orderedappend_paths(),
> it uses them, even if explicit sort of the cheapest child path could be more
> efficient.
> 
> We encountered this issue on partitioned table with two indexes, where one
> is suitable for sorting, and another is good for selecting data. MergeAppend
> was generated
> with subpaths doing index scan on suitably ordered index and filtering a lot
> of data.
> The suggested fix allows MergeAppend to consider sorting on cheapest
> childrel total path as an alternative.
> 
> -- 
> Best regards,
> Alexander Pyhalov,
> Postgres Professional

> From d5eb3d326d83e2ca47c17552fcc6fd27b6b98d4e Mon Sep 17 00:00:00 2001
> From: Alexander Pyhalov <a.pyhalov@postgrespro.ru>
> Date: Tue, 18 Jun 2024 15:56:18 +0300
> Subject: [PATCH] MergeAppend could consider using sorted best path.
> 
> This helps when index with suitable pathkeys is not
> good for filtering data.
> ---
>  .../postgres_fdw/expected/postgres_fdw.out    |  6 +-
>  src/backend/optimizer/path/allpaths.c         | 21 +++++
>  src/test/regress/expected/inherit.out         | 45 +++++++++-
>  src/test/regress/expected/partition_join.out  | 87 +++++++++++--------
>  src/test/regress/expected/union.out           |  6 +-
>  src/test/regress/sql/inherit.sql              | 17 ++++
>  6 files changed, 141 insertions(+), 41 deletions(-)
> 
> diff --git a/contrib/postgres_fdw/expected/postgres_fdw.out b/contrib/postgres_fdw/expected/postgres_fdw.out
> index ea566d50341..687591e4a97 100644
> --- a/contrib/postgres_fdw/expected/postgres_fdw.out
> +++ b/contrib/postgres_fdw/expected/postgres_fdw.out
> @@ -10074,13 +10074,15 @@ SELECT t1.a, t2.b FROM fprt1 t1 INNER JOIN fprt2 t2 ON (t1.a = t2.b) WHERE t1.a
>     ->  Nested Loop
>           Join Filter: (t1.a = t2.b)
>           ->  Append
> -               ->  Foreign Scan on ftprt1_p1 t1_1
> +               ->  Sort
> +                     Sort Key: t1_1.a
> +                     ->  Foreign Scan on ftprt1_p1 t1_1
>                 ->  Foreign Scan on ftprt1_p2 t1_2
>           ->  Materialize
>                 ->  Append
>                       ->  Foreign Scan on ftprt2_p1 t2_1
>                       ->  Foreign Scan on ftprt2_p2 t2_2
> -(10 rows)
> +(12 rows)
>  
>  SELECT t1.a, t2.b FROM fprt1 t1 INNER JOIN fprt2 t2 ON (t1.a = t2.b) WHERE t1.a % 25 = 0 ORDER BY 1,2 FOR UPDATE OF t1;
>    a  |  b  
> diff --git a/src/backend/optimizer/path/allpaths.c b/src/backend/optimizer/path/allpaths.c
> index 4895cee9944..827bc469269 100644
> --- a/src/backend/optimizer/path/allpaths.c
> +++ b/src/backend/optimizer/path/allpaths.c
> @@ -1845,6 +1845,27 @@ generate_orderedappend_paths(PlannerInfo *root, RelOptInfo *rel,
>  				/* Assert we do have an unparameterized path for this child */
>  				Assert(cheapest_total->param_info == NULL);
>  			}
> +			else
> +			{
> +				/*
> +				 * Even if we found necessary pathkeys, using unsorted path
> +				 * can be more efficient.
> +				 */
> +				Path		sort_path;
> +
> +				cost_sort(&sort_path,
> +						  root,
> +						  pathkeys,
> +						  childrel->cheapest_total_path->total_cost,
> +						  childrel->cheapest_total_path->rows,
> +						  childrel->cheapest_total_path->pathtarget->width,
> +						  0.0,
> +						  work_mem,
> +						  -1.0 /* need all tuples to sort them */ );
> +
> +				if (compare_path_costs(&sort_path, cheapest_total, TOTAL_COST) < 0)
> +					cheapest_total = childrel->cheapest_total_path;
> +			}
>  
>  			/*
>  			 * When building a fractional path, determine a cheapest
> diff --git a/src/test/regress/expected/inherit.out b/src/test/regress/expected/inherit.out
> index ad732134148..16e78c8d2ff 100644
> --- a/src/test/regress/expected/inherit.out
> +++ b/src/test/regress/expected/inherit.out
> @@ -1555,6 +1555,7 @@ insert into matest2 (name) values ('Test 4');
>  insert into matest3 (name) values ('Test 5');
>  insert into matest3 (name) values ('Test 6');
>  set enable_indexscan = off;  -- force use of seqscan/sort, so no merge
> +set enable_sort = off; -- avoid sorting below MergeAppend
>  explain (verbose, costs off) select * from matest0 order by 1-id;
>                           QUERY PLAN                         
>  ------------------------------------------------------------
> @@ -1608,6 +1609,7 @@ select min(1-id) from matest0;
>  (1 row)
>  
>  reset enable_indexscan;
> +reset enable_sort;
>  set enable_seqscan = off;  -- plan with fewest seqscans should be merge
>  set enable_parallel_append = off; -- Don't let parallel-append interfere
>  explain (verbose, costs off) select * from matest0 order by 1-id;
> @@ -1702,7 +1704,9 @@ order by t1.b limit 10;
>           Merge Cond: (t1.b = t2.b)
>           ->  Merge Append
>                 Sort Key: t1.b
> -               ->  Index Scan using matest0i on matest0 t1_1
> +               ->  Sort
> +                     Sort Key: t1_1.b
> +                     ->  Seq Scan on matest0 t1_1
>                 ->  Index Scan using matest1i on matest1 t1_2
>           ->  Materialize
>                 ->  Merge Append
> @@ -1711,7 +1715,7 @@ order by t1.b limit 10;
>                             Filter: (c = d)
>                       ->  Index Scan using matest1i on matest1 t2_2
>                             Filter: (c = d)
> -(14 rows)
> +(16 rows)
>  
>  reset enable_nestloop;
>  drop table matest0 cascade;
> @@ -2663,6 +2667,43 @@ explain (costs off) select * from mcrparted where a = 10 order by a, abs(b), c;
>  
>  reset enable_bitmapscan;
>  drop table mcrparted;
> +-- Check that sort path can be used by MergeAppend even when there are suitable pathkeys
> +create table hash_parted (i int, j int, k int) partition by hash(i);
> +create table hash_parted_1 partition of hash_parted for values with (modulus 4, remainder 0);
> +create table hash_parted_2 partition of hash_parted for values with (modulus 4, remainder 1);
> +create table hash_parted_3 partition of hash_parted for values with (modulus 4, remainder 2);
> +create table hash_parted_4 partition of hash_parted for values with (modulus 4, remainder 3);
> +--create table hash_parted_5 partition of hash_parted for values with (modulus 6, remainder 4);
> +--create table hash_parted_6 partition of hash_parted for values with (modulus 6, remainder 5);
> +create index on hash_parted(j);
> +create index on hash_parted(k);
> +insert into hash_parted select i, i, i from generate_series(1,10000) i;
> +analyze hash_parted;
> +explain (costs off) select * from hash_parted where k<100 order by j limit 100;
> +                               QUERY PLAN                                
> +-------------------------------------------------------------------------
> + Limit
> +   ->  Merge Append
> +         Sort Key: hash_parted.j
> +         ->  Sort
> +               Sort Key: hash_parted_1.j
> +               ->  Index Scan using hash_parted_1_k_idx on hash_parted_1
> +                     Index Cond: (k < 100)
> +         ->  Sort
> +               Sort Key: hash_parted_2.j
> +               ->  Index Scan using hash_parted_2_k_idx on hash_parted_2
> +                     Index Cond: (k < 100)
> +         ->  Sort
> +               Sort Key: hash_parted_3.j
> +               ->  Index Scan using hash_parted_3_k_idx on hash_parted_3
> +                     Index Cond: (k < 100)
> +         ->  Sort
> +               Sort Key: hash_parted_4.j
> +               ->  Index Scan using hash_parted_4_k_idx on hash_parted_4
> +                     Index Cond: (k < 100)
> +(19 rows)
> +
> +drop table hash_parted;
>  -- Ensure LIST partitions allow an Append to be used instead of a MergeAppend
>  create table bool_lp (b bool) partition by list(b);
>  create table bool_lp_true partition of bool_lp for values in(true);
> diff --git a/src/test/regress/expected/partition_join.out b/src/test/regress/expected/partition_join.out
> index 6d07f86b9bc..80d480d33d5 100644
> --- a/src/test/regress/expected/partition_join.out
> +++ b/src/test/regress/expected/partition_join.out
> @@ -1309,28 +1309,32 @@ SELECT t1.a, t1.c, t2.b, t2.c, t3.a + t3.b, t3.c FROM (prt1 t1 LEFT JOIN prt2 t2
>  -- This should generate a partitionwise join, but currently fails to
>  EXPLAIN (COSTS OFF)
>  SELECT t1.a, t2.b FROM (SELECT * FROM prt1 WHERE a < 450) t1 LEFT JOIN (SELECT * FROM prt2 WHERE b > 250) t2 ON t1.a = t2.b WHERE t1.b = 0 ORDER BY t1.a, t2.b;
> -                        QUERY PLAN                         
> ------------------------------------------------------------
> - Incremental Sort
> +                           QUERY PLAN                            
> +-----------------------------------------------------------------
> + Sort
>     Sort Key: prt1.a, prt2.b
> -   Presorted Key: prt1.a
> -   ->  Merge Left Join
> -         Merge Cond: (prt1.a = prt2.b)
> -         ->  Sort
> -               Sort Key: prt1.a
> -               ->  Append
> -                     ->  Seq Scan on prt1_p1 prt1_1
> -                           Filter: ((a < 450) AND (b = 0))
> -                     ->  Seq Scan on prt1_p2 prt1_2
> -                           Filter: ((a < 450) AND (b = 0))
> -         ->  Sort
> -               Sort Key: prt2.b
> -               ->  Append
> +   ->  Merge Right Join
> +         Merge Cond: (prt2.b = prt1.a)
> +         ->  Append
> +               ->  Sort
> +                     Sort Key: prt2_1.b
>                       ->  Seq Scan on prt2_p2 prt2_1
>                             Filter: (b > 250)
> +               ->  Sort
> +                     Sort Key: prt2_2.b
>                       ->  Seq Scan on prt2_p3 prt2_2
>                             Filter: (b > 250)
> -(19 rows)
> +         ->  Materialize
> +               ->  Append
> +                     ->  Sort
> +                           Sort Key: prt1_1.a
> +                           ->  Seq Scan on prt1_p1 prt1_1
> +                                 Filter: ((a < 450) AND (b = 0))
> +                     ->  Sort
> +                           Sort Key: prt1_2.a
> +                           ->  Seq Scan on prt1_p2 prt1_2
> +                                 Filter: ((a < 450) AND (b = 0))
> +(23 rows)
>  
>  SELECT t1.a, t2.b FROM (SELECT * FROM prt1 WHERE a < 450) t1 LEFT JOIN (SELECT * FROM prt2 WHERE b > 250) t2 ON t1.a = t2.b WHERE t1.b = 0 ORDER BY t1.a, t2.b;
>    a  |  b  
> @@ -1350,25 +1354,33 @@ SELECT t1.a, t2.b FROM (SELECT * FROM prt1 WHERE a < 450) t1 LEFT JOIN (SELECT *
>  -- partitionwise join does not apply
>  EXPLAIN (COSTS OFF)
>  SELECT t1.a, t2.b FROM prt1 t1, prt2 t2 WHERE t1::text = t2::text AND t1.a = t2.b ORDER BY t1.a;
> -                                       QUERY PLAN                                        
> ------------------------------------------------------------------------------------------
> +                            QUERY PLAN                            
> +------------------------------------------------------------------
>   Merge Join
> -   Merge Cond: ((t1.a = t2.b) AND (((((t1.*)::prt1))::text) = ((((t2.*)::prt2))::text)))
> -   ->  Sort
> -         Sort Key: t1.a, ((((t1.*)::prt1))::text)
> -         ->  Result
> -               ->  Append
> -                     ->  Seq Scan on prt1_p1 t1_1
> -                     ->  Seq Scan on prt1_p2 t1_2
> -                     ->  Seq Scan on prt1_p3 t1_3
> -   ->  Sort
> -         Sort Key: t2.b, ((((t2.*)::prt2))::text)
> -         ->  Result
> -               ->  Append
> +   Merge Cond: (t1.a = t2.b)
> +   Join Filter: ((((t2.*)::prt2))::text = (((t1.*)::prt1))::text)
> +   ->  Append
> +         ->  Sort
> +               Sort Key: t1_1.a
> +               ->  Seq Scan on prt1_p1 t1_1
> +         ->  Sort
> +               Sort Key: t1_2.a
> +               ->  Seq Scan on prt1_p2 t1_2
> +         ->  Sort
> +               Sort Key: t1_3.a
> +               ->  Seq Scan on prt1_p3 t1_3
> +   ->  Materialize
> +         ->  Append
> +               ->  Sort
> +                     Sort Key: t2_1.b
>                       ->  Seq Scan on prt2_p1 t2_1
> +               ->  Sort
> +                     Sort Key: t2_2.b
>                       ->  Seq Scan on prt2_p2 t2_2
> +               ->  Sort
> +                     Sort Key: t2_3.b
>                       ->  Seq Scan on prt2_p3 t2_3
> -(16 rows)
> +(24 rows)
>  
>  SELECT t1.a, t2.b FROM prt1 t1, prt2 t2 WHERE t1::text = t2::text AND t1.a = t2.b ORDER BY t1.a;
>   a  | b  
> @@ -4906,21 +4918,26 @@ EXPLAIN (COSTS OFF)
>  SELECT t1.*, t2.* FROM alpha t1 INNER JOIN beta t2 ON (t1.a = t2.a AND t1.b = t2.b) WHERE t1.b >= 125 AND t1.b < 225 ORDER BY t1.a, t1.b;
>                               QUERY PLAN                             
>  --------------------------------------------------------------------
> - Sort
> + Merge Append
>     Sort Key: t1.a, t1.b
> -   ->  Append
> +   ->  Sort
> +         Sort Key: t1_1.a, t1_1.b
>           ->  Hash Join
>                 Hash Cond: ((t1_1.a = t2_1.a) AND (t1_1.b = t2_1.b))
>                 ->  Seq Scan on alpha_neg_p1 t1_1
>                       Filter: ((b >= 125) AND (b < 225))
>                 ->  Hash
>                       ->  Seq Scan on beta_neg_p1 t2_1
> +   ->  Sort
> +         Sort Key: t1_2.a, t1_2.b
>           ->  Hash Join
>                 Hash Cond: ((t2_2.a = t1_2.a) AND (t2_2.b = t1_2.b))
>                 ->  Seq Scan on beta_neg_p2 t2_2
>                 ->  Hash
>                       ->  Seq Scan on alpha_neg_p2 t1_2
>                             Filter: ((b >= 125) AND (b < 225))
> +   ->  Sort
> +         Sort Key: t1_4.a, t1_4.b
>           ->  Hash Join
>                 Hash Cond: ((t2_4.a = t1_4.a) AND (t2_4.b = t1_4.b))
>                 ->  Append
> @@ -4935,7 +4952,7 @@ SELECT t1.*, t2.* FROM alpha t1 INNER JOIN beta t2 ON (t1.a = t2.a AND t1.b = t2
>                                   Filter: ((b >= 125) AND (b < 225))
>                             ->  Seq Scan on alpha_pos_p3 t1_6
>                                   Filter: ((b >= 125) AND (b < 225))
> -(29 rows)
> +(34 rows)
>  
>  SELECT t1.*, t2.* FROM alpha t1 INNER JOIN beta t2 ON (t1.a = t2.a AND t1.b = t2.b) WHERE t1.b >= 125 AND t1.b < 225 ORDER BY t1.a, t1.b;
>   a  |  b  |  c   | a  |  b  |  c   
> diff --git a/src/test/regress/expected/union.out b/src/test/regress/expected/union.out
> index 0fd0e1c38b3..4c1c173d8e6 100644
> --- a/src/test/regress/expected/union.out
> +++ b/src/test/regress/expected/union.out
> @@ -1195,12 +1195,14 @@ select event_id
>  ----------------------------------------------------------
>   Merge Append
>     Sort Key: events.event_id
> -   ->  Index Scan using events_pkey on events
> +   ->  Sort
> +         Sort Key: events.event_id
> +         ->  Seq Scan on events
>     ->  Sort
>           Sort Key: events_1.event_id
>           ->  Seq Scan on events_child events_1
>     ->  Index Scan using other_events_pkey on other_events
> -(7 rows)
> +(9 rows)
>  
>  drop table events_child, events, other_events;
>  reset enable_indexonlyscan;
> diff --git a/src/test/regress/sql/inherit.sql b/src/test/regress/sql/inherit.sql
> index e3bcfdb181e..5331e49283f 100644
> --- a/src/test/regress/sql/inherit.sql
> +++ b/src/test/regress/sql/inherit.sql
> @@ -586,11 +586,13 @@ insert into matest3 (name) values ('Test 5');
>  insert into matest3 (name) values ('Test 6');
>  
>  set enable_indexscan = off;  -- force use of seqscan/sort, so no merge
> +set enable_sort = off; -- avoid sorting below MergeAppend
>  explain (verbose, costs off) select * from matest0 order by 1-id;
>  select * from matest0 order by 1-id;
>  explain (verbose, costs off) select min(1-id) from matest0;
>  select min(1-id) from matest0;
>  reset enable_indexscan;
> +reset enable_sort;
>  
>  set enable_seqscan = off;  -- plan with fewest seqscans should be merge
>  set enable_parallel_append = off; -- Don't let parallel-append interfere
> @@ -976,6 +978,21 @@ reset enable_bitmapscan;
>  
>  drop table mcrparted;
>  
> +-- Check that sort path can be used by MergeAppend even when there are suitable pathkeys
> +create table hash_parted (i int, j int, k int) partition by hash(i);
> +create table hash_parted_1 partition of hash_parted for values with (modulus 4, remainder 0);
> +create table hash_parted_2 partition of hash_parted for values with (modulus 4, remainder 1);
> +create table hash_parted_3 partition of hash_parted for values with (modulus 4, remainder 2);
> +create table hash_parted_4 partition of hash_parted for values with (modulus 4, remainder 3);
> +--create table hash_parted_5 partition of hash_parted for values with (modulus 6, remainder 4);
> +--create table hash_parted_6 partition of hash_parted for values with (modulus 6, remainder 5);
> +create index on hash_parted(j);
> +create index on hash_parted(k);
> +insert into hash_parted select i, i, i from generate_series(1,10000) i;
> +analyze hash_parted;
> +explain (costs off) select * from hash_parted where k<100 order by j limit 100;
> +drop table hash_parted;
> +
>  -- Ensure LIST partitions allow an Append to be used instead of a MergeAppend
>  create table bool_lp (b bool) partition by list(b);
>  create table bool_lp_true partition of bool_lp for values in(true);
> -- 
> 2.34.1
> 


-- 
  Bruce Momjian  <bruce@momjian.us>        https://momjian.us
  EDB                                      https://enterprisedb.com

  When a patient asks the doctor, "Am I going to die?", he means 
  "Am I going to die soon?"

Re: MergeAppend could consider sorting cheapest child path

Andy Fan <zhihuifan1213@163.com> — 2024-10-17T00:33:44Z

Bruce Momjian <bruce@momjian.us> writes:

> Is this still being considered?

I'd +1 on this feature. I guess this would be more useful on parallel
case, where the Sort can be pushed down to parallel worker, and in the
distributed database case, where the Sort can be pushed down to multiple
nodes, at the result, the leader just do the merge works.

At the high level implementaion, sorting *cheapest* child path looks
doesn't add too much overhead on the planning effort. 

-- 
Best Regards
Andy Fan

Re: MergeAppend could consider sorting cheapest child path

Nikita Malakhov <hukutoc@gmail.com> — 2024-10-28T19:46:31Z

Hi!

I've checked this thread and examples in it, and do not see stable
improvements
in base tests. Sometimes base tests are considerably slower with patch,
like:


explain analyze
select t1.* from matest0 t1, matest0 t2
where t1.b = t2.b and t2.c = t2.d
order by t1.b limit 10;
                                                                  QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.46..19.90 rows=10 width=16) (actual time=0.007..0.008
rows=0 loops=1)
   ->  Merge Join  (cost=0.46..181.24 rows=93 width=16) (actual
time=0.007..0.007 rows=0 loops=1)
         Merge Cond: (t1.b = t2.b)
         ->  Merge Append  (cost=0.17..90.44 rows=1851 width=16) (actual
time=0.006..0.007 rows=0 loops=1)
               Sort Key: t1.b
               ->  Sort  (cost=0.01..0.02 rows=1 width=16) (actual
time=0.004..0.004 rows=0 loops=1)
                     Sort Key: t1_1.b
                     Sort Method: quicksort  Memory: 25kB
                     ->  Seq Scan on matest0 t1_1  (cost=0.00..0.00 rows=1
width=16) (actual time=0.002..0.002 rows=0 loops=1)
               ->  Index Scan using matest1i on matest1 t1_2
 (cost=0.15..71.90 rows=1850 width=16) (actual time=0.002..0.002 rows=0
loops=1)
         ->  Materialize  (cost=0.29..84.81 rows=10 width=4) (never
executed)
               ->  Merge Append  (cost=0.29..84.78 rows=10 width=4) (never
executed)
                     Sort Key: t2.b
                     ->  Index Scan using matest0i on matest0 t2_1
 (cost=0.12..8.14 rows=1 width=4) (never executed)
                           Filter: (c = d)
                     ->  Index Scan using matest1i on matest1 t2_2
 (cost=0.15..76.53 rows=9 width=4) (never executed)
                           Filter: (c = d)
 Planning Time: 0.252 ms
 Execution Time: 0.048 ms
(19 rows)

explain analyze
select t1.* from matest0 t1, matest0 t2
where t1.b = t2.b and t2.c = t2.d
order by t1.b limit 10;
                                                                  QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.57..20.88 rows=10 width=16) (actual time=0.004..0.004
rows=0 loops=1)
   ->  Merge Join  (cost=0.57..189.37 rows=93 width=16) (actual
time=0.003..0.004 rows=0 loops=1)
         Merge Cond: (t1.b = t2.b)
         ->  Merge Append  (cost=0.29..98.56 rows=1851 width=16) (actual
time=0.002..0.003 rows=0 loops=1)
               Sort Key: t1.b
               ->  Index Scan using matest0i on matest0 t1_1
 (cost=0.12..8.14 rows=1 width=16) (actual time=0.002..0.002 rows=0 loops=1)
               ->  Index Scan using matest1i on matest1 t1_2
 (cost=0.15..71.90 rows=1850 width=16) (actual time=0.001..0.001 rows=0
loops=1)
         ->  Materialize  (cost=0.29..84.81 rows=10 width=4) (never
executed)
               ->  Merge Append  (cost=0.29..84.78 rows=10 width=4) (never
executed)
                     Sort Key: t2.b
                     ->  Index Scan using matest0i on matest0 t2_1
 (cost=0.12..8.14 rows=1 width=4) (never executed)
                           Filter: (c = d)
                     ->  Index Scan using matest1i on matest1 t2_2
 (cost=0.15..76.53 rows=9 width=4) (never executed)
                           Filter: (c = d)
 Planning Time: 0.278 ms
 Execution Time: 0.025 ms
(16 rows)

(patched)
explain analyze
select t1.* from matest0 t1, matest0 t2
where t1.b = t2.b and t2.c = t2.d
order by t1.b limit 10;
                                                                  QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.46..19.90 rows=10 width=16) (actual time=0.007..0.008
rows=0 loops=1)
   ->  Merge Join  (cost=0.46..181.24 rows=93 width=16) (actual
time=0.007..0.007 rows=0 loops=1)
         Merge Cond: (t1.b = t2.b)
         ->  Merge Append  (cost=0.17..90.44 rows=1851 width=16) (actual
time=0.006..0.007 rows=0 loops=1)
               Sort Key: t1.b
               ->  Sort  (cost=0.01..0.02 rows=1 width=16) (actual
time=0.004..0.004 rows=0 loops=1)
                     Sort Key: t1_1.b
                     Sort Method: quicksort  Memory: 25kB
                     ->  Seq Scan on matest0 t1_1  (cost=0.00..0.00 rows=1
width=16) (actual time=0.002..0.002 rows=0 loops=1)
               ->  Index Scan using matest1i on matest1 t1_2
 (cost=0.15..71.90 rows=1850 width=16) (actual time=0.002..0.002 rows=0
loops=1)
         ->  Materialize  (cost=0.29..84.81 rows=10 width=4) (never
executed)
               ->  Merge Append  (cost=0.29..84.78 rows=10 width=4) (never
executed)
                     Sort Key: t2.b
                     ->  Index Scan using matest0i on matest0 t2_1
 (cost=0.12..8.14 rows=1 width=4) (never executed)
                           Filter: (c = d)
                     ->  Index Scan using matest1i on matest1 t2_2
 (cost=0.15..76.53 rows=9 width=4) (never executed)
                           Filter: (c = d)
 Planning Time: 0.252 ms
 Execution Time: 0.048 ms
(19 rows)

(vanilla)
explain analyze
select t1.* from matest0 t1, matest0 t2
where t1.b = t2.b and t2.c = t2.d
order by t1.b limit 10;
                                                                  QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.57..20.88 rows=10 width=16) (actual time=0.004..0.004
rows=0 loops=1)
   ->  Merge Join  (cost=0.57..189.37 rows=93 width=16) (actual
time=0.003..0.004 rows=0 loops=1)
         Merge Cond: (t1.b = t2.b)
         ->  Merge Append  (cost=0.29..98.56 rows=1851 width=16) (actual
time=0.002..0.003 rows=0 loops=1)
               Sort Key: t1.b
               ->  Index Scan using matest0i on matest0 t1_1
 (cost=0.12..8.14 rows=1 width=16) (actual time=0.002..0.002 rows=0 loops=1)
               ->  Index Scan using matest1i on matest1 t1_2
 (cost=0.15..71.90 rows=1850 width=16) (actual time=0.001..0.001 rows=0
loops=1)
         ->  Materialize  (cost=0.29..84.81 rows=10 width=4) (never
executed)
               ->  Merge Append  (cost=0.29..84.78 rows=10 width=4) (never
executed)
                     Sort Key: t2.b
                     ->  Index Scan using matest0i on matest0 t2_1
 (cost=0.12..8.14 rows=1 width=4) (never executed)
                           Filter: (c = d)
                     ->  Index Scan using matest1i on matest1 t2_2
 (cost=0.15..76.53 rows=9 width=4) (never executed)
                           Filter: (c = d)
 Planning Time: 0.278 ms
 Execution Time: 0.025 ms
(16 rows)

--
Nikita Malakhov
Postgres Professional
The Russian Postgres Company
https://postgrespro.ru/

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-03-28T08:19:30Z

Andy Fan писал(а) 2024-10-17 03:33:
> Bruce Momjian <bruce@momjian.us> writes:
> 
>> Is this still being considered?
> 
> I'd +1 on this feature. I guess this would be more useful on parallel
> case, where the Sort can be pushed down to parallel worker, and in the
> distributed database case, where the Sort can be pushed down to 
> multiple
> nodes, at the result, the leader just do the merge works.
> 
> At the high level implementaion, sorting *cheapest* child path looks
> doesn't add too much overhead on the planning effort.

Hi.

I've updated patch. One more interesting case which we found - when 
fractional path is selected, it still can be more expensive than sorted 
cheapest total path (as we look only on indexes whith necessary 
pathkeys, not on indexes which allow efficiently fetch data).
So far couldn't find artificial example, but we've seen inadequate index 
selection due to this issue - instead of using index suited for filters 
in where, index, suitable for sorting was selected as one having the 
cheapest fractional cost.
-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-04-24T13:01:18Z

On 3/28/25 09:19, Alexander Pyhalov wrote:
> Andy Fan писал(а) 2024-10-17 03:33:
> I've updated patch. One more interesting case which we found - when 
> fractional path is selected, it still can be more expensive than sorted 
> cheapest total path (as we look only on indexes whith necessary 
> pathkeys, not on indexes which allow efficiently fetch data).
> So far couldn't find artificial example, but we've seen inadequate index 
> selection due to this issue - instead of using index suited for filters 
> in where, index, suitable for sorting was selected as one having the 
> cheapest fractional cost.
I think it is necessary to generalise the approach a little.

Each MergeAppend subpath candidate that fits pathkeys should be compared 
to the overall-optimal path + explicit Sort node. Let's label this 
two-node composition as base_path. There are three cases exist: 
startup-optimal, total-optimal and fractional-optimal.
In the startup case, base_path should use cheapest_startup_path, the 
total-optimal case - cheapest_total_path and for a fractional case, we 
may employ the get_cheapest_fractional_path routine to detect proper 
base_path.

It may provide a more effective plan either in full, fractional and 
partial scan cases:
1. The Sort node may be pushed down to subpaths under a parallel or 
async Append.
2. When a minor set of subpaths doesn't have a proper index, and it is 
profitable to sort them instead of switching to plain Append.

In general, analysing the regression tests changed by this code, I see 
that the cost model prefers a series of small sortings instead of a 
single massive one. May be it will show some profit for execution time.

I am not afraid of any palpable planning overhead here because we just 
do cheap cost estimation and comparison operations that don't need 
additional memory allocations. The caller is responsible for building a 
proper Sort node if this method is chosen as optimal.

In the attachment, see the patch written according to the idea. There 
are I introduced two new routines:
get_cheapest_path_for_pathkeys_ext
get_cheapest_fractional_path_for_pathkeys_ext

I have designed the code that way to reduce duplicated code in the 
generate_orderedappend_paths routine. But the main point is that I 
envision these new routines may be reused elsewhere.

This feature looks сlose to the one we discussed before [1]. So, let me 
CC the people from the previous conversation to the discussion.

[1] 
https://www.postgresql.org/message-id/flat/CAN-LCVPxnWB39CUBTgOQ9O7Dd8DrA_tpT1EY3LNVnUuvAX1NjA%40mail.gmail.com

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-04-25T09:16:29Z

Andrei Lepikhov писал(а) 2025-04-24 16:01:
> On 3/28/25 09:19, Alexander Pyhalov wrote:
>> Andy Fan писал(а) 2024-10-17 03:33:
>> I've updated patch. One more interesting case which we found - when 
>> fractional path is selected, it still can be more expensive than 
>> sorted cheapest total path (as we look only on indexes whith necessary 
>> pathkeys, not on indexes which allow efficiently fetch data).
>> So far couldn't find artificial example, but we've seen inadequate 
>> index selection due to this issue - instead of using index suited for 
>> filters in where, index, suitable for sorting was selected as one 
>> having the cheapest fractional cost.
> I think it is necessary to generalise the approach a little.
> 
> Each MergeAppend subpath candidate that fits pathkeys should be 
> compared to the overall-optimal path + explicit Sort node. Let's label 
> this two-node composition as base_path. There are three cases exist: 
> startup-optimal, total-optimal and fractional-optimal.
> In the startup case, base_path should use cheapest_startup_path, the 
> total-optimal case - cheapest_total_path and for a fractional case, we 
> may employ the get_cheapest_fractional_path routine to detect proper 
> base_path.
> 
> It may provide a more effective plan either in full, fractional and 
> partial scan cases:
> 1. The Sort node may be pushed down to subpaths under a parallel or 
> async Append.
> 2. When a minor set of subpaths doesn't have a proper index, and it is 
> profitable to sort them instead of switching to plain Append.
> 
> In general, analysing the regression tests changed by this code, I see 
> that the cost model prefers a series of small sortings instead of a 
> single massive one. May be it will show some profit for execution time.
> 
> I am not afraid of any palpable planning overhead here because we just 
> do cheap cost estimation and comparison operations that don't need 
> additional memory allocations. The caller is responsible for building a 
> proper Sort node if this method is chosen as optimal.
> 
> In the attachment, see the patch written according to the idea. There 
> are I introduced two new routines:
> get_cheapest_path_for_pathkeys_ext
> get_cheapest_fractional_path_for_pathkeys_ext

Hi. I'm a bit confused that 
get_cheapest_fractional_path_for_pathkeys_ext() looks only on sorting 
cheapest fractional path, and get_cheapest_path_for_pathkeys_ext() in 
STARTUP_COST case looks only on sorting cheapest_startup_path.
Usually, sorted cheapest_total_path will be cheaper than sorted 
fractional/startup path at least by startup cost (as after sorting it 
includes total_cost of input path). But we ignore this case when 
selecting cheapest_startup and cheapest_fractional subpaths. As result 
selected cheapest_startup and cheapest_fractional can be not cheapest 
for startup or selecting a fraction of rows.

Consider the partition with the following access paths:

1) cheapest_startup without required pathkeys:
   startup_cost: 0.42
   total_cost: 4004

2) some index_path  with required pathkeys:
   startup_cost: 6.6
   total_cost: 2000

3) cheapest_total_path:
   startup_cost: 0.42
   total_cost: 3.48

Here, when selecting cheapest startup subpath we'll compare costs of 
index path (2) and sorted cheapest_startup (1), but will ignore sorted 
cheapest_total_path (3), despite the fact that it really can be the 
cheapest startup path, providing required sorting order.

-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-04-25T15:13:26Z

On 4/25/25 11:16, Alexander Pyhalov wrote:
> Andrei Lepikhov писал(а) 2025-04-24 16:01:
>> On 3/28/25 09:19, Alexander Pyhalov wrote:
>> In the attachment, see the patch written according to the idea. There 
>> are I introduced two new routines:
>> get_cheapest_path_for_pathkeys_ext
>> get_cheapest_fractional_path_for_pathkeys_ext
> 
> Hi. I'm a bit confused that 
Thanks for the participation!

> get_cheapest_fractional_path_for_pathkeys_ext() looks only on sorting 
> cheapest fractional path, and get_cheapest_path_for_pathkeys_ext() in 
> STARTUP_COST case looks only on sorting cheapest_startup_path.
At first, at the moment, I don't understand why we calculate the 
cheapest_startup path at all. In my opinion, after commit 6b94e7a [1, 
2], the min-fractional path totally covers the case. I began this 
discussion in [3] - maybe we need to scrutinise that issue beforehand.

Looking into the min-fractional-path + Sort, we propose a path for the 
case when extracting minor part of tuples with sorting later is cheaper 
than doing a massive job of non-selective index scan. You also may 
imagine the case of a JOIN as a subpath: non-sorted, highly selective 
parameterised NestLoop may be way more optimal than MergeJoin, which 
fits the pathkeys.

> Usually, sorted cheapest_total_path will be cheaper than sorted 
> fractional/startup path at least by startup cost (as after sorting it 
> includes total_cost of input path). But we ignore this case when 
> selecting cheapest_startup and cheapest_fractional subpaths. As result 
> selected cheapest_startup and cheapest_fractional can be not cheapest 
> for startup or selecting a fraction of rows.
I don't know what you mean by that. The cheapest_total_path is 
considered when we chose optimal cheapest_total path. The same works for 
the fractional path - get_cheapest_fractional_path gives us the most 
optimal fractional path and probes cheapest_total_path too.
As above, not sure about min-startup case for now. I can imagine 
MergeAppend over sophisticated subquery: non-sorted includes highly 
parameterised JOINs and the alternative (with pathkeys) includes 
HashJoin, drastically increasing startup cost. It is only a theory, of 
course. So, lets discover how min-startup works.

At the end, when the sorted path already estimated, we each time compare 
it with previously selected pathkeys-cheapest. So, if the sorted path is 
worse, we end up with the original path and don't lose anything.

[1] 
https://www.postgresql.org/message-id/e8f9ec90-546d-e948-acce-0525f3e92773%40enterprisedb.com
[2] 
https://www.postgresql.org/message-id/1581042da8044e71ada2d6e3a51bf7bb%40index.de
[3] 
https://www.postgresql.org/message-id/f0206ef2-6b5a-4d07-8770-cfa7cd30f685@gmail.com

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-04-29T13:52:40Z

On 4/25/25 17:13, Andrei Lepikhov wrote:
> On 4/25/25 11:16, Alexander Pyhalov wrote:
>> Usually, sorted cheapest_total_path will be cheaper than sorted 
>> fractional/startup path at least by startup cost (as after sorting it 
>> includes total_cost of input path). But we ignore this case when 
>> selecting cheapest_startup and cheapest_fractional subpaths. As result 
>> selected cheapest_startup and cheapest_fractional can be not cheapest 
>> for startup or selecting a fraction of rows.
> I don't know what you mean by that. The cheapest_total_path is 
> considered when we chose optimal cheapest_total path. The same works for 
> the fractional path - get_cheapest_fractional_path gives us the most 
> optimal fractional path and probes cheapest_total_path too.
> As above, not sure about min-startup case for now. I can imagine 
> MergeAppend over sophisticated subquery: non-sorted includes highly 
> parameterised JOINs and the alternative (with pathkeys) includes 
> HashJoin, drastically increasing startup cost. It is only a theory, of 
> course. So, lets discover how min-startup works.
After a second thought I have caught your idea. I agree that for a 
fractional path it have no sense to choose any other path except a 
cheapest total one.
There are the modified patch in the attachment.

Also, to be more objective, I propose to use examples in argumentation - 
something like in attached test2.sql script.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-04-29T17:25:48Z

Andrei Lepikhov писал(а) 2025-04-29 16:52:
> On 4/25/25 17:13, Andrei Lepikhov wrote:
>> On 4/25/25 11:16, Alexander Pyhalov wrote:
>>> Usually, sorted cheapest_total_path will be cheaper than sorted 
>>> fractional/startup path at least by startup cost (as after sorting it 
>>> includes total_cost of input path). But we ignore this case when 
>>> selecting cheapest_startup and cheapest_fractional subpaths. As 
>>> result selected cheapest_startup and cheapest_fractional can be not 
>>> cheapest for startup or selecting a fraction of rows.
>> I don't know what you mean by that. The cheapest_total_path is 
>> considered when we chose optimal cheapest_total path. The same works 
>> for the fractional path - get_cheapest_fractional_path gives us the 
>> most optimal fractional path and probes cheapest_total_path too.
>> As above, not sure about min-startup case for now. I can imagine 
>> MergeAppend over sophisticated subquery: non-sorted includes highly 
>> parameterised JOINs and the alternative (with pathkeys) includes 
>> HashJoin, drastically increasing startup cost. It is only a theory, of 
>> course. So, lets discover how min-startup works.
> After a second thought I have caught your idea. I agree that for a 
> fractional path it have no sense to choose any other path except a 
> cheapest total one.
> There are the modified patch in the attachment.
> 
> Also, to be more objective, I propose to use examples in argumentation 
> - something like in attached test2.sql script.

Hi.
I've looked through new patch and found minor inconsistencies in 
get_cheapest_path_for_pathkeys_ext() and 
get_cheapest_fractional_path_for_pathkeys_ext().

In get_cheapest_fractional_path_for_pathkeys_ext() we check that 
base_path is not NULL
        path = get_cheapest_fractional_path_for_pathkeys(rel->pathlist, 
pathkeys,
                                                                          
                                required_outer, fraction);

        base_path = rel->cheapest_total_path;

        /* Stop here if the path doesn't satisfy necessary conditions */
        if (!base_path || !bms_is_subset(PATH_REQ_OUTER(base_path), 
required_outer))
                return path;

But it seems, base_path can't be NULL (as add_paths_to_append_rel() is 
called after set_rel_pathlist() for childrels).
However,  path can. Can we do these two functions 
get_cheapest_path_for_pathkeys_ext() and 
get_cheapest_fractional_path_for_pathkeys_ext()
more similar?

Also we check base_path for required_outer and require_parallel_safe, 
but if cheapest path for pathkeys is NULL, these checks are not 
performed. Luckily, they seen to be no-op anyway due to 
cheapest_total->param_info == NULL and function arguments being NULL 
(required_outer) and false (require_parallel_safe). Should we do 
something about this? Don't know, perhaps, remove these misleading 
arguments?

Now, if we return cheapest_total_path from 
get_cheapest_fractional_path_for_pathkeys_ext() if cheapest paths for 
pathkeys don't exist, do the following lines


                                 /*
                                  * If we found no path with matching 
pathkeys, use the
                                  * cheapest total path instead.
                                  *
                                  * XXX We might consider partially 
sorted paths too (with an
                                  * incremental sort on top). But we'd 
have to build all the
                                  * incremental paths, do the costing 
etc.
                                  */
                                 if (!cheapest_fractional)
                                         cheapest_fractional = 
cheapest_total;

become no-op? And we do return non-null path from  
get_cheapest_fractional_path_for_pathkeys_ext(), as it seems we return 
either cheapest_total_path or cheapest fractional path from 
get_cheapest_fractional_path_for_pathkeys_ext().

-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-05-05T11:38:39Z

On 4/29/25 19:25, Alexander Pyhalov wrote:
> Andrei Lepikhov писал(а) 2025-04-29 16:52:
> But it seems, base_path can't be NULL
Correct. Fixed.

> 
> Also we check base_path for required_outer and require_parallel_safe, 
> but if cheapest path for pathkeys is NULL, these checks are not 
> performed. 
Thanks. Fixed.

 > Luckily, they seen to be no-op anyway due to cheapest_total- > 
 >param_info == NULL and function arguments being NULL (required_outer)
> and false (require_parallel_safe). Should we do something about this? 
> Don't know, perhaps, remove these misleading arguments?
The main reason why I introduced these _ext routines was that this 
schema may be used somewhere else. And in that case parameterised paths 
may exist. Who knows, may be parameterised paths will be introduced for 
merge append too?

> become no-op? And we do return non-null path from 
> get_cheapest_fractional_path_for_pathkeys_ext(), as it seems we return 
> either cheapest_total_path or cheapest fractional path from 
> get_cheapest_fractional_path_for_pathkeys_ext().
Ok.

Let's check next version of the patch in the attachment.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-05-05T11:41:17Z

On 5/5/25 13:38, Andrei Lepikhov wrote:
> Let's check next version of the patch in the attachment.
Oops, I forgot some tails - see this new version.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-05-05T13:56:36Z

Andrei Lepikhov писал(а) 2025-05-05 14:38:
> On 4/29/25 19:25, Alexander Pyhalov wrote:
>> Andrei Lepikhov писал(а) 2025-04-29 16:52:
>> But it seems, base_path can't be NULL
> Correct. Fixed.
> 
>> 
>> Also we check base_path for required_outer and require_parallel_safe, 
>> but if cheapest path for pathkeys is NULL, these checks are not 
>> performed.
> Thanks. Fixed.
> 
>> Luckily, they seen to be no-op anyway due to cheapest_total- > 
>> >param_info == NULL and function arguments being NULL (required_outer)
>> and false (require_parallel_safe). Should we do something about this? 
>> Don't know, perhaps, remove these misleading arguments?
> The main reason why I introduced these _ext routines was that this 
> schema may be used somewhere else. And in that case parameterised paths 
> may exist. Who knows, may be parameterised paths will be introduced for 
> merge append too?
> 
>> become no-op? And we do return non-null path from 
>> get_cheapest_fractional_path_for_pathkeys_ext(), as it seems we return 
>> either cheapest_total_path or cheapest fractional path from 
>> get_cheapest_fractional_path_for_pathkeys_ext().
> Ok.
> 
> Let's check next version of the patch in the attachment.

Hi.

Both functions are a bit different:

        Path   *base_path = rel->cheapest_total_path;
        Path   *path;

        path = get_cheapest_path_for_pathkeys(rel->pathlist, pathkeys,
                                                                          
         required_outer, cost_criterion,
                                                                          
         require_parallel_safe);

        /* Stop here if the path doesn't satisfy necessary conditions */
        if ((require_parallel_safe && !base_path->parallel_safe) ||
                !bms_is_subset(PATH_REQ_OUTER(base_path), 
required_outer))
                return path;


Here comment speaks about "the path", and check is performed on 
base_path, could it be misleading?

In get_cheapest_fractional_path_for_pathkeys_ext():

        path = get_cheapest_fractional_path_for_pathkeys(rel->pathlist, 
pathkeys,
                                                                          
                                required_outer, fraction);

        base_path = rel->cheapest_total_path;

        /* Stop here if the path doesn't satisfy necessary conditions */
        if (!bms_is_subset(PATH_REQ_OUTER(base_path), required_outer))
                return path;


Here "the path" also refers to base_path, but here at least it's the 
last path we've just looked at. Should we make base_path initialization 
consistent and fix comment a bit, so that there's no possible ambiguity 
and it's evident that it refers to the base_path?

Also logic a bit differs if path is NULL. In 
get_cheapest_path_for_pathkeys_ext() we explicitly check for path being 
NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only after 
calculating sort cost.

I've tried to fix comments a bit and unified functions definitions.
-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-05-07T05:02:05Z

On 5/5/2025 15:56, Alexander Pyhalov wrote:
> Andrei Lepikhov писал(а) 2025-05-05 14:38:
> Also logic a bit differs if path is NULL. In 
> get_cheapest_path_for_pathkeys_ext() we explicitly check for path being 
> NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only after 
> calculating sort cost.
> 
> I've tried to fix comments a bit and unified functions definitions.
Generally seems ok, I'm not a native speaker to judge the comments. But:
if (base_path && path != base_path)

What is the case in your mind where the base_path pointer still may be 
null at that point?

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-05-07T06:57:16Z

Andrei Lepikhov писал(а) 2025-05-07 08:02:
> On 5/5/2025 15:56, Alexander Pyhalov wrote:
>> Andrei Lepikhov писал(а) 2025-05-05 14:38:
>> Also logic a bit differs if path is NULL. In 
>> get_cheapest_path_for_pathkeys_ext() we explicitly check for path 
>> being NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only 
>> after calculating sort cost.
>> 
>> I've tried to fix comments a bit and unified functions definitions.
> Generally seems ok, I'm not a native speaker to judge the comments. 
> But:
> if (base_path && path != base_path)
> 
> What is the case in your mind where the base_path pointer still may be 
> null at that point?

Hi.

It seems if some childrel doesn't have valid pathlist, subpaths_valid 
would be false in add_paths_to_append_rel()
and generate_orderedappend_paths() will not  be called. So when we 
iterate over live_childrels,
all of them will have cheapest_total path. This is why we can assert 
that base_path is not NULL.
-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-05-07T09:03:04Z

On 7/5/2025 08:57, Alexander Pyhalov wrote:
> Andrei Lepikhov писал(а) 2025-05-07 08:02:
>> On 5/5/2025 15:56, Alexander Pyhalov wrote:
>>> Andrei Lepikhov писал(а) 2025-05-05 14:38:
>>> Also logic a bit differs if path is NULL. In 
>>> get_cheapest_path_for_pathkeys_ext() we explicitly check for path 
>>> being NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only 
>>> after calculating sort cost.
>>>
>>> I've tried to fix comments a bit and unified functions definitions.
>> Generally seems ok, I'm not a native speaker to judge the comments. But:
>> if (base_path && path != base_path)
>>
>> What is the case in your mind where the base_path pointer still may be 
>> null at that point?
> 
> Hi.
> 
> It seems if some childrel doesn't have valid pathlist, subpaths_valid 
> would be false in add_paths_to_append_rel()
> and generate_orderedappend_paths() will not  be called. So when we 
> iterate over live_childrels,
> all of them will have cheapest_total path. This is why we can assert 
> that base_path is not NULL.
I'm not sure I understand you correctly. Under which conditions will 
rel->cheapest_total_path be set to NULL for a childrel? Could you 
provide an example?

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Pyhalov <a.pyhalov@postgrespro.ru> — 2025-05-07T09:06:05Z

Andrei Lepikhov писал(а) 2025-05-07 12:03:
> On 7/5/2025 08:57, Alexander Pyhalov wrote:
>> Andrei Lepikhov писал(а) 2025-05-07 08:02:
>>> On 5/5/2025 15:56, Alexander Pyhalov wrote:
>>>> Andrei Lepikhov писал(а) 2025-05-05 14:38:
>>>> Also logic a bit differs if path is NULL. In 
>>>> get_cheapest_path_for_pathkeys_ext() we explicitly check for path 
>>>> being NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only 
>>>> after calculating sort cost.
>>>> 
>>>> I've tried to fix comments a bit and unified functions definitions.
>>> Generally seems ok, I'm not a native speaker to judge the comments. 
>>> But:
>>> if (base_path && path != base_path)
>>> 
>>> What is the case in your mind where the base_path pointer still may 
>>> be null at that point?
>> 
>> Hi.
>> 
>> It seems if some childrel doesn't have valid pathlist, subpaths_valid 
>> would be false in add_paths_to_append_rel()
>> and generate_orderedappend_paths() will not  be called. So when we 
>> iterate over live_childrels,
>> all of them will have cheapest_total path. This is why we can assert 
>> that base_path is not NULL.
> I'm not sure I understand you correctly. Under which conditions will 
> rel->cheapest_total_path be set to NULL for a childrel? Could you 
> provide an example?

Sorry, perhaps I was not clear enough. I've stated the opposite - it 
seems we can be sure that it's not NULL.
-- 
Best regards,
Alexander Pyhalov,
Postgres Professional

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-06-02T18:21:32Z

Hi, Alexander!

On Wed, May 7, 2025 at 12:06 PM Alexander Pyhalov
<a.pyhalov@postgrespro.ru> wrote:
> Andrei Lepikhov писал(а) 2025-05-07 12:03:
> > On 7/5/2025 08:57, Alexander Pyhalov wrote:
> >> Andrei Lepikhov писал(а) 2025-05-07 08:02:
> >>> On 5/5/2025 15:56, Alexander Pyhalov wrote:
> >>>> Andrei Lepikhov писал(а) 2025-05-05 14:38:
> >>>> Also logic a bit differs if path is NULL. In
> >>>> get_cheapest_path_for_pathkeys_ext() we explicitly check for path
> >>>> being NULL, in get_cheapest_fractional_path_for_pathkeys_ext() only
> >>>> after calculating sort cost.
> >>>>
> >>>> I've tried to fix comments a bit and unified functions definitions.
> >>> Generally seems ok, I'm not a native speaker to judge the comments.
> >>> But:
> >>> if (base_path && path != base_path)
> >>>
> >>> What is the case in your mind where the base_path pointer still may
> >>> be null at that point?
> >>
> >> Hi.
> >>
> >> It seems if some childrel doesn't have valid pathlist, subpaths_valid
> >> would be false in add_paths_to_append_rel()
> >> and generate_orderedappend_paths() will not  be called. So when we
> >> iterate over live_childrels,
> >> all of them will have cheapest_total path. This is why we can assert
> >> that base_path is not NULL.
> > I'm not sure I understand you correctly. Under which conditions will
> > rel->cheapest_total_path be set to NULL for a childrel? Could you
> > provide an example?
>
> Sorry, perhaps I was not clear enough. I've stated the opposite - it
> seems we can be sure that it's not NULL.

Thank you for your work on this subject!

I have the following question.  I see patch changes some existing
plans from Sort(Append(...)) to MergeAppend(Sort(), ..., Sort(...)) or
even Materialize(MergeAppend(Sort(), ..., Sort(...))).  This should be
some problem in cost_sort().  Otherwise, that would mean that Sort
node doesn't know how to do its job: explicit splitting dataset into
pieces then merging sorting result appears to be cheaper, but Sort
node contains merge-sort algorithm inside and it's supposed to be more
efficient.  Could you, please, revise the patch to avoid these
unwanted changes?

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-06-03T13:23:47Z

On 2/6/2025 20:21, Alexander Korotkov wrote:
> I have the following question.  I see patch changes some existing
> plans from Sort(Append(...)) to MergeAppend(Sort(), ..., Sort(...)) or
> even Materialize(MergeAppend(Sort(), ..., Sort(...))).  This should be
> some problem in cost_sort().  Otherwise, that would mean that Sort
> node doesn't know how to do its job: explicit splitting dataset into
> pieces then merging sorting result appears to be cheaper, but Sort
> node contains merge-sort algorithm inside and it's supposed to be more
> efficient.  Could you, please, revise the patch to avoid these
> unwanted changes?
I think, this issue is related to corner-cases of the 
compare_path_costs_fuzzily.

Let's glance into one of the problematic queries:
EXPLAIN (COSTS ON)
SELECT c collate "C", count(c) FROM pagg_tab3 GROUP BY c collate "C" 
ORDER BY 1;

if you play with the plan, you can find that total_cost of the 
Sort->Append path is cheaper:

Sort  (cost=2.40..2.41 rows=4 width=40)
->  Append  (cost=1.15..2.36 rows=4 width=40)
Merge Append  (cost=2.37..2.42 rows=4 width=40)

But the difference is less than fuzz_factor. In this case, Postgres 
probes startup_cost, which is obviously less for the MergeAppend strategy.
This is a good decision, and I think it should stay as is.
What can we do here? We might change the test to increase the cost gap. 
However, while designing this patch, I skimmed through each broken query 
and didn't find a reason to specifically shift to the Sort->Append 
strategy, as it tested things that were not dependent on Append or Sort.

To establish a stable foundation for discussion, I conducted simple 
tests - see, for example, a couple of queries in the attachment. As I 
see it, Sort->Append works faster: in my test bench, it takes 1250ms on 
average versus 1430ms, and it also has lower costs - the same for data 
with and without massive numbers of duplicates. Playing with sizes of 
inputs, I see the same behaviour.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-06-03T13:38:47Z

On Tue, Jun 3, 2025 at 4:23 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> On 2/6/2025 20:21, Alexander Korotkov wrote:
> > I have the following question.  I see patch changes some existing
> > plans from Sort(Append(...)) to MergeAppend(Sort(), ..., Sort(...)) or
> > even Materialize(MergeAppend(Sort(), ..., Sort(...))).  This should be
> > some problem in cost_sort().  Otherwise, that would mean that Sort
> > node doesn't know how to do its job: explicit splitting dataset into
> > pieces then merging sorting result appears to be cheaper, but Sort
> > node contains merge-sort algorithm inside and it's supposed to be more
> > efficient.  Could you, please, revise the patch to avoid these
> > unwanted changes?
> I think, this issue is related to corner-cases of the
> compare_path_costs_fuzzily.
>
> Let's glance into one of the problematic queries:
> EXPLAIN (COSTS ON)
> SELECT c collate "C", count(c) FROM pagg_tab3 GROUP BY c collate "C"
> ORDER BY 1;
>
> if you play with the plan, you can find that total_cost of the
> Sort->Append path is cheaper:
>
> Sort  (cost=2.40..2.41 rows=4 width=40)
> ->  Append  (cost=1.15..2.36 rows=4 width=40)
> Merge Append  (cost=2.37..2.42 rows=4 width=40)
>
> But the difference is less than fuzz_factor. In this case, Postgres
> probes startup_cost, which is obviously less for the MergeAppend strategy.
> This is a good decision, and I think it should stay as is.
> What can we do here? We might change the test to increase the cost gap.
> However, while designing this patch, I skimmed through each broken query
> and didn't find a reason to specifically shift to the Sort->Append
> strategy, as it tested things that were not dependent on Append or Sort.
>
> To establish a stable foundation for discussion, I conducted simple
> tests - see, for example, a couple of queries in the attachment. As I
> see it, Sort->Append works faster: in my test bench, it takes 1250ms on
> average versus 1430ms, and it also has lower costs - the same for data
> with and without massive numbers of duplicates. Playing with sizes of
> inputs, I see the same behaviour.

I run your tests.  For Sort(Append()) case I've got actual
time=811.047..842.473.  For MergeAppend case I've got actual time
actual time=723.678..967.004.  That looks interesting.  At some point
we probably should teach our Sort node to start returning tuple before
finishing the last merge stage.

However, I think costs are not adequate to the timing.  Our cost model
predicts that startup cost of MergeAppend is less than startup cost of
Sort(Append()).  And that's correct.  However, in fast total time of
MergeAppend is bigger than total time of Sort(Append()).  The
differences in these two cases are comparable.  I think we need to
just our cost_sort() to reflect that.

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-06-03T13:53:50Z

On 3/6/2025 15:38, Alexander Korotkov wrote:
> On Tue, Jun 3, 2025 at 4:23 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> To establish a stable foundation for discussion, I conducted simple
>> tests - see, for example, a couple of queries in the attachment. As I
>> see it, Sort->Append works faster: in my test bench, it takes 1250ms on
>> average versus 1430ms, and it also has lower costs - the same for data
>> with and without massive numbers of duplicates. Playing with sizes of
>> inputs, I see the same behaviour.
> 
> I run your tests.  For Sort(Append()) case I've got actual
> time=811.047..842.473.  For MergeAppend case I've got actual time
> actual time=723.678..967.004.  That looks interesting.  At some point
> we probably should teach our Sort node to start returning tuple before
> finishing the last merge stage.
> 
> However, I think costs are not adequate to the timing.  Our cost model
> predicts that startup cost of MergeAppend is less than startup cost of
> Sort(Append()).  And that's correct.  However, in fast total time of
> MergeAppend is bigger than total time of Sort(Append()).  The
> differences in these two cases are comparable.  I think we need to
> just our cost_sort() to reflect that.
May you explain your idea? As I see (and have shown in the previous 
message), the total cost of the Sort->Append is fewer than 
MergeAppend->Sort.
Additionally, as I mentioned earlier, the primary reason for choosing 
MergeAppend in the regression test was a slight total cost difference 
that triggered the startup cost comparison.
May you show the query and its explain, that is a subject of concern for 
you?

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-06-03T14:05:13Z

On Tue, Jun 3, 2025 at 4:53 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> On 3/6/2025 15:38, Alexander Korotkov wrote:
> > On Tue, Jun 3, 2025 at 4:23 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> >> To establish a stable foundation for discussion, I conducted simple
> >> tests - see, for example, a couple of queries in the attachment. As I
> >> see it, Sort->Append works faster: in my test bench, it takes 1250ms on
> >> average versus 1430ms, and it also has lower costs - the same for data
> >> with and without massive numbers of duplicates. Playing with sizes of
> >> inputs, I see the same behaviour.
> >
> > I run your tests.  For Sort(Append()) case I've got actual
> > time=811.047..842.473.  For MergeAppend case I've got actual time
> > actual time=723.678..967.004.  That looks interesting.  At some point
> > we probably should teach our Sort node to start returning tuple before
> > finishing the last merge stage.
> >
> > However, I think costs are not adequate to the timing.  Our cost model
> > predicts that startup cost of MergeAppend is less than startup cost of
> > Sort(Append()).  And that's correct.  However, in fast total time of
> > MergeAppend is bigger than total time of Sort(Append()).  The
> > differences in these two cases are comparable.  I think we need to
> > just our cost_sort() to reflect that.
> May you explain your idea? As I see (and have shown in the previous
> message), the total cost of the Sort->Append is fewer than
> MergeAppend->Sort.
> Additionally, as I mentioned earlier, the primary reason for choosing
> MergeAppend in the regression test was a slight total cost difference
> that triggered the startup cost comparison.
> May you show the query and its explain, that is a subject of concern for
> you?

My point is that difference in total cost is very small.  For small
datasets it could be even within the fuzzy limit.  However, in
practice difference in total time is as big as difference in startup
time.  So, it would be good to make the total cost difference bigger.

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-06-03T14:35:57Z

On 3/6/2025 16:05, Alexander Korotkov wrote:
> On Tue, Jun 3, 2025 at 4:53 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> Additionally, as I mentioned earlier, the primary reason for choosing
>> MergeAppend in the regression test was a slight total cost difference
>> that triggered the startup cost comparison.
>> May you show the query and its explain, that is a subject of concern for
>> you?
> 
> My point is that difference in total cost is very small.  For small
> datasets it could be even within the fuzzy limit.  However, in
> practice difference in total time is as big as difference in startup
> time.  So, it would be good to make the total cost difference bigger.
For me, it seems like a continuation of the 7d8ac98 discussion. We may 
charge a small fee for MergeAppend to adjust the balance, of course.
However, I think this small change requires a series of benchmarks to 
determine how it affects the overall cost balance. Without examples it 
is hard to say how important this issue is and its worthiness to 
commence such work.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-06-03T22:41:50Z

On Tue, Jun 3, 2025 at 5:35 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> On 3/6/2025 16:05, Alexander Korotkov wrote:
> > On Tue, Jun 3, 2025 at 4:53 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> >> Additionally, as I mentioned earlier, the primary reason for choosing
> >> MergeAppend in the regression test was a slight total cost difference
> >> that triggered the startup cost comparison.
> >> May you show the query and its explain, that is a subject of concern for
> >> you?
> >
> > My point is that difference in total cost is very small.  For small
> > datasets it could be even within the fuzzy limit.  However, in
> > practice difference in total time is as big as difference in startup
> > time.  So, it would be good to make the total cost difference bigger.
> For me, it seems like a continuation of the 7d8ac98 discussion. We may
> charge a small fee for MergeAppend to adjust the balance, of course.
> However, I think this small change requires a series of benchmarks to
> determine how it affects the overall cost balance. Without examples it
> is hard to say how important this issue is and its worthiness to
> commence such work.

Yes, I think it's fair to charge the MergeAppend node.  We currently
cost it similarly to Sort merge stage, but it's clearly more
expensive.  It dealing on the executor level dealing with Slot's etc,
while Sort node have a set of lower level optimizations.

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-06-04T12:52:04Z

On 4/6/2025 00:41, Alexander Korotkov wrote:
> On Tue, Jun 3, 2025 at 5:35 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> On 3/6/2025 16:05, Alexander Korotkov wrote:
>>> On Tue, Jun 3, 2025 at 4:53 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>>>> Additionally, as I mentioned earlier, the primary reason for choosing
>>>> MergeAppend in the regression test was a slight total cost difference
>>>> that triggered the startup cost comparison.
>>>> May you show the query and its explain, that is a subject of concern for
>>>> you?
>>>
>>> My point is that difference in total cost is very small.  For small
>>> datasets it could be even within the fuzzy limit.  However, in
>>> practice difference in total time is as big as difference in startup
>>> time.  So, it would be good to make the total cost difference bigger.
>> For me, it seems like a continuation of the 7d8ac98 discussion. We may
>> charge a small fee for MergeAppend to adjust the balance, of course.
>> However, I think this small change requires a series of benchmarks to
>> determine how it affects the overall cost balance. Without examples it
>> is hard to say how important this issue is and its worthiness to
>> commence such work.
> 
> Yes, I think it's fair to charge the MergeAppend node.  We currently
> cost it similarly to Sort merge stage, but it's clearly more
> expensive.  It dealing on the executor level dealing with Slot's etc,
> while Sort node have a set of lower level optimizations.
As I see it, it makes sense to charge MergeAppend for the heap operation 
or, what is more logical, reduce the charge on Sort due to internal 
optimisations.
Playing with both approaches, I found that it breaks many more tests 
than the current patch does. Hence, it needs additional work on the 
results analysis to realise how correct these changes are.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-07-22T11:13:44Z

On 4/6/2025 00:41, Alexander Korotkov wrote:
> On Tue, Jun 3, 2025 at 5:35 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> For me, it seems like a continuation of the 7d8ac98 discussion. We may
>> charge a small fee for MergeAppend to adjust the balance, of course.
>> However, I think this small change requires a series of benchmarks to
>> determine how it affects the overall cost balance. Without examples it
>> is hard to say how important this issue is and its worthiness to
>> commence such work.
> 
> Yes, I think it's fair to charge the MergeAppend node.  We currently
> cost it similarly to Sort merge stage, but it's clearly more
> expensive.  It dealing on the executor level dealing with Slot's etc,
> while Sort node have a set of lower level optimizations.
After conducting additional research, I concluded that you are correct, 
and the current cost model doesn't allow the optimiser to detect the 
best option. A simple test with a full scan and sort of a partitioned 
table (see attachment) shows that the query plan prefers small sortings 
merged by the MergeAppend node. I have got the following results for 
different numbers of tuples to be sorted (in the range from 10 tuples to 
1E8):

EXPLAIN SELECT * FROM test ORDER BY y;

1E1: Sort  (cost=9.53..9.57 rows=17 width=8)
1E2: Sort  (cost=20.82..21.07 rows=100)
1E3: Merge Append  (cost=56.19..83.69 rows=1000)
1E4: Merge Append  (cost=612.74..887.74 rows=10000)
1E5: Merge Append  (cost=7754.19..10504.19 rows=100000)
1E6: Merge Append  (cost=94092.25..121592.25 rows=1000000)
1E7: Merge Append  (cost=1106931.22..1381931.22 rows=10000000)
1E8: Merge Append  (cost=14097413.40..16847413.40 rows=100000000)

That happens because both total costs lie within the fuzzy factor gap, 
and the optimiser chooses the path based on the startup cost, which is 
obviously better for the MergeAppend case.

At the same time, execution, involving a single Sort node, dominates the 
MergeAppend case:

1E3: MergeAppend: 1.927 ms, Sort: 0.720 ms
1E4: MergeAppend: 10.090 ms, Sort: 7.583 ms
1E5: MergeAppend: 118.885 ms, Sort: 88.492 ms
1E6: MergeAppend: 1372.717 ms, Sort: 1106.184 ms
1E7: MergeAppend: 15103.893 ms, Sort: 13415.806 ms
1E8: MergeAppend: 176553.133 ms, Sort: 149458.787 ms

Looking inside the code, I found the only difference we can employ to 
rationalise the cost model change: re-structuring of a heap. The 
siftDown routine employs two tuple comparisons to find the proper 
position for a tuple. So, we have objections to changing the constant in 
the cost model of the merge operation:

@@ -2448,7 +2448,7 @@ cost_merge_append(Path *path, PlannerInfo *root,
         logN = LOG2(N);

         /* Assumed cost per tuple comparison */
-       comparison_cost = 2.0 * cpu_operator_cost;
+       comparison_cost = 4.0 * cpu_operator_cost;

         /* Heap creation cost */
         startup_cost += comparison_cost * N * logN;

The exact change also needs to be made in the cost_gather_merge 
function, of course.
At this moment, I'm not sure that it should be multiplied by 2 - it is a 
subject for further discussion. However, it fixes the current issue and 
adds a little additional cost to the merge operation, which, as I see 
it, is quite limited.
Please see the new version of the patch attached.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-07-26T22:51:13Z

On Tue, Jul 22, 2025 at 2:13 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>
> On 4/6/2025 00:41, Alexander Korotkov wrote:
> > On Tue, Jun 3, 2025 at 5:35 PM Andrei Lepikhov <lepihov@gmail.com>
wrote:
> >> For me, it seems like a continuation of the 7d8ac98 discussion. We may
> >> charge a small fee for MergeAppend to adjust the balance, of course.
> >> However, I think this small change requires a series of benchmarks to
> >> determine how it affects the overall cost balance. Without examples it
> >> is hard to say how important this issue is and its worthiness to
> >> commence such work.
> >
> > Yes, I think it's fair to charge the MergeAppend node.  We currently
> > cost it similarly to Sort merge stage, but it's clearly more
> > expensive.  It dealing on the executor level dealing with Slot's etc,
> > while Sort node have a set of lower level optimizations.
> After conducting additional research, I concluded that you are correct,
> and the current cost model doesn't allow the optimiser to detect the
> best option. A simple test with a full scan and sort of a partitioned
> table (see attachment) shows that the query plan prefers small sortings
> merged by the MergeAppend node. I have got the following results for
> different numbers of tuples to be sorted (in the range from 10 tuples to
> 1E8):
>
> EXPLAIN SELECT * FROM test ORDER BY y;
>
> 1E1: Sort  (cost=9.53..9.57 rows=17 width=8)
> 1E2: Sort  (cost=20.82..21.07 rows=100)
> 1E3: Merge Append  (cost=56.19..83.69 rows=1000)
> 1E4: Merge Append  (cost=612.74..887.74 rows=10000)
> 1E5: Merge Append  (cost=7754.19..10504.19 rows=100000)
> 1E6: Merge Append  (cost=94092.25..121592.25 rows=1000000)
> 1E7: Merge Append  (cost=1106931.22..1381931.22 rows=10000000)
> 1E8: Merge Append  (cost=14097413.40..16847413.40 rows=100000000)
>
> That happens because both total costs lie within the fuzzy factor gap,
> and the optimiser chooses the path based on the startup cost, which is
> obviously better for the MergeAppend case.
>
> At the same time, execution, involving a single Sort node, dominates the
> MergeAppend case:
>
> 1E3: MergeAppend: 1.927 ms, Sort: 0.720 ms
> 1E4: MergeAppend: 10.090 ms, Sort: 7.583 ms
> 1E5: MergeAppend: 118.885 ms, Sort: 88.492 ms
> 1E6: MergeAppend: 1372.717 ms, Sort: 1106.184 ms
> 1E7: MergeAppend: 15103.893 ms, Sort: 13415.806 ms
> 1E8: MergeAppend: 176553.133 ms, Sort: 149458.787 ms
>
> Looking inside the code, I found the only difference we can employ to
> rationalise the cost model change: re-structuring of a heap. The
> siftDown routine employs two tuple comparisons to find the proper
> position for a tuple. So, we have objections to changing the constant in
> the cost model of the merge operation:
>
> @@ -2448,7 +2448,7 @@ cost_merge_append(Path *path, PlannerInfo *root,
>          logN = LOG2(N);
>
>          /* Assumed cost per tuple comparison */
> -       comparison_cost = 2.0 * cpu_operator_cost;
> +       comparison_cost = 4.0 * cpu_operator_cost;
>
>          /* Heap creation cost */
>          startup_cost += comparison_cost * N * logN;
>
> The exact change also needs to be made in the cost_gather_merge
> function, of course.
> At this moment, I'm not sure that it should be multiplied by 2 - it is a
> subject for further discussion. However, it fixes the current issue and
> adds a little additional cost to the merge operation, which, as I see
> it, is quite limited.
> Please see the new version of the patch attached.

I've checked the cost adjustment you've made.  If you change the cost of
top-N sort, you must also change the prior if condition on when it gets
selected.  We currently do the switch on tuples =  2 * limit_tuples.  If we
apply the proposed change, we should switch on tuples = limit_tuples^2 ^
2.  But also, in order for this cost to reflect reality, we must change
tuplesort_puttuple_common() in the same way.  These inconsistencies lead to
failures on contrib/postgres_fdw checks.  But these changes don't appear to
be a win.  See the example below.  Top-N sort appears to be a win for
LIMITS up to 500000.

# EXPLAIN ANALYZE SELECT * FROM (SELECT random() r FROM generate_series(1,
1000000) i) x ORDER BY x.r LIMIT 10000;
                                                                    QUERY
PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=112157.85..112182.85 rows=10000 width=8) (actual
time=638.998..639.841 rows=10000.00 loops=1)
   ->  Sort  (cost=112157.85..114657.85 rows=1000000 width=8) (actual
time=638.996..639.340 rows=10000.00 loops=1)
         Sort Key: (random())
         Sort Method: quicksort  Memory: 24577kB
         ->  Function Scan on generate_series i  (cost=0.00..12500.00
rows=1000000 width=8) (actual time=126.582..205.610 rows=1000000.00 loops=1)
 Planning Time: 0.118 ms
 Execution Time: 653.283 ms
(7 rows)

# EXPLAIN ANALYZE SELECT * FROM (SELECT random() r FROM generate_series(1,
1000000) i) x ORDER BY x.r LIMIT 500000;
                                                                    QUERY
PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=112157.85..113407.85 rows=500000 width=8) (actual
time=646.522..688.573 rows=500000.00 loops=1)
   ->  Sort  (cost=112157.85..114657.85 rows=1000000 width=8) (actual
time=646.520..663.562 rows=500000.00 loops=1)
         Sort Key: (random())
         Sort Method: quicksort  Memory: 24577kB
         ->  Function Scan on generate_series i  (cost=0.00..12500.00
rows=1000000 width=8) (actual time=129.028..208.936 rows=1000000.00 loops=1)
 Planning Time: 0.188 ms
 Execution Time: 713.738 ms
(7 rows)

# EXPLAIN ANALYZE SELECT * FROM (SELECT random() r FROM generate_series(1,
1000000) i) x ORDER BY x.r LIMIT 10000;
                                                                    QUERY
PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=78938.56..78963.56 rows=10000 width=8) (actual
time=412.633..413.459 rows=10000.00 loops=1)
   Buffers: shared hit=3, temp read=1709 written=1709
   ->  Sort  (cost=78938.56..81438.56 rows=1000000 width=8) (actual
time=412.631..412.969 rows=10000.00 loops=1)
         Sort Key: (random())
         Sort Method: top-N heapsort  Memory: 769kB
         Buffers: shared hit=3, temp read=1709 written=1709
         ->  Function Scan on generate_series i  (cost=0.00..12500.00
rows=1000000 width=8) (actual time=185.892..333.233 rows=1000000.00 loops=1)
               Buffers: temp read=1709 written=1709
 Planning:
   Buffers: shared hit=7 read=8
 Planning Time: 2.058 ms
 Execution Time: 416.040 ms
(12 rows)

# EXPLAIN ANALYZE SELECT * FROM (SELECT random() r FROM generate_series(1,
1000000) i) x ORDER BY x.r LIMIT 500000;
                                                                    QUERY
PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=112157.85..113407.85 rows=500000 width=8) (actual
time=631.185..673.768 rows=500000.00 loops=1)
   ->  Sort  (cost=112157.85..114657.85 rows=1000000 width=8) (actual
time=631.183..649.072 rows=500000.00 loops=1)
         Sort Key: (random())
         Sort Method: quicksort  Memory: 24577kB
         ->  Function Scan on generate_series i  (cost=0.00..12500.00
rows=1000000 width=8) (actual time=121.274..200.453 rows=1000000.00 loops=1)
 Planning Time: 0.243 ms
 Execution Time: 698.841 ms
(7 rows)

I've another idea.  cost_tuplesort() puts 2.0 under logarithm to prefer
tuplesort over heapsort.  I think we can adjust cost_gather_merge() and
cost_merge_append() to do the same.  0001 patch implements that.  I think
the plan changes of 0001 might be reasonable since most cases deal with
small rowsets.  One thing concerns me: 0002 still affects one of the
postgres_fdw checks.  Could you, please, take a look?

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-07-31T14:20:04Z

On 27/7/2025 00:51, Alexander Korotkov wrote:
> On Tue, Jul 22, 2025 at 2:13 PM Andrei Lepikhov <lepihov@gmail.com 
> I've another idea.  cost_tuplesort() puts 2.0 under logarithm to prefer 
> tuplesort over heapsort.  I think we can adjust cost_gather_merge() and 
> cost_merge_append() to do the same.  0001 patch implements that.  I 
> think the plan changes of 0001 might be reasonable since most cases deal 
> with small rowsets.  One thing concerns me: 0002 still affects one of 
> the postgres_fdw checks.  Could you, please, take a look?
Thanks for the idea!
I analysed your approach a little bit.
Initially, I ran the test script I had created previously [1] and 
discovered that on a large scale (1e6 - 1e7 tuples), the plan still 
defaults to MergeAppend, which deviates from the execution time (7190 ms 
for Sort+Append and 8450 ms for MergeAppend+Sort).

Attempting to find out the reason, I combined all the costs into a 
single formula for each strategy:

MergeAppend+Sort:
total_cost =CO*ntuples*(1+2*log(ntuples)) + Ccput * 0.5 * ntuples+ 
2*CO*N*log(N) + A
Sort+Append:
total_cost = CO*ntuples*(1+2*log(ntuples))+ Ccput * 0.5 * ntuples + A

Terms:
- A - sum of total costs of underlying subtrees
- CO - cpu_operator_cost
- Ccput - cpu_tuple_cost
- N - number of subpaths (streams)

Given the significant gap in total execution time between these 
strategies, I believe it would be reasonable to introduce a coefficient 
to the equation's 'ntuples' variable component that will keep the gap 
between big quicksort and MergeAppend's heapsort out of the fuzzy factor 
gap.

Discovering papers on the value of constant in quicksort [2] and 
heapsort [3], I realised that there is a difference. The constant's 
value varies in a wide range: 1.3-1.5 for quicksort and 2-3 for 
heapsort. Considering that we should change the current cost model as 
little as possible, not to break the balance, we may just increase the 
constant value for the heap sort to maintain a bare minimum gap between 
strategies out of the fuzzy factor. In this case, the merge append 
constant should be around 3.8 - 4.0.

With this minor change, we see a shift in the regression tests. Most of 
these changes were introduced by the new append strategy. Although I 
haven't analysed these changes in depth yet, I believe they are all 
related to the small data sets and should fade out on a larger scale.

See this minor correction in the attachment. postgres_fdw tests are 
stable now.

[1] 
https://github.com/danolivo/conf/blob/main/Scripts/sort-vs-mergeappend-3.sql
[2] https://en.wikipedia.org/wiki/Quicksort?utm_source=chatgpt.com
[2] https://arxiv.org/abs/1504.01459

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-09-01T20:26:03Z

On Thu, Jul 31, 2025 at 5:20 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> On 27/7/2025 00:51, Alexander Korotkov wrote:
> > On Tue, Jul 22, 2025 at 2:13 PM Andrei Lepikhov <lepihov@gmail.com
> > I've another idea.  cost_tuplesort() puts 2.0 under logarithm to prefer
> > tuplesort over heapsort.  I think we can adjust cost_gather_merge() and
> > cost_merge_append() to do the same.  0001 patch implements that.  I
> > think the plan changes of 0001 might be reasonable since most cases deal
> > with small rowsets.  One thing concerns me: 0002 still affects one of
> > the postgres_fdw checks.  Could you, please, take a look?
> Thanks for the idea!
> I analysed your approach a little bit.
> Initially, I ran the test script I had created previously [1] and
> discovered that on a large scale (1e6 - 1e7 tuples), the plan still
> defaults to MergeAppend, which deviates from the execution time (7190 ms
> for Sort+Append and 8450 ms for MergeAppend+Sort).
>
> Attempting to find out the reason, I combined all the costs into a
> single formula for each strategy:
>
> MergeAppend+Sort:
> total_cost =CO*ntuples*(1+2*log(ntuples)) + Ccput * 0.5 * ntuples+
> 2*CO*N*log(N) + A
> Sort+Append:
> total_cost = CO*ntuples*(1+2*log(ntuples))+ Ccput * 0.5 * ntuples + A
>
> Terms:
> - A - sum of total costs of underlying subtrees
> - CO - cpu_operator_cost
> - Ccput - cpu_tuple_cost
> - N - number of subpaths (streams)
>
> Given the significant gap in total execution time between these
> strategies, I believe it would be reasonable to introduce a coefficient
> to the equation's 'ntuples' variable component that will keep the gap
> between big quicksort and MergeAppend's heapsort out of the fuzzy factor
> gap.
>
> Discovering papers on the value of constant in quicksort [2] and
> heapsort [3], I realised that there is a difference. The constant's
> value varies in a wide range: 1.3-1.5 for quicksort and 2-3 for
> heapsort. Considering that we should change the current cost model as
> little as possible, not to break the balance, we may just increase the
> constant value for the heap sort to maintain a bare minimum gap between
> strategies out of the fuzzy factor. In this case, the merge append
> constant should be around 3.8 - 4.0.
>
> With this minor change, we see a shift in the regression tests. Most of
> these changes were introduced by the new append strategy. Although I
> haven't analysed these changes in depth yet, I believe they are all
> related to the small data sets and should fade out on a larger scale.
>
> See this minor correction in the attachment. postgres_fdw tests are
> stable now.

I have another idea.  What if we allow MergeAppend paths only when at
least one subpath is preordered.  This trick also allow us to exclude
MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
changes now have much less volume and looks more reasonable.  What do
you think?

Also, do you think get_cheapest_fractional_path_for_pathkeys_ext() and
get_cheapest_path_for_pathkeys_ext() should consider incremental sort?
 The revised patch teaches them to do so.

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Richard Guo <guofenglinux@gmail.com> — 2025-09-02T01:27:56Z

On Tue, Sep 2, 2025 at 5:26 AM Alexander Korotkov <aekorotkov@gmail.com> wrote:
> I have another idea.  What if we allow MergeAppend paths only when at
> least one subpath is preordered.  This trick also allow us to exclude
> MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
> changes now have much less volume and looks more reasonable.  What do
> you think?

I skimmed through the test case changes, and I'm not sure all of them
are actual improvements.  For example:

          ->  Append
-               ->  Foreign Scan on ftprt1_p1 t1_1
+               ->  Sort
+                     Sort Key: t1_1.a
+                     ->  Foreign Scan on ftprt1_p1 t1_1
                ->  Foreign Scan on ftprt1_p2 t1_2

It seems that this patch moves the sort operation for ftprt1_p1 from
the remote server to local.  I'm not sure if this is an improvement,
or why it applies only to ftprt1_p1 and not to ftprt1_p2 (they have
very similar statistics).

Besides, I noticed that some plans have changed from an "Index Scan
with Index Cond" to a "Seq Scan with Filter + Sort".  I'm also not
sure whether this change results in better performance.

- Richard

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-09-04T09:52:24Z

On 2/9/2025 03:27, Richard Guo wrote:
> On Tue, Sep 2, 2025 at 5:26 AM Alexander Korotkov <aekorotkov@gmail.com> wrote:
>> I have another idea.  What if we allow MergeAppend paths only when at
>> least one subpath is preordered.  This trick also allow us to exclude
>> MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
>> changes now have much less volume and looks more reasonable.  What do
>> you think?
> 
> I skimmed through the test case changes, and I'm not sure all of them
> are actual improvements.  For example:
> 
>            ->  Append
> -               ->  Foreign Scan on ftprt1_p1 t1_1
> +               ->  Sort
> +                     Sort Key: t1_1.a
> +                     ->  Foreign Scan on ftprt1_p1 t1_1
>                  ->  Foreign Scan on ftprt1_p2 t1_2
> 
> It seems that this patch moves the sort operation for ftprt1_p1 from
> the remote server to local.  I'm not sure if this is an improvement,
> or why it applies only to ftprt1_p1 and not to ftprt1_p2 (they have
> very similar statistics).
I had a look into this case. The next stuff happens.
Initially, within generate_orderedappend_paths, the planner creates an 
Append according to the 'match_partition_order' strategy, which 
dominates the others.
Next, pathlists of 'Foreign Scan on ftprt1_p1' and 'Foreign Scan on 
ftprt1_p2' are different: the first one contains two paths:
1. startup_cost: 100.000, total_cost: 103.090, pathkeys: false
2. startup_cost: 102.880, total_cost: 103.110, pathkeys: true

And the second subpath has only one option to scan:
startup_cost: 100.000, total_cost: 103.660, pathkeys: true

Before, the optimiser always chose the path with pathkeys. However, this 
patch attempts to do its best by comparing ForeignScan+Sort and ForeignScan.
Comparing the total path with the explicit Sort and pre-sorted one, we have:
- ForeignScan+Sort: startup_cost: 103.100, total_cost: 103.105
- Presorted: startup_cost: 102.880, total_cost: 103.110
And here is the issue: a difference in the third sign after decimal 
point. Let's check remote estimations with and without Sort:

With:
LockRows (cost=2.88..2.90 rows=1 width=25)
-> Sort (cost=2.88..2.89 rows=1 width=25)
Sort Key: t1.a
-> Seq Scan on public.fprt1_p1 t1 (cost=0.00..2.88 ...

Without:
LockRows (cost=0.00..2.88 rows=1 width=25)
-> Seq Scan on public.fprt1_p1 t1 (cost=0.00..2.88 ...

As you can see, according to these estimations, LockRows costs nothing 
without sorting and 0.1 with Sort. So, fluctuation was added by 
EXPLAIN's rounding.

What to do? At first, we can do nothing and just correct the output. But 
I don't like unstable tests. We can adjust the query slightly to 
increase the estimations or improve the estimation using extended 
statistics. I prefer the more elegant variant with extended statistics.
See the attachment for a sketch on how to stabilise the output. With 
this patch applied before this feature, the test output stays the same.

> 
> Besides, I noticed that some plans have changed from an "Index Scan
> with Index Cond" to a "Seq Scan with Filter + Sort".  I'm also not
> sure whether this change results in better performance.
As you know, according to the cost model, SeqScan looks better on scans 
of tiny tables and full scans. I didn't delve as deeply into these cases 
yet as I did in the previous one, but it's clear that we're still seeing 
the issue with tiny tables.

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-09-05T08:45:41Z

On 1/9/2025 22:26, Alexander Korotkov wrote:
> On Thu, Jul 31, 2025 at 5:20 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> See this minor correction in the attachment. postgres_fdw tests are
>> stable now.
> 
> I have another idea.  What if we allow MergeAppend paths only when at
> least one subpath is preordered.  This trick also allow us to exclude
> MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
> changes now have much less volume and looks more reasonable.  What do
> you think?
I believe a slight mistake has been made with the total_has_ordered / 
startup_has_ordered parameters, which has caused unnecessary test 
changes in inherit.out (See updated patch in the attachment). Although 
not the best test in general (it depends on the autovacuum), it 
highlighted the case where a startup-optimal strategy is necessary, even 
when a fractional-optimal path is available, which may lead to continue 
of the discussion [1].>
> Also, do you think get_cheapest_fractional_path_for_pathkeys_ext() and
> get_cheapest_path_for_pathkeys_ext() should consider incremental sort?
>   The revised patch teaches them to do so.
Following 55a780e9476 [2] it should be considered, of course.

[1] 
https://www.postgresql.org/message-id/CAPpHfduicoMCJ0b0mMvMQ5KVqLimJ7pKdxajciSF%2BP7JF31v%2BA%40mail.gmail.com
[2] 
https://www.postgresql.org/message-id/CAMbWs49wSNPPD%3DFOQqzjPNZ_N9EGDv%3D7-ou0dFgd0HSwP3fTAg%40mail.gmail.com?utm_source=chatgpt.com

-- 
regards, Andrei Lepikhov

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-09-07T11:26:17Z

On Fri, Sep 5, 2025 at 11:45 AM Andrei Lepikhov <lepihov@gmail.com> wrote:
>
> On 1/9/2025 22:26, Alexander Korotkov wrote:
> > On Thu, Jul 31, 2025 at 5:20 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> >> See this minor correction in the attachment. postgres_fdw tests are
> >> stable now.
> >
> > I have another idea.  What if we allow MergeAppend paths only when at
> > least one subpath is preordered.  This trick also allow us to exclude
> > MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
> > changes now have much less volume and looks more reasonable.  What do
> > you think?
> I believe a slight mistake has been made with the total_has_ordered /
> startup_has_ordered parameters, which has caused unnecessary test
> changes in inherit.out (See updated patch in the attachment). Although
> not the best test in general (it depends on the autovacuum), it
> highlighted the case where a startup-optimal strategy is necessary, even
> when a fractional-optimal path is available, which may lead to continue
> of the discussion [1].>
> > Also, do you think get_cheapest_fractional_path_for_pathkeys_ext() and
> > get_cheapest_path_for_pathkeys_ext() should consider incremental sort?
> >   The revised patch teaches them to do so.
> Following 55a780e9476 [2] it should be considered, of course.

Great, thank you for catching this.  The diff of costs is attached.  I
see the costs now are better or within the fuzz factor.

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Richard Guo <guofenglinux@gmail.com> — 2025-09-08T08:39:40Z

On Sun, Sep 7, 2025 at 8:26 PM Alexander Korotkov <aekorotkov@gmail.com> wrote:
> Great, thank you for catching this.  The diff of costs is attached.  I
> see the costs now are better or within the fuzz factor.

Will have a review by the end of this commitfest.

- Richard

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-09-08T08:49:10Z

On Mon, Sep 8, 2025 at 11:39 AM Richard Guo <guofenglinux@gmail.com> wrote:
> On Sun, Sep 7, 2025 at 8:26 PM Alexander Korotkov <aekorotkov@gmail.com> wrote:
> > Great, thank you for catching this.  The diff of costs is attached.  I
> > see the costs now are better or within the fuzz factor.
>
> Will have a review by the end of this commitfest.

Great, thank you, Richard!

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-10-02T14:49:26Z

On Mon, Sep 8, 2025 at 11:39 AM Richard Guo <guofenglinux@gmail.com> wrote:
>
> On Sun, Sep 7, 2025 at 8:26 PM Alexander Korotkov <aekorotkov@gmail.com> wrote:
> > Great, thank you for catching this.  The diff of costs is attached.  I
> > see the costs now are better or within the fuzz factor.
>
> Will have a review by the end of this commitfest.

Did you manage to take a look at this patch?

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Alena Rybakina <a.rybakina@postgrespro.ru> — 2025-10-02T22:42:38Z

On 07.09.2025 14:26, Alexander Korotkov wrote:
> On Fri, Sep 5, 2025 at 11:45 AM Andrei Lepikhov <lepihov@gmail.com> wrote:
>> On 1/9/2025 22:26, Alexander Korotkov wrote:
>>> On Thu, Jul 31, 2025 at 5:20 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
>>>> See this minor correction in the attachment. postgres_fdw tests are
>>>> stable now.
>>> I have another idea.  What if we allow MergeAppend paths only when at
>>> least one subpath is preordered.  This trick also allow us to exclude
>>> MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
>>> changes now have much less volume and looks more reasonable.  What do
>>> you think?
>> I believe a slight mistake has been made with the total_has_ordered /
>> startup_has_ordered parameters, which has caused unnecessary test
>> changes in inherit.out (See updated patch in the attachment). Although
>> not the best test in general (it depends on the autovacuum), it
>> highlighted the case where a startup-optimal strategy is necessary, even
>> when a fractional-optimal path is available, which may lead to continue
>> of the discussion [1].>
>>> Also, do you think get_cheapest_fractional_path_for_pathkeys_ext() and
>>> get_cheapest_path_for_pathkeys_ext() should consider incremental sort?
>>>    The revised patch teaches them to do so.
>> Following 55a780e9476 [2] it should be considered, of course.
> Great, thank you for catching this.  The diff of costs is attached.  I
> see the costs now are better or within the fuzz factor.
>
Hi! I looked at regression test changes but one of them confused me.

Example where the plan shape changed:

EXPLAIN (COSTS OFF)
SELECT t1.a, t2.b
FROM (SELECT * FROM prt1 WHERE a < 450) t1
LEFT JOIN (SELECT * FROM prt2 WHERE b > 250) t2
   ON t1.a = t2.b
WHERE t1.b = 0
ORDER BY t1.a, t2.b;

-- before
                         QUERY PLAN
-----------------------------------------------------------
  Incremental Sort
    Sort Key: prt1.a, prt2.b
    Presorted Key: prt1.a
    ->  Merge Left Join
          Merge Cond: (prt1.a = prt2.b)
          ->  Sort
                Sort Key: prt1.a
                ->  Append
                      ->  Seq Scan on prt1_p1 prt1_1
                            Filter: ((a < 450) AND (b = 0))
                      ->  Seq Scan on prt1_p2 prt1_2
                            Filter: ((a < 450) AND (b = 0))
          ->  Sort
                Sort Key: prt2.b
                ->  Append
                      ->  Seq Scan on prt2_p2 prt2_1
                            Filter: (b > 250)
                      ->  Seq Scan on prt2_p3 prt2_2
                            Filter: (b > 250)
(19 rows)

-- now
                            QUERY PLAN
-----------------------------------------------------------------
  Sort
    Sort Key: prt1.a, prt2.b
    ->  Merge Right Join
          Merge Cond: (prt2.b = prt1.a)
          ->  Append
                ->  Sort
                      Sort Key: prt2_1.b
                      ->  Seq Scan on prt2_p2 prt2_1
                            Filter: (b > 250)
                ->  Sort
                      Sort Key: prt2_2.b
                      ->  Seq Scan on prt2_p3 prt2_2
                            Filter: (b > 250)
          ->  Materialize
                ->  Append
                      ->  Sort
                            Sort Key: prt1_1.a
                            ->  Seq Scan on prt1_p1 prt1_1
                                  Filter: ((a < 450) AND (b = 0))
                      ->  Sort
                            Sort Key: prt1_2.a
                            ->  Seq Scan on prt1_p2 prt1_2
                                  Filter: ((a < 450) AND (b = 0))
(23 rows)

Previously we had incremental sort on (t1.a, t2.b) with prt1.a already 
presorted; now we sort both t1.a and t2.b after a merge right join. It 
looks inefficiently or I missed something?

Other tests looked fine for me.

Re: MergeAppend could consider sorting cheapest child path

Alexander Korotkov <aekorotkov@gmail.com> — 2025-10-03T06:04:53Z

Hi, Alena!

On Fri, Oct 3, 2025 at 1:42 AM Alena Rybakina <a.rybakina@postgrespro.ru> wrote:
> On 07.09.2025 14:26, Alexander Korotkov wrote:
> > On Fri, Sep 5, 2025 at 11:45 AM Andrei Lepikhov <lepihov@gmail.com> wrote:
> >> On 1/9/2025 22:26, Alexander Korotkov wrote:
> >>> On Thu, Jul 31, 2025 at 5:20 PM Andrei Lepikhov <lepihov@gmail.com> wrote:
> >>>> See this minor correction in the attachment. postgres_fdw tests are
> >>>> stable now.
> >>> I have another idea.  What if we allow MergeAppend paths only when at
> >>> least one subpath is preordered.  This trick also allow us to exclude
> >>> MergeAppend(Sort) dominating Sort(Append).  I see the regression tests
> >>> changes now have much less volume and looks more reasonable.  What do
> >>> you think?
> >> I believe a slight mistake has been made with the total_has_ordered /
> >> startup_has_ordered parameters, which has caused unnecessary test
> >> changes in inherit.out (See updated patch in the attachment). Although
> >> not the best test in general (it depends on the autovacuum), it
> >> highlighted the case where a startup-optimal strategy is necessary, even
> >> when a fractional-optimal path is available, which may lead to continue
> >> of the discussion [1].>
> >>> Also, do you think get_cheapest_fractional_path_for_pathkeys_ext() and
> >>> get_cheapest_path_for_pathkeys_ext() should consider incremental sort?
> >>>    The revised patch teaches them to do so.
> >> Following 55a780e9476 [2] it should be considered, of course.
> > Great, thank you for catching this.  The diff of costs is attached.  I
> > see the costs now are better or within the fuzz factor.
> >
> Hi! I looked at regression test changes but one of them confused me.
>
> Example where the plan shape changed:
>
> EXPLAIN (COSTS OFF)
> SELECT t1.a, t2.b
> FROM (SELECT * FROM prt1 WHERE a < 450) t1
> LEFT JOIN (SELECT * FROM prt2 WHERE b > 250) t2
>    ON t1.a = t2.b
> WHERE t1.b = 0
> ORDER BY t1.a, t2.b;
>
> -- before
>                          QUERY PLAN
> -----------------------------------------------------------
>   Incremental Sort
>     Sort Key: prt1.a, prt2.b
>     Presorted Key: prt1.a
>     ->  Merge Left Join
>           Merge Cond: (prt1.a = prt2.b)
>           ->  Sort
>                 Sort Key: prt1.a
>                 ->  Append
>                       ->  Seq Scan on prt1_p1 prt1_1
>                             Filter: ((a < 450) AND (b = 0))
>                       ->  Seq Scan on prt1_p2 prt1_2
>                             Filter: ((a < 450) AND (b = 0))
>           ->  Sort
>                 Sort Key: prt2.b
>                 ->  Append
>                       ->  Seq Scan on prt2_p2 prt2_1
>                             Filter: (b > 250)
>                       ->  Seq Scan on prt2_p3 prt2_2
>                             Filter: (b > 250)
> (19 rows)
>
> -- now
>                             QUERY PLAN
> -----------------------------------------------------------------
>   Sort
>     Sort Key: prt1.a, prt2.b
>     ->  Merge Right Join
>           Merge Cond: (prt2.b = prt1.a)
>           ->  Append
>                 ->  Sort
>                       Sort Key: prt2_1.b
>                       ->  Seq Scan on prt2_p2 prt2_1
>                             Filter: (b > 250)
>                 ->  Sort
>                       Sort Key: prt2_2.b
>                       ->  Seq Scan on prt2_p3 prt2_2
>                             Filter: (b > 250)
>           ->  Materialize
>                 ->  Append
>                       ->  Sort
>                             Sort Key: prt1_1.a
>                             ->  Seq Scan on prt1_p1 prt1_1
>                                   Filter: ((a < 450) AND (b = 0))
>                       ->  Sort
>                             Sort Key: prt1_2.a
>                             ->  Seq Scan on prt1_p2 prt1_2
>                                   Filter: ((a < 450) AND (b = 0))
> (23 rows)
>
> Previously we had incremental sort on (t1.a, t2.b) with prt1.a already
> presorted; now we sort both t1.a and t2.b after a merge right join. It
> looks inefficiently or I missed something?
>
> Other tests looked fine for me.

Thank you for taking a look at this.

According to our cost model incremental sort has additional overhead
but gives huge wins on large row sets.  The row sets here are very
small.  You can get from [1] that the total cost became smaller.

Links.
1. https://www.postgresql.org/message-id/CAPpHfdsn_mPy1v6Gf8rmdkBDsDLU%2B%3DJ4M4sBzgaFv21cWruZFA%40mail.gmail.com

------
Regards,
Alexander Korotkov
Supabase

Re: MergeAppend could consider sorting cheapest child path

Richard Guo <guofenglinux@gmail.com> — 2025-10-03T07:05:02Z

On Thu, Oct 2, 2025 at 11:49 PM Alexander Korotkov <aekorotkov@gmail.com> wrote:
> On Mon, Sep 8, 2025 at 11:39 AM Richard Guo <guofenglinux@gmail.com> wrote:
> > Will have a review by the end of this commitfest.

> Did you manage to take a look at this patch?

Sorry, I haven't had a chance to review it yet, but it's on my to-do
list.  I'll get to it as soon as I can.

- Richard

Re: MergeAppend could consider sorting cheapest child path

Richard Guo <guofenglinux@gmail.com> — 2025-10-15T06:45:23Z

On Fri, Oct 3, 2025 at 4:05 PM Richard Guo <guofenglinux@gmail.com> wrote:
> Sorry, I haven't had a chance to review it yet, but it's on my to-do
> list.  I'll get to it as soon as I can.

I've had some time to review this patch, but I have a few concerns.
>From the changes in the test cases, it seems that this patch
encourages using MergeAppend+Sort over Sort+Append.  However, I'm not
sure MergeAppend+Sort is always more efficient than Sort+Append.
While it is in some cases, there are likely cases where it isn't.

I also noticed the hack you added to avoid using MergeAppend+Sort when
none of the chosen subpaths are ordered.  It seems to me that this
contradicts the idea of this patch.  If MergeAppend+Sort is indeed a
better plan, why wouldn't it apply in cases where no chosen subpaths
are ordered?

For example, imagine a table with 1000 child tables, where only one
child has a chosen subpath that is ordered, and the other 999 do not.
In this case, this patch would consider using MergeAppend+Sort, but I
don't think there's much practical difference between this case and
one where none of the chosen subpaths are ordered.

Moreover, I think this hack may cause us to miss some paths that the
current master is able to explore.  When child pathkeys exist, the
master can generate MergeAppend paths.  However, with the hack in
this patch, if none of the chosen subpaths for the child tables are
ordered, the MergeAppend paths will be missed.  I think this is a
regression.

Regarding the code, for the newly added function
get_cheapest_path_for_pathkeys_ext(), I think it's a reasonable
expectation from the function name that the returned path satisfies
the given pathkeys.  However, this function can return a path that is
not ordered according to those pathkeys, which I think is not a good
design choice.

Also, I'm not sure about this coding style:

+   if (path == NULL)
+
+       /*
+        * Current pathlist doesn't fit the pathkeys. No need to check extra
+        * sort path ways.
+        */
+       return base_path;

On one hand, I don't see this style often in our codebase.  On the
other hand, I have noticed commits that try to fix this style by
adding braces (cf. commit aadf7db66).  So I wonder if we can avoid
this style altogether from the start.

The commit message states that "To arrange the cost model, change the
merge cost multiplier".  However, I didn't find any related changes in
the patch.  Am I missing something?  Additionally, if you did change
some cost model multiplier, I think it's better to support this change
with benchmark results.

- Richard

Re: MergeAppend could consider sorting cheapest child path

David Rowley <dgrowleyml@gmail.com> — 2025-10-15T07:59:40Z

On Wed, 15 Oct 2025 at 19:45, Richard Guo <guofenglinux@gmail.com> wrote:
> I also noticed the hack you added to avoid using MergeAppend+Sort when
> none of the chosen subpaths are ordered.  It seems to me that this
> contradicts the idea of this patch.  If MergeAppend+Sort is indeed a
> better plan, why wouldn't it apply in cases where no chosen subpaths
> are ordered?

FWIW, I've not really followed this closely, but from the parts I have
read it seems the patch could cause a Sort -> unsorted path to be used
over a path that's already correctly sorted. This reminds me of a
patch I proposed in [1] and then subsequently decided it was a bad
idea in [2] because of concerns of having too many Sorts in a single
plan. Sort only calls tuplesort_end() at executor shutdown, so that
means possibly using up to work_mem per sort node. If you have 1000x
Sort nodes, then that's up to 1000x work_mem. Since the planner
doesn't have any abilities to consider the overall memory consumption,
I thought it was a bad idea due to increased OOM risk. If I'm not
mistaken it looks like this could suffer from the same problem.

David

[1] https://postgr.es/m/CAApHDvojKdBR3MR59JXmaCYbyHB6Q_5qPRU%2Bdy93En8wm%2BXiDA%40mail.gmail.com
[2] https://postgr.es/m/CAApHDvohAZLQSW4AiHUKmLGNuHYbi0pves%2B9_9ik3cAYevc2GQ%40mail.gmail.com

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-10-15T09:26:45Z

On 15/10/2025 09:59, David Rowley wrote:
> On Wed, 15 Oct 2025 at 19:45, Richard Guo <guofenglinux@gmail.com> wrote:
>> I also noticed the hack you added to avoid using MergeAppend+Sort when
>> none of the chosen subpaths are ordered.  It seems to me that this
>> contradicts the idea of this patch.  If MergeAppend+Sort is indeed a
>> better plan, why wouldn't it apply in cases where no chosen subpaths
>> are ordered?
> 
> FWIW, I've not really followed this closely, but from the parts I have
> read it seems the patch could cause a Sort -> unsorted path to be used
> over a path that's already correctly sorted. This reminds me of a
> patch I proposed in [1] and then subsequently decided it was a bad
> idea in [2] because of concerns of having too many Sorts in a single
> plan. Sort only calls tuplesort_end() at executor shutdown, so that
> means possibly using up to work_mem per sort node. If you have 1000x
> Sort nodes, then that's up to 1000x work_mem. Since the planner
> doesn't have any abilities to consider the overall memory consumption,
> I thought it was a bad idea due to increased OOM risk. If I'm not
> mistaken it looks like this could suffer from the same problem.
Thanks for your feedback!
This patch originated from the practice of how table partitioning can 
severely impact query execution. It is a rare case in our experience 
when all partitions have symmetrical indexes, especially those located 
remotely. People adopt a set of indexes according to the current load 
profile on hot partitions. In fact, it is a typical case when a 
timestamp orders partitions, and most of them are rarely updated.

So, the goal is to use MergeAppend when only a few partitions lack a 
proper index.
The concern about memory consumption makes sense, of course. However, we 
choose to sort based on cost estimations that usually work when the 
optimiser decides between fetching many tuples during an Index Scan, 
compared to only a few tuples to fetch with subsequent sorting. 
Additionally, scan estimation typically yields good predictions 
(compared to JOIN), and I personally estimate the OOM risk to be low.

Additionally, this patch revealed an issue with the cost model: there is 
no significant difference between a single massive Sort and multiple 
sorts followed by MergeAppend. Our experiments show that it is incorrect 
(one Sort operator demonstrates more efficacy) and may be corrected.

-- 
regards, Andrei Lepikhov,
pgEdge

Re: MergeAppend could consider sorting cheapest child path

David Rowley <dgrowleyml@gmail.com> — 2025-10-15T12:35:44Z

On Wed, 15 Oct 2025 at 22:26, Andrei Lepikhov <lepihov@gmail.com> wrote:
> This patch originated from the practice of how table partitioning can
> severely impact query execution. It is a rare case in our experience
> when all partitions have symmetrical indexes, especially those located
> remotely. People adopt a set of indexes according to the current load
> profile on hot partitions. In fact, it is a typical case when a
> timestamp orders partitions, and most of them are rarely updated.
>
> So, the goal is to use MergeAppend when only a few partitions lack a
> proper index.

hmm... doesn't that already work?

create table hp (a int ) partition by hash(a);
create table hp0 partition of hp for values with(modulus 2, remainder 0);
create table hp1 partition of hp for values with(modulus 2, remainder 1);
create index on hp0(a);

explain (costs off) select * from hp order by a;

 Merge Append
   Sort Key: hp.a
   ->  Index Only Scan using hp0_a_idx on hp0 hp_1
   ->  Sort
         Sort Key: hp_2.a
         ->  Seq Scan on hp1 hp_2

Or is this a case of that you want to also consider Seq Scan on hp0 ->
Sort if it's cheaper than Index Scan on hp0_a_idx just in case that's
enough to make Merge Append cheap enough to beat Append -> Sort?


> The concern about memory consumption makes sense, of course. However, we
> choose to sort based on cost estimations that usually work when the
> optimiser decides between fetching many tuples during an Index Scan,
> compared to only a few tuples to fetch with subsequent sorting.
> Additionally, scan estimation typically yields good predictions
> (compared to JOIN), and I personally estimate the OOM risk to be low.
>
> Additionally, this patch revealed an issue with the cost model: there is
> no significant difference between a single massive Sort and multiple
> sorts followed by MergeAppend. Our experiments show that it is incorrect
> (one Sort operator demonstrates more efficacy) and may be corrected.

Do you mean "no significant difference [in the costings] between"?

Not sure if I follow you here. You've said "one Sort operator
demonstrates more efficacy", do you mean Sort atop of Append is
better? If so, why does the patch try to encourage plans with Merge
Append with many Sorts?

David

Re: MergeAppend could consider sorting cheapest child path

Andrei Lepikhov <lepihov@gmail.com> — 2025-11-04T14:46:35Z

On 15/10/2025 14:35, David Rowley wrote:
> On Wed, 15 Oct 2025 at 22:26, Andrei Lepikhov <lepihov@gmail.com> wrote:
> Or is this a case of that you want to also consider Seq Scan on hp0 ->
> Sort if it's cheaper than Index Scan on hp0_a_idx just in case that's
> enough to make Merge Append cheap enough to beat Append -> Sort?
I spent some time reviewing original user complaints. However, after 
switching employers, I no longer have direct access to the reports :((( 
- it was the main benefit of working for the company, which has massive 
migrations from Oracle and SQL Server.
I recall the problem raised with multiple foreign partitions, where 
MergeAppend by X is a preferable strategy (due to the need for ORDER BY 
X, or MergeJoin, etc). For some partitions, IndexScan(X) fetches too 
many tuples from disk. In this case, IndexScan(Y) + Sort (X) drastically 
improves the situation. That's why we proposed to look into the 
cheaper_total path + sort, not only the path that fits pathkeys.
>> Additionally, this patch revealed an issue with the cost model: there is
>> no significant difference between a single massive Sort and multiple
>> sorts followed by MergeAppend. Our experiments show that it is incorrect
>> (one Sort operator demonstrates more efficacy) and may be corrected.
> 
> Do you mean "no significant difference [in the costings] between"?
Yes>
> Not sure if I follow you here. You've said "one Sort operator
> demonstrates more efficacy", do you mean Sort atop of Append is
> better? If so, why does the patch try to encourage plans with Merge
> Append with many Sorts?
Sort-Append definitely better than MergeAppend-IndexScan.
This patch just reveals the issue that current cost model doesn't differ 
these two strategies. In the corner case it triggers a suboptimal plan.

-- 
regards, Andrei Lepikhov,
pgEdge