Received: from malur.postgresql.org ([217.196.149.56]) by arkaria.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 (Exim 4.94.2) (envelope-from ) id 1qqgLx-000YZq-QD for pgsql-hackers@arkaria.postgresql.org; Wed, 11 Oct 2023 21:02:50 +0000 Received: from localhost ([127.0.0.1] helo=malur.postgresql.org) by malur.postgresql.org with esmtp (Exim 4.94.2) (envelope-from ) id 1qqgKx-000hKS-01 for pgsql-hackers@arkaria.postgresql.org; Wed, 11 Oct 2023 21:01:47 +0000 Received: from magus.postgresql.org ([2a02:c0:301:0:ffff::29]) by malur.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 (Exim 4.94.2) (envelope-from ) id 1qqgKw-000hKJ-Gk for pgsql-hackers@lists.postgresql.org; Wed, 11 Oct 2023 21:01:47 +0000 Received: from forward500b.mail.yandex.net ([178.154.239.144]) by magus.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 (Exim 4.94.2) (envelope-from ) id 1qqgKr-0003Tp-1v for pgsql-hackers@postgresql.org; Wed, 11 Oct 2023 21:01:46 +0000 Received: from mail-nwsmtp-smtp-production-main-19.sas.yp-c.yandex.net (mail-nwsmtp-smtp-production-main-19.sas.yp-c.yandex.net [IPv6:2a02:6b8:c14:4081:0:640:557:0]) by forward500b.mail.yandex.net (Yandex) with ESMTP id 76D9661134; Thu, 12 Oct 2023 00:01:39 +0300 (MSK) Received: by mail-nwsmtp-smtp-production-main-19.sas.yp-c.yandex.net (smtp/Yandex) with ESMTPSA id c1mo3GeDcmI0-s8idFntD; Thu, 12 Oct 2023 00:01:38 +0300 X-Yandex-Fwd: 1 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=yandex.ru; s=mail; t=1697058099; bh=HWmPQzx8FCiRb6xoRpab1cgTFhqHOikgEsXdV9GBCGw=; h=In-Reply-To:Cc:Date:References:To:Subject:Message-ID:From; b=nZSpXM55WlhcAXMAAhIVzzVLi+Eb4aBKhNWVmLbT9AyHeUlZBtgnHhKT3V4GGB9k8 Inauw5rGAVmrEPcs/zqIAS0RFA0obv86aP5yeV5g6e7+xrGtLvCCe5fFALKT2hk6Q2 ZiVh7ns0lkWVR+OLFEQdM9NI7oJXI+Kr+xgne5gw= Authentication-Results: mail-nwsmtp-smtp-production-main-19.sas.yp-c.yandex.net; dkim=pass header.i=@yandex.ru Content-Type: multipart/mixed; boundary="------------tKB0E3ud2iUXVjYXku0t0Am0" Message-ID: Date: Thu, 12 Oct 2023 00:01:37 +0300 MIME-Version: 1.0 User-Agent: Mozilla Thunderbird Subject: Re: A new strategy for pull-up correlated ANY_SUBLINK To: Andy Fan Cc: pgsql-hackers , Tom Lane , vignesh C , Richard Guo , Andrey Lepikhov References: <247851.1668293143@sss.pgh.pa.us> Content-Language: en-US From: Alena Rybakina In-Reply-To: List-Id: List-Help: List-Subscribe: List-Post: List-Owner: List-Archive: Archived-At: Precedence: bulk This is a multi-part message in MIME format. --------------tKB0E3ud2iUXVjYXku0t0Am0 Content-Type: multipart/alternative; boundary="------------0xfuT0opCT4d0IGU0LO2Rb00" --------------0xfuT0opCT4d0IGU0LO2Rb00 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 8bit Hi! I reviewed your patch and it was interesting for me! Thank you for the explanation. It was really informative for me! > > I think we need the restriction and that should be enough for this feature > . Given the query Richard provided before: > > explain > select * from tenk1 A where exists > (select 1 from tenk2 B > where A.hundred in (select C.hundred FROM tenk2 C > WHERE c.odd = b.odd)); > > It first can be converted to the below format without any issue. > > SELECT * FROM tenk1 A SEMI JOIN tenk2 B > on A.hundred in (select C.hundred FROM tenk2 C > WHERE c.odd = b.odd); > > Then without the restriction, since we only pull the varnos from > sublink->testexpr, then it is {A}, so it convert to > > SELECT * FROM > (tenk1 A SEMI JOIN LATERAL (SELECT c.hundred FROM tenk2 C) > ON c.odd = b.odd AND a.hundred = v.hundred) > SEMI JOIN on tenk2 B ON TRUE; > > then the above query is NOT A VALID QUERY since: > 1. The above query is *not* same as > > SELECT * FROM (tenk1 A SEMI JOIN tenk2 B) on true > SEMI JOIN LATERAL (SELECT c.hundred FROM tenk2 C) v > ON v.odd = b.odd; > > 2. The above query requires b.odd when B is not available. So it is > right that an optimizer can't generate a plan for it. The fix would > be to do the restriction before applying this optimization. > > I'm not sure pull-up-subquery can play any role here, IIUC, the bad thing > happens before pull-up-subquery. > > I also write & analyze more test and found no issue by me > > 1. SELECT * FROM tenk1 A LEFT JOIN tenk2 B > ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd); > ==> should not be pull-up to rarg of the left join since A.hundred is not > available. > > 2.  SELECT * FROM tenk1 A LEFT JOIN tenk2 B > ON B.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = a.odd); > ==> should not be pull-up to rarg of the left join since A.odd is not > available. > > 3. SELECT * FROM tenk1 A LEFT JOIN tenk2 B > ON B.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd); > ==> should be pull-up to rarg of left join. > > 4. SELECT * FROM tenk1 A INNER JOIN tenk2 B > ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd); > ==> pull-up as expected. > > 5. SELECT * FROM tenk1 A RIGHT JOIN tenk2 B > ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd); > ==> should not be pull-up into larg of left join since b.odd is not > available. > > After reviewing, I want to suggest some changes related to the code and tests. First of all, I think, it would be better to "treat" change to "consider" and rewrite the pull-up check condition in two lines: /*  * If the sub-select refers to any Vars of the parent query, we so let's  * considering it as LATERAL.  (Vars of higher levels don't matter here.)  */ use_lateral = !bms_is_empty(sub_ref_outer_relids) && bms_is_subset(sub_ref_outer_relids, available_rels); if (!use_lateral && !bms_is_empty(sub_ref_outer_relids))     return NULL; Secondly, I noticed another interesting feature in your patch and I think it could be added to the test. If we get only one row from the aggregated subquery, we can pull-up it in the subquery scan filter. postgres=# explain (costs off) SELECT * FROM tenk1 A LEFT JOIN tenk2 B ON B.hundred in (SELECT min(c.hundred) FROM tenk2 C WHERE c.odd = b.odd);                           QUERY PLAN --------------------------------------------------------------  Nested Loop Left Join    ->  Seq Scan on tenk1 a    ->  Materialize          ->  Nested Loop                ->  Seq Scan on tenk2 b *->  Subquery Scan on "ANY_subquery"                      Filter: (b.hundred = "ANY_subquery".min)*                      ->  Aggregate                            ->  Seq Scan on tenk2 c                                  Filter: (odd = b.odd) (10 rows) It was impossible without your patch: postgres=# explain (costs off) SELECT * FROM tenk1 A LEFT JOIN tenk2 B ON B.hundred in (SELECT min(c.hundred) FROM tenk2 C WHERE c.odd = b.odd);                     QUERY PLAN ---------------------------------------------------  Nested Loop Left Join    ->  Seq Scan on tenk1 a    ->  Materialize          ->  Seq Scan on tenk2 b                Filter: (SubPlan 1)                SubPlan 1                  ->  Aggregate                        ->  Seq Scan on tenk2 c                              Filter: (odd = b.odd) (9 rows) And I found an alternative query, when aggregated sublink will pull-up into JoinExpr condition. explain (costs off) SELECT * FROM tenk1 A LEFT JOIN tenk2 B ON B.hundred in (SELECT count(c.hundred) FROM tenk2 C group by (c.odd));                          QUERY PLAN -------------------------------------------------------------  Nested Loop Left Join    ->  Seq Scan on tenk1 a    ->  Materialize          ->  Hash Semi Join *Hash Cond: (b.hundred = "ANY_subquery".count)*                ->  Seq Scan on tenk2 b                ->  Hash                      ->  Subquery Scan on "ANY_subquery"                            ->  HashAggregate                                  Group Key: c.odd                                  ->  Seq Scan on tenk2 c (11 rows) Unfortunately, I found a request when sublink did not pull-up, as in the examples above. I couldn't quite figure out why. create table a (x int, y int, z int, t int); create table b (x int, t int); create unique index on a (t, x); create index on b (t,x); insert into a select id, id, id, id FROM generate_series(1,100000) As id; insert into b select id, id FROM generate_series(1,1000) As id; explain (analyze, costs off, buffers) select b.x, b.x, a.y from b     left join a         on b.x=a.x and *b.t in             (select max(a0.t) *              from a a0              where a0.x = b.x and                    a0.t = b.t); QUERY PLAN ------------------------------------------------------------------------------------------------------------  Hash Right Join (actual time=1.150..58.512 rows=1000 loops=1)    Hash Cond: (a.x = b.x) *Join Filter: (SubPlan 2)*    Buffers: shared hit=3546    ->  Seq Scan on a (actual time=0.023..15.798 rows=100000 loops=1)          Buffers: shared hit=541    ->  Hash (actual time=1.038..1.042 rows=1000 loops=1)          Buckets: 4096  Batches: 1  Memory Usage: 72kB          Buffers: shared hit=5          ->  Seq Scan on b (actual time=0.047..0.399 rows=1000 loops=1)                Buffers: shared hit=5    SubPlan 2      ->  Result (actual time=0.018..0.018 rows=1 loops=1000)            Buffers: shared hit=3000            InitPlan 1 (returns $2)              ->  Limit (actual time=0.015..0.016 rows=1 loops=1000)                    Buffers: shared hit=3000                    ->  Index Only Scan using a_t_x_idx on a a0 (actual time=0.014..0.014 rows=1 loops=1000)                          Index Cond: ((t IS NOT NULL) AND (t = b.t) AND (x = b.x))                          Heap Fetches: 1000                          Buffers: shared hit=3000  Planning Time: 0.630 ms  Execution Time: 58.941 ms (23 rows) I thought it would be: explain (analyze, costs off, buffers) select b.x, b.x, a.y from b     left join a on         b.x=a.x and *b.t =             (select max(a0.t) *              from a a0              where a0.x = b.x and                    a0.t <= b.t); QUERY PLAN ---------------------------------------------------------------------------------------------------------------------  Hash Right Join (actual time=1.181..67.927 rows=1000 loops=1)    Hash Cond: (a.x = b.x) *Join Filter: (b.t = (SubPlan 2))*    Buffers: shared hit=3546    ->  Seq Scan on a (actual time=0.022..17.109 rows=100000 loops=1)          Buffers: shared hit=541    ->  Hash (actual time=1.065..1.068 rows=1000 loops=1)          Buckets: 4096  Batches: 1  Memory Usage: 72kB          Buffers: shared hit=5          ->  Seq Scan on b (actual time=0.049..0.401 rows=1000 loops=1)                Buffers: shared hit=5    SubPlan 2      ->  Result (actual time=0.025..0.025 rows=1 loops=1000)            Buffers: shared hit=3000            InitPlan 1 (returns $2)              ->  Limit (actual time=0.024..0.024 rows=1 loops=1000)                    Buffers: shared hit=3000                    ->  Index Only Scan Backward using a_t_x_idx on a a0 (actual time=0.023..0.023 rows=1 loops=1000)                          Index Cond: ((t IS NOT NULL) AND (t <= b.t) AND (x = b.x))                          Heap Fetches: 1000                          Buffers: shared hit=3000  Planning Time: 0.689 ms  Execution Time: 68.220 ms (23 rows) If you noticed, it became possible after replacing the "in" operator with "=". I took the liberty of adding this to your patch and added myself as reviewer, if you don't mind. -- Regards, Alena Rybakina --------------0xfuT0opCT4d0IGU0LO2Rb00 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: 8bit

Hi!

I reviewed your patch and it was interesting for me!

Thank you for the explanation. It was really informative for me!


I think we need the restriction and that should be enough for this feature
. Given the query Richard provided before:

explain
select * from tenk1 A where exists
(select 1 from tenk2 B
where A.hundred in (select C.hundred FROM tenk2 C
WHERE c.odd = b.odd));

It first can be converted to the below format without any issue.

SELECT * FROM tenk1 A SEMI JOIN tenk2 B
on A.hundred in (select C.hundred FROM tenk2 C
WHERE c.odd = b.odd);

Then without the restriction, since we only pull the varnos from
sublink->testexpr, then it is {A}, so it convert to

SELECT * FROM 
(tenk1 A SEMI JOIN LATERAL (SELECT c.hundred FROM tenk2 C)
ON c.odd = b.odd AND a.hundred = v.hundred) 
SEMI JOIN on tenk2 B ON TRUE;

then the above query is NOT A VALID QUERY since:
1. The above query is *not* same as

SELECT * FROM (tenk1 A SEMI JOIN tenk2 B) on true
SEMI JOIN LATERAL (SELECT c.hundred FROM tenk2 C) v 
ON v.odd = b.odd;

2. The above query requires b.odd when B is not available. So it is
right that an optimizer can't generate a plan for it. The fix would
be to do the restriction before applying this optimization.

I'm not sure pull-up-subquery can play any role here, IIUC, the bad thing
happens before pull-up-subquery.

I also write & analyze more test and found no issue by me

1. SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd);
==> should not be pull-up to rarg of the left join since A.hundred is not
available.

2.  SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON B.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = a.odd);
==> should not be pull-up to rarg of the left join since A.odd is not
available.

3. SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON B.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd);
==> should be pull-up to rarg of left join.

4. SELECT * FROM tenk1 A INNER JOIN tenk2 B
ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd);
==> pull-up as expected.

5. SELECT * FROM tenk1 A RIGHT JOIN tenk2 B
ON A.hundred in (SELECT c.hundred FROM tenk2 C WHERE c.odd = b.odd);
==> should not be pull-up into larg of left join since b.odd is not
available.


After reviewing, I want to suggest some changes related to the code and tests.


First of all, I think, it would be better to "treat" change to "consider" and rewrite the pull-up check condition in two lines:

/*
 * If the sub-select refers to any Vars of the parent query, we so let's
 * considering it as LATERAL.  (Vars of higher levels don't matter here.)
 */

use_lateral = !bms_is_empty(sub_ref_outer_relids) &&
               bms_is_subset(sub_ref_outer_relids, available_rels);

if (!use_lateral && !bms_is_empty(sub_ref_outer_relids))
    return NULL;


Secondly, I noticed another interesting feature in your patch and I think it could be added to the test.

If we get only one row from the aggregated subquery, we can pull-up it in the subquery scan filter.

postgres=# explain (costs off)
SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON B.hundred in (SELECT min(c.hundred) FROM tenk2 C WHERE c.odd = b.odd);

                          QUERY PLAN                          
--------------------------------------------------------------
 Nested Loop Left Join
   ->  Seq Scan on tenk1 a
   ->  Materialize
         ->  Nested Loop
               ->  Seq Scan on tenk2 b
               ->  Subquery Scan on "ANY_subquery"
                     Filter: (b.hundred = "ANY_subquery".min)
                     ->  Aggregate
                           ->  Seq Scan on tenk2 c
                                 Filter: (odd = b.odd)
(10 rows)

It was impossible without your patch:

postgres=# explain (costs off)
SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON B.hundred in (SELECT min(c.hundred) FROM tenk2 C WHERE c.odd = b.odd);
                    QUERY PLAN                     
---------------------------------------------------
 Nested Loop Left Join
   ->  Seq Scan on tenk1 a
   ->  Materialize
         ->  Seq Scan on tenk2 b
               Filter: (SubPlan 1)
               SubPlan 1
                 ->  Aggregate
                       ->  Seq Scan on tenk2 c
                             Filter: (odd = b.odd)
(9 rows)


And I found an alternative query, when aggregated sublink will pull-up into JoinExpr condition.

explain (costs off)
SELECT * FROM tenk1 A LEFT JOIN tenk2 B
ON B.hundred in (SELECT count(c.hundred) FROM tenk2 C group by (c.odd));
                         QUERY PLAN                          
-------------------------------------------------------------
 Nested Loop Left Join
   ->  Seq Scan on tenk1 a
   ->  Materialize
         ->  Hash Semi Join
               Hash Cond: (b.hundred = "ANY_subquery".count)
               ->  Seq Scan on tenk2 b
               ->  Hash
                     ->  Subquery Scan on "ANY_subquery"
                           ->  HashAggregate
                                 Group Key: c.odd
                                 ->  Seq Scan on tenk2 c
(11 rows)


Unfortunately, I found a request when sublink did not pull-up, as in the examples above. I couldn't quite figure out why.

create table a (x int, y int, z int, t int);
create table b (x int, t int);
create unique index on a (t, x);
create index on b (t,x);
insert into a select id, id, id, id FROM generate_series(1,100000) As id;
insert into b select id, id FROM generate_series(1,1000) As id;

explain (analyze, costs off, buffers)
select b.x, b.x, a.y
from b
    left join a
        on b.x=a.x and
           b.t in
            (select max(a0.t)
             from a a0
             where a0.x = b.x and
                   a0.t = b.t);

                                                 QUERY PLAN                                                 
------------------------------------------------------------------------------------------------------------
 Hash Right Join (actual time=1.150..58.512 rows=1000 loops=1)
   Hash Cond: (a.x = b.x)
   Join Filter: (SubPlan 2)
   Buffers: shared hit=3546
   ->  Seq Scan on a (actual time=0.023..15.798 rows=100000 loops=1)
         Buffers: shared hit=541
   ->  Hash (actual time=1.038..1.042 rows=1000 loops=1)
         Buckets: 4096  Batches: 1  Memory Usage: 72kB
         Buffers: shared hit=5
         ->  Seq Scan on b (actual time=0.047..0.399 rows=1000 loops=1)
               Buffers: shared hit=5
   SubPlan 2
     ->  Result (actual time=0.018..0.018 rows=1 loops=1000)
           Buffers: shared hit=3000
           InitPlan 1 (returns $2)
             ->  Limit (actual time=0.015..0.016 rows=1 loops=1000)
                   Buffers: shared hit=3000
                   ->  Index Only Scan using a_t_x_idx on a a0 (actual time=0.014..0.014 rows=1 loops=1000)
                         Index Cond: ((t IS NOT NULL) AND (t = b.t) AND (x = b.x))
                         Heap Fetches: 1000
                         Buffers: shared hit=3000
 Planning Time: 0.630 ms
 Execution Time: 58.941 ms
(23 rows)

I thought it would be:

explain (analyze, costs off, buffers)
select b.x, b.x, a.y
from b
    left join a on
        b.x=a.x and
        b.t =
            (select max(a0.t)
             from a a0
             where a0.x = b.x and
                   a0.t <= b.t);

                                                     QUERY PLAN                                                      
---------------------------------------------------------------------------------------------------------------------
 Hash Right Join (actual time=1.181..67.927 rows=1000 loops=1)
   Hash Cond: (a.x = b.x)
   Join Filter: (b.t = (SubPlan 2))
   Buffers: shared hit=3546
   ->  Seq Scan on a (actual time=0.022..17.109 rows=100000 loops=1)
         Buffers: shared hit=541
   ->  Hash (actual time=1.065..1.068 rows=1000 loops=1)
         Buckets: 4096  Batches: 1  Memory Usage: 72kB
         Buffers: shared hit=5
         ->  Seq Scan on b (actual time=0.049..0.401 rows=1000 loops=1)
               Buffers: shared hit=5
   SubPlan 2
     ->  Result (actual time=0.025..0.025 rows=1 loops=1000)
           Buffers: shared hit=3000
           InitPlan 1 (returns $2)
             ->  Limit (actual time=0.024..0.024 rows=1 loops=1000)
                   Buffers: shared hit=3000
                   ->  Index Only Scan Backward using a_t_x_idx on a a0 (actual time=0.023..0.023 rows=1 loops=1000)
                         Index Cond: ((t IS NOT NULL) AND (t <= b.t) AND (x = b.x))
                         Heap Fetches: 1000
                         Buffers: shared hit=3000
 Planning Time: 0.689 ms
 Execution Time: 68.220 ms
(23 rows)

If you noticed, it became possible after replacing the "in" operator with "=".


I took the liberty of adding this to your patch and added myself as reviewer, if you don't mind.


-- 
Regards,
Alena Rybakina
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