案例:调整查询重写GUC参数rewrite_rule

rewrite_rule包含了多个查询重写规则:magicset、partialpush、uniquecheck、disablerep、intargetlist、predpush。下面简要说明一下其中重要的几个规则的使用场景:

目标列子查询提升参数intargetlist

通过将目标列中子查询提升,转为JOIN,往往可以极大提升查询性能。举例如下查询:

openGauss=#  set rewrite_rule='none';
SET
openGauss=# create table t1(c1 int,c2 int);
CREATE TABLE
openGauss=# create table t2(c1 int,c2 int);
CREATE TABLE
openGauss=#  explain (verbose on, costs off) select c1,(select avg(c2) from t2 where t2.c2=t1.c2) from t1 where t1.c1<100 order by t1.c2;
                  QUERY PLAN
-----------------------------------------------
 Sort
   Output: t1.c1, ((SubPlan 1)), t1.c2
   Sort Key: t1.c2
   ->  Seq Scan on public.t1
         Output: t1.c1, (SubPlan 1), t1.c2
         Filter: (t1.c1 < 100)
         SubPlan 1
           ->  Aggregate
                 Output: avg(t2.c2)
                 ->  Seq Scan on public.t2
                       Output: t2.c1, t2.c2
                       Filter: (t2.c2 = t1.c2)
(12 rows)

由于目标列中的相关子查询(select avg(c2) from t2 where t2.c2=t1.c2)无法提升的缘故,导致每扫描t1的一行数据,就会触发子查询的一次执行,效率低下。如果打开intargetlist参数会把子查询提升转为JOIN,来提升查询的性能:

openGauss=#  set rewrite_rule='intargetlist';
SET
openGauss=# explain (verbose on, costs off) select c1,(select avg(c2) from t2 where t2.c2=t1.c2) from t1 where t1.c1<100 order by t1.c2;
                  QUERY PLAN
-----------------------------------------------
 Sort
   Output: t1.c1, (avg(t2.c2)), t1.c2
   Sort Key: t1.c2
   ->  Hash Left Join
         Output: t1.c1, (avg(t2.c2)), t1.c2
         Hash Cond: (t1.c2 = t2.c2)
         ->  Seq Scan on public.t1
               Output: t1.c1, t1.c2
               Filter: (t1.c1 < 100)
         ->  Hash
               Output: (avg(t2.c2)), t2.c2
               ->  HashAggregate
                     Output: avg(t2.c2), t2.c2
                     Group By Key: t2.c2
                     ->  Seq Scan on public.t2
                           Output: t2.c2
(16 rows)

提升无agg的子查询uniquecheck

子链接提升需要保证对于每个条件只有一行输出,对于有agg的子查询可以自动提升,对于无agg的子查询如:

select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c2) ;

重写为:

select t1.c1 from t1 join (select t2.c1 from t2 where t2.c1 is not null group by t2.c1(unique check)) tt(c1) on tt.c1=t1.c1;

为了保证语义等价,子查询tt必须保证对于每个group by t2.c1只能有一行输出。打开uniquecheck查询重写参数保证可以提升并且等价,如果在运行时输出了多于一行的数据,就会报错。

openGauss=# set rewrite_rule='uniquecheck';
SET
openGauss=#  explain verbose select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c1);
                                     QUERY PLAN
-------------------------------------------------------------------------------------
 Hash Join  (cost=43.36..104.40 rows=2149 distinct=[200, 200] width=4)
   Output: t1.c1
   Hash Cond: (t1.c1 = subquery."?column?")
   ->  Seq Scan on public.t1  (cost=0.00..31.49 rows=2149 width=4)
         Output: t1.c1, t1.c2
   ->  Hash  (cost=40.86..40.86 rows=200 width=8)
         Output: subquery."?column?", subquery.c1
         ->  Subquery Scan on subquery  (cost=36.86..40.86 rows=200 width=8)
               Output: subquery."?column?", subquery.c1
               ->  HashAggregate  (cost=36.86..38.86 rows=200 width=4)
                     Output: t2.c1, t2.c1
                     Group By Key: t2.c1
                     Filter: (t2.c1 IS NOT NULL)
                     Unique Check Required
                     ->  Seq Scan on public.t2  (cost=0.00..31.49 rows=2149 width=4)
                           Output: t2.c1
(16 rows)

注意:因为分组group by t2.c1 unique check发生在过滤条件tt.c1=t1.c1之前,可能导致原来不报错的查询重写之后报错。举例:

有t1,t2表,其中的数据为:

openGauss=#  select * from t1 order by c2;
 c1 | c2
----+----
  1 |  1
  2 |  2
  3 |  3
(3 rows)
openGauss=#  select * from t2 order by c2;
 c1 | c2
----+----
  1 |  1
  2 |  2
  3 |  3
  4 |  4
  4 |  4
  5 |  5
(6 rows)

分别关闭和打开uniquecheck参数对比,打开之后报错。

openGauss=#  select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c2) ;
 c1
----
  1
  2
  3
(3 rows)
openGauss=#  set rewrite_rule='uniquecheck';
SET
openGauss=#  select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c2) ;
ERROR:  more than one row returned by a subquery used as an expression

去除多余distinct和group by子句remove_redundant_distinct_group_by

子查询提升需要保证没有distinct、group by子句,而对于如下ANY_sublink的语句:

explain select t1.c1 from t1 where t1.c2 = 5 and t1.c1 in (select t2.c1 from t2 group by t2.c1);

或者

explain select t1.c1 from t1 where t1.c2 = 5 and t1.c1 in (select distinct t2.c1 from t2);

可以发现distinct或group by对子查询的结果并无影响,仅做了去重,在in场景下并无意义,可以直接去除,重写为:

explain select t1.c1 from t1 where t1.c2 = 5 and t1.c1 in (select t2.c1 from t2);

具体的执行计划变更如下:

openGauss=# explain select t1.c1 from t1 where t1.c2 = 5 and t1.c1 in (select t2.c1 from t2 group by t2.c1);
                                    QUERY PLAN
----------------------------------------------------------------------------------
 Hash Right Semi Join  (cost=52.01..56.79 rows=6 width=4)
   Hash Cond: (t2.c1 = t1.c1)
   ->  HashAggregate  (cost=36.86..38.86 rows=200 width=4)
         Group By Key: t2.c1
         ->  Seq Scan on t2  (cost=0.00..31.49 rows=2149 width=4)
   ->  Hash  (cost=15.01..15.01 rows=11 width=4)
         ->  Bitmap Heap Scan on t1  (cost=4.34..15.01 rows=11 width=4)
               Recheck Cond: (c2 = 5)
               ->  Bitmap Index Scan on t1_idx  (cost=0.00..4.33 rows=11 width=0)
                     Index Cond: (c2 = 5)
(10 rows)

openGauss=# set rewrite_rule = 'remove_redundant_distinct_group_by';
SET
openGauss=# explain select t1.c1 from t1 where t1.c2 = 5 and t1.c1 in (select t2.c1 from t2 group by t2.c1);
                                 QUERY PLAN
-----------------------------------------------------------------------------
 Nested Loop Semi Join  (cost=4.34..23.55 rows=6 width=4)
   ->  Bitmap Heap Scan on t1  (cost=4.34..15.01 rows=11 width=4)
         Recheck Cond: (c2 = 5)
         ->  Bitmap Index Scan on t1_idx  (cost=0.00..4.33 rows=11 width=0)
               Index Cond: (c2 = 5)
   ->  Index Only Scan using t2_idx on t2  (cost=0.00..4.47 rows=11 width=4)
         Index Cond: (c1 = t1.c1)
(7 rows)

原先扫描t2表时,由于存在group by子句,导致t2.c1 = t1.c1过滤条件无法下推到扫描中,需要做全表扫描。如果打开remove_redundant_distinct_group_by参数,去掉了group by子句,选择了参数化路径,提升了查询性能。

需要注意的是,即使打开了该参数,部分场景也不会做该优化,原因是可能会影响结果:

  • 对于distinct场景,使用了distinct on子句或limit子句。
  • 对于group by场景,使用了聚集函数、窗口函数、having子句、groupingSets或limit子句。
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    openGauss 2024-07-19 00:56:42
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