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:
set rewrite_rule='none';
create table t1(c1 int,c2 int);
create table t2(c1 int,c2 int);
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;
返回结果为如下:
SET
CREATE TABLE
CREATE TABLE
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:
set rewrite_rule='intargetlist';
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;
返回结果为如下:
SET
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。
set rewrite_rule='uniquecheck';
explain verbose select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c1);
返回结果为如下:
SET
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)
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:
创建测试表t1、t2表:
create table t1(c1 int,c2 int);
insert into t1 values(1,1),(2,2),(3,3);
create table t2(c1 int,c2 int);
insert into t2 values(1,1),(2,2),(3,3),(4,4),(4,4),(5,5);
select * from t1 order by c2;
select * from t2 order by c2;
查询结果显示为如下:
c1 | c2
----+----
1 | 1
2 | 2
3 | 3
(3 rows)
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。
set rewrite_rule='none';
select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c2) ;
set rewrite_rule='uniquecheck';
select t1.c1 from t1 where t1.c1 = (select t2.c1 from t2 where t1.c1=t2.c2) ;
返回结果为如下:
SET
c1
----
1
2
3
(3 rows)
SET
ERROR: more than one row returned by a subquery used as an expression