更新时间:2024-07-03 GMT+08:00
案例:改写SQL消除子查询
现象描述
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select 1, (select count(*) from normal_date n where n.id = a.id) as GZCS from normal_date a; |
此SQL性能较差,查看发现执行计划中存在SubPlan,具体如下:
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QUERY PLAN --------------------------------------------------------------------------------------------------------------------------------------- Seq Scan on normal_date a (cost=0.00..888118.42 rows=5129 width=4) (actual time=2.394..22194.907 rows=10000 loops=1) SubPlan 1 -> Aggregate (cost=173.12..173.12 rows=1 width=8) (actual time=22179.496..22179.942 rows=10000 loops=10000) -> Seq Scan on normal_date n (cost=0.00..173.11 rows=1 width=0) (actual time=11279.349..22159.608 rows=10000 loops=10000) Filter: (id = a.id) Rows Removed by Filter: 99990000 Total runtime: 22196.415 ms (7 rows) |
优化说明
此优化的核心就是消除子查询。分析业务场景发现a.id不为null,那么从SQL语义出发,可以等价改写SQL为:
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select count(*) from normal_date n, normal_date a where n.id = a.id group by a.id; 计划如下: QUERY PLAN ---------------------------------------------------------------------------------------------------------------------------------- HashAggregate (cost=480.86..532.15 rows=5129 width=12) (actual time=21.539..24.356 rows=10000 loops=1) Group By Key: a.id -> Hash Join (cost=224.40..455.22 rows=5129 width=4) (actual time=6.402..13.484 rows=10000 loops=1) Hash Cond: (n.id = a.id) -> Seq Scan on normal_date n (cost=0.00..160.29 rows=5129 width=4) (actual time=0.087..1.459 rows=10000 loops=1) -> Hash (cost=160.29..160.29 rows=5129 width=4) (actual time=6.065..6.065 rows=10000 loops=1) Buckets: 32768 Batches: 1 Memory Usage: 352kB -> Seq Scan on normal_date a (cost=0.00..160.29 rows=5129 width=4) (actual time=0.046..2.738 rows=10000 loops=1) Total runtime: 26.844 ms (9 rows) |
为了保证改写的等效性,在normal_date.id加了not null约束。
父主题: 实际调优案例