【发布时间】:2021-04-22 12:59:56
【问题描述】:
在使用外部引用时,在子连接中使用 ON 和 WHERE 有什么区别?
以这两条 SQL 语句为例(寻找 10 个人没有关闭的任务,使用 person_task 与多对多关系):
select p.name
from person p
where exists (
select 1
from person_task pt
join task t on pt.task_id = t.id
and t.state <> 'closed'
and pt.person_id = p.id -- ON
)
limit 10
select p.name
from person p
where exists (
select 1
from person_task pt
join task t on pt.task_id = t.id and t.state <> 'closed'
where pt.person_id = p.id -- WHERE
)
limit 10
它们产生相同的结果,但带有 ON 的语句要快得多。
这里对应EXPLAIN (ANALYZE)语句:
-- USING ON
Limit (cost=0.00..270.98 rows=10 width=8) (actual time=10.412..60.876 rows=10 loops=1)
-> Seq Scan on person p (cost=0.00..28947484.16 rows=1068266 width=8) (actual time=10.411..60.869 rows=10 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 68
SubPlan 1
-> Nested Loop (cost=1.00..20257.91 rows=1632 width=0) (actual time=0.778..0.778 rows=0 loops=78)
-> Index Scan using person_taskx1 on person_task pt (cost=0.56..6551.27 rows=1632 width=8) (actual time=0.633..0.633 rows=0 loops=78)
Index Cond: (id = p.id)
-> Index Scan using taskxpk on task t (cost=0.44..8.40 rows=1 width=8) (actual time=1.121..1.121 rows=1 loops=10)
Index Cond: (id = pt.task_id)
Filter: (state <> 'open')
Planning Time: 0.466 ms
Execution Time: 60.920 ms
-- USING WHERE
Limit (cost=2818814.57..2841563.37 rows=10 width=8) (actual time=29.075..6884.259 rows=10 loops=1)
-> Merge Semi Join (cost=2818814.57..59308642.64 rows=24832 width=8) (actual time=29.075..6884.251 rows=10 loops=1)
Merge Cond: (p.id = pt.person_id)
-> Index Scan using personxpk on person p (cost=0.43..1440340.27 rows=2136533 width=16) (actual time=0.003..0.168 rows=18 loops=1)
-> Gather Merge (cost=1001.03..57357094.42 rows=40517669 width=8) (actual time=9.441..6881.180 rows=23747 loops=1)
Workers Planned: 2
Workers Launched: 2
-> Nested Loop (cost=1.00..52679350.05 rows=16882362 width=8) (actual time=1.862..4207.577 rows=7938 loops=3)
-> Parallel Index Scan using person_taskx1 on person_task pt (cost=0.56..25848782.35 rows=16882362 width=16) (actual time=1.344..1807.664 rows=7938 loops=3)
-> Index Scan using taskxpk on task t (cost=0.44..1.59 rows=1 width=8) (actual time=0.301..0.301 rows=1 loops=23814)
Index Cond: (id = pt.task_id)
Filter: (state <> 'open')
Planning Time: 0.430 ms
Execution Time: 6884.349 ms
因此是否应该始终使用 ON 语句来过滤 sub JOIN 中的值?或者发生了什么? 我在这个例子中使用了 Postgres。
【问题讨论】:
标签: sql postgresql performance join select