PG递归收敛的秘诀：从618794毫秒到11毫秒的惊人提速

标签

PostgreSQL , 少量not in大量 , 收敛优化 , 递归优化 , 收敛查询优化 select (300 ids) not in (select ids from 300万)

背景

有一个这样的场景，一张小表A，里面存储了一些ID，大约几百个。

（比如说巡逻车辆ID，环卫车辆的ID，公交车，微公交的ID）。

另外有一张日志表B，每条记录中的ID是来自前面那张小表的，但不是每个ID都出现在这张日志表中，比如说一天可能只有几十个ID会出现在这个日志表的当天的数据中。

（比如车辆的行车轨迹数据，每秒上报轨迹，数据量就非常庞大）。

那么我怎么快速的找出今天没有出现的ID呢。

（哪些巡逻车辆没有出现在这个片区，是不是偷懒了？哪些环卫车辆没有出行，哪些公交或微公交没有出行）？

select id from A where id not in (select id from B where time between ? and ?);

这个QUERY会很慢，有什么优化方法呢。

当然，你还可以让车辆签到的方式来解决这个问题，但是总有未签到的，或者没有这种设计的时候，那么怎么解决呢？

优化方法

其实方法也很精妙，和我之前做的两个CASE很相似。

《时序数据合并场景加速分析和实现 - 复合索引，窗口分组查询加速，变态递归加速》

《distinct xx和count(distinct xx)的变态递归优化方法 - 索引收敛(skip scan)扫描》

在B表中，其实ID的值是很稀疏的，只是由于是流水，所以总量大。

优化的手段就是对B的取值区间，做递归的收敛查询，然后再做NOT IN就很快了。

例子

建表

create table a(id int primary key, info text);

create table b(id int primary key, aid int, crt_time timestamp);

create index b_aid on b(aid);

插入测试数据

-- a表插入1000条

insert into a select generate_series(1,1000), md5(random()::text);

-- b表插入500万条，只包含aid的500个id。

insert into b select generate_series(1,5000000), generate_series(1,500), clock_timestamp();

优化前的性能

\timing

explain (analyze,verbose,timing,costs,buffers) select * from a where id not in (select aid from b);

QUERY PLAN

----------------------------------------------------------------------------------------------------------------------------------

Seq Scan on public.a (cost=0.00..67030021.50 rows=500 width=37) (actual time=2932.080..618776.881 rows=500 loops=1)

Output: a.id, a.info

Filter: (NOT (SubPlan 1))

Rows Removed by Filter: 500

Buffers: shared hit=27037, temp read=4264454 written=8545

SubPlan 1

-> Materialize (cost=0.00..121560.00 rows=5000000 width=4) (actual time=0.002..298.049 rows=2500125 loops=1000)

Output: b.aid

Buffers: shared hit=27028, temp read=4264454 written=8545

-> Seq Scan on public.b (cost=0.00..77028.00 rows=5000000 width=4) (actual time=0.009..888.427 rows=5000000 loops=1)

Output: b.aid

Buffers: shared hit=27028

Planning time: 0.969 ms

Execution time: 618794.299 ms

(14 rows)

优化后的性能

explain (analyze,verbose,timing,costs,buffers)

select * from a where id not in

(

with recursive skip as (

(

select min(aid) aid from b where aid is not null

)

union all

(

select (select min(aid) aid from b where b.aid > s.aid and b.aid is not null)

from skip s where s.aid is not null

) -- 这里的where s.aid is not null 一定要加,否则就死循环了.

)

select aid from skip where aid is not null

);

QUERY PLAN

------------------------------------------------------------------------------------------------------

Seq Scan on public.a (cost=54.98..76.48 rows=500 width=37) (actual time=10.837..10.957 rows=500 loops=1)

Output: a.id, a.info

Filter: (NOT (hashed SubPlan 5))

Rows Removed by Filter: 500

Buffers: shared hit=2012

SubPlan 5

-> CTE Scan on skip (cost=52.71..54.73 rows=100 width=4) (actual time=0.042..10.386 rows=500 loops=1)

Output: skip.aid

Filter: (skip.aid IS NOT NULL)

Rows Removed by Filter: 1

Buffers: shared hit=2003

CTE skip

-> Recursive Union (cost=0.46..52.71 rows=101 width=4) (actual time=0.037..10.104 rows=501 loops=1)

Buffers: shared hit=2003

-> Result (cost=0.46..0.47 rows=1 width=4) (actual time=0.036..0.036 rows=1 loops=1)

Output:

Buffers: shared hit=4

InitPlan 3 (returns )

-> Limit (cost=0.43..0.46 rows=1 width=4) (actual time=0.031..0.032 rows=1 loops=1)

Output: b_1.aid

Buffers: shared hit=4

-> Index Only Scan using b_aid on public.b b_1 (cost=0.43..131903.43 rows=5000000 width=4) (actual time=0.030..0.030 rows=1 loops=1)

Output: b_1.aid

Index Cond: (b_1.aid IS NOT NULL)

Heap Fetches: 1

Buffers: shared hit=4

-> WorkTable Scan on skip s (cost=0.00..5.02 rows=10 width=4) (actual time=0.019..0.019 rows=1 loops=501)

Output: (SubPlan 2)

Filter: (s.aid IS NOT NULL)

Rows Removed by Filter: 0

Buffers: shared hit=1999

SubPlan 2

-> Result (cost=0.47..0.48 rows=1 width=4) (actual time=0.018..0.018 rows=1 loops=500)

Output:

Buffers: shared hit=1999

InitPlan 1 (returns )

-> Limit (cost=0.43..0.47 rows=1 width=4) (actual time=0.017..0.017 rows=1 loops=500)

Output: b.aid

Buffers: shared hit=1999

-> Index Only Scan using b_aid on public.b (cost=0.43..66153.48 rows=1666667 width=4) (actual time=0.017..0.017 rows=1 loops=500)

Output: b.aid

Index Cond: ((b.aid > s.aid) AND (b.aid IS NOT NULL))

Heap Fetches: 499

Buffers: shared hit=1999

Planning time: 0.323 ms

Execution time: 11.082 ms

(46 rows)

采用收敛查询优化后，耗时从 618794毫秒 降低到了 11毫秒 ，感觉一下子节约了好多青春。