欢迎您访问程序员文章站本站旨在为大家提供分享程序员计算机编程知识!
您现在的位置是: 首页  >  IT编程

浅谈pg_hint_plan定制执行计划

程序员文章站 2022-07-09 18:33:27
有的时候pg给出的执行计划由于很多原因并不是最优的,需要手动指定执行路径时我们可以加载pg_hint_plan这个插件。1 安装插件预先安装postgresql10.7cd postgresql-10...

有的时候pg给出的执行计划由于很多原因并不是最优的,需要手动指定执行路径时我们可以加载pg_hint_plan这个插件。

1 安装插件

预先安装postgresql10.7

cd postgresql-10.7/contrib/
wget https://github.com/ossc-db/pg_hint_plan/archive/rel10_1_3_3.tar.gz
tar xzvf pg_hint_plan-rel10_1_3_3.tar.gz
cd pg_hint_plan-rel10_1_3_3
make
make install

检查文件

cd $pghome
ls lib/pg_hint_plan.so
lib/pg_hint_plan.so
ls share/extension/
pg_hint_plan--1.3.0--1.3.1.sql pg_hint_plan--1.3.2--1.3.3.sql pg_hint_plan.control plpgsql.control
pg_hint_plan--1.3.1--1.3.2.sql pg_hint_plan--1.3.3.sql   plpgsql--1.0.sql  plpgsql--unpackaged--1.0.sql

2 加载插件

2.1 当前会话加载

load 'pg_hint_plan';

注意这样加载只在当前回话生效。

2.2 用户、库级自动加载

alter user postgres set session_preload_libraries='pg_hint_plan';
alter database postgres set session_preload_libraries='pg_hint_plan';

配置错了的话就连不上数据库了!

如果配置错了,连接template1库执行

alter database postgres reset session_preload_libraries;
alter user postgres reset session_preload_libraries;

2.3 cluster级自动加载

在postgresql.conf中修改shared_preload_libraries=‘pg_hint_plan'

重启数据库

3 检查是否已经加载

pg_hint_plan加载后在extension里面是看不到的,所以需要确认插件是否已经加载

show session_preload_libraries;
 session_preload_libraries
---------------------------
 pg_hint_plan

或者

show shared_preload_libraries;

如果使用load方式加载不需要检查。

4 使用插件定制执行计划

4.1 初始化测试数据

create table t1 (id int, t int, name varchar(255));
create table t2 (id int , salary int);
create table t3 (id int , age int);
insert into t1 values (1,200,'jack');
insert into t1 values (2,300,'tom');
insert into t1 values (3,400,'john');
insert into t2 values (1,40000);
insert into t2 values (2,38000);
insert into t2 values (3,18000);
insert into t3 values (3,38);
insert into t3 values (2,55);
insert into t3 values (1,12);
explain analyze select * from t1 left join t2 on t1.id=t2.id left join t3 on t1.id=t3.id;
              query plan
-------------------------------------------------------------------------------------------------------------------------
 hash right join (cost=89.82..337.92 rows=17877 width=540) (actual time=0.053..0.059 rows=3 loops=1)
 hash cond: (t3.id = t1.id)
 -> seq scan on t3 (cost=0.00..32.60 rows=2260 width=8) (actual time=0.002..0.002 rows=3 loops=1)
 -> hash (cost=70.05..70.05 rows=1582 width=532) (actual time=0.042..0.043 rows=3 loops=1)
   buckets: 2048 batches: 1 memory usage: 17kb
   -> hash right join (cost=13.15..70.05 rows=1582 width=532) (actual time=0.034..0.039 rows=3 loops=1)
    hash cond: (t2.id = t1.id)
    -> seq scan on t2 (cost=0.00..32.60 rows=2260 width=8) (actual time=0.002..0.002 rows=3 loops=1)
    -> hash (cost=11.40..11.40 rows=140 width=524) (actual time=0.017..0.017 rows=3 loops=1)
      buckets: 1024 batches: 1 memory usage: 9kb
      -> seq scan on t1 (cost=0.00..11.40 rows=140 width=524) (actual time=0.010..0.011 rows=3 loops=1)
 planning time: 0.154 ms
 execution time: 0.133 ms

创建索引

create index idx_t1_id on t1(id);
create index idx_t2_id on t2(id);
create index idx_t3_id on t3(id);
explain analyze select * from t1 left join t2 on t1.id=t2.id left join t3 on t1.id=t3.id;
             query plan
--------------------------------------------------------------------------------------------------------------
 hash left join (cost=2.14..3.25 rows=3 width=540) (actual time=0.045..0.047 rows=3 loops=1)
 hash cond: (t1.id = t3.id)
 -> hash left join (cost=1.07..2.14 rows=3 width=532) (actual time=0.030..0.032 rows=3 loops=1)
   hash cond: (t1.id = t2.id)
   -> seq scan on t1 (cost=0.00..1.03 rows=3 width=524) (actual time=0.005..0.006 rows=3 loops=1)
   -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.007..0.007 rows=3 loops=1)
    buckets: 1024 batches: 1 memory usage: 9kb
    -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)
 -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.005..0.005 rows=3 loops=1)
   buckets: 1024 batches: 1 memory usage: 9kb
   -> seq scan on t3 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.002 rows=3 loops=1)
 planning time: 0.305 ms
 execution time: 0.128 ms

4.2 强制走index scan

/*+ indexscan(t1 idx_d)
/*+ indexscan(t1 idx_t1_id)
explain (analyze,buffers) select * from t1 where id=2;
           query plan
----------------------------------------------------------------------------------------------
 seq scan on t1 (cost=0.00..1.04 rows=1 width=524) (actual time=0.011..0.013 rows=1 loops=1)
 filter: (id = 2)
 rows removed by filter: 2
 buffers: shared hit=1
 planning time: 0.058 ms
 execution time: 0.028 ms
explain (analyze,buffers) /*+ indexscan(t1) */select * from t1 where id=2;
             query plan
----------------------------------------------------------------------------------------------------------------
 index scan using idx_t1_id on t1 (cost=0.13..8.15 rows=1 width=524) (actual time=0.044..0.046 rows=1 loops=1)
 index cond: (id = 2)
 buffers: shared hit=1 read=1
 planning time: 0.145 ms
 execution time: 0.072 ms
explain (analyze,buffers) /*+ indexscan(t1 idx_t1_id) */select * from t1 where id=2;
             query plan
----------------------------------------------------------------------------------------------------------------
 index scan using idx_t1_id on t1 (cost=0.13..8.15 rows=1 width=524) (actual time=0.016..0.017 rows=1 loops=1)
 index cond: (id = 2)
 buffers: shared hit=2
 planning time: 0.079 ms
 execution time: 0.035 ms

4.3 强制多条件组合

/*+ indexscan(t2) indexscan(t1 idx_t1_id) */
/*+ seqscan(t2) indexscan(t1 idx_t1_id) */
explain analyze select * from t1 join t2 on (t1.id = t2.id);
            query plan
--------------------------------------------------------------------------------------------------------
 hash join (cost=1.07..2.14 rows=3 width=532) (actual time=0.018..0.020 rows=3 loops=1)
 hash cond: (t1.id = t2.id)
 -> seq scan on t1 (cost=0.00..1.03 rows=3 width=524) (actual time=0.006..0.007 rows=3 loops=1)
 -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.005..0.005 rows=3 loops=1)
   buckets: 1024 batches: 1 memory usage: 9kb
   -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.001..0.003 rows=3 loops=1)
 planning time: 0.114 ms
 execution time: 0.055 ms
(8 rows)

组合两个条件走indexscan

/*+ indexscan(t2) indexscan(t1 idx_t1_id) */explain analyze select * from t1 join t2 on (t1.id = t2.id);
              query plan
-----------------------------------------------------------------------------------------------------------------------
 merge join (cost=0.26..24.40 rows=3 width=532) (actual time=0.047..0.053 rows=3 loops=1)
 merge cond: (t1.id = t2.id)
 -> index scan using idx_t1_id on t1 (cost=0.13..12.18 rows=3 width=524) (actual time=0.014..0.015 rows=3 loops=1)
 -> index scan using idx_t2_id on t2 (cost=0.13..12.18 rows=3 width=8) (actual time=0.026..0.028 rows=3 loops=1)

组合两个条件走indexscan+seqscan

/*+ seqscan(t2) indexscan(t1 idx_t1_id) */explain analyze select * from t1 join t2 on (t1.id = t2.id);
              query plan
-----------------------------------------------------------------------------------------------------------------------
 nested loop (cost=0.13..13.35 rows=3 width=532) (actual time=0.025..0.032 rows=3 loops=1)
 join filter: (t1.id = t2.id)
 rows removed by join filter: 6
 -> index scan using idx_t1_id on t1 (cost=0.13..12.18 rows=3 width=524) (actual time=0.016..0.018 rows=3 loops=1)
 -> materialize (cost=0.00..1.04 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=3)
   -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.004..0.005 rows=3 loops=1)

4.4 强制指定join method

/*+ nestloop(t1 t2) mergejoin(t1 t2 t3) leading(t1 t2 t3) */
/*+ nestloop(t1 t2 t3) mergejoin(t2 t3) leading(t1 (t2 t3)) */
explain analyze select * from t1 left join t2 on t1.id=t2.id left join t3 on t1.id=t3.id;
             query plan
--------------------------------------------------------------------------------------------------------------
 hash left join (cost=2.14..3.25 rows=3 width=540) (actual time=0.053..0.056 rows=3 loops=1)
 hash cond: (t1.id = t3.id)
 -> hash left join (cost=1.07..2.14 rows=3 width=532) (actual time=0.036..0.038 rows=3 loops=1)
   hash cond: (t1.id = t2.id)
   -> seq scan on t1 (cost=0.00..1.03 rows=3 width=524) (actual time=0.007..0.007 rows=3 loops=1)
   -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.009..0.009 rows=3 loops=1)
    buckets: 1024 batches: 1 memory usage: 9kb
    -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)
 -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.006..0.006 rows=3 loops=1)
   buckets: 1024 batches: 1 memory usage: 9kb
   -> seq scan on t3 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)

强制走循环嵌套连接

/*+ nestloop(t1 t2) mergejoin(t1 t2 t3) leading(t1 t2 t3) */
explain analyze select * from t1 left join t2 on t1.id=t2.id left join t3 on t1.id=t3.id;
              query plan
--------------------------------------------------------------------------------------------------------------------
 merge left join (cost=3.28..3.34 rows=3 width=540) (actual time=0.093..0.096 rows=3 loops=1)
 merge cond: (t1.id = t3.id)
 -> sort (cost=2.23..2.23 rows=3 width=532) (actual time=0.077..0.078 rows=3 loops=1)
   sort key: t1.id
   sort method: quicksort memory: 25kb
   -> nested loop left join (cost=0.00..2.20 rows=3 width=532) (actual time=0.015..0.020 rows=3 loops=1)
    join filter: (t1.id = t2.id)
    rows removed by join filter: 6
    -> seq scan on t1 (cost=0.00..1.03 rows=3 width=524) (actual time=0.005..0.005 rows=3 loops=1)
    -> materialize (cost=0.00..1.04 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=3)
      -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)
 -> sort (cost=1.05..1.06 rows=3 width=8) (actual time=0.012..0.013 rows=3 loops=1)
   sort key: t3.id
   sort method: quicksort memory: 25kb
   -> seq scan on t3 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)

控制连接顺序

/*+ nestloop(t1 t2 t3) mergejoin(t2 t3) leading(t1 (t2 t3)) */
explain analyze select * from t1 left join t2 on t1.id=t2.id left join t3 on t1.id=t3.id;
query plan
--------------------------------------------------------------------------------------------------------------
 nested loop left join (cost=1.07..3.31 rows=3 width=540) (actual time=0.036..0.041 rows=3 loops=1)
 join filter: (t1.id = t3.id)
 rows removed by join filter: 6
 -> hash left join (cost=1.07..2.14 rows=3 width=532) (actual time=0.030..0.032 rows=3 loops=1)
   hash cond: (t1.id = t2.id)
   -> seq scan on t1 (cost=0.00..1.03 rows=3 width=524) (actual time=0.008..0.009 rows=3 loops=1)
   -> hash (cost=1.03..1.03 rows=3 width=8) (actual time=0.007..0.007 rows=3 loops=1)
    buckets: 1024 batches: 1 memory usage: 9kb
    -> seq scan on t2 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.004 rows=3 loops=1)
 -> materialize (cost=0.00..1.04 rows=3 width=8) (actual time=0.001..0.002 rows=3 loops=3)
   -> seq scan on t3 (cost=0.00..1.03 rows=3 width=8) (actual time=0.002..0.003 rows=3 loops=1)

4.5 控制单条sql的cost

/*+ set(seq_page_cost 20.0) seqscan(t1) */
/*+ set(seq_page_cost 20.0) seqscan(t1) */explain analyze select * from t1 where id > 1;
           query plan
-----------------------------------------------------------------------------------------------
 seq scan on t1 (cost=0.00..20.04 rows=1 width=524) (actual time=0.011..0.013 rows=2 loops=1)
 filter: (id > 1)
 rows removed by filter: 1

set seq_page_cost 200,注意下面的cost已经变成了200.04

/*+ set(seq_page_cost 200.0) seqscan(t1) */explain analyze select * from t1 where id > 1;
           query plan
------------------------------------------------------------------------------------------------
 seq scan on t1 (cost=0.00..200.04 rows=1 width=524) (actual time=0.010..0.011 rows=2 loops=1)
 filter: (id > 1)
 rows removed by filter: 1

以上为个人经验,希望能给大家一个参考,也希望大家多多支持。如有错误或未考虑完全的地方,望不吝赐教。