一、概述

Plan Hint是PG社区官方版”永远”不考虑引入的功能之一，社区开发者的理念是，引入Hint功能，会掩盖优化器本身的问题，导致缺陷不被暴露出来。但对于使用者来讲，遇到某些SQL的查询计划不好，性能出了问题，其他方法又不奏效的情况下，首先的目标还是想尽快解决问题，而Hint就可以在这种时候帮助到我们。

二、配置

在postgresql.conf中修改shared_preload_libraries=‘pg_hint_plan'

三、示例

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
 
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

2、强制走Index Scan

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

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)
 
/*+ 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)
 
/*+ 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、强制指定join method

/*+ 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)
 
/*+ 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)

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

Postgresql 定制执行计划pg_hint_plan的更多相关文章

  1. PostgreSQL EXPLAIN执行计划学习--多表连接几种Join方式比较

    转了一部分.稍后再修改. 三种多表Join的算法: 一． NESTED LOOP: 对于被连接的数据子集较小的情况,嵌套循环连接是个较好的选择.在嵌套循环中,内表被外表驱动,外表返回的每一行都要在内表 ...

  2. postgresql中执行计划

    1.Explain explain select * from tablename; 2.explain输出josn格式 explain (format json) select * from tab ...

  3. PostgreSQL 修改执行计划 GroupAggregate 为 HashAggregate

    1.前言 PostgreSQL 聚合算法有两种,HashAggregate and GroupAggregate .我们知道GroupAggregate 需要对记录进行排序,而 HashAggrega ...

  4. PostgreSQL 执行计划

    简介 PostgreSQL是“世界上最先进的开源关系型数据库”.因为出现较晚,所以客户人群基数较MySQL少,但是发展势头很猛,最大优势是完全开源. MySQL是“世界上最流行的开源关系型数据库”.当 ...

  5. PostgreSQL执行计划：Bitmap scan VS index only scan

    之前了解过postgresql的Bitmap scan,只是粗略地了解到是通过标记数据页面来实现数据检索的,执行计划中的的Bitmap scan一些细节并不十分清楚.这里借助一个执行计划来分析bitm ...

  6. PostgreSQL 与 Oracle 访问分区表执行计划差异

    熟悉Oracle 的DBA都知道,Oracle 访问分区表时,对于没有提供分区条件的,也就是在无法使用分区剪枝情况下,优化器会根据全局的统计信息制定执行计划,该执行计划针对所有分区适用.在分析利弊之前 ...

  7. postgreSQL执行计划

    " class="wiz-editor-body wiz-readonly" contenteditable="false"> explain命 ...

  8. PostgreSQL执行计划的解析

    一个顺序磁盘页面操作的cost值由系统参数seq_page_cost (floating point)参数指定的,由于这个参数默认为1.0,所以我们可以认为一次顺序磁盘页面操作的cost值为1.下面o ...

  9. MySQL— 索引，视图，触发器，函数，存储过程，执行计划，慢日志，分页性能

    一.索引,分页性能,执行计划,慢日志 (1)索引的种类,创建语句,名词补充(最左前缀匹配,覆盖索引,索引合并,局部索引等): import sys # http://www.cnblogs.com/w ...

  10. MySQL统计信息以及执行计划预估方式初探

    数据库中的统计信息在不同(精确)程度上描述了表中数据的分布情况,执行计划通过统计信息获取符合查询条件的数据大小(行数),来指导执行计划的生成.在以Oracle和SQLServer为代表的商业数据库,和 ...

随机推荐

  1. Android ViewPager2 + TabLayout + BottomNavigationView

    Android ViewPager2 + TabLayout + BottomNavigationView 实际案例 本篇主要介绍一下 ViewPager2 + TabLayout + BottomN ...

  2. 互联网最全cka真题解析-2022

    1.CKA真题解析kubectl自动补全及帮助信息1.配置kubectl自动补全apt install bash-completion source <(kubectl completion b ...

  3. 解决SpringMVC重定向参数无法携带问题

    解决SpringMVC重定向参数无法携带问题 场景 重定向时请求参数会丢失,我们往往需要重新携带请求参数,我们可以进⾏⼿动参数拼接如下: return "redirect:handle01? ...

  4. 第三篇:前端基础之JavaScript

    前端基础之JavaScript   JavaScript概述 ECMAScript和JavaScript的关系 1996年11月,JavaScript的创造者--Netscape公司,决定将JavaS ...

  5. [OpenCV实战]16 使用OpenCV实现多目标跟踪

    目录 1 背景介绍 2 基于MultiTracker的多目标跟踪 2.1 创建单个对象跟踪器 2.2 读取视频的第一帧 2.3 在第一帧中确定我们跟踪的对象 2.4 初始化MultiTrackerer ...

  6. Rust-01 启航

    安装 所谓工欲善其事必先利其器,我们学习Rust当然需要安装Rust.我们可以从Rust官网下载rustup工具进行rust的安装.安装完成后,我们在命令行中输入rustc --version便可以查 ...

  7. 【FAQ】推送服务常见问题及解决方案

    一.推送成功收不到消息,推送返回:{"message":"success","requestID":"1523868*****28 ...

  8. C++string与int的相互转换（使用C++11）

    一.int转string #include <iostream> #include <string> int main() { double f = 23.43; double ...

  9. Hugging Face 2023 实习生招募计划

    Hugging Face 2023 实习生招募计划 想参与到 <王婆卖瓜>「最酷的 AI 社区」</王婆卖瓜>,共同构建未来吗?今天,我们为大家分享 Hugging Face ...

  10. .NET周报【1月第3期 2023-01-20】

    这应该是2023年农历新年前的最后一篇.NET周报,再次预祝大家新年快乐! 国内文章 看我是如何用C#编写一个小于8KB的贪吃蛇游戏的 https://www.cnblogs.com/InCerry/ ...