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淺談pg_hint_plan定制執(zhí)行計劃
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有的時候PG給出的執(zhí)行計劃由于很多原因并不是最優(yōu)的，需要手動指定執(zhí)行路徑時我們可以加載pg_hint_plan這個插件。

1 安裝插件

預(yù)先安裝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

檢查文件

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 加載插件

2.1 當(dāng)前會話加載

LOAD 'pg_hint_plan';

注意這樣加載只在當(dāng)前回話生效。

2.2 用戶、庫級自動加載

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

配置錯了的話就連不上數(shù)據(jù)庫了！

如果配置錯了，連接template1庫執(zhí)行

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

2.3 cluster級自動加載

在postgresql.conf中修改shared_preload_libraries=‘pg_hint_plan'

重啟數(shù)據(jù)庫

3 檢查是否已經(jīng)加載

pg_hint_plan加載后在extension里面是看不到的，所以需要確認(rèn)插件是否已經(jīng)加載

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

或者

show shared_preload_libraries;

如果使用load方式加載不需要檢查。

4 使用插件定制執(zhí)行計劃

4.1 初始化測試數(shù)據(jù)

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

創(chuàng)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 強(qiáng)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 強(qiáng)制多條件組合

/*+ 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)

組合兩個條件走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)

組合兩個條件走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 強(qiáng)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)

強(qiáng)制走循環(huán)嵌套連接

/*+ 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)

控制連接順序

/*+ 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 控制單條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已經(jīng)變成了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

以上為個人經(jīng)驗，希望能給大家一個參考，也希望大家多多支持腳本之家。如有錯誤或未考慮完全的地方，望不吝賜教。

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