MySQL中对于not in和minus使用的优化

优化前:

select count(t.id)

from test t

where t.status = 1

and t.id not in (select distinct a.app_id

from test2 a

where a.type = 1

and a.rule_id in (152, 153, 154))

17:20:57 laojiu>@plan

PLAN_TABLE_OUTPUT

————————————————————————————————————————-

Plan hash value: 684502086

—————————————————————————————-

| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |

—————————————————————————————-

| 0 | SELECT STATEMENT | | 1 | 18 | 176K (2)| 00:35:23 |

| 1 | SORT AGGREGATE | | 1 | 18 | | |

|* 2 | FILTER | | | | | |

|* 3 | TABLE ACCESS FULL| test | 1141 | 20538 | 845 (2)| 00:00:11 |

|* 4 | TABLE ACCESS FULL| test2 | 1 | 12 | 309 (2)| 00:00:04 |

—————————————————————————————-

Predicate Information (identified by operation id):

—————————————————

2 – filter( NOT EXISTS (SELECT /*+ */ 0 FROM “test2″ “A” WHERE

“A”.”type”=1 AND (“A”.”RULE_ID”=152 OR “A”.”RULE_ID”=153 OR

“A”.”RULE_ID”=154) AND LNNVL(“A”.”APP_ID”<>:B1)))

3 – filter(“T”.”status”=1)

4 – filter(“A”.”type”=1 AND (“A”.”RULE_ID”=152 OR “A”.”RULE_ID”=153 OR

“A”.”RULE_ID”=154) AND LNNVL(“A”.”APP_ID”<>:B1))

Statistics

———————————————————-

0 recursive calls

0 db block gets

1762169 consistent gets

0 physical reads

0 redo size

519 bytes sent via SQL*Net to client

492 bytes received via SQL*Net from client

2 SQL*Net roundtrips to/from client

0 sorts (memory)

0 sorts (disk)

1 rows processed

21 rows selected.

优化后:

select count(*) from(

select t.id

from test t

where t.status = 1

minus

select distinct a.app_id

from test2 a

where a.type = 1

and a.rule_id in (152, 153, 154))

17:23:33 laojiu>@plan

PLAN_TABLE_OUTPUT

————————————————————————————————————————-

Plan hash value: 631655686

————————————————————————————————–

| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |

————————————————————————————————–

| 0 | SELECT STATEMENT | | 1 | | | 1501 (2)| 00:00:19 |

| 1 | SORT AGGREGATE | | 1 | | | | |

| 2 | VIEW | | 1141 | | | 1501 (2)| 00:00:19 |

| 3 | MINUS | | | | | | |

| 4 | SORT UNIQUE | | 1141 | 20538 | | 846 (2)| 00:00:11 |

|* 5 | TABLE ACCESS FULL| test | 1141 | 20538 | | 845 (2)| 00:00:11 |

| 6 | SORT UNIQUE | | 69527 | 814K| 3632K| 654 (2)| 00:00:08 |

|* 7 | TABLE ACCESS FULL| test2 | 84140 | 986K| | 308 (2)| 00:00:04 |

————————————————————————————————–

Predicate Information (identified by operation id):

—————————————————

5 – filter(“T”.”status”=1)

7 – filter(“A”.”type”=1 AND (“A”.”RULE_ID”=152 OR “A”.”RULE_ID”=153 OR

“A”.”RULE_ID”=154))

21 rows selected.

Statistics

———————————————————-

1 recursive calls

0 db block gets

2240 consistent gets

0 physical reads

0 redo size

516 bytes sent via SQL*Net to client

492 bytes received via SQL*Net from client

2 SQL*Net roundtrips to/from client

2 sorts (memory)

0 sorts (disk)

1 rows processed

在优化sql的时候,我们需要转变一下思路,等价的改写sql;

改写后的sql由于逻辑读得到了天翻地覆的改变,很快得到结果。

第一条sql执行计划中有一个函数,LNNVL(“A”.”APP_ID”<>:B1),lnnvl(exp)

如果exp的结果是false或者是unknown,那么lnnvl返回true;

如果exp的结果是true,返回false.

以上是 MySQL中对于not in和minus使用的优化 的全部内容, 来源链接: utcz.com/z/315251.html

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