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分类: Mysql/postgreSQL

2013-07-25 14:40:22

用explain extended查看执行计划会比explain多一列 filtered。
filtered列给出了一个百分比的值,这个百分比值和rows列的值一起使用,可以估计出那些将要和explain中的前一个表进行连接的行的数目。
前一个表就是指explain 的 id列的值比当前表的id小的表。

1. mysql sql查询中,in是会走索引的:

点击(此处)折叠或打开

  1. mysql> explain extended select *,sleep(0.2) from testinfo where id in (1232,232,324,2342,23);
  2. +----+-------------+----------+-------+---------------+---------+---------+------+------+----------+-------------+
  3. | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
  4. +----+-------------+----------+-------+---------------+---------+---------+------+------+----------+-------------+
  5. | 1 | SIMPLE | testinfo | range | PRIMARY | PRIMARY | 4 | NULL | 5 | 100.00 | Using where |
  6. +----+-------------+----------+-------+---------------+---------+---------+------+------+----------+-------------+
  7. 1 row in set, 1 warning (0.00 sec)

  8. mysql> show warnings \G
  9. *************************** 1. row ***************************
  10.   Level: Note
  11.    Code: 1003
  12. Message: select `test`.`testinfo`.`id` AS `id`,`test`.`testinfo`.`idtest` AS `idtest`,`test`.`testinfo`.`nametest` AS `nametest`,`test`.`testinfo`.`author` AS `author`,`test`.`testinfo`.`typetest` AS `typetest`,sleep(0.2) AS `sleep(0.2)` from `test`.`testinfo` where (`test`.`testinfo`.`id` in (1232,232,324,2342,23))
  13. 1 row in set (0.00 sec)

  14. mysql> select *,sleep(0.2) from testinfo where id in (1232,232,324,2342,23);
  15. 5 rows in set (1.02 sec)

  16. # Time: 130725 11:47:51
  17. # User@Host: root[root] @ localhost []
  18. # Query_time: 1.017450 Lock_time: 0.000219 Rows_sent: 5 Rows_examined: 5
  19. SET timestamp=1374724071;
  20. select *,sleep(0.2) from testinfo where id in (1232,232,324,2342,23);
可见,id in (1232,232,324,2342,23) 是走了主键索引,而且效果很好,扫描5行就出结果了。




2.看看sql为:select count(*) from testinfo where id not in (select id from testinfo group by idtest);的效率

点击(此处)折叠或打开

  1. mysql> explain extended select count(*) from testinfo where id not in (select id from testinfo group by idtest);
  2. +----+--------------------+----------+-------+---------------+------------+---------+------+------+-----------+--------------------------+
  3. | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
  4. +----+--------------------+----------+-------+---------------+------------+---------+------+------+-----------+--------------------------+
  5. | 1 | PRIMARY | testinfo | index | NULL | key_idtest | 62 | NULL | 8761 | 100.00 | Using where; Using index |
  6. | 2 | DEPENDENT SUBQUERY | testinfo | index | NULL | key_idtest | 62 | NULL | 1 | 876100.00 | Using index |
  7. +----+--------------------+----------+-------+---------------+------------+---------+------+------+-----------+--------------------------+
  8. 2 rows in set, 1 warning (0.00 sec)
       表面上看都走了索引,但仔细发现filtered列为876100,这个值很大,直接影响到执行sql时扫描的行数。

  1. mysql> show warnings \G
  2. *************************** 1. row ***************************
  3.   Level: Note
  4.    Code: 1003
  5. Message: select count(0) AS `count(*)` from `test`.`testinfo` where (not(<in_optimizer>(`test`.`testinfo`.`id`,<exists>(select `test`.`testinfo`.`id` from `test`.`testinfo` group by `test`.`testinfo`.`idtest` having (<cache>(`test`.`testinfo`.`id`) = <ref_null_helper>(`test`.`testinfo`.`id`))))))
  6. 1 row in set (0.00 sec)
  7. 可见,经过mysql优化器后,in 给转换成exists的方式,下面实际执行一次sql花了36秒
  8. mysql> select count(*) from testinfo where id not in (select id from testinfo group by idtest);
  9. +----------+
  10. | count(*) |
  11. +----------+
  12. | 1059 |
  13. +----------+
  14. 1 row in set (36.79 sec)

  15. 根据上面的执行计划,估算大概的扫描的行数为:76755121
  16. mysql> select 8761*((876100*1)/100)
  17.     -> ;
  18. +-----------------------+
  19. | 8761*((876100*1)/100) |
  20. +-----------------------+
  21. | 76755121.0000 |
  22. +-----------------------+
  23. 1 row in set (0.00 sec)

  24. 而实际执行扫描的行数为:50910026
  25. # User@Host: root[root] @ localhost []
  26. # Query_time: 36.793302 Lock_time: 0.000227 Rows_sent: 1 Rows_examined: 50910026
  27. SET timestamp=1374723426;
  28. select count(*) from testinfo where id not in (select id from testinfo group by idtest);
从上面测试可知,in里面的子查询并非是先查出结果后再执行外层的查询。当in中子查询含有group by时,需注意是否会产生扫描的行数很大,sql执行效率很低。

3.将上面的sql变换一下:
先创建一个临时表:
create table wjlcn_temp(id int auto_increment primary key);
再将中间结果insert到临时表中:
insert into wjlcn_temp select id from testinfo group by idtest;
再来查询结果:select count(*) from testinfo where id not in (select id from wjlcn_temp);

点击(此处)折叠或打开

  1. mysql> explain extended select count(*) from testinfo where id not in (select id from wjlcn_temp);
  2. +----+--------------------+------------+-----------------+---------------+------------+---------+------+------+----------+--------------------------+
  3. | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
  4. +----+--------------------+------------+-----------------+---------------+------------+---------+------+------+----------+--------------------------+
  5. | 1 | PRIMARY | testinfo | index | NULL | key_idtest | 62 | NULL | 8761 | 100.00 | Using where; Using index |
  6. | 2 | DEPENDENT SUBQUERY | wjlcn_temp | unique_subquery | PRIMARY | PRIMARY | 4 | func | 1 | 100.00 | Using index |
  7. +----+--------------------+------------+-----------------+---------------+------------+---------+------+------+----------+--------------------------+
  8. 2 rows in set, 1 warning (0.00 sec)


  9. mysql> show warnings \G
  10. *************************** 1. row ***************************
  11.   Level: Note
  12.    Code: 1003
  13. Message: select count(0) AS `count(*)` from `test`.`testinfo` where (not(<in_optimizer>(`test`.`testinfo`.`id`,<exists>(<primary_index_lookup>(<cache>(`test`.`testinfo`.`id`) in wjlcn_temp on PRIMARY)))))
  14. 1 row in set (0.00 sec)

  15. mysql> select count(*),sleep(1) from testinfo where id not in (select id from wjlcn_temp);
  16. +----------+----------+
  17. | count(*) | sleep(1) |
  18. +----------+----------+
  19. | 1059 | 0 |
  20. +----------+----------+
  21. 1 row in set (1.02 sec)


  22. # Time: 130725 11:41:04
  23. # User@Host: root[root] @ localhost []
  24. # Query_time: 1.026054 Lock_time: 0.000231 Rows_sent: 1 Rows_examined: 9999
  25. SET timestamp=1374723664;
  26. select count(*),sleep(1) from testinfo where id not in (select id from wjlcn_temp);
从上面可以看到执行计划的filtered列为100,跟上面的sql有很大的区别。
其次,在explain中出现了unique_subquery

文档中解释:
unique_subquery
This type replaces ref for some IN subqueries of the following form:

value IN (SELECT primary_key FROM single_table WHERE some_expr)
unique_subquery is just an index lookup function that replaces the subquery completely for better efficiency.

当sql中出现unique_subquery时,sql会自动替换in 后面的子查询。从上面的执行计划中可以看到sql实际执行的是:
select count(0) AS `count(*)` from `test`.`testinfo` where (not(<in_optimizer>(`test`.`testinfo`.`id`,<exists>(<primary_index_lookup>(<cache>(`test`.`testinfo`.`id`) in wjlcn_temp on PRIMARY)))))
当sql中用到 primary_index_lookup时,sql的执行效率也比较好。
从慢查询中看到扫描的行数为:9999,而实际的执行时间为:Query_time: 1.026054 - 1 =0.026054秒。
比起前面的36秒好了很多,如果表的记录数更大时,执行时间相差更加明显。

所以,在sql中用in子查询时,最后看看执行计划。若在线上大表频繁执行 select count(*) from testinfo where id not in (select id from testinfo group by idtest);类的sql,可能会导致服务器的性能问题。

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