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[数据库]找到 mysql 数据库中的不良索引


为了演示,首先建两个包含不良索引的表,并弄点数据。

  1. mysql> show create table test1\G
  2. *************************** 1. row ***************************
  3. Table: test1
  4. Create Table: CREATE TABLE `test1` (
  5. `id` int(11) NOT NULL,
  6. `f1` int(11) DEFAULT NULL,
  7. `f2` int(11) DEFAULT NULL,
  8. `f3` int(11) DEFAULT NULL,
  9. PRIMARY KEY (`id`),
  10. KEY `k1` (`f1`,`id`),
  11. KEY `k2` (`id`,`f1`),
  12. KEY `k3` (`f1`),
  13. KEY `k4` (`f1`,`f3`),
  14. KEY `k5` (`f1`,`f3`,`f2`)
  15. ) ENGINE=InnoDB DEFAULT CHARSET=latin1
  16. 1 row in set (0.00 sec)
  17. mysql> show create table test2\G
  18. *************************** 1. row ***************************
  19. Table: test2
  20. Create Table: CREATE TABLE `test2` (
  21. `id1` int(11) NOT NULL DEFAULT '0',
  22. `id2` int(11) NOT NULL DEFAULT '0',
  23. `b` int(11) DEFAULT NULL,
  24. PRIMARY KEY (`id1`,`id2`),
  25. KEY `k1` (`b`)
  26. ) ENGINE=InnoDB DEFAULT CHARSET=latin1
  27. 1 row in set (0.00 sec)
  28. mysql> select count(*) from test2 group by b;
  29. +----------+
  30. | count(*) |
  31. +----------+
  32. | 32 |
  33. | 17 |
  34. +----------+
  35. 2 rows in set (0.00 sec)

1. 包含主键的索引

innodb 本身是聚簇表,每个二级索引本身就包含主键,类似 f1, id 的索引实际虽然没有害处,但反映了使用者对 mysql 索引不了解。而类似 id, f1 的是多余索引,会浪费存储空间,并影响数据更新性能。包含主键的索引用这样一句 sql 就能全部找出来。

  1. mysql> select c.*, pk from
  2. -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
  3. -> from INFORMATION_SCHEMA.STATISTICS
  4. -> where index_name != 'PRIMARY' and table_schema != 'mysql'
  5. -> group by table_schema, table_name, index_name) c,
  6. -> (select table_schema, table_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') pk
  7. -> from INFORMATION_SCHEMA.STATISTICS
  8. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
  9. -> group by table_schema, table_name) p
  10. -> where c.table_name = p.table_name and c.table_schema = p.table_schema and c.cols like concat('%', pk, '%');
  11. +--------------+------------+------------+---------+------+
  12. | table_schema | table_name | index_name | cols | pk |
  13. +--------------+------------+------------+---------+------+
  14. | test | test1 | k1 | |f1|id| | |id| |
  15. | test | test1 | k2 | |id|f1| | |id| |
  16. +--------------+------------+------------+---------+------+
  17. 2 rows in set (0.04 sec)

2. 重复索引前缀

包含重复前缀的索引,索引能由另一个包含该前缀的索引完全代替,是多余索引。多余的索引会浪费存储空间,并影响数据更新性能。这样的索引同样用一句 sql 可以找出来。

  1. mysql> select c1.table_schema, c1.table_name, c1.index_name,c1.cols,c2.index_name, c2.cols from
  2. -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
  3. -> from INFORMATION_SCHEMA.STATISTICS
  4. -> where table_schema != 'mysql' and index_name!='PRIMARY'
  5. -> group by table_schema,table_name,index_name) c1,
  6. -> (select table_schema, table_name,index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
  7. -> from INFORMATION_SCHEMA.STATISTICS
  8. -> where table_schema != 'mysql' and index_name != 'PRIMARY'
  9. -> group by table_schema, table_name, index_name) c2
  10. -> where c1.table_name = c2.table_name and c1.table_schema = c2.table_schema and c1.cols like concat(c2.cols, '%') and c1.index_name != c2.index_name;
  11. +--------------+------------+------------+------------+------------+---------+
  12. | table_schema | table_name | index_name | cols | index_name | cols |
  13. +--------------+------------+------------+------------+------------+---------+
  14. | test | test1 | k1 | |f1|id| | k3 | |f1| |
  15. | test | test1 | k4 | |f1|f3| | k3 | |f1| |
  16. | test | test1 | k5 | |f1|f3|f2| | k3 | |f1| |
  17. | test | test1 | k5 | |f1|f3|f2| | k4 | |f1|f3| |
  18. +--------------+------------+------------+------------+------------+---------+
  19. 4 rows in set (0.02 sec)

3. 低区分度索引

这样的索引由于仍然会扫描大量记录,在实际查询时通常会被忽略。但是在某些情况下仍然是有用的。因此需要根据实际情况进一步分析。这里是区分度小于 10% 的索引,可以根据需要调整参数。

  1. mysql> select p.table_schema, p.table_name, c.index_name, c.car, p.car total from
  2. -> (select table_schema, table_name, index_name, max(cardinality) car
  3. -> from INFORMATION_SCHEMA.STATISTICS
  4. -> where index_name != 'PRIMARY'
  5. -> group by table_schema, table_name,index_name) c,
  6. -> (select table_schema, table_name, max(cardinality) car
  7. -> from INFORMATION_SCHEMA.STATISTICS
  8. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
  9. -> group by table_schema,table_name) p
  10. -> where c.table_name = p.table_name and c.table_schema = p.table_schema and p.car > 0 and c.car / p.car < 0.1;
  11. +--------------+------------+------------+------+-------+
  12. | table_schema | table_name | index_name | car | total |
  13. +--------------+------------+------------+------+-------+
  14. | test | test2 | k1 | 4 | 49 |
  15. +--------------+------------+------------+------+-------+
  16. 1 row in set (0.04 sec)

4. 复合主键

由于 innodb 是聚簇表,每个二级索引都会包含主键值。复合主键会造成二级索引庞大,而影响二级索引查询性能,并影响更新性能。同样需要根据实际情况进一步分析。

  1. mysql> select table_schema, table_name, group_concat(column_name order by seq_in_index separator ',') cols, max(seq_in_index) len
  2. -> from INFORMATION_SCHEMA.STATISTICS
  3. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
  4. -> group by table_schema, table_name having len>1;
  5. +--------------+------------+-----------------------------------+------+
  6. | table_schema | table_name | cols | len |
  7. +--------------+------------+-----------------------------------+------+
  8. | test | test2 | id1,id2 | 2 |
  9. +--------------+------------+-----------------------------------+------+
  10. 1 rows in set (0.01 sec)

(题图来自:webfish.se)

原文:http://xiezhenye.com/2015/01/%E6%89%BE%E5%88%B0-mysql-%E6%95%B0%E6%8D%AE%E5%BA%93%E4%B8%AD%E7%9A%84%E4%B8%8D%E8%89%AF%E7%B4%A2%E5%BC%95.html作者: 谢振业

 

 

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