[MySQL优化案例]系列 — 典型性索引引发CPU负载飙升问题

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收到一个mysql服务器负载告警，上去一看，load average都飙到280多了，用top一看，CPU跑到了336%，不过IO和内存的负载并不高，根据经验，应该又是一起索引引起的惨案了。

看下processlist以及slow query情况，发现有一个SQL经常出现，执行计划中的扫描记录数看着还可以，单次执行耗时为0.07s，还不算太大。乍一看，可能不是它引发的，但出现频率实在太高，而且执行计划看起来也不够完美：

mysql> explain SELECT count(1) FROM a , b WHERE a.id = b.video_id and b.state = 1 AND b.column_id = ’81’\G

*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: b
type: index_merge
possible_keys: columnid_videoid,column_id,state,video_time_stamp,idx_videoid
key: column_id,state
key_len: 4,4
ref: NULL
rows: 100
Extra: Using intersect(column_id,state); Using where
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: b.video_id
rows: 1
Extra: Using where; Using index

再看下该表的索引情况：

mysql> show index from b\G

*************************** 1. row ***************************
Table: b
Non_unique: 0
Key_name: PRIMARY
Seq_in_index: 1
Column_name: id
Collation: A
Cardinality: 167483
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:
*************************** 2. row ***************************
Table: b
Non_unique: 1
Key_name: column_id
Seq_in_index: 1
Column_name: column_id
Collation: A
Cardinality: 8374
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:
*************************** 3. row ***************************
Table: b
Non_unique: 1
Key_name: state
Seq_in_index: 2
Column_name: state
Collation: A
Cardinality: 5
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:

可以看到执行计划中，使用的是index merge，效率自然没有用联合索引(也有的叫做覆盖索引)来的好了，而且 state 字段的基数（唯一性）太差，索引效果很差。删掉两个独立索引，修改成联合看看效果如何：

mysql> show index from b;

*************************** 1. row ***************************
Table: b
Non_unique: 0
Key_name: PRIMARY
Seq_in_index: 1
Column_name: id
Collation: A
Cardinality: 128151
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:
*************************** 2. row ***************************
Table: b
Non_unique: 1
Key_name: idx_columnid_state
Seq_in_index: 1
Column_name: column_id
Collation: A
Cardinality: 3203
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:
*************************** 3. row ***************************
Table: b
Non_unique: 1
Key_name: idx_columnid_state
Seq_in_index: 2
Column_name: state
Collation: A
Cardinality: 3463
Sub_part: NULL
Packed: NULL
Null:
Index_type: BTREE
Comment:
Index_comment:

mysql> explain SELECT count(1) FROM a , b WHERE a.id = b.video_id and b.state = 1  AND b.column_id = ’81’ \G

*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: b
type: ref
possible_keys: columnid_videoid,idx_videoid,idx_columnid_state
key: columnid_videoid
key_len: 4
ref: const
rows: 199
Extra: Using where
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: b.video_id
rows: 1
Extra: Using where; Using index

可以看到执行计划变成了只用到了 idx_columnid_state 索引，而且 ref 类型也变成了 const，SQL执行耗时也从0.07s变成了0.00s，相应的CPU负载也从336%突降到了12%不到。

总结下，从多次历史经验来看，如果CPU负载持续很高，但内存和IO都还好的话，这种情况下，首先想到的一定是索引问题，十有八九错不了。