《优化案例 | CASE WHEN进行SQL改写优化》要点：
本文介绍了优化案例 | CASE WHEN进行SQL改写优化，希望对您有用。如果有疑问，可以联系我们。
今天给大家分享一个通过SQL改写而独辟蹊径的SQL优化案例
发现SLOW QUERY LOG中有下面这样一条记录：
...
# Query_time: 59.503827 Lock_time: 0.000198 Rows_sent: 641227 Rows_examined: 13442472 Rows_affected: 0
...
select uid,sum(power) powerup from t1 where
date>='2017-03-31' and
UNIX_TIMESTAMP(STR_TO_DATE(concat(date,' ',hour),'%Y-%m-%d %H'))>=1490965200 and
UNIX_TIMESTAMP(STR_TO_DATE(concat(date,' ',hour),'%Y-%m-%d %H'))<1492174801 and
aType in (1,6,9) group by uid;实话说,看到这个SQL我也忍不住想骂人啊,究竟是哪个脑残的XX狗设计的?
竟然把日期时间中的 date 和 hour 给独立出来成两列,查询时再合并成一个新的条件,简直无力吐槽.
吐槽归吐槽,该干活还得干活,谁让咱是DBA呢,SQL优化是咱的拿手好戏不是嘛~
不厌其烦地再说一遍SQL优化思路.
想要优化一个SQL,一般来说就是先看执行计划,观察是否尽可能用到索引,
同时要关注预计扫描的行数,
以及是否产生了临时表(Using temporary) 或者
是否需要进行排序(Using filesort),
想办法消除这些情况.
毫无疑问,想要优化,先看表DDL以及执行计划：
CREATE TABLE `t1` (
`id` bigint(20) unsigned NOT NULL AUTO_INCREMENT,
`date` date NOT NULL DEFAULT '0000-00-00',
`hour` char(2) NOT NULL DEFAULT '00',
`kid` int(4) NOT NULL DEFAULT '0',
`uid` int(11) NOT NULL DEFAULT '0',
`aType` tinyint(2) NOT NULL DEFAULT '0',
`src` tinyint(2) NOT NULL DEFAULT '1',
`aid` int(11) NOT NULL DEFAULT '1',
`acount` int(11) NOT NULL DEFAULT '1',
`power` decimal(20,2) DEFAULT '0.00',
PRIMARY KEY (`id`,`date`),
UNIQUE KEY `did` (`date`,`hour`,`kid`,`uid`,`aType`,`src`,`aid`)
) ENGINE=InnoDB AUTO_INCREMENT=50486620 DEFAULT CHARSET=utf8mb4
/*!50500 PARTITION BY RANGE COLUMNS(`date`)
(PARTITION p20170316 VALUES LESS THAN ('2017-03-17') ENGINE = InnoDB,
PARTITION p20170317 VALUES LESS THAN ('2017-03-18') ENGINE = InnoDB
...
yejr@imysql.com[myDB]> EXPLAIN select uid,sum(power) powerup from t1 where
date>='2017-03-31' and
UNIX_TIMESTAMP(STR_TO_DATE(concat(date,' ',hour),'%Y-%m-%d %H'))>=1490965200 and
UNIX_TIMESTAMP(STR_TO_DATE(concat(date,' ',hour),'%Y-%m-%d %H'))<1492174801 and
aType in (1,6,9) group by uid\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t1
partitions: p20170324,p20170325,....all partition
type: ALL
possible_keys: did
key: NULL
key_len: NULL
ref: NULL
rows: 25005577
filtered: 15.00
Extra: Using where; Using temporary; Using filesort明显的,这个SQL效率非常低,全表扫描、没有索引、有临时表、需要额外排序,什么倒霉催的全赶上了.
这个SQL是想统计符合条件的power列总和,虽然 date 列已有索引,但WHERE子句中却对 date 列加了函数,而且还是 date 和 hour 两列的组合条件,那就无法用到这个索引了.
还好,有个聪明伶俐的妹子,突发起想(事实上这位妹子本来就擅长做SQL优化的~),可以用 CASE WHEN 方法来改造下SQL,改成像下面这样的：
select uid,sum(powerup+powerup1) from
(
select uid,
case when concat(date,' ',hour) >='2017-03-24 13:00' then power else '0' end as powerup,
case when concat(date,' ',hour) < '2017-03-25 13:00' then power else '0' end as powerup1
from t1
where date>='2017-03-24'
and date <'2017-03-25'
and aType in (1,6,9)
) a group by uid;是不是很有才,直接把这个没办法用到索引的条件给用CASE WHEN来改造了.看看新的SQL执行计划：
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t1
partitions: p20170324
type: range
possible_keys: did
key: idx2_date_addRedType
key_len: 4
ref: NULL
rows: 876375
filtered: 30.00
Extra: Using index condition; Using temporary; Using filesort看看这个SQL的执行代价：
+----------------------------+---------+
| Variable_name | Value |
+----------------------------+---------+
| Handler_read_first | 1 |
| Handler_read_key | 1834590 |
| Handler_read_last | 0 |
| Handler_read_next | 1834589 |
| Handler_read_prev | 0 |
| Handler_read_rnd | 232276 |
| Handler_read_rnd_next | 232277 |
+----------------------------+---------+及其SLOW QUERY LOG记录的信息：
# Query_time: 6.381254 Lock_time: 0.000166 Rows_sent: 232276 Rows_examined: 2299141 Rows_affected: 0
# Bytes_sent: 4237347 Tmp_tables: 1 Tmp_disk_tables: 0 Tmp_table_sizes: 4187168
# InnoDB_trx_id: 0
# QC_Hit: No Full_scan: No Full_join: No Tmp_table: Yes Tmp_table_on_disk: No
# Filesort: Yes Filesort_on_disk: No Merge_passes: 0
# InnoDB_IO_r_ops: 0 InnoDB_IO_r_bytes: 0 InnoDB_IO_r_wait: 0.000000
# InnoDB_rec_lock_wait: 0.000000 InnoDB_queue_wait: 0.000000
# InnoDB_pages_distinct: 9311看起来还不是太理想啊,虽然不再扫描全表了,但毕竟还是 有临时表 和 额外排序,想办法消除后再对比看下.
有个变化不知道大家注意到没,新的SLOW QUERY LOG记录多了不少信息,这是因为用了Percona分支版本的插件才支持,这个功能确实不错,甚至还能记录Profiling的详细信息,强烈推荐.
我们新建个 uid 列上的索引,看看能除临时表及排序后的代价如何,看看这个的开销会不会更低.
yejr@imysql.com[myDB]> ALTER TABLE t1 ADD INDEX idx_uid(uid);
yejr@imysql.com[myDB]> EXPLAIN select uid,sum(powerup+powerup1) from
(
select uid,
case when concat(date,' ',hour) >='2017-03-24 13:00' then power else '0' end as powerup,
case when concat(date,' ',hour) < '2017-03-25 13:00' then power else '0' end as powerup1
from t1
where date>='2017-03-24'
and date <'2017-03-25'
and aType in (1,6,9)
) a group by uid\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: if_date_hour_army_count
partitions: p20170331,p20170401...
type: index
possible_keys: did,idx_uid
key: idx_uid
key_len: 4
ref: NULL
rows: 12701520
filtered: 15.00
Extra: Using where看看添加索引后SQL的执行代价：
+----------------------------+---------+
| Variable_name | Value |
+----------------------------+---------+
| Handler_read_first | 1 |
| Handler_read_key | 1 |
| Handler_read_last | 0 |
| Handler_read_next | 1834589 |
| Handler_read_prev | 0 |
| Handler_read_rnd | 0 |
| Handler_read_rnd_next | 0 |
+----------------------------+---------+及其SLOW QUERY LOG记录的信息：
# Query_time: 5.772286 Lock_time: 0.000330 Rows_sent: 232276 Rows_examined: 1834589 Rows_affected: 0
# Bytes_sent: 4215071 Tmp_tables: 0 Tmp_disk_tables: 0 Tmp_table_sizes: 0
# InnoDB_trx_id: 0
# QC_Hit: No Full_scan: Yes Full_join: No Tmp_table: No Tmp_table_on_disk: No
# Filesort: No Filesort_on_disk: No Merge_passes: 0
# InnoDB_IO_r_ops: 0 InnoDB_IO_r_bytes: 0 InnoDB_IO_r_wait: 0.000000
# InnoDB_rec_lock_wait: 0.000000 InnoDB_queue_wait: 0.000000
# InnoDB_pages_distinct: 11470我们注意到,虽然加了 uid 列索引后的SQL扫描的data page更多了,但执行效率其实是更高的,因为消除了 临时表 和 额外排序,这从 Handlerread% 的结果中也能看出来,很显然它的顺序I/O更多,随机I/O更少,所以虽然需要扫描的 data page 更多,实际上效率却是更快的.
再想想这个SQL还有优化空间吗,显然是有的,那就是把数据表重新设计,将 date 和 hour 列整合到一起,这样就不用费劲的拼凑条件并且也能用到索引了.
作者： 陈丽寒、叶金荣
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