(请原谅我, 标题党一回, 花几分钟看看, 或许对你有帮助).最近工作上遇到一个”神奇”的问题, 或许对大家有帮助, 因此形成本文.
背景
最近工作上遇到一个"神奇"的问题, 或许对大家有帮助, 因此形成本文.
问题大概是, 我有两个表 TableA, TableB, 其中 TableA 表大概百万行级别(存量业务数据), TableB 表几行(新业务场景, 数据还未膨胀起来), 语义上 TableA.columnA = TableB.columnA, 其中 columnA 上建立了索引, 但查询的时候确巨慢无比, 基本上到 5-6 秒, 明显跟预期不符合.
下面我以一个具体的例子来说明吧, 模拟其中的 SQL 查询场景.
场景重现
user_info表, 为了场景尽量简单, 我只 mock 了其中的三列数据.
mysql> desc user_info;
+-------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| uid | varchar(64) | NO | MUL | NULL | |
| name | varchar(255) | YES | | NULL | |
+-------+--------------+------+-----+---------+----------------+
3 rows in set (0.00 sec)
user_score表, 其中uid和user_info.uid语义一致:
mysql> desc user_info;
+-------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| uid | varchar(64) | NO | MUL | NULL | |
| name | varchar(255) | YES | | NULL | |
+-------+--------------+------+-----+---------+----------------+
3 rows in set (0.00 sec)
- 其中数据情况如下, 都是很常见的场景.
mysql> select * from user_score limit 2;
+----+--------------------------------------+-------+
| id | uid | score |
+----+--------------------------------------+-------+
| 5 | 111111111 | 100 |
| 6 | 55116d58-be26-4eb7-8f7e-bd2d49fbb968 | 100 |
+----+--------------------------------------+-------+
2 rows in set (0.00 sec)
mysql> select * from user_info limit 2;
+----+--------------------------------------+-------------+
| id | uid | name |
+----+--------------------------------------+-------------+
| 1 | 111111111 | tanglei |
| 2 | 55116d58-be26-4eb7-8f7e-bd2d49fbb968 | hudsonemily |
+----+--------------------------------------+-------------+
2 rows in set (0.00 sec)
mysql> select count(*) from user_score
-> union
-> select count(*) from user_info;
+----------+
| count(*) |
+----------+
| 4 |
| 3000003 |
+----------+
2 rows in set (1.39 sec)
- 索引情况是:
mysql> show index from user_score;
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| user_score | 0 | PRIMARY | 1 | id | A | 4 | NULL | NULL | | BTREE | | |
| user_score | 1 | index_uid | 1 | uid | A | 4 | NULL | NULL | YES | BTREE | | |
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
2 rows in set (0.00 sec)
mysql> show index from user_info;
+-----------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-----------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| user_info | 0 | PRIMARY | 1 | id | A | 2989934 | NULL | NULL | | BTREE | | |
| user_info | 1 | index_uid | 1 | uid | A | 2989934 | NULL | NULL | | BTREE | | |
+-----------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
2 rows in set (0.00 sec)
- 查询业务场景: 已知
user_score.id, 需要关联查询对应user_info的信息, (大家先忽略这个具体业务场景是否合理哈). 那么对应的 SQL 很自然的如下:
mysql> select * from user_score us
-> inner join user_info ui on us.uid = ui.uid
-> where us.id = 5;
+----+-----------+-------+---------+-----------+---------+
| id | uid | score | id | uid | name |
+----+-----------+-------+---------+-----------+---------+
| 5 | 111111111 | 100 | 1 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685399 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685400 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685401 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685402 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685403 | 111111111 | tanglei |
+----+-----------+-------+---------+-----------+---------+
6 rows in set (1.18 sec)
请忽略其中的数据, 我刚开始 mock 了 100W, 然后又重复导入了两遍, 因此数据有一些重复. 300W 数据, 最后查询出来也是 1.18 秒. 按道理应该更快的. 老规矩 explain 看看啥情况?
mysql> explain
-> select * from user_score us
-> inner join user_info ui on us.uid = ui.uid
-> where us.id = 5;
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
| 1 | SIMPLE | us | const | PRIMARY,index_uid | PRIMARY | 4 | const | 1 | NULL |
| 1 | SIMPLE | ui | ALL | NULL | NULL | NULL | NULL | 2989934 | Using where |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
2 rows in set (0.00 sec)
发现 user_info表没用上索引, 全表扫描近 300W 数据? 现象是这样, 为什么呢?
你不妨思考一下, 如果你遇到这种场景, 应该怎么去排查?
我当时也是"一顿操作猛如虎", 然并卵? 尝试了什么多种 sql 写法来完成这个操作.
比如更换Join表的顺序(驱动表/被驱动表)
mysql> explain select * from user_info ui inner join user_score us on us.uid = ui.uid where us.id = 5;
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
| 1 | SIMPLE | us | const | PRIMARY,index_uid | PRIMARY | 4 | const | 1 | NULL |
| 1 | SIMPLE | ui | ALL | NULL | NULL | NULL | NULL | 2989934 | Using where |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+-------------+
2 rows in set (0.00 sec)
再比如用子查询:
mysql> explain select * from user_info where uid in (select uid from user_score where id = 5);
+----+-------------+------------+-------+-------------------+---------+---------+-------+---------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------+-------------------+---------+---------+-------+---------+-------------+
| 1 | SIMPLE | user_score | const | PRIMARY,index_uid | PRIMARY | 4 | const | 1 | NULL |
| 1 | SIMPLE | user_info | ALL | NULL | NULL | NULL | NULL | 2989934 | Using where |
+----+-------------+------------+-------+-------------------+---------+---------+-------+---------+-------------+
2 rows in set (0.00 sec)
最终, 还是没有结果. 但直接单表查询写 SQL 确能用上索引.
mysql> select * from user_info where uid = '111111111';
+---------+-----------+---------+
| id | uid | name |
+---------+-----------+---------+
| 1 | 111111111 | tanglei |
| 3685399 | 111111111 | tanglei |
| 3685400 | 111111111 | tanglei |
| 3685401 | 111111111 | tanglei |
| 3685402 | 111111111 | tanglei |
| 3685403 | 111111111 | tanglei |
+---------+-----------+---------+
6 rows in set (0.01 sec)
mysql> explain select * from user_info where uid = '111111111';
+----+-------------+-----------+------+---------------+-----------+---------+-------+------+-----------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-----------+------+---------------+-----------+---------+-------+------+-----------------------+
| 1 | SIMPLE | user_info | ref | index_uid | index_uid | 194 | const | 6 | Using index condition |
+----+-------------+-----------+------+---------------+-----------+---------+-------+------+-----------------------+
1 row in set (0.01 sec)
问题解决
尝试更换检索条件, 比如更换 uid 直接关联查询, 索引仍然用不上, 差点放弃了都. 在准备求助 DBA 前, 看了下表的建表语句.
mysql> show create table user_info;
+-----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Table | Create Table |
+-----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| user_info | CREATE TABLE `user_info` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`uid` varchar(64) NOT NULL,
`name` varchar(255) DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `index_uid` (`uid`) USING BTREE
) ENGINE=InnoDB AUTO_INCREMENT=3685404 DEFAULT CHARSET=utf8 |
+-----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)
mysql> show create table user_score;
+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Table | Create Table |
+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| user_score | CREATE TABLE `user_score` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`uid` varchar(64) NOT NULL,
`score` float DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `index_uid` (`uid`)
) ENGINE=InnoDB AUTO_INCREMENT=9 DEFAULT CHARSET=utf8mb4 |
+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)
完全有理由怀疑因为字符集不一致的问题导致索引失效的问题了. 于是修改了小表(真实线上环境可别乱操作)的字符集与大表一致, 再测试下.
mysql> select * from user_score us
-> inner join user_info ui on us.uid = ui.uid
-> where us.id = 5;
+----+-----------+-------+---------+-----------+---------+
| id | uid | score | id | uid | name |
+----+-----------+-------+---------+-----------+---------+
| 5 | 111111111 | 100 | 1 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685399 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685400 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685401 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685402 | 111111111 | tanglei |
| 5 | 111111111 | 100 | 3685403 | 111111111 | tanglei |
+----+-----------+-------+---------+-----------+---------+
6 rows in set (0.00 sec)
mysql> explain
-> select * from user_score us
-> inner join user_info ui on us.uid = ui.uid
-> where us.id = 5;
+----+-------------+-------+-------+-------------------+-----------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+-------------------+-----------+---------+-------+------+-------+
| 1 | SIMPLE | us | const | PRIMARY,index_uid | PRIMARY | 4 | const | 1 | NULL |
| 1 | SIMPLE | ui | ref | index_uid | index_uid | 194 | const | 6 | NULL |
+----+-------------+-------+-------+-------------------+-----------+---------+-------+------+-------+
2 rows in set (0.00 sec)
果然 work 了.
挖掘根因
其实深究原因, 就是网上各种 MySQL军规/规约所提到的, "索引列不要参与计算". 这次这个 case, 如果知道 explain extended + show warnings 这个工具的话, (以前都不知道explain后面还能加 extended 参数), 可能就尽早"恍然大悟"了. (最新的 MySQL 8.0版本貌似不需要另外加这个关键字).
看下效果. (啊, 我还得把字符集改回去!!!)
mysql> explain extended select * from user_score us inner join user_info ui on us.uid = ui.uid where us.id = 5;
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+----------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+----------+-------------+
| 1 | SIMPLE | us | const | PRIMARY,index_uid | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| 1 | SIMPLE | ui | ALL | NULL | NULL | NULL | NULL | 2989934 | 100.00 | Using where |
+----+-------------+-------+-------+-------------------+---------+---------+-------+---------+----------+-------------+
2 rows in set, 1 warning (0.00 sec)
mysql> show warnings;
+-------+------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Level | Code | Message |
+-------+------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Note | 1003 | /* select#1 */ select '5' AS `id`,'111111111' AS `uid`,'100' AS `score`,`test`.`ui`.`id` AS `id`,`test`.`ui`.`uid` AS `uid`,`test`.`ui`.`name` AS `name` from `test`.`user_score` `us` join `test`.`user_info` `ui` where (('111111111' = convert(`test`.`ui`.`uid` using utf8mb4))) |
+-------+------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)
索引列参与计算了, 每次都要根据字符集去转换, 全表扫描, 你说能快得起来么?
至于这个问题为什么会发生? 综合来看, 就是因为历史原因, 老业务场景中的原表是假 utf8, 新业务新表采用了真 utf8mb4.
- 考虑新表的时候, 忽略和原库字符集的比较. 其实, 发现库里面的不同表可能都有不同的字符集, 不同人建的时候可能都依据个人喜好去选择了不同的字符集. 由此可见, 开发规范有多重要.
- 虽然知道索引列不能参与计算, 但这个场景下都是相同的类型,
varchar(64)最终查询过程中仍然发生了类型转换. 因此需要把字段字符集不一致等同于字段类型不一致. - 如果这个 case, 利用
fail-fast的理念的话, 发现不一致, 直接不让 join 会不会更好? (就像char v.s varchar不能 join 一样).
留一道思考题
你能解释如下情况吗? 查询结果表现为何不一致? 注意一下 SQL 的执行顺序, 查询优化器工作流程, 以及其中的 Using join buffer (Block Nested Loop), 建议多看看 MySQL 官方手册 深入背后原理.
mysql> select * from user_info ui
-> inner join user_score us on us.uid = ui.uid
-> where us.uid = '111111111';
+---------+-----------+---------+----+-----------+-------+
| id | uid | name | id | uid | score |
+---------+-----------+---------+----+-----------+-------+
| 1 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685399 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685400 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685401 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685402 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685403 | 111111111 | tanglei | 5 | 111111111 | 100 |
+---------+-----------+---------+----+-----------+-------+
6 rows in set (1.14 sec)
mysql> select * from user_info ui
-> inner join user_score us on us.uid = ui.uid
-> where ui.uid = '111111111';
+---------+-----------+---------+----+-----------+-------+
| id | uid | name | id | uid | score |
+---------+-----------+---------+----+-----------+-------+
| 1 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685399 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685400 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685401 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685402 | 111111111 | tanglei | 5 | 111111111 | 100 |
| 3685403 | 111111111 | tanglei | 5 | 111111111 | 100 |
+---------+-----------+---------+----+-----------+-------+
6 rows in set (0.00 sec)
mysql> explain
-> select * from user_info ui
-> inner join user_score us on us.uid = ui.uid
-> where us.uid = '111111111';
+----+-------------+-------+------+---------------+-----------+---------+-------+---------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+-----------+---------+-------+---------+----------------------------------------------------+
| 1 | SIMPLE | us | ref | index_uid | index_uid | 258 | const | 1 | Using index condition |
| 1 | SIMPLE | ui | ALL | NULL | NULL | NULL | NULL | 2989934 | Using where; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------+---------------+-----------+---------+-------+---------+----------------------------------------------------+
2 rows in set (0.00 sec)
mysql> explain
-> select * from user_info ui
-> inner join user_score us on us.uid = ui.uid
-> where ui.uid = '111111111';
+----+-------------+-------+------+---------------+-----------+---------+-------+------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+-----------+---------+-------+------+----------------------------------------------------+
| 1 | SIMPLE | ui | ref | index_uid | index_uid | 194 | const | 6 | Using index condition |
| 1 | SIMPLE | us | ALL | index_uid | NULL | NULL | NULL | 4 | Using where; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------+---------------+-----------+---------+-------+------+----------------------------------------------------+
2 rows in set (0.01 sec)
说明: 本文测试场景基于 MySQL 5.6, 另外, 本文案例只是为了说明问题, 其中的 SQL 并不规范(例如尽量别用 select * 之类的), 请勿模仿(模仿了我也不负责). 为了写本文, 可花了不少时间, 建 DB, 灌mock数据等等, 如果觉得有用, 还望你帮忙"在看", "转发". 最后留一个思考题供讨论, 欢迎留言说出你的看法.
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