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MySql 字符集不同导致 left join 慢查询的问题解决

作者:鱼蛮子9527

当两个表的字符集不一样,在使用字符型字段进行表连接查询时,就需要特别注意下查询耗时是否符合预期,本文主要介绍了MySql 字符集不同导致 left join 慢查询的问题解决,感兴趣的可以了解一下

在 MySql 建表时候一般会指定字符集,大多数情况下为了更好的兼容性无脑选了 utf8mb4。但是有时会因为选错,或历史遗留问题,导致使用了 utf8 字符集。当两个表的字符集不一样,在使用字符型字段进行表连接查询时,就需要特别注意下查询耗时是否符合预期。

有次使用 left join 写一个 SQL,发现用时明显超过预期,经过一顿折腾才发现是两个表字符集不一样,特此记录一下。

问题分析

mysql> SELECT COUNT( *) from app_bind_rel t left join app_config_control_sn p on t.host_sn = p.host_sn ;
+-----------+
| COUNT( *) |
+-----------+
|     13447 |
+-----------+
1 row in set (0.89 sec)

例如上面的 SQL,左表 1W 条数据,右表 400 多条数据,在 host_sn 字段上都有索引,查询竟然用了近 900ms,怎么会这么慢?

mysql> explain SELECT COUNT( *) from app_bind_rel t left join app_config_control_sn p on t.host_sn = p.host_sn ;
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+-------+----------+-----------------------------------------------------------------+
| id | select_type | table | partitions | type  | possible_keys | key         | key_len | ref  | rows  | filtered | Extra                                                           |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+-------+----------+-----------------------------------------------------------------+
|  1 | SIMPLE      | t     | NULL       | index | NULL          | idx_host_sn | 122     | NULL | 10791 |   100.00 | Using index                                                     |
|  1 | SIMPLE      | p     | NULL       | index | NULL          | idx_host_sn | 152     | NULL |   457 |   100.00 | Using where; Using index; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+-------+----------+-----------------------------------------------------------------+
2 rows in set, 1 warning (0.00 sec)

查看下执行计划,的确是使用了索引,但是细看 Extra 列发现较正常的连表查询多了“Using join buffer (Block Nested Loop)”这一信息,这个具体是什么意思我们后面再说。
然后我们再看下详细的执行计划,使用 explain formart=json。

{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "988640.52"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t",
          "access_type": "index",
          "key": "idx_host_sn",
          "used_key_parts": [
            "host_sn"
          ],
          "key_length": "122",
          "rows_examined_per_scan": 10791,
          "rows_produced_per_join": 10791,
          "filtered": "100.00",
          "using_index": true,
          "cost_info": {
            "read_cost": "161.00",
            "eval_cost": "2158.20",
            "prefix_cost": "2319.20",
            "data_read_per_join": "2M"
          },
          "used_columns": [
            "host_sn"
          ]
        }
      },
      {
        "table": {
          "table_name": "p",
          "access_type": "index",
          "key": "idx_host_sn",
          "used_key_parts": [
            "host_sn"
          ],
          "key_length": "152",
          "rows_examined_per_scan": 457,
          "rows_produced_per_join": 4931487,
          "filtered": "100.00",
          "using_index": true,
          "using_join_buffer": "Block Nested Loop",
          "cost_info": {
            "read_cost": "23.92",
            "eval_cost": "986297.40",
            "prefix_cost": "988640.52",
            "data_read_per_join": "865M"
          },
          "used_columns": [
            "host_sn"
          ],
          "attached_condition": "<if>(is_not_null_compl(p), (`db0`.`t`.`host_sn` = convert(`db0`.`p`.`host_sn` using utf8mb4)), true)"
        }
      }
    ]
  }
}

特别需要关注的是这一对 KV

"attached_condition": "<if>(is_not_null_compl(p), (`collection_bullet_0000`.`t`.`host_sn` = convert(`collection_bullet_0000`.`p`.`host_sn` using utf8mb4)), true)"

看字面意思就是当 p 表不为空的时候,执行表连接需要先将 p 表的 host_sn 字段转变为 utf8mb4 字符集。我们应该都知道在表连接中使用了函数的话,是无法使用索引的。
所以再回到上面我看到的“Using join buffer (Block Nested Loop)”问题,来解释下这是一个什么过程。

Nested-Loop Join

MySql 官网对 Nested-Loop Join 有做过解释,其实做开发的同学看到名字就大体知道是啥,不就是循环嵌套嘛。

MySql  中分为 Nested-Loop Join 算法跟 Block Nested-Loop Join 算法。

例如,有如下三个表,t1、t2、t3 使用了这三种 join type。

Table   Join Type
t1      range
t2      ref
t3      ALL

当使用 Nested-Loop Join 算法时,其 join 过程如下所示,其实就是简单的三层循环。

for each row in t1 matching range {
  for each row in t2 matching reference key {
    for each row in t3 {
      if row satisfies join conditions, send to client
    }
  }
}

Block Nested-Loop Join(BNL) 算法是对 Nested-Loop Join 算法的一种优化。BNL 算法缓冲外部循环中读取的行来减少内部循环中读取表的次数。例如,将 10 行数据读取到缓冲器中,并且将缓冲器传递到下一个循环内部,内部循环中读取的每一行与缓冲器中的所有 10 行进行比较。这将使读取内部表的次数减少一个数量级。

for each row in t1 matching range {
  for each row in t2 matching reference key {
    store used columns from t1, t2 in join buffer
    if buffer is full {
      for each row in t3 {
        for each t1, t2 combination in join buffer {
          if row satisfies join conditions, send to client
        }
      }
      empty join buffer
    }
  }
}

if buffer is not empty {
  for each row in t3 {
    for each t1, t2 combination in join buffer {
      if row satisfies join conditions, send to client
    }
  }
}

算法实现如上,只有当 “join buffer” 满的时候才会触发 t3 表的读取,如果 “join buffer” 的 size = 10 那么就可以减少 10 倍的 t3 表被读取次数,从内存中读取数据的效率显然要比从磁盘读取的效率高的多。从而提升 join 的效率。

但其实再好的优化毕竟也是嵌套循环,做开发的同学应该都知道 O(N²) 的时间复杂度是无法接受的。这也是我们这个查询这么慢的根因。

解决办法

解决办法其实很简单,修改右表的字符集就可以解决。

在变更数据集之前我们先用 show table status 查看下当前表的状态。

mysql> show table status like 'app_config_control_sn';
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+-----------------+----------+----------------+---------+
| Name                  | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time         | Update_time         | Check_time | Collation       | Checksum | Create_options | Comment |
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+-----------------+----------+----------------+---------+
| app_config_control_sn | InnoDB |      10 | Dynamic    |  457 |            143 |       65536 |               0 |        32768 |         0 |           1041 | 2023-04-17 03:25:45 | 2023-04-17 03:27:24 | NULL       | utf8_general_ci |     NULL |                | SN      |
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+-----------------+----------+----------------+---------+
1 row in set (0.00 sec)

接着使用如下命令变更表的字符集。

mysql> ALTER TABLE app_config_control_sn CONVERT TO CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci;
Query OK, 457 rows affected (0.09 sec)
Records: 457  Duplicates: 0  Warnings: 0

再次使用 show table status 命令查看下表的状态。

mysql> show table status like 'app_config_control_sn';
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+--------------------+----------+----------------+---------+
| Name                  | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time         | Update_time         | Check_time | Collation          | Checksum | Create_options | Comment |
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+--------------------+----------+----------------+---------+
| app_config_control_sn | InnoDB |      10 | Dynamic    |  457 |            143 |       65536 |               0 |        32768 |         0 |           1041 | 2023-04-17 03:50:11 | 2023-04-17 03:50:11 | NULL       | utf8mb4_general_ci |     NULL |                | SN      |
+-----------------------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+------------+--------------------+----------+----------------+---------+
1 row in set (0.01 sec)

可以看到表的字符集已经发生了变化,那我们再次执行开始的 SQL 及 explain 语句,确认下问题是否已经解决。

mysql> SELECT COUNT( *) from app_bind_rel t left join app_config_control_sn p on t.host_sn = p.host_sn ;
+-----------+
| COUNT( *) |
+-----------+
|     13447 |
+-----------+
1 row in set (0.03 sec)

mysql> explain SELECT COUNT( *) from app_bind_rel t left join app_config_control_sn p on t.host_sn = p.host_sn ;
+----+-------------+-------+------------+-------+---------------+-------------+---------+---------------+-------+----------+--------------------------+
| id | select_type | table | partitions | type  | possible_keys | key         | key_len | ref           | rows  | filtered | Extra                    |
+----+-------------+-------+------------+-------+---------------+-------------+---------+---------------+-------+----------+--------------------------+
|  1 | SIMPLE      | t     | NULL       | index | NULL          | idx_host_sn | 122     | NULL          | 10791 |   100.00 | Using index              |
|  1 | SIMPLE      | p     | NULL       | ref   | idx_host_sn   | idx_host_sn | 202     | db0.t.host_sn |     2 |   100.00 | Using where; Using index |
+----+-------------+-------+------------+-------+---------------+-------------+---------+---------------+-------+----------+--------------------------+
2 rows in set, 1 warning (0.00 sec)

可以看到耗时已经只需要 30ms 左右,这个就比较符合预期,而在执行计划中也不再会有“Using join buffer (Block Nested Loop)”信息。

其他

mysql> SELECT COUNT( *) from app_bind_rel t join app_config_control_sn p on t.host_sn = p.host_sn ;
+-----------+
| COUNT( *) |
+-----------+
|       730 |
+-----------+
1 row in set (0.01 sec)

在没有变更字符集之前,当我们将 left join 修改为 join 的时候会发现耗时减少了 100 倍,只用了 10 ms,这是为什么呢?

mysql> explain SELECT COUNT( *) from app_bind_rel t join app_config_control_sn p on t.host_sn = p.host_sn ;
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type  | possible_keys | key         | key_len | ref  | rows | filtered | Extra                    |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+--------------------------+
|  1 | SIMPLE      | p     | NULL       | index | NULL          | idx_host_sn | 152     | NULL |  457 |   100.00 | Using index              |
|  1 | SIMPLE      | t     | NULL       | ref   | idx_host_sn   | idx_host_sn | 122     | func |    1 |   100.00 | Using where; Using index |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+--------------------------+
2 rows in set, 1 warning (0.00 sec)

查看执行计划,发现使用 join 的时候不会有 “Using join buffer (Block Nested Loop)”。再细看执行计划,发现驱动表已经由 t 表变为了 p 表。

{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "643.80"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "p",
          "access_type": "index",
          "key": "idx_host_sn",
          "used_key_parts": [
            "host_sn"
          ],
          "key_length": "152",
          "rows_examined_per_scan": 457,
          "rows_produced_per_join": 457,
          "filtered": "100.00",
          "using_index": true,
          "cost_info": {
            "read_cost": "4.00",
            "eval_cost": "91.40",
            "prefix_cost": "95.40",
            "data_read_per_join": "82K"
          },
          "used_columns": [
            "host_sn"
          ]
        }
      },
      {
        "table": {
          "table_name": "t",
          "access_type": "ref",
          "possible_keys": [
            "idx_host_sn"
          ],
          "key": "idx_host_sn",
          "used_key_parts": [
            "host_sn"
          ],
          "key_length": "122",
          "ref": [
            "func"
          ],
          "rows_examined_per_scan": 1,
          "rows_produced_per_join": 457,
          "filtered": "100.00",
          "using_index": true,
          "cost_info": {
            "read_cost": "457.00",
            "eval_cost": "91.40",
            "prefix_cost": "643.80",
            "data_read_per_join": "117K"
          },
          "used_columns": [
            "host_sn"
          ],
          "attached_condition": "(`db0`.`t`.`host_sn` = convert(`db0`.`p`.`host_sn` using utf8mb4))"
        }
      }
    ]
  }
}

查看详细的执行计划,可以看到

"attached_condition": "(`collection_bullet_0000`.`t`.`host_sn` = convert(`collection_bullet_0000`.`p`.`host_sn` using utf8mb4))"

这对 KV 依然是存在的,但是 "using_join_buffer": "Block Nested Loop" 已经不存在了。这个其实主要是因为当 p 表变为驱动表的时候,会先将自己的 host_sn 字段转为 utf8mb4 字符集,再与 t 表进行关联。t 表由于本来就是 utf8mb4 字符集且存在索引,就可以正常走数据库索引了,所以查询耗时也就大大降低。而使用 left join 时候,t 表作为驱动表是无法优化改变的。

可见在表连接中即使使用了函数也不一定就没法走索引,关键还是要看用法及明确处理过程。
记得刚学习数据库的时候,老师还特别强调驱动表一定要写在左边,而随着数据库技术的不断迭代发展,数据库已经能更智能的自动帮我们优化处理过程,之前很多的数据库规则也不需要了。

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