记录下MySQL的分区表

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分区表的结构

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audit_log 表的结构定义如下：

mysql> SHOW CREATE TABLE audit_log\G
*************************** 1. row ***************************
       Table: audit_log
Create Table: CREATE TABLE `audit_log` (
  `id` bigint(20) unsigned NOT NULL AUTO_INCREMENT COMMENT '日志ID',
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100))
) ENGINE=MyISAM AUTO_INCREMENT=14650005 DEFAULT CHARSET=utf8mb4
1 row in set (0.00 sec)

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表中模拟了 1400 万数据（从2021-07-19至2025-07-22每天一万条）：

mysql> SELECT COUNT(*) FROM audit_log;
+----------+
| COUNT(*) |
+----------+
| 14650004 |
+----------+
1 row in set (0.00 sec)

mysql>

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分区前的数据表文件：

➜  data ll demo_db/audit_log*
-rw-r----- 1 dnsmasq systemd-journal  13K  7月 23 11:32 demo_db/audit_log.frm
-rw-r----- 1 dnsmasq systemd-journal 2.2G  7月 23 11:33 demo_db/audit_log.MYD
-rw-r----- 1 dnsmasq systemd-journal 562M  7月 23 11:35 demo_db/audit_log.MYI
➜  data

这个mysql容器之前调试时设置成了 MyISAM，分区表建议使用 InnoDB 存储引擎：

MyISAM 不支持事务，没有 Redo log，无法保证服务崩溃后的数据一致性。

MyISAM 只有表级锁，虽然写入操作只涉及一个分区，但是还是会锁定整张表。

MyISAM 存储引擎下，每个分区都会生成一个 .MYD 和 .MYI 文件，如果是按月或按日的分区，会导致文件系统 inode 和目录项激增，也会快速消耗服务器的文件描述符资源 (open_files_limit)，可能导致 Can't open file 错误。

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转换为按季度的分区表

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步骤1: 移除原自增主键

mysql> ALTER TABLE audit_log DROP PRIMARY KEY, MODIFY id BIGINT UNSIGNED NOT NULL;
Query OK, 14650004 rows affected (2 min 49.20 sec)

mysql>

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步骤2: 添加复合主键 (id + log_time)，分区键必须属于主键（是主键或是主键的一部分）

mysql> ALTER TABLE audit_log ADD PRIMARY KEY (id, log_time);
Query OK, 14650004 rows affected (3 min 5.18 sec)

mysql>

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步骤3: 定义分区方案（按季度分区）

ALTER TABLE audit_log 
PARTITION BY RANGE COLUMNS(log_time) (
    PARTITION p2021Q3 VALUES LESS THAN ('2021-10-01'),
    PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01'),
	PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01'),
	PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01'),
	PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01'),
	PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01'),
	PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01'),
	PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01'),
	PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01'),
	PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01'),
	PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01'),
	PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01'),
	PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01'),
	PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01'),
	PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01'),
	PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01'),
	PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01'),
    PARTITION p_future VALUES LESS THAN (MAXVALUE)
);


mysql> ALTER TABLE audit_log 
    -> PARTITION BY RANGE COLUMNS(log_time) (
    -> PARTITION p2021Q3 VALUES LESS THAN ('2021-10-01'),
    -> PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01'),
    -> PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01'),
    -> PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01'),
    -> PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01'),
    -> PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01'),
    -> PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01'),
    -> PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01'),
    -> PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01'),
    -> PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01'),
    -> PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01'),
    -> PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01'),
    -> PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01'),
    -> PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01'),
    -> PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01'),
    -> PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01'),
    -> PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01'),
    -> PARTITION p_future VALUES LESS THAN (MAXVALUE)
    -> );
Query OK, 14650004 rows affected, 1 warning (2 min 17.65 sec)

mysql>

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分区之后的数据表文件：

➜  data ll demo_db/audit_log*
-rw-r----- 1 dnsmasq systemd-journal  13K  7月 23 11:38 demo_db/audit_log.frm
-rw-r----- 1 dnsmasq systemd-journal  184  7月 23 11:38 demo_db/audit_log.par
-rw-r----- 1 dnsmasq systemd-journal 112M  7月 23 11:38 demo_db/audit_log#P#p2021Q3.MYD
-rw-r----- 1 dnsmasq systemd-journal  92M  7月 23 11:38 demo_db/audit_log#P#p2021Q3.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:38 demo_db/audit_log#P#p2021Q4.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:38 demo_db/audit_log#P#p2021Q4.MYI
-rw-r----- 1 dnsmasq systemd-journal 136M  7月 23 11:38 demo_db/audit_log#P#p2022Q1.MYD
-rw-r----- 1 dnsmasq systemd-journal 112M  7月 23 11:39 demo_db/audit_log#P#p2022Q1.MYI
-rw-r----- 1 dnsmasq systemd-journal 138M  7月 23 11:39 demo_db/audit_log#P#p2022Q2.MYD
-rw-r----- 1 dnsmasq systemd-journal 113M  7月 23 11:39 demo_db/audit_log#P#p2022Q2.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:39 demo_db/audit_log#P#p2022Q3.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:39 demo_db/audit_log#P#p2022Q3.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:39 demo_db/audit_log#P#p2022Q4.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:39 demo_db/audit_log#P#p2022Q4.MYI
-rw-r----- 1 dnsmasq systemd-journal 136M  7月 23 11:39 demo_db/audit_log#P#p2023Q1.MYD
-rw-r----- 1 dnsmasq systemd-journal 112M  7月 23 11:39 demo_db/audit_log#P#p2023Q1.MYI
-rw-r----- 1 dnsmasq systemd-journal 138M  7月 23 11:39 demo_db/audit_log#P#p2023Q2.MYD
-rw-r----- 1 dnsmasq systemd-journal 113M  7月 23 11:39 demo_db/audit_log#P#p2023Q2.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:39 demo_db/audit_log#P#p2023Q3.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:39 demo_db/audit_log#P#p2023Q3.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:39 demo_db/audit_log#P#p2023Q4.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:39 demo_db/audit_log#P#p2023Q4.MYI
-rw-r----- 1 dnsmasq systemd-journal 138M  7月 23 11:39 demo_db/audit_log#P#p2024Q1.MYD
-rw-r----- 1 dnsmasq systemd-journal 113M  7月 23 11:40 demo_db/audit_log#P#p2024Q1.MYI
-rw-r----- 1 dnsmasq systemd-journal 138M  7月 23 11:40 demo_db/audit_log#P#p2024Q2.MYD
-rw-r----- 1 dnsmasq systemd-journal 113M  7月 23 11:40 demo_db/audit_log#P#p2024Q2.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:40 demo_db/audit_log#P#p2024Q3.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:40 demo_db/audit_log#P#p2024Q3.MYI
-rw-r----- 1 dnsmasq systemd-journal 139M  7月 23 11:40 demo_db/audit_log#P#p2024Q4.MYD
-rw-r----- 1 dnsmasq systemd-journal 114M  7月 23 11:40 demo_db/audit_log#P#p2024Q4.MYI
-rw-r----- 1 dnsmasq systemd-journal 136M  7月 23 11:40 demo_db/audit_log#P#p2025Q1.MYD
-rw-r----- 1 dnsmasq systemd-journal 112M  7月 23 11:40 demo_db/audit_log#P#p2025Q1.MYI
-rw-r----- 1 dnsmasq systemd-journal 138M  7月 23 11:40 demo_db/audit_log#P#p2025Q2.MYD
-rw-r----- 1 dnsmasq systemd-journal 113M  7月 23 11:40 demo_db/audit_log#P#p2025Q2.MYI
-rw-r----- 1 dnsmasq systemd-journal  34M  7月 23 11:40 demo_db/audit_log#P#p2025Q3.MYD
-rw-r----- 1 dnsmasq systemd-journal  28M  7月 23 11:40 demo_db/audit_log#P#p2025Q3.MYI
-rw-r----- 1 dnsmasq systemd-journal    0  7月 23 11:38 demo_db/audit_log#P#p_future.MYD
-rw-r----- 1 dnsmasq systemd-journal 2.0K  7月 23 11:38 demo_db/audit_log#P#p_future.MYI
➜  data

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转换后的常规查询对比

按原主键 id 的查询

mysql> use demo_db;

Database changed
mysql> 
mysql> EXPLAIN SELECT * FROM audit_log WHERE id = 10000001\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2021Q3,p2021Q4,p2022Q1,p2022Q2,p2022Q3,p2022Q4,p2023Q1,p2023Q2,p2023Q3,p2023Q4,p2024Q1,p2024Q2,p2024Q3,p2024Q4,p2025Q1,p2025Q2,p2025Q3,p_future
         type: ref
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 8
          ref: const
         rows: 15
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

mysql> 


mysql> use demo_db_bak;

Database changed
mysql> 
mysql> EXPLAIN SELECT * FROM audit_log WHERE id = 10000001\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: NULL
         type: const
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 8
          ref: const
         rows: 1
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

mysql>

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直接按 id 查询，分区后的 type 是 ref，分区前的是 const

type显示的是访问类型，访问类型表示我是以何种方式去访问我们的数据，最容易想的是全表扫描，直接暴力的遍历一张表去寻找需要的数据，效率非常低下。

访问的类型有很多，效率从最好到最坏依次是：

system > const > eq_ref > ref > fulltext > ref_or_null > index_merge > unique_subquery > index_subquery > range > index > ALL

rows: 15 表示优化器预估需检查15行（约等于分区数量），实际是扫描所有分区的主键索引。

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按普通索引字段的查询

mysql> EXPLAIN SELECT * FROM audit_log WHERE operator_id = 'user_000001'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2021Q3,p2021Q4,p2022Q1,p2022Q2,p2022Q3,p2022Q4,p2023Q1,p2023Q2,p2023Q3,p2023Q4,p2024Q1,p2024Q2,p2024Q3,p2024Q4,p2025Q1,p2025Q2,p2025Q3,p_future
         type: ref
possible_keys: aal_idx_operator
          key: aal_idx_operator
      key_len: 258
          ref: const
         rows: 15
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

mysql>



mysql> EXPLAIN SELECT * FROM audit_log WHERE operator_id = 'user_000001'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: NULL
         type: ref
possible_keys: aal_idx_operator
          key: aal_idx_operator
      key_len: 258
          ref: const
         rows: 1
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

mysql>

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按 log_time 范围的查询（跨分区和不跨分区）

mysql> EXPLAIN SELECT * FROM audit_log WHERE log_time between '2025-03-31 00:00:00' and '2025-04-01 23:59:59'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2025Q1,p2025Q2
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 22191
     filtered: 100.00
        Extra: Using index condition
1 row in set, 1 warning (0.00 sec)

mysql>
mysql> EXPLAIN SELECT * FROM audit_log WHERE log_time between '2025-04-01 00:00:00' and '2025-04-01 23:59:59'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2025Q2
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 9472
     filtered: 100.00
        Extra: Using index condition
1 row in set, 1 warning (0.00 sec)

mysql>


mysql> EXPLAIN SELECT * FROM audit_log WHERE log_time between '2025-03-31 00:00:00' and '2025-04-01 23:59:59'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: NULL
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 16468
     filtered: 100.00
        Extra: Using index condition
1 row in set, 1 warning (0.00 sec)

mysql> 
mysql> EXPLAIN SELECT * FROM audit_log WHERE log_time between '2025-04-01 00:00:00' and '2025-04-01 23:59:59'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: NULL
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 8234
     filtered: 100.00
        Extra: Using index condition
1 row in set, 1 warning (0.01 sec)

mysql>

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程序中的查询时间对比

没有指定 log_time 范围，分区后会检索所有分区，查询变慢；

// demo_db 库，1.03ms
// [2025-07-23 14:06:04][1.03]select count(*) as aggregate from `audit_log`
$count = DB::connection('mysql')->table('audit_log')->count();
echo 'count = ' . $count . PHP_EOL; // count = 14650004


// demo_db_bak 库，0.58ms
[2025-07-23 14:06:04][0.58]select count(*) as aggregate from `audit_log`
$count = DB::connection('mysql_test')->table('audit_log')->count();
echo 'count = ' . $count . PHP_EOL; // count = 14650004

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// demo_db 库，12.67ms
// [2025-07-23 14:08:57][12.67]select count(*) as aggregate from `audit_log` where `operator_id` = 'user_000001'
$count = DB::connection('mysql')->table('audit_log')->where('operator_id', '=', 'user_000001')->count();
echo 'count = ' . $count . PHP_EOL; // count = 1


// demo_db_bak 库，0.68ms
// [2025-07-23 14:08:57][0.68]select count(*) as aggregate from `audit_log` where `operator_id` = 'user_000001'
$count = DB::connection('mysql_test')->table('audit_log')->where('operator_id', '=', 'user_000001')->count();
echo 'count = ' . $count . PHP_EOL; // count = 1

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// demo_db 库，80.81ms
[2025-07-23 14:15:12][80.81]select count(*) as aggregate from `audit_log` where `log_time` between '2025-07-01 00:00:00' and '2025-07-31 23:59:59' and `operator_id` = 'user_000001'
$count = DB::connection('mysql')->table('audit_log')->whereBetween('log_time', ['2025-07-01 00:00:00', '2025-07-31 23:59:59'])->where('operator_id', '=', 'user_000001')->count();
echo 'count = ' . $count . PHP_EOL;

// demo_db_bak 库，319.2ms
[2025-07-23 14:15:12][319.2]select count(*) as aggregate from `audit_log` where `log_time` between '2025-07-01 00:00:00' and '2025-07-31 23:59:59' and `operator_id` = 'user_000001'
$count = DB::connection('mysql_test')->table('audit_log')->whereBetween('log_time', ['2025-07-01 00:00:00', '2025-07-31 23:59:59'])->where('operator_id', '=', 'user_000001')->count();
echo 'count = ' . $count . PHP_EOL;

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查看分区数据分布

mysql> SELECT PARTITION_NAME, TABLE_ROWS FROM INFORMATION_SCHEMA.PARTITIONS WHERE TABLE_NAME = 'audit_log';
+----------------+------------+
| PARTITION_NAME | TABLE_ROWS |
+----------------+------------+
| p2021Q3        |     740000 |
| p2021Q4        |     920000 |
| p2022Q1        |     900000 |
| p2022Q2        |     910000 |
| p2022Q3        |     920000 |
| p2022Q4        |     920000 |
| p2023Q1        |     900000 |
| p2023Q2        |     910000 |
| p2023Q3        |     920000 |
| p2023Q4        |     920000 |
| p2024Q1        |     910000 |
| p2024Q2        |     910000 |
| p2024Q3        |     920000 |
| p2024Q4        |     920000 |
| p2025Q1        |     900000 |
| p2025Q2        |     910000 |
| p2025Q3        |     220004 |
| p_future       |          0 |
| NULL           |   14650004 |
+----------------+------------+
19 rows in set (0.00 sec)

mysql>

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在摘要描述字段上的模糊搜索

摘要描述字段上的索引是 aal_idx_summary (action_summary(100))，使用 “%搜索内容%” 时索引不生效，对比下此时的查询：

mysql> SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00'\G
*************************** 1. row ***************************
COUNT(*): 220004
1 row in set (0.02 sec)

mysql> 
mysql> EXPLAIN SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00' AND action_summary LIKE '%系统配置%'\G 
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2025Q3,p_future
         type: ALL
possible_keys: aal_idx_log_time
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 220004
     filtered: 11.11
        Extra: Using where
1 row in set, 2 warnings (0.00 sec)

mysql> 
mysql> SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00' AND action_summary LIKE '%系统配置%'\G
*************************** 1. row ***************************
COUNT(*): 55001
1 row in set (0.06 sec)

mysql>


mysql> SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00'\G
*************************** 1. row ***************************
COUNT(*): 220004
1 row in set (0.03 sec)

mysql> 
mysql> EXPLAIN SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00' AND action_summary LIKE '%系统配置%'\G 
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: NULL
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 152015
     filtered: 11.11
        Extra: Using index condition; Using where
1 row in set, 1 warning (0.01 sec)

mysql>
mysql> SELECT COUNT(*) FROM audit_log WHERE log_time > '2025-07-01 00:00:00' AND action_summary LIKE '%系统配置%'\G
*************************** 1. row ***************************
COUNT(*): 55001
1 row in set (0.27 sec)

mysql>

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MySQL 5.6+ 并且是InnoDB时，可以增加全文索引

ALTER TABLE audit_log ADD FULLTEXT ft_action_summary (action_summary);

查询时使用：（执行计划将从 ALL → fulltext，性能提升10倍以上）：
SELECT 
	COUNT(*) 
FROM 
	audit_log 
WHERE 
	log_time > '2025-07-01'
	AND MATCH(action_summary) AGAINST('系统配置' IN BOOLEAN MODE);

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按 log_time 进行分区后，禁止在该字段上做函数转换

-- 错误示范
SELECT * FROM audit_log WHERE DATE(log_time) BETWEEN '2024-03-16' AND '2024-04-15';
SELECT * FROM audit_log WHERE YEAR(log_time) = 2024 AND QUARTER(log_time) = 2;

-- 正确示范：
SELECT * FROM audit_log WHERE log_time >= '2024-03-16 00:00:00' AND log_time <= '2024-04-15 23:59:59';
SELECT * FROM audit_log WHERE log_time >= '2024-04-01 00:00:00' AND log_time <= '2024-06-30 23:59:59';

破坏索引使用：对字段使用函数后，MySQL 无法使用该字段的索引；
破坏分区裁剪：分区优化依赖字段的原始值，函数处理会使优化器无法识别分区边界；
强制全表扫描：每次查询都需要对所有分区数据执行函数计算；

‍

查询优化

当查询条件跨越多个分区（如 WHERE log_time BETWEEN '2024-03-16' AND '2024-04-15' 跨越Q1和Q2分区）时，可采取以下优化策略：
分区裁剪优化（核心策略）

确保分区裁剪生效，禁止在分区字段上使用函数

-- 禁止在分区字段（这里是 log_time）上使用函数
SELECT * FROM audit_log WHERE YEAR(log_time) = 2025;
-- 确保使用直接日期比较
SELECT count(*) FROM audit_log WHERE log_time >= '2025-01-01 00:00:00';

-- 明确指定分区范围（当已知分区时）
SELECT * FROM audit_log PARTITION (p2024Q1, p2024Q2) WHERE log_time BETWEEN '2024-03-16' AND '2024-04-15';

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覆盖索引+分区提示优化

-- 未优化查询 (跨两个季度分区)
SELECT COUNT(*) FROM audit_log WHERE log_time >= '2024-03-16 00:00:00' AND log_time <= '2024-04-15 23:59:59' AND action_type = 'UPDATE';

-- 添加覆盖索引
ALTER TABLE audit_log ADD INDEX idx_cross_partition (log_time, action_type, operator_id);

-- 优化后 (覆盖索引+分区提示)
SELECT COUNT(*) FROM audit_log PARTITION (p2024Q1, p2024Q2) USE INDEX (idx_cross_partition) WHERE log_time BETWEEN '2024-03-16 00:00:00' AND '2024-04-15 23:59:59' AND action_type = 'UPDATE';

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-- 未优化查询 (跨两个季度分区)
mysql> SELECT COUNT(*) FROM audit_log WHERE log_time >= '2024-03-16 00:00:00' AND log_time <= '2024-04-15 23:59:59' AND action_type = 'UPDATE'\G
*************************** 1. row ***************************
COUNT(*): 0
1 row in set (0.38 sec)

mysql> 
mysql> 
mysql> EXPLAIN SELECT COUNT(*) FROM audit_log WHERE log_time >= '2024-03-16 00:00:00' AND log_time <= '2024-04-15 23:59:59'
 AND action_type = 'UPDATE'\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2024Q1,p2024Q2
         type: range
possible_keys: aal_idx_log_time
          key: aal_idx_log_time
      key_len: 5
          ref: NULL
         rows: 323026
     filtered: 10.00
        Extra: Using index condition; Using where
1 row in set, 1 warning (0.00 sec)

mysql> 


mysql> ALTER TABLE audit_log ADD INDEX idx_cross_partition (log_time, action_type, operator_id);
Query OK, 14650004 rows affected, 1 warning (2 min 49.10 sec)

mysql> 


-- 优化后 (覆盖索引+分区提示)
mysql> SELECT COUNT(*) FROM audit_log PARTITION (p2024Q1, p2024Q2) USE INDEX (idx_cross_partition) WHERE log_time BETWEEN '2024-03-16 00:00:00' AND '2024-04-15 23:59:59' AND action_type = 'UPDATE'\G
*************************** 1. row ***************************
COUNT(*): 0
1 row in set (0.09 sec)

mysql> 
mysql> EXPLAIN SELECT COUNT(*) FROM audit_log PARTITION (p2024Q1, p2024Q2) USE INDEX (idx_cross_partition) WHERE log_time BETWEEN
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: audit_log
   partitions: p2024Q1,p2024Q2
         type: range
possible_keys: idx_cross_partition
          key: idx_cross_partition
      key_len: 207
          ref: NULL
         rows: 362118
     filtered: 10.00
        Extra: Using where; Using index
1 row in set, 1 warning (0.00 sec)

mysql>

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添加覆盖索引前的执行计划：Using index condition; Using where，先过滤时间，再回表过滤 action_type。

添加覆盖索引后的执行计划：Using where; Using index，直接在覆盖索引中完成过滤；

‍

历史数据的归档

历史数据归档后，系统中如果还需要提供这部分数据的查询服务，需要提供单独的查询入口，或者在查询的业务逻辑中根据查询的日期范围切换所连接的数据表（或数据库）。

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步骤1：创建与分区结构完全相同的归档表

CREATE TABLE audit_log_archive_2021Q3 LIKE audit_log;

-- 移除归档表的分区定义（使其成为普通表）
ALTER TABLE audit_log_archive_2021Q3 REMOVE PARTITIONING;

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操作记录：

mysql> CREATE TABLE audit_log_archive_2021Q3 LIKE audit_log;
Query OK, 0 rows affected, 1 warning (0.02 sec)

mysql>
mysql> SHOW CREATE TABLE audit_log_archive_2021Q3\G
*************************** 1. row ***************************
       Table: audit_log_archive_2021Q3
Create Table: CREATE TABLE `audit_log_archive_2021Q3` (
  `id` bigint(20) unsigned NOT NULL,
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`,`log_time`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100)),
  KEY `idx_cross_partition` (`log_time`,`action_type`,`operator_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8mb4
/*!50500 PARTITION BY RANGE  COLUMNS(log_time)
(PARTITION p2021Q3 VALUES LESS THAN ('2021-10-01') ENGINE = MyISAM,
 PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01') ENGINE = MyISAM,
 PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01') ENGINE = MyISAM,
 PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01') ENGINE = MyISAM,
 PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01') ENGINE = MyISAM,
 PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01') ENGINE = MyISAM,
 PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01') ENGINE = MyISAM,
 PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01') ENGINE = MyISAM,
 PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01') ENGINE = MyISAM,
 PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01') ENGINE = MyISAM,
 PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01') ENGINE = MyISAM,
 PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01') ENGINE = MyISAM,
 PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01') ENGINE = MyISAM,
 PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01') ENGINE = MyISAM,
 PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01') ENGINE = MyISAM,
 PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01') ENGINE = MyISAM,
 PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01') ENGINE = MyISAM,
 PARTITION p_future VALUES LESS THAN (MAXVALUE) ENGINE = MyISAM) */
1 row in set, 1 warning (0.00 sec)

mysql> 
mysql> ALTER TABLE audit_log_archive_2021Q3 REMOVE PARTITIONING;
Query OK, 0 rows affected (0.02 sec)

mysql> 
mysql> SHOW CREATE TABLE audit_log_archive_2021Q3\G
*************************** 1. row ***************************
       Table: audit_log_archive_2021Q3
Create Table: CREATE TABLE `audit_log_archive_2021Q3` (
  `id` bigint(20) unsigned NOT NULL,
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`,`log_time`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100)),
  KEY `idx_cross_partition` (`log_time`,`action_type`,`operator_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8mb4
1 row in set (0.00 sec)

mysql>

‍

步骤2：执行分区交换

ALTER TABLE audit_log EXCHANGE PARTITION p2021Q3 WITH TABLE audit_log_archive_2021Q3;

‍

操作记录：

mysql> ALTER TABLE audit_log EXCHANGE PARTITION p2021Q3 WITH TABLE audit_log_archive_2021Q3;
Query OK, 0 rows affected (0.01 sec)

mysql>
mysql> SELECT COUNT(*) FROM audit_log_archive_2021Q3;
+----------+
| COUNT(*) |
+----------+
|   740000 |
+----------+
1 row in set (0.00 sec)

mysql>

‍

步骤3：验证后删除原分区

-- 检查交换后分区是否为空
SELECT COUNT(*) FROM audit_log PARTITION (p2021Q3);

-- 删除空分区
ALTER TABLE audit_log DROP PARTITION p2021Q3;

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操作记录：

mysql> SELECT COUNT(*) FROM audit_log PARTITION (p2021Q3);
+----------+
| COUNT(*) |
+----------+
|        0 |
+----------+
1 row in set, 1 warning (0.01 sec)

mysql> 
mysql> ALTER TABLE audit_log DROP PARTITION p2021Q3;
Query OK, 0 rows affected, 1 warning (0.02 sec)

mysql>
mysql> SHOW CREATE TABLE audit_log\G
*************************** 1. row ***************************
       Table: audit_log
Create Table: CREATE TABLE `audit_log` (
  `id` bigint(20) unsigned NOT NULL,
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`,`log_time`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100)),
  KEY `idx_cross_partition` (`log_time`,`action_type`,`operator_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8mb4
/*!50500 PARTITION BY RANGE  COLUMNS(log_time)
(PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01') ENGINE = MyISAM,
 PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01') ENGINE = MyISAM,
 PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01') ENGINE = MyISAM,
 PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01') ENGINE = MyISAM,
 PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01') ENGINE = MyISAM,
 PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01') ENGINE = MyISAM,
 PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01') ENGINE = MyISAM,
 PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01') ENGINE = MyISAM,
 PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01') ENGINE = MyISAM,
 PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01') ENGINE = MyISAM,
 PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01') ENGINE = MyISAM,
 PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01') ENGINE = MyISAM,
 PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01') ENGINE = MyISAM,
 PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01') ENGINE = MyISAM,
 PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01') ENGINE = MyISAM,
 PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01') ENGINE = MyISAM,
 PARTITION p_future VALUES LESS THAN (MAXVALUE) ENGINE = MyISAM) */
1 row in set, 1 warning (0.00 sec)

mysql>

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将归档的数据迁移到同实例的其他数据库

mysql> RENAME TABLE demo_db.audit_log_archive_2021Q3 TO demo_db_bak.audit_log_archive_2021Q3; 
Query OK, 0 rows affected (0.01 sec)

mysql>

当前操作的用户要有这两个库的权限；

如果存储引擎是 InnoDB 的可以对迁移后的数据进行压缩：ALTER TABLE audit_log_archive_2021Q3 ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;

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迁移到不同的MySQL服务器

# 1. 导出表结构和数据
mysqldump -uroot -p demo_db audit_log_archive_2021Q3 > archive_2021Q3.sql;

# 2. 传输文件到目标服务器
scp archive_2021Q3.sql user@remote-server:/tmp/

# 3. 在目标服务器导入
mysql -u root -p demo_db_bak < /tmp/archive_2021Q3.sql

# 4. 在当前服务器上删除当前归档表
DROP TABLE current_db.audit_log_archive_2021Q3;

若目标服务器使用不同 MySQL 版本，需测试兼容性；

‍

定期添加新分区

如：提前添加下一个季度（2025-09-30 之前添加 2025Q4 分区），或者提前添加下一年的分区（2025-12-31 之前添加 2026Q1，2026Q2，2026Q3，2026Q4）

-- 示例：添加下一季度（2025Q4）的分区
ALTER TABLE audit_log REORGANIZE PARTITION p_future INTO (
    PARTITION p2025Q4 VALUES LESS THAN ('2026-01-01'),
    PARTITION p_future VALUES LESS THAN (MAXVALUE)
);

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操作记录：

mysql> ALTER TABLE audit_log REORGANIZE PARTITION p_future INTO (
    ->     PARTITION p2025Q4 VALUES LESS THAN ('2026-01-01'),
    ->     PARTITION p_future VALUES LESS THAN (MAXVALUE)
    -> );
Query OK, 0 rows affected, 1 warning (0.01 sec)

mysql> 
mysql> SHOW CREATE TABLE audit_log\G
*************************** 1. row ***************************
       Table: audit_log
Create Table: CREATE TABLE `audit_log` (
  `id` bigint(20) unsigned NOT NULL,
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`,`log_time`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100)),
  KEY `idx_cross_partition` (`log_time`,`action_type`,`operator_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8mb4
/*!50500 PARTITION BY RANGE  COLUMNS(log_time)
(PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01') ENGINE = MyISAM,
 PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01') ENGINE = MyISAM,
 PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01') ENGINE = MyISAM,
 PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01') ENGINE = MyISAM,
 PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01') ENGINE = MyISAM,
 PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01') ENGINE = MyISAM,
 PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01') ENGINE = MyISAM,
 PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01') ENGINE = MyISAM,
 PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01') ENGINE = MyISAM,
 PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01') ENGINE = MyISAM,
 PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01') ENGINE = MyISAM,
 PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01') ENGINE = MyISAM,
 PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01') ENGINE = MyISAM,
 PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01') ENGINE = MyISAM,
 PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01') ENGINE = MyISAM,
 PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01') ENGINE = MyISAM,
 PARTITION p2025Q4 VALUES LESS THAN ('2026-01-01') ENGINE = MyISAM,
 PARTITION p_future VALUES LESS THAN (MAXVALUE) ENGINE = MyISAM) */
1 row in set, 1 warning (0.00 sec)

mysql>

‍

建议分区表还是在 InnoDB 下使用，将 audit_log 转为 InnoDB

-- 转换表引擎
ALTER TABLE audit_log ENGINE=InnoDB;
-- 转换后需重建所有分区
ALTER TABLE audit_log REBUILD PARTITION ALL;

‍

mysql> ALTER TABLE audit_log ENGINE=InnoDB;
Query OK, 13910004 rows affected (2 min 34.70 sec)

mysql> 
mysql> ALTER TABLE audit_log REBUILD PARTITION ALL;
Query OK, 0 rows affected (3 min 50.76 sec)

mysql> 
mysql> SHOW CREATE TABLE audit_log\G
*************************** 1. row ***************************
       Table: audit_log
Create Table: CREATE TABLE `audit_log` (
  `id` bigint(20) unsigned NOT NULL,
  `log_time` datetime NOT NULL COMMENT '日志产生时间',
  `operator_id` varchar(64) NOT NULL COMMENT '操作人ID (索引)',
  `operator_name` varchar(128) NOT NULL COMMENT '操作人名称快照',
  `action_type` varchar(50) NOT NULL COMMENT '操作类型',
  `target_type` varchar(50) NOT NULL COMMENT '目标类型',
  `target_id` varchar(64) NOT NULL COMMENT '目标ID',
  `target_name` varchar(255) NOT NULL COMMENT '目标名称快照',
  `action_summary` varchar(500) NOT NULL COMMENT '操作摘要描述',
  `change_count` int(10) unsigned DEFAULT '0' COMMENT '变更项数量',
  `entity_count` int(10) unsigned DEFAULT '0' COMMENT '涉及实体数量',
  PRIMARY KEY (`id`,`log_time`),
  KEY `aal_idx_log_time` (`log_time`),
  KEY `aal_idx_operator` (`operator_id`),
  KEY `aal_idx_target` (`target_type`,`target_id`),
  KEY `aal_idx_summary` (`action_summary`(100)),
  KEY `idx_cross_partition` (`log_time`,`action_type`,`operator_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
/*!50500 PARTITION BY RANGE  COLUMNS(log_time)
(PARTITION p2021Q4 VALUES LESS THAN ('2022-01-01') ENGINE = InnoDB,
 PARTITION p2022Q1 VALUES LESS THAN ('2022-04-01') ENGINE = InnoDB,
 PARTITION p2022Q2 VALUES LESS THAN ('2022-07-01') ENGINE = InnoDB,
 PARTITION p2022Q3 VALUES LESS THAN ('2022-10-01') ENGINE = InnoDB,
 PARTITION p2022Q4 VALUES LESS THAN ('2023-01-01') ENGINE = InnoDB,
 PARTITION p2023Q1 VALUES LESS THAN ('2023-04-01') ENGINE = InnoDB,
 PARTITION p2023Q2 VALUES LESS THAN ('2023-07-01') ENGINE = InnoDB,
 PARTITION p2023Q3 VALUES LESS THAN ('2023-10-01') ENGINE = InnoDB,
 PARTITION p2023Q4 VALUES LESS THAN ('2024-01-01') ENGINE = InnoDB,
 PARTITION p2024Q1 VALUES LESS THAN ('2024-04-01') ENGINE = InnoDB,
 PARTITION p2024Q2 VALUES LESS THAN ('2024-07-01') ENGINE = InnoDB,
 PARTITION p2024Q3 VALUES LESS THAN ('2024-10-01') ENGINE = InnoDB,
 PARTITION p2024Q4 VALUES LESS THAN ('2025-01-01') ENGINE = InnoDB,
 PARTITION p2025Q1 VALUES LESS THAN ('2025-04-01') ENGINE = InnoDB,
 PARTITION p2025Q2 VALUES LESS THAN ('2025-07-01') ENGINE = InnoDB,
 PARTITION p2025Q3 VALUES LESS THAN ('2025-10-01') ENGINE = InnoDB,
 PARTITION p2025Q4 VALUES LESS THAN ('2026-01-01') ENGINE = InnoDB,
 PARTITION p_future VALUES LESS THAN (MAXVALUE) ENGINE = InnoDB) */
1 row in set (0.00 sec)

mysql>

‍

posted @ 2025-08-12 09:22 zhpj 阅读(16) 评论(0) 收藏举报

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zhpj

记录下MySQL的分区表

记录下MySQL的分区表

分区表的结构

转换为按季度的分区表

转换后的常规查询对比

按原主键 id 的查询

按普通索引字段的查询

按 log_time 范围的查询（跨分区和不跨分区）

程序中的查询时间对比

查看分区数据分布

在摘要描述字段上的模糊搜索

按 log_time 进行分区后，禁止在该字段上做函数转换

查询优化

确保分区裁剪生效，禁止在分区字段上使用函数

覆盖索引+分区提示优化

历史数据的归档

将归档的数据迁移到同实例的其他数据库

迁移到不同的MySQL服务器

定期添加新分区

建议分区表还是在 InnoDB 下使用，将 audit_log 转为 InnoDB

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