MySQL表碎片整理

1. 计算碎片大小

要整理碎片，首先要了解碎片的计算方法。

可以通过show table [from|in db_name] status like '%table_name%'命令查看：

mysql> show table from employees status like 't1'G
*************************** 1. row ***************************
           Name: t1
         Engine: InnoDB
        Version: 10
     Row_format: Dynamic
           Rows: 1176484
 Avg_row_length: 86
    Data_length: 101842944
Max_data_length: 0
   Index_length: 0
      Data_free: 39845888
 Auto_increment: NULL
    Create_time: 2018-08-28 13:40:19
    Update_time: 2018-08-28 13:50:43
     Check_time: NULL
      Collation: utf8mb4_general_ci
       Checksum: NULL
 Create_options: 
        Comment: 
1 row in set (0.00 sec)

碎片大小 = 数据总大小 - 实际表空间文件大小

• 数据总大小 = Data_length + Data_length = 101842944

• 实际表空间文件大小 = rows * Avg_row_length = 1176484 * 86 = 101177624

• 碎片大小 = (101842944 - 101177624) / 1024 /1024 = 0.63MB

通过information_schema.tables的DATA_FREE列查看表有没有碎片：

SELECT t.TABLE_SCHEMA,
       t.TABLE_NAME,
       t.TABLE_ROWS,
       t.DATA_LENGTH,
       t.INDEX_LENGTH,
       concat(round(t.DATA_FREE / 1024 / 1024, 2), 'M') AS datafree
FROM information_schema.tables t
WHERE t.TABLE_SCHEMA = 'employees'


+--------------+--------------+------------+-------------+--------------+----------+
| TABLE_SCHEMA | TABLE_NAME   | TABLE_ROWS | DATA_LENGTH | INDEX_LENGTH | datafree |
+--------------+--------------+------------+-------------+--------------+----------+
| employees    | departments  |          9 |       16384 |        16384 | 0.00M    |
| employees    | dept_emp     |     331143 |    12075008 |     11567104 | 0.00M    |
| employees    | dept_manager |         24 |       16384 |        32768 | 0.00M    |
| employees    | employees    |     299335 |    15220736 |            0 | 0.00M    |
| employees    | salaries     |    2838426 |   100270080 |     36241408 | 5.00M    |
| employees    | t1           |    1191784 |    48824320 |     17317888 | 5.00M    |
| employees    | titles       |     442902 |    20512768 |     11059200 | 0.00M    |
| employees    | ttt          |          2 |       16384 |            0 | 0.00M    |
+--------------+--------------+------------+-------------+--------------+----------+
8 rows in set (0.00 sec)

2. 整理碎片

2.1 使用alter table table_name engine = innodb命令进行整理。

 root@localhost [employees] 14:27:01> alter table t1   engine=innodb;

 Query OK, 0 rows affected (5.69 sec)
 Records: 0  Duplicates: 0  Warnings: 0

 root@localhost [employees] 14:27:15> show table status like 't1'G
 *************************** 1. row ***************************
           Name: t1
         Engine: InnoDB
        Version: 10
     Row_format: Dynamic
           Rows: 1191062
 Avg_row_length: 48
    Data_length: 57229312
Max_data_length: 0
   Index_length: 0
      Data_free: 2097152
 Auto_increment: NULL
    Create_time: 2018-08-28 14:27:15
    Update_time: NULL
     Check_time: NULL
      Collation: utf8mb4_general_ci
       Checksum: NULL
 Create_options: 
        Comment: 
 1 row in set (0.00 sec)

2.2 使用pt-online-schema-change工具也能进行在线整理表结构，收集碎片等操作。

 [root@mysqldb1 14:29:29 /root]
 # pt-online-schema-change --alter="ENGINE=innodb" D=employees,t=t1 --execute
 Cannot chunk the original table `employees`.`t1`: There is no good index and the table is oversized. at /opt/percona-toolkit-3.0.11/bin/pt-online-schema-change line 5852.

 需表上有主键或唯一索引才能运行

 [root@mysqldb1 14:31:16 /root]
# pt-online-schema-change --alter='engine=innodb' D=employees,t=salaries --execute
No slaves found.  See --recursion-method if host mysqldb1 has slaves.
Not checking slave lag because no slaves were found and --check-slave-lag was not specified.
Operation, tries, wait:
  analyze_table, 10, 1
  copy_rows, 10, 0.25
  create_triggers, 10, 1
  drop_triggers, 10, 1
  swap_tables, 10, 1
  update_foreign_keys, 10, 1
Altering `employees`.`salaries`...
Creating new table...
Created new table employees._salaries_new OK.
Altering new table...
Altered `employees`.`_salaries_new` OK.
2018-08-28T14:37:01 Creating triggers...
2018-08-28T14:37:01 Created triggers OK.
2018-08-28T14:37:01 Copying approximately 2838426 rows...
Copying `employees`.`salaries`:  74% 00:10 remain
2018-08-28T14:37:41 Copied rows OK.
2018-08-28T14:37:41 Analyzing new table...
2018-08-28T14:37:42 Swapping tables...
2018-08-28T14:37:42 Swapped original and new tables OK.
2018-08-28T14:37:42 Dropping old table...
2018-08-28T14:37:42 Dropped old table `employees`.`_salaries_old` OK.
2018-08-28T14:37:42 Dropping triggers...
2018-08-28T14:37:42 Dropped triggers OK.
Successfully altered `employees`.`salaries`.

2.3 使用optimize table命令，整理碎片。

运行OPTIMIZE TABLE， InnoDB创建一个新的.ibd具有临时名称的文件，只使用存储的实际数据所需的空间。优化完成后，InnoDB删除旧.ibd文件并将其替换为新文件。如果先前的.ibd文件显着增长但实际数据仅占其大小的一部分，则运行OPTIMIZE TABLE可以回收未使用的空间。

mysql>optimize table account;
+--------------+----------+----------+-------------------------------------------------------------------+
| Table        | Op       | Msg_type | Msg_text                                                          |
+--------------+----------+----------+-------------------------------------------------------------------+
| test.account | optimize | note     | Table does not support optimize, doing recreate + analyze instead |
| test.account | optimize | status   | OK                                                                |
+--------------+----------+----------+-------------------------------------------------------------------+
2 rows in set (0.09 sec)

3.整理表碎片shell脚本

# cat optimize_table.sh

#!/bin/sh
socket=/tmp/mysql3306.sock
time=`date +"%Y-%m-%d"`
SQL="select concat(d.TABLE_SCHEMA,'.',d.TABLE_NAME) from information_schema.TABLES d where d.TABLE_SCHEMA = 'employees'"

optimize_table_name=$(/usr/local/mysql/bin/mysql -S $socket -e "$SQL"|grep -v "TABLE_NAME")

echo "Begin Optimize Table at: "`date +"%Y-%m-%d %H:%M:%S"`>/tmp/optimize_table_$time.log

for table_list in $optimize_table_name
do

echo `date +"%Y-%m-%d %H:%M:%S"` "alter table $table_list engine=innodb ...">>/tmp/optimize_table_$time.log
/usr/local/mysql/bin/mysql -S $socket -e "alter table $table_list engine=innoDB"

done
echo "End Optimize Table at: "`date +"%Y-%m-%d %H:%M:%S"`>>/tmp/optimize_table_$time.log

输出内容

# cat optimize_table_2018-08-30.log

Begin Optimize Table at: 2018-08-30 08:43:21
2018-08-30 08:43:21 alter table employees.departments engine=innodb ...
2018-08-30 08:43:21 alter table employees.dept_emp engine=innodb ...
2018-08-30 08:43:27 alter table employees.dept_manager engine=innodb ...
2018-08-30 08:43:27 alter table employees.employees engine=innodb ...
2018-08-30 08:43:32 alter table employees.salaries engine=innodb ...
2018-08-30 08:44:02 alter table employees.t1 engine=innodb ...
2018-08-30 08:44:17 alter table employees.titles engine=innodb ...
2018-08-30 08:44:28 alter table employees.ttt engine=innodb ...
End Optimize Table at: 2018-08-30 08:44:28