MySQL表碎片整理
计算碎片大小
整理碎片
整理表碎片shell脚本
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 + Index_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.
需要表上有主键或唯一索引才能执行
[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
#!/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
