本文档主要介绍了PolarDB的在线分区维护功能。
在MySQL社区版中,对分区表数据的访问操作(DML)与分区维护操作(DDL)是相互阻塞的,这使得分区维护操作只能在业务低峰时段进行。而对分区表进行创建和删除分区操作是比较频繁的,这极大限制了分区表的使用。在线分区维护功能增强了分区的DML和特定DDL(增加、删除分区)的并行能力,更好的让用户对分区表进行Roll-In和Roll-Out。如下图所示:
前提条件
集群版本需为PolarDB MySQL版8.0版本且小版本为8.0.2.2.0及以上。您可以通过查询版本号确认集群版本。
已经开启partition_level_mdl_enabled参数。具体操作请参见设置集群参数和节点参数。
参数名称
级别
参数说明
loose_partition_level_mdl_enabled
Global
PARTITION Level MDL功能开关,取值范围如下:
ON:开启PARTITION Level MDL功能
OFF:关闭PARTITION Level MDL功能
说明修改该参数需要重启集群。
transaction_isolation参数的全局隔离级别需要设置为READ-COMMITTED。具体操作请参见设置集群参数和节点参数。
使用限制
目前支持DROP/EXCHANGE/REBUILD/REORGANIZE PARTITION操作、RANGE和LIST分区方式的ADD PARTITION操作的在线分区维护功能,其他DDL操作将在后续版本支持。
由于隔离级别可以设置为session级别,如果transaction-isolation设置为REPEATABLE-READ或者更强的隔离级别,在并发执行DDL过程中,可能会报错
ERROR HY000: Table definition has changed, please retry transaction
,这属于正常现象。原因是事务访问到了DDL所创建出来的新分区,可通过重新执行事务解决。
使用说明及示例
在线分区维护功能,使得分区表的数据访问和分区维护相互不影响,用户可以更自由的进行分区维护,而不影响分区表业务流量,使用示例及效果如下:
#在客户端1上输出tr表结构
SHOW CREATE TABLE tr\G
*************************** 1. row ***************************
Table: tr
Create Table: CREATE TABLE `tr` (
`id` int(11) DEFAULT NULL,
`name` varchar(50) DEFAULT NULL,
`purchased` date DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci
/*!50100 PARTITION BY RANGE (year(`purchased`))
(PARTITION p0 VALUES LESS THAN (1990) ENGINE = InnoDB,
PARTITION p1 VALUES LESS THAN (1995) ENGINE = InnoDB,
PARTITION p2 VALUES LESS THAN (2000) ENGINE = InnoDB,
PARTITION p3 VALUES LESS THAN (2005) ENGINE = InnoDB,
PARTITION p4 VALUES LESS THAN (2010) ENGINE = InnoDB,
PARTITION p5 VALUES LESS THAN (2015) ENGINE = InnoDB) */
1 row in set (0.00 sec)
#在客户端1上开启事务
BEGIN;
Query OK, 0 rows affected (0.01 sec)
SELECT * FROM tr WHERE purchased >= '2010-01-01';
+------+----------------+------------+
| id | name | purchased |
+------+----------------+------------+
| 5 | exercise bike | 2014-05-09 |
| 7 | espresso maker | 2011-11-22 |
+------+----------------+------------+
2 rows in set (0.01 sec)
#在客户端2上创建新分区
ALTER TABLE tr ADD PARTITION (PARTITION p6 VALUES LESS THAN (2020));
INSERT INTO tr VALUES (11, 'hope', '2017-11-04'), (12, 'carmen', '2018-06-08');
#在同一个事务内,通过客户端1可以访问到新增分区的数据
SELECT * FROM tr WHERE purchased >= '2010-01-01';
+------+----------------+------------+
| id | name | purchased |
+------+----------------+------------+
| 5 | exercise bike | 2014-05-09 |
| 7 | espresso maker | 2011-11-22 |
| 11 | hope | 2017-11-04 |
| 12 | carmen | 2018-06-08 |
+------+----------------+------------+
4 rows in set (0.00 sec)
#在客户端2上删除旧分区
ALTER TABLE tr DROP PARTITION p0;
#在客户端1上输出表定义,可以看到新分区p6存在,旧分区p0已不存在
SHOW CREATE TABLE tr\G
*************************** 1. row ***************************
Table: tr
Create Table: CREATE TABLE `tr` (
`id` int(11) DEFAULT NULL,
`name` varchar(50) DEFAULT NULL,
`purchased` date DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci
/*!50100 PARTITION BY RANGE (year(`purchased`))
(PARTITION p1 VALUES LESS THAN (1995) ENGINE = InnoDB,
PARTITION p2 VALUES LESS THAN (2000) ENGINE = InnoDB,
PARTITION p3 VALUES LESS THAN (2005) ENGINE = InnoDB,
PARTITION p4 VALUES LESS THAN (2010) ENGINE = InnoDB,
PARTITION p5 VALUES LESS THAN (2015) ENGINE = InnoDB,
PARTITION p6 VALUES LESS THAN (2020) ENGINE = InnoDB) */
1 row in set (0.00 sec)
#在客户端1上提交事务
COMMIT;
性能表现
下面针对DML和DDL交互下的两种最主要场景长事务阻塞DDL和耗时DDL,在分别开启和关闭在线分区维护功能的情况下,进行性能对比验证。
场景一:长事务阻塞DDL
此场景下对分区表做分区维护DDL操作,由于存在未提交的长事务,从而阻塞DDL操作的进行。被阻塞的DDL操作会进一步阻塞所有新产生的DML操作,导致了数据库流量跌零。
从上图可以看到,在功能关闭时,当DDL操作发生后,sysbench在该表的流量迅速跌零,数据库呈现完全不可用的状态。用户只能通过取消DDL操作或者提交所有未提交的长事务后,数据库才能恢复正常;在功能开启后,可以看到:
在正常情况下,sysbench的吞吐量与在线分区维护功能关闭时完全一致,说明在线分区维护功能的引入并没有带来性能方面的损耗;
未提交的长事务并不会阻塞分区维护操作的执行,同时数据库上的DML流量很稳定,几乎没有受到影响。
场景二:耗时DDL
该场景下,分区维护DDL操作虽然没有受到其他SQL语句的阻塞,但是在本身执行分区维护DDL操作耗时的情况下,对DML吞吐量有影响。
从上图可以看到,在功能关闭时,长耗时DDL操作在执行期间导致了DML吞吐量的剧烈抖动;在功能开启后,长耗时DDL操作在执行期间对 DML的吞吐量几乎没有影响。
查看MDL锁状态
在线分区维护功能是通过引入分区级别的MDL锁,来降低在DML和DDL过程中获取的锁粒度,从而增加并发性来实现的。在分区维护过程中,通过performance_schema.metadata_locks
表可以查看分区级别的MDL锁获取情况。示例如下:
#在客户端1上输出tr表结构
SHOW CREATE TABLE tr\G
*************************** 1. row ***************************
Table: tr
Create Table: CREATE TABLE `tr` (
`id` int(11) DEFAULT NULL,
`name` varchar(50) DEFAULT NULL,
`purchased` date DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci
/*!50100 PARTITION BY RANGE (year(`purchased`))
(PARTITION p0 VALUES LESS THAN (1990) ENGINE = InnoDB,
PARTITION p1 VALUES LESS THAN (1995) ENGINE = InnoDB,
PARTITION p2 VALUES LESS THAN (2000) ENGINE = InnoDB,
PARTITION p3 VALUES LESS THAN (2005) ENGINE = InnoDB,
PARTITION p4 VALUES LESS THAN (2010) ENGINE = InnoDB,
PARTITION p5 VALUES LESS THAN (2015) ENGINE = InnoDB) */
1 row in set (0.00 sec)
#在客户端1上开启事务
BEGIN;
Query OK, 0 rows affected (0.01 sec)
SELECT * FROM tr WHERE purchased >= '2010-01-01';
+------+----------------+------------+
| id | name | purchased |
+------+----------------+------------+
| 5 | exercise bike | 2014-05-09 |
| 7 | espresso maker | 2011-11-22 |
+------+----------------+------------+
2 rows in set (0.01 sec)
#在客户端1上查看MDL锁的状态
SELECT * FROM performance_schema.metadata_locks;
+-------------+--------------------+----------------+-------------+-----------------------+---------------------+---------------+-------------+-------------------+-----------------+----------------+
| OBJECT_TYPE | OBJECT_SCHEMA | OBJECT_NAME | COLUMN_NAME | OBJECT_INSTANCE_BEGIN | LOCK_TYPE | LOCK_DURATION | LOCK_STATUS | SOURCE | OWNER_THREAD_ID | OWNER_EVENT_ID |
+-------------+--------------------+----------------+-------------+-----------------------+---------------------+---------------+-------------+-------------------+-----------------+----------------+
| TABLE | test | tr | NULL | 140734887898944 | SHARED_READ | TRANSACTION | GRANTED | sql_parse.cc:6759 | 67 | 17 |
| PARTITION | test | tr | p5 | 140734887896704 | SHARED_READ | TRANSACTION | GRANTED | sql_parse.cc:6502 | 67 | 17 |
| TABLE | performance_schema | metadata_locks | NULL | 140734879511488 | SHARED_READ | TRANSACTION | GRANTED | sql_parse.cc:6759 | 68 | 4 |
| SCHEMA | performance_schema | NULL | NULL | 140734879511648 | INTENTION_EXCLUSIVE | TRANSACTION | GRANTED | dd_schema.cc:108 | 68 | 4 |
+-------------+--------------------+----------------+-------------+-----------------------+---------------------+---------------+-------------+-------------------+-----------------+----------------+
4 rows in set (0.02 sec)
#在客户端1上可以看到,获得tr表级的SHARED_READ锁和剪枝后实际需要访问p5分区级别的SHARED_READ锁。接下来,通过客户端2尝试将分区p5删除
ALTER TABLE tr DROP PARTITION p5;
#由于分区p5正在被客户端1问,所以上述操作会进入等待状态,通过下述命令可以看到该线程正在等待分区级别的MDL锁。
SHOW PROCESSLIST;
+----+-----------------+-----------+------+---------+------+-------------------------------------+----------------------------------+
| Id | User | Host | db | Command | Time | State | Info |
+----+-----------------+-----------+------+---------+------+-------------------------------------+----------------------------------+
| 4 | event_scheduler | localhost | NULL | Daemon | 1550 | Waiting on empty queue | NULL |
| 8 | root | localhost | test | Sleep | 426 | | NULL |
| 9 | root | localhost | NULL | Query | 0 | starting | SHOW PROCESSLIST |
| 10 | root | localhost | test | Query | 10 | Waiting for partition metadata lock | ALTER TABLE tr DROP PARTITION p5 |
+----+-----------------+-----------+------+---------+------+-------------------------------------+----------------------------------+
4 rows in set (0.00 sec)
#通过客户端1提交事务后,客户端2能够顺利完成分区的维护。
查看在线分区维护次数
通过STATUS变量Online_altered_partition
参数可以监控进行在线分区维护的次数,示例如下:
SHOW STATUS LIKE 'Online_altered_partition';
+--------------------------+-------+
| Variable_name | Value |
+--------------------------+-------+
| Online_altered_partition | 2565 |
+--------------------------+-------+
1 row in set (0.00 sec)