猛然间听到这样的问题,还是很惊讶的,因为我们讨论最多的是如何避免replication复制延迟,特别是在读写分离的环境下,主库或从库压力大的情况下,master写入的数据很难快速到slave,如这样的架构一主多从 ,特别是现在一些电子商务类的网上商城。所以听到要
猛然间听到这样的问题,还是很惊讶的,因为我们讨论最多的是如何避免replication复制延迟,特别是在读写分离的环境下,主库或从库压力大的情况下,master写入的数据很难快速到slave,如这样的架构一主多从 ,特别是现在一些电子商务类的网上商城。所以听到要replication间人为延迟 如一个小时或两个小时这样的需求,很是惊讶。
目前mysql 还没有实现这样的功能,google了一把,目前说是mysql 5.6已经有了这功能,而且也有第三方工具来实现,详细的可以查看这哥们的博客 :
http://www.db110.com/?p=3871 上面介绍的比较详细,我摘抄如下:
pt-slave-delay
mysql同步在快速的网络中是毫秒级的,如果有误操作,从库也很快变更了,对于一些频繁进行,不是经过严格测试的升级,可能带来风险.
可考虑配置一个延迟复制的副本,以改善故障情况下的可恢复性.
mysql 5.6版本已经支持延迟复制,如果5.1版本,可以用percona工具出品的一个工具pt-slave-delay
pt-slave-delay – Make a MySQL slave server lag behind its master.
下载: wget percona.com/get/pt-slave-delay
安装: 略
语法: pt-slave-delay [OPTION...] SLAVE-HOST [MASTER-HOST]
选项值一般可以用默认的. 默认是延迟1小时.
如: pt-slave-delay –delay 1m –interval 15s –run-time 10m slavehost
运行这个工具10分钟(默认是永久运行的) . 从库保持一直滞后主库1分钟,每次检查间隔15秒,那么理论上是延迟1分钟15秒.
这个工具是低风险的.
它的原理是: 检查主库的日志到了哪里了(可以用show slave status 命令查看relay日志) , 对比已经应用的日志, 就知道延迟的时间了.
每隔1分钟检查(默认),不断启动,关闭 replication SQL thread 来保持主从一直延时固定的时间.
如果正在运行这个工具,那么 Ctrl-C 退出后,它是友好的退出的,意即他会启动复制sql线程.
生产环境示例:
./pt-slave-delay u=xxxx,S=/tmp/mysql.sock,p=d1\\ccc(\* –log /home/mysql/scripts/log/delay.log –daemonize
当时第一反应是目前mysql 无法实现,后来想了想,只能认为的写程序去控制,比对两个库日志读的是否一致,写脚本来控制了,大概就这样的思路。

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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