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前两天遇到一个1205(ER_LOCK_WAIT_TIMEOUT)的错误,弄了半天终于找到原因,掌握原理+细心才能找到罪归祸首。下面我给大家分享下这个问题的分析处理过程,希望对大家有所帮助。接到slave error告警后,看到现场是这样的:slave重做binlog因为锁超时中断,报HA_ERR_LOCK_WAIT_TIMEOUT错误。
超时,easy啊,心想估计是有大事务长期持有锁,导致其他事务超时等待。但是这个库是只读的备库,不可能有写事务,通过show processlist命令也确实没有发现写事务,倒是有一个大查询任务。当时觉得MVCC查询不上锁啊,直接无视。我尝试重新start slave,发现没过几秒钟,错误依然出现,并且Exec_Master_Log_Pos没有变化,这说明同样的事务尝试写错误,依然被堵住,导致锁超时等待了。这一定是事务持有锁导致锁超时,但机器上除了查询,啥也木有。隔离级别,确认下隔离级别,虽然生产环境中机器都是RC(读提交)模式,但也不排除这种可能。但结果再次让我失望,事务隔离级别是读提交。
会不会是存储引擎的问题,我又验证了一把,表是innodb存储引擎,读不存在说是上表锁的情况。无语了,难道innodb的MVCC,读在某些情况下也上锁?这岂不是与读不上锁上违背吗?继续排查问题,查看锁等待情况:
select * from information_schema.innodb_lock_waits;
这说明确实有事务堵住了更新。继续,
SELECT r.trx_id waiting_trx_id,
r.trx_query waiting_query,
b.trx_id blocking_trx_id,
b.trx_query blocking_query,
b.trx_mysql_thread_id blocking_thread,
b.trx_started,
b.trx_wait_started
FROM information_schema.innodb_lock_waits w
INNER JOIN information_schema.innodb_trx b
ON b.trx_id = w.blocking_trx_id
INNER JOIN information_schema.innodb_trx r
ON r.trx_id = w.requesting_trx_id
从图中可以看到,blocking_query确实是select语句,靠,难道真是它上锁了,上的什么锁呢?
select * from information_schema.innodb_locks;
可以看到一个读锁和一个写锁,这说明了,查询的确是上了记录的读锁,锁应该都是在innodb层面加的。到底为啥会上读锁呢?
select trx_id,trx_state,trx_isolation_level from information_schema.innodb_trx;
答案揭晓了,可以看到RUNNING的事务隔离级别是SERIALIZABLE,串行化隔离级别导致读上锁,进而阻塞复制无法进行下去。
这个例子其实很简单,通过这个例子可以看到,information_schema下面的几张表太重要了,暴露了很多信息,方便我们排查问题。同时排查问题时,一定要坚信原理,并且细心,问题总会水落石出。
bitsCN.com
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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