本文实例讲述了MySQL切分查询用法。分享给大家供大家参考,具体如下:
对于大查询有时需要‘分而治之',将大查询切分为小查询: 每个查询功能完全一样,但只完成原来的一小部分,每次查询只返回一小部分结果集。
删除旧的数据就是一个很好地例子。定期清理旧数据时,如果一条sql涉及了大量的数据时,可能会一次性锁住多个表或行,耗费了大量的系统资源,却阻塞了其他很多小的但重要的查询。将一个大得DELETE语句切分为较小的查询时,可以尽量减少影响msql的性能,同时减少mysql复制造成的延迟。
例如,每个月会运行一次的语句,以清理三个月前的数据:
代码如下:
mysql> DELETE FROM messages WHERE dt 可以用以下的方法来完成这样的任务: 一次删除一万行数据是个比较高效且对服务器影响较小的做法。同时如果每次删除数据时暂停一会,可以将服务器原本的一次性压力分散到一个较长的时间段中,从而减少删除时锁表锁行的时间。 更多关于MySQL相关内容感兴趣的读者可查看本站专题:《MySQL事务操作技巧汇总》、《MySQL存储过程技巧大全》、《MySQL数据库锁相关技巧汇总》及《MySQL常用函数大汇总》 以上就是MySQL切分查询用法分析_MySQL的内容,更多相关内容请关注PHP中文网(www.php.cn)!rows_affected = 0
do {
rows_affected = do_query("DELETE FROM messages WHERE dt<DATE_SUB(NOW(), INTERVAL 3 MONTH) LIMIT 10000")
}while rows_affected>0

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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