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MySQL内部临时表策略 通过对MySQL数据库源码的跟踪和调试,以及参考MySQL官方文档,对MySQL内部临时表使用策略进行整理,以便于更加深入的理解。使用内部临时表条件 MySQL内部临时表的使用有一定的策略,从源码中关于SQL查询是否需要内部临时表。可以总结如下: 1、DISTINCT查询,但是简单的DISTINCT查询,比如对primary key、unique key等DISTINCT查询时,查询优化器会将DISTINCT条件优化,去除DISTINCT条件,也不会创建临时表; 2、不是第一个表的字段使用ORDER BY 或者GROUP BY; 3、ORDER BY和GROUP BY使用不同的顺序; 4、用户需要缓存结果; 5、ROLLUP查询。 源码如下所示 代码地址:sql_select.cc:854,函数:JOIN::optimize(),位置:sql_select.cc:1399 /* Check if we need to create a temporary table. This has to be done if all tables are not already read (const tables) and one of the following conditions holds: - We are using DISTINCT (simple distinct's are already optimized away) - We are using an ORDER BY or GROUP BY on fields not in the first table - We are using different ORDER BY and GROUP BY orders - The user wants us to buffer the result. When the WITH ROLLUP modifier is present, we cannot skip temporary table creation for the DISTINCT clause just because there are only const tables. */ need_tmp= (( const_tables != tables && (( select_distinct || !simple_order || !simple_group) || ( group_list && order ) || test(select_options & OPTION_BUFFER_RESULT))) || ( rollup.state != ROLLUP:: STATE_NONE && select_distinct )); 内部临时表使用原则 但是使用了内部临时表,那么他是怎么存储的呢?原则是这样的: 1、当查询结果较小的情况下,使用heap存储引擎进行存储。也就是说在内存中存储查询结果。 2、当查询结果较大的情况下,使用myisam存储引擎进行存储。 3、当查询结果最初较小,但是不断增大的情况下,将会有从heap存储引擎转化为myisam存储引擎存储查询结果。 什么情况算是查询结果较小呢?从源码中if的几个参数可以看出: 1、有blob字段的情况; 2、使用唯一限制的情况; 3、当前表定义为大表的情况; 4、查询结果的选项为小结果集的情况; 5、查询结果的选项为强制使用myisam的情况。 源码如下所示 代码地址:sql_select.cc:10229,函数:create_tmp_table(),位置:sql_select.cc:10557 /* If result table is small; use a heap */ /* future: storage engine selection can be made dynamic? */ if ( blob_count || using_unique_constraint || ( thd->variables .big_tables && !( select_options & SELECT_SMALL_RESULT )) || ( select_options & TMP_TABLE_FORCE_MYISAM )) { share->db_plugin = ha_lock_engine(0, myisam_hton); table->file = get_new_handler( share, &table ->mem_root, share->db_type ()); if (group && ( param->group_parts > table-> file->max_key_parts () || param->group_length > table-> file->max_key_length ())) using_unique_constraint=1; } else { share->db_plugin = ha_lock_engine(0, heap_hton); table->file = get_new_handler( share, &table ->mem_root, share->db_type ()); } 代码地址:sql_select.cc:11224,函数:create_myisam_from_heap(),位置:sql_select.cc:11287 /* copy all old rows from heap table to MyISAM table This is the only code that uses record[1] to read/write but this is safe as this is a temporary MyISAM table without timestamp/autoincrement or partitioning. */ while (! table->file ->rnd_next( new_table.record [1])) { write_err= new_table .file-> ha_write_row(new_table .record[1]); DBUG_EXECUTE_IF("raise_error" , write_err= HA_ERR_FOUND_DUPP_KEY ;); if (write_err ) goto err ; }官方文档相关内容 以上内容只是源码表面的问题,通过查询MySQL的官方文档,得到了更为权威的官方信息。 临时表创建的条件: 1、如果order by条件和group by的条件不一样,或者order by或group by的不是join队列中的第一个表的字段。 2、DISTINCT联合order by条件的查询。 3、如果使用了SQL_SMALL_RESULT选项,MySQL使用memory临时表,否则,查询询结果需要存储到磁盘。 临时表不使用内存表的原则: 1、表中有BLOB或TEXT类型。 2、group by或distinct条件中的字段大于512个字节。 3、如果使用了UNION或UNION ALL,任何查询列表中的字段大于512个字节。 此外,使用内存表最大为tmp_table_size和max_heap_table_size的最小值。如果超过该值,转化为myisam存储引擎存储到磁盘。
参考资料:1、MySQL源码:MySQL-5.5.202、MySQL官方文档:http://dev.mysql.com/doc/refman/5.5/en/internal-temporary-tables.html 作者 king_wangheng bitsCN.com

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

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The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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