The performance problems of MySQL temporary tables mainly stem from disk drop tables, improper sorting operations, unreasonable explicit use, and disk IO pressure. 1. Temporary tables are created in memory first, but big data types or characteristics will cause drops. You can judge and optimize fields, parameters and indexes by monitoring Created\_tmp\_disk\_tables; 2. Sorting or grouping without indexes will cause temporary table inflation. Indexes should be added, column participation should be reduced, and join order should be optimized; 3. Explicit temporary tables should pay attention to connection validity and reuse to avoid frequent creation; 4. Disk temporary tables may cause IO and space problems, tmpdir should be monitored, SSD should be used, and the number of temporary tables should be limited.
The performance problems of MySQL temporary tables are actually something that many developers are prone to getting stuck in actual development. Especially when handling large amounts of data or complex queries, improper use of temporary tables can lead to obvious performance bottlenecks.

The following common questions and optimization suggestions are compiled based on the most easiest situations in daily use.
1. Is the temporary table memory or disk?
By default, the temporary table of MySQL will first try to use the MEMORY
engine to store it in memory. However, if the temporary table is too large (such as BLOB, TEXT type fields), or some features that do not support memory are used, it will automatically switch to using the MyISAM
or InnoDB
storage engine and write to disk.

How do you tell if you use a disk?
You can view the status variables:
SHOW STATUS LIKE 'Created_tmp%tables';
If the Created_tmp_disk_tables
value is too high, it means that many temporary tables have fallen out of the disk, which will affect the speed.

what to do?
- Try to avoid using TEXT/BLOB fields in temporary tables;
- Increase
tmp_table_size
andmax_heap_table_size
parameters, but do not exceed the available memory of the system; - Ensure that sorting, deduplication and other operations can be indexed.
2. Large-scale sorting or group by causes temporary table bloating
When performing operations containing ORDER BY
, GROUP BY
, DISTINCT
, etc., if there is no appropriate index, MySQL will most likely need to create temporary tables to complete these operations.
Typical phenomena:
A prompt like "Using temporary; Using filesort" often appears in the slow query log.
Optimization suggestions:
- Add an index to fields involving sorting or grouping;
- Avoid unnecessary columns participating in sorting and reduce temporary table size;
- If the order is done after the join operation, consider adjusting the order or method of the join.
3. Explicit temporary table vs internal temporary table
Sometimes we will explicitly create temporary tables to cache intermediate results. This practice itself is fine, but we should pay attention to the following points:
- An explicit temporary table is only valid for the current connection and will be automatically deleted if the connection is disconnected;
- Do not create and destroy temporary tables frequently, as this will increase the burden;
- Reuse temporary tables appropriately to avoid repeated calculations.
If you find that internal temporary tables appear frequently in your SQL, it may be where the statement structure can be optimized.
4. Temporary table files occupy high IO or space
When a temporary table is written to disk, a temporary section in .frm
and .MYD
files (if MyISAM) or the temporary section in the InnoDB tablespace is generated in the temporary directory of MySQL.
FAQ:
- The disk space where the temporary directory resides is insufficient;
- Poor IO performance causes temporary table read and write slower;
- Remaining temporary files are not cleaned regularly (although MySQL usually cleans up automatically);
Solution:
- Monitor the disk space where tmpdir is located;
- Put tmpdir on a high-speed SSD;
- Set the appropriate max_tmp_tables_per_connection to limit the number of temporary tables used by the connection;
Basically these are the more common points. Temporary tables themselves are quite practical tools, but if they are not used well, they can easily drag down the overall performance. The key is to control its scale and life cycle, and try to make MySQL efficiently process it in memory.
The above is the detailed content of Troubleshooting MySQL Temp Table Performance. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

mysqldump is a common tool for performing logical backups of MySQL databases. It generates SQL files containing CREATE and INSERT statements to rebuild the database. 1. It does not back up the original file, but converts the database structure and content into portable SQL commands; 2. It is suitable for small databases or selective recovery, and is not suitable for fast recovery of TB-level data; 3. Common options include --single-transaction, --databases, --all-databases, --routines, etc.; 4. Use mysql command to import during recovery, and can turn off foreign key checks to improve speed; 5. It is recommended to test backup regularly, use compression, and automatic adjustment.

To view the size of the MySQL database and table, you can query the information_schema directly or use the command line tool. 1. Check the entire database size: Execute the SQL statement SELECTtable_schemaAS'Database',SUM(data_length index_length)/1024/1024AS'Size(MB)'FROMinformation_schema.tablesGROUPBYtable_schema; you can get the total size of all databases, or add WHERE conditions to limit the specific database; 2. Check the single table size: use SELECTta

Character set and sorting rules issues are common when cross-platform migration or multi-person development, resulting in garbled code or inconsistent query. There are three core solutions: First, check and unify the character set of database, table, and fields to utf8mb4, view through SHOWCREATEDATABASE/TABLE, and modify it with ALTER statement; second, specify the utf8mb4 character set when the client connects, and set it in connection parameters or execute SETNAMES; third, select the sorting rules reasonably, and recommend using utf8mb4_unicode_ci to ensure the accuracy of comparison and sorting, and specify or modify it through ALTER when building the library and table.

MySQL supports transaction processing, and uses the InnoDB storage engine to ensure data consistency and integrity. 1. Transactions are a set of SQL operations, either all succeed or all fail to roll back; 2. ACID attributes include atomicity, consistency, isolation and persistence; 3. The statements that manually control transactions are STARTTRANSACTION, COMMIT and ROLLBACK; 4. The four isolation levels include read not committed, read submitted, repeatable read and serialization; 5. Use transactions correctly to avoid long-term operation, turn off automatic commits, and reasonably handle locks and exceptions. Through these mechanisms, MySQL can achieve high reliability and concurrent control.

The setting of character sets and collation rules in MySQL is crucial, affecting data storage, query efficiency and consistency. First, the character set determines the storable character range, such as utf8mb4 supports Chinese and emojis; the sorting rules control the character comparison method, such as utf8mb4_unicode_ci is case-sensitive, and utf8mb4_bin is binary comparison. Secondly, the character set can be set at multiple levels of server, database, table, and column. It is recommended to use utf8mb4 and utf8mb4_unicode_ci in a unified manner to avoid conflicts. Furthermore, the garbled code problem is often caused by inconsistent character sets of connections, storage or program terminals, and needs to be checked layer by layer and set uniformly. In addition, character sets should be specified when exporting and importing to prevent conversion errors

The most direct way to connect to MySQL database is to use the command line client. First enter the mysql-u username -p and enter the password correctly to enter the interactive interface; if you connect to the remote database, you need to add the -h parameter to specify the host address. Secondly, you can directly switch to a specific database or execute SQL files when logging in, such as mysql-u username-p database name or mysql-u username-p database name

To set up asynchronous master-slave replication for MySQL, follow these steps: 1. Prepare the master server, enable binary logs and set a unique server-id, create a replication user and record the current log location; 2. Use mysqldump to back up the master library data and import it to the slave server; 3. Configure the server-id and relay-log of the slave server, use the CHANGEMASTER command to connect to the master library and start the replication thread; 4. Check for common problems, such as network, permissions, data consistency and self-increase conflicts, and monitor replication delays. Follow the steps above to ensure that the configuration is completed correctly.

MySQL query performance optimization needs to start from the core points, including rational use of indexes, optimization of SQL statements, table structure design and partitioning strategies, and utilization of cache and monitoring tools. 1. Use indexes reasonably: Create indexes on commonly used query fields, avoid full table scanning, pay attention to the combined index order, do not add indexes in low selective fields, and avoid redundant indexes. 2. Optimize SQL queries: Avoid SELECT*, do not use functions in WHERE, reduce subquery nesting, and optimize paging query methods. 3. Table structure design and partitioning: select paradigm or anti-paradigm according to read and write scenarios, select appropriate field types, clean data regularly, and consider horizontal tables to divide tables or partition by time. 4. Utilize cache and monitoring: Use Redis cache to reduce database pressure and enable slow query
