临时表让用户只能够操作各自的数据中而互不干扰,不用担心会破坏或影响其他SESSION/TRANSACTION的数据。临时表分为SESSION、TRANSACTION两种。1. SESSION级的临时表数据在整个SESSION都存在,直到结束此次SESSION;2. TRANSACTION级的临时表数据在TRANACTION
临时表让用户只能够操作各自的数据中而互不干扰,不用担心会破坏或影响其他SESSION/TRANSACTION的数据。 临时表分为SESSION、TRANSACTION两种。 1. SESSION级的临时表数据在整个SESSION都存在,直到结束此次SESSION; 2. TRANSACTION级的临时表数据在TRANACTION结束后消失,即COMMIT/ROLLBACK或结束SESSION都会清除TRANACTION临时表数据。 两种临时表的语法: create global temporary table 临时表名 on commit preserve|delete rows 用preserve时就是SESSION级的临时表,用delete就是TRANSACTION级的临时表 一、SESSION级临时表 1、建立临时表 create global temporary table temp_tbl(col_a varchar2(30)) on commit preserve rows 2、插入数据 insert into temp_tbl values('test session table') 3、提交 commit; 4、查询数据 select *from temp_tbl


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

MySQL functions can be used for data processing and calculation. 1. Basic usage includes string processing, date calculation and mathematical operations. 2. Advanced usage involves combining multiple functions to implement complex operations. 3. Performance optimization requires avoiding the use of functions in the WHERE clause and using GROUPBY and temporary tables.

Efficient methods for batch inserting data in MySQL include: 1. Using INSERTINTO...VALUES syntax, 2. Using LOADDATAINFILE command, 3. Using transaction processing, 4. Adjust batch size, 5. Disable indexing, 6. Using INSERTIGNORE or INSERT...ONDUPLICATEKEYUPDATE, these methods can significantly improve database operation efficiency.

In MySQL, add fields using ALTERTABLEtable_nameADDCOLUMNnew_columnVARCHAR(255)AFTERexisting_column, delete fields using ALTERTABLEtable_nameDROPCOLUMNcolumn_to_drop. When adding fields, you need to specify a location to optimize query performance and data structure; before deleting fields, you need to confirm that the operation is irreversible; modifying table structure using online DDL, backup data, test environment, and low-load time periods is performance optimization and best practice.


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