要提高查询速度,一般: 1.不需要删除的字段,建主键;有可能要被删除的字段,建索引。 2.假如一次提交5W个号码,每个都要和数据
要提高查询速度,一般:
1.不需要删除的字段,建主键;有可能要被删除的字段,建索引。
2.假如一次提交5W个号码,每个都要和数据库里90W号码进行比较5W个号码中哪些号码是90W号码中的。那么将90W号码建一个表,一个字段就是号码字段,然后把该字段设为主键即可。
update前100条为0,另外一个程序找状态为0的,要提高速度,要将这100条(所有条)的ID建索引。
3.不管对什么字段建的什么索引,该字段只有放在where条件中使用时,,索引才生效,假如放到not in或者其他条件中,索引无效。
另外,有个语句:
对于sql中红色字体:(mainid和sjtdid在这里的都是唯一的,但是在表中不一样,不知道怎么说,只想说where后的条件顺序不一样,速度不一样,对某些字段加索引,速度更快)
情况1.(此时mianid未建索引)
情况2.(此时mianid未建索引)
情况3.(对mainid建索引,mianid是另外一个表的id)
4.Oracle序列,类似sqlserver自增主键,是数字类型的。使用序列也可以加快查询速度。
---建序列:
CREATE SEQUENCE seq_mxid
INCREMENT BY 1 -- 每次加几个
START WITH 1 -- 从1开始计数
NOMAXVALUE -- 不设置最大值
NOCYCLE -- 一直累加,不循环
;
---使用序列

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.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

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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