数据库并发操作存在的异常情况 — 脏读 设置数据库的隔离级别 : setTRANSACTION ISOLATION LEVEL READUNCOMMITTEDspan style=font-size:14px业务情景:/span 张三准备用 ATM 机向其北京招行的帐户汇 1000 块钱,在汇之前先用其智能手机的手机银行客户端查询
数据库并发操作存在的异常情况—脏读
设置数据库的隔离级别:
setTRANSACTION ISOLATION LEVEL READUNCOMMITTED<span style="font-size:14px">业务情景:</span>
张三准备用ATM机向其北京招行的帐户汇1000块钱,在汇之前先用其智能手机的手机银行客户端查询到其北京账户还剩100,接着他用ATM机向其北京帐户打过去1000,在提示确认提交时,他又用手机查看了一下其帐户余额竟然为1100。
数据库并发操作存在的异常情况—不可重复读
设置数据库的隔离级别:
setTRANSACTION ISOLATION LEVEL READCOMMITTED ;<span style="font-size:14px">业务情景:</span>
张三用其智能手机的手机银行客户端查询其招行帐户余额为100元,他没有马上退出,去做了一会别的事,在此过程中他老婆在一个ATM机上向其帐户上汇入了1000元,他回来后又刷新了一下余额,竟然为1100元。
数据库并发操作存在的异常情况——幻读(Magic read)
设置数据库的隔离级别:
setTRANSACTION ISOLATION LEVEL REPEATABLEREAD;<span style="font-size:14px">业务情景:</span>
张三用其智能手机的手机银行客户端查询其招行帐户余额为300元,他准备用其中的200去抢购一个商品,在他没付款之前他的老婆取走100元,他再次查看了一下余额,还是300元,他花了200支付了商品,在支付完后,他再次查了一下余额,竟然发现账户里一毛钱都没有啦!
数据库并发操作存在的情况— 不能并发
设置数据库的隔离级别:
<span style="color:#000000">setTRANSACTION ISOLATION LEVEL SERIALIZABLE;</span>
业务情景:
张三用其智能手机的手机银行客户端查询其招行帐户余额为99.9元,但他需要100元才能支付抢购,他QQ告知老婆在线等待,他老婆立马找到一个ATM机准备向其帐户上汇入了100元,但钱就是汇不进去。

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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