The basic principle is to let the master database handle transactional queries, while the slave database handles SELECT queries. Database replication is used to synchronize changes caused by transactional queries to slave databases in the cluster.
Jan Kneschke introduced this technique and the connection pool issue in detail in "MySQL Proxy learns R/W Splitting":
In order to achieve read and write separation, we need a connection pool. We only switch to a backend if we have an authenticated connection open to that backend. The MySQL protocol starts with a handshake. When entering the query/return result stage, it is too late to authenticate the new connection. We must ensure that we have enough open connections to keep things functioning properly.
LUA script to implement read-write separation:
--Read-write separation
--
--Send all non-transactional Selects to a slave database
if is_in_transaction == 0 and packet:byte() == proxy.COM_QUERY and packet:sub(2, 7) == "SELECT" then local max_conns = -1 local max_conns_ndx = 0 for i = 1, #proxy.servers do local s = proxy.servers[i] -- 需要选择一个拥有空闲连接的从数据库 if s.type == proxy.BACKEND_TYPE_RO and s.idling_connections > 0 then if max_conns == -1 or s.connected_clients < max_conns then max_conns = s.connected_clients max_conns_ndx = i end end end -- 至此,我们找到了一个拥有空闲连接的从数据库 if max_conns_ndx > 0 then proxy.connection.backend_ndx = max_conns_ndx end else -- 发送到主数据库 end return proxy.PROXY_SEND_QUERY
Note: This technique can also be used to implement other data distribution strategies, For example, Sharding.
The above is the content of mysql reading and writing separation (basics). For more related articles, please pay attention to the PHP Chinese website (www.php.cn)!

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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