1. Why do you never feel confident when people ask you about MySQL optimization knowledge
1. Because you just answer some big questions The tuning principles of optimization,
a. For example: "Establish a reasonable index" (What kind of index is reasonable?)
b. "Separation of tables and databases" (What strategy should be used to divide tables and databases?)
c. "Master-slave separation" (What middleware should be used?)
2. There is no analysis from a detailed to quantitative level.
a.What if qps improves %N?
b. Has the file sorting been reduced?
c. How much has the number of scanned lines of statements been reduced?
2. How to do it?
When mysql is not efficient, what we ## must do first is not to optimize, but Yes---Diagnostic analysis to find out where the bottleneck is. CPU, memory, IO? Peak value, single statement
1. Analyze common commands
a).show processlist Enable slow query to obtain the problematic SQL
b).explain analysis statement
2. The statement waiting time is long:
c). Tuning server parameters (such as buffer, number of threads, etc.)
3. Statement execution time is long:
d). There are many table associations (table design is defective)
e). The index is not optimized
f). Statements are not optimized (where conditional calculation statements, etc.)
.
Wait
This is just a simple description.
So, this series of blogs will analyze the aspects related to MySQL, from optimization to index creation, consolidate the study and make a summary, and share my experience with everyone.
I hope this embarrassing situation will never happen again in the future. I think I understand, but in fact I still don’t.
In the form of pictures, this section gives an overall overview of the context that needs to be mastered, which is also the route of your own learning. The overall picture is as follows:
Figure 1. MySQL server tuning ideas
Figure 2. SQL optimization
Figure 3. Index learning
Above This is the content of Mysql optimization and indexing general analysis [illustration]. For more related content, 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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