MySQL optimization tips: key techniques to conquer the interviewer!

As a typical representative of relational databases, MySQL is more popular than any other database. Therefore, in Java interviews, MySQL is an important knowledge point that will definitely be asked. There is an extremely common interview question in MySQL. Let's take a look at it systematically. This is the MySQL tuning question we are going to discuss today.

The general idea of ​​MySQL tuning is as follows:

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The specific tuning ideas are as follows.

1. Query statement optimization

1. Try to avoid using SELECT * and query only the columns you need.
2. Use JOIN instead of subqueries to reduce the level of nested queries.
3. Avoid using LIKE '%value%' in the WHERE clause, which causes a full table scan.
4. Use the LIMIT clause appropriately to limit the number of query results.

2. Index optimization

1. Use indexes properly : including primary key indexes, unique indexes, common indexes, and joint indexes, etc. Make sure to create indexes on columns that are frequently used in query conditions.
2. Avoid over-indexing : Each index takes up additional storage space and can affect the performance of write operations.

3. Table structure optimization

1. Vertical table partitioning : Separate infrequently used fields or large fields (such as TEXT and BLOB) in a table into separate tables to reduce the size of the main table and I/O overhead.
2. Horizontal table partitioning : Spread the data in a table into multiple tables according to certain rules (such as date, region, etc.), and each table contains part of the data. This can improve query efficiency and reduce lock contention for a single table.
3. Archiving old data : Regularly archive infrequently used old data into historical tables to reduce the amount of data in the main table and improve query performance.

4. Architecture Optimization

1. Read-write separation : Read-write separation is achieved through master-slave replication, which distributes read operations to multiple slave servers and reduces the load on the master server.
2. Database sharding (horizontal sharding/vertical sharding) : Split a large database into multiple small databases, each containing part of the data. Sharding can improve the scalability and query performance of the database.
3. Distributed databases : such as TiDB and ES.
4. Use cache : Use cache (such as Memcached, Redis, etc.) at the application level to reduce the number of direct accesses to the database.

5. Upgrade your hardware

1. Choose a high-performance CPU : to support complex query processing and a large number of concurrent accesses.
2. Increase memory capacity : Because MySQL uses a large amount of memory to cache data and indexes, thereby improving query efficiency.
3. Use high-speed disks , such as SSDs (solid-state drives), to reduce I/O waiting time. At the same time, consider using RAID technology to improve disk read and write performance and reliability.
4. Optimize network configuration : ensure efficient and stable data transmission between database server and client.