MySQL is a popular data management system, which can store all kinds of data and is often used by the program backend, MySQL can be accessed through multiple programming languages and applications, such as PHP Python, Java, etc. Do you know the MySql statement optimization techniques?
Complete set of MySql statement optimization techniques
1. Create an index: ensure that the key fields and common query conditions of the table have appropriate indexes. For large tables, indexing can greatly improve query speed. Try to avoid full table scanning, which will consume a lot of time and resources. You can determine whether an index is used by using the EXPLAIN command, and create or adjust the index as needed.
2. Reasonable paging: If you do not need to return all data at once, you can use paging. When querying large tables, it is a wise choice to query only part of the data at a time. Through paging, you can reduce the amount of data queried each time to an affordable range, thus avoiding excessive memory consumption. You can use the LIMIT keyword to specify the amount of data for each query, and remember to set the offset as needed.
3. Optimize query statements: When writing query statements, try to avoid using subqueries JOIN operations and other complex statements may slow down the query speed. Try to use simple statements, preferably single table queries, to improve query efficiency. If you must use complex query statements, you can consider splitting sub queries or JOIN operations into multiple smaller query operations.
4. Reasonable use of cache: For data frequently queried, you can consider caching it to improve query speed. The cache can use memory databases such as Redis, or use the built-in cache function of MySQL. When using cache, you should pay attention to cache strategy, such as expiration time, cache update, etc.
5. Hardware optimization: For large table queries, hardware optimization is also a very important part. If possible, use servers with higher configurations, such as more CPUs and memory. Using SSD hard disk can greatly improve the query speed. When using MySQL, reasonable settings of innodb_buffer_pool_size and other parameters can also improve the query speed.
Common optimization schemes:
1. Index optimization: ensure that frequently used columns are indexed and avoid unnecessary indexes.
2. Data partition: partition data according to certain rules to improve query speed.
3. Cache: use database cache to store frequently used data to avoid repeated queries.
4. Data compression: Compress the stored data to save storage space.
5. Distributed storage: consider using distributed storage technology to distribute data storage and processing load.
6. Process optimization: Manage database connections and avoid redundant queries.
7. Code optimization: optimize query statements to improve query speed.
8. Server upgrade: upgrade the database server to improve data processing speed.
MySql is very helpful to us in our work. It can effectively improve work efficiency. Mastering the above skills is very useful. I hope the above content can help you.
