Database slow query optimization practice: application in PHP programming

Database Slow Query Optimization Practice: Application in PHP Programming

As a PHP programmer, we often encounter the problem of low database query efficiency during the development process, which is the so-called "slow query". If not optimized, these slow queries can cause programs to run slowly and create a poor user experience. This article mainly introduces several optimization ideas and practical techniques to help PHP programmers solve the problem of slow queries.

1. Reduce the number of database queries as much as possible

Reducing the number of database queries is an important way to improve system efficiency. In actual development, we can achieve this through the following methods:

1. Caching query results

Using cache is a good way to respond quickly. Cache the query results in memory. When the same query request comes next time, you can directly return the data in the cache without querying the database again. Common caching solutions include Memcached and Redis.

2. Batch operation

When you need to perform multiple queries or updates to the database, you can change to batch operation. For example, in a CMS system, if you need to query the classification information of multiple articles, you can use the IN statement to query the classification information of multiple articles at once.

3. Aggregation query

In development, it is often necessary to query the average value, maximum value, minimum value, total number, etc. of data. In this case, aggregation query can be used. For example, for an online mall, if you need to query the sum of the number of comments on all products, you can use SELECT sum(comment_count) FROM the goods table.

2. Optimize query statements

1. Use indexes

Optimizing query statements is an important means to improve query efficiency, and using indexes can improve query efficiency. Adding indexes to the fields that need to be queried allows the database to find data that meets the conditions faster. In addition to using regular B-Tree indexes, full-text indexes and hash indexes can also be used.

2. Avoid using the SELECT * statement

In actual development, we often use the SELECT statement to query all fields. However, doing so will reduce query efficiency and even cause a full table scan. Therefore, try to avoid using the SELECT statement and only query the required fields, which can greatly improve query efficiency.

3. Try to avoid using subqueries when using join operations

When using join operations, subqueries can be used in some cases, but using subqueries will reduce the query efficiency of MySQL. Therefore, try to avoid using subqueries when using join operations, and use JOIN or LEFT JOIN operations whenever possible.

3. Avoid unnecessary loops

1. Use foreach instead of for

foreach is easier to understand than for, the code is more readable, and foreach itself has some Optimization can improve performance when traversing array types, so it is recommended to use foreach instead of for in actual development to reduce unnecessary loops.

2. Use caching mechanism

When traversing the data in the database, you can use the caching mechanism. Through the caching mechanism, the program can cache the data that has been read into the memory, thereby avoiding repeated queries.

4. Database hardware optimization

1. Hard disk, CPU, memory upgrade

If it is really impossible to solve the slow query problem by optimizing query statements or avoiding unnecessary loops, You can also consider optimizing at the hardware level, such as upgrading hard drives, CPUs, memory and other hardware devices.

2. Sub-database and sub-table

With the development of applications, the amount of data is also increasing. At this time, we need to consider using the solution of sub-database and sub-table to solve the problem. The main purpose of sharding is to split the data in the same server to different servers, thereby reducing the load on a single server; the main purpose of sharding is to split the data in a single table into different tables according to certain rules. , thereby reducing the amount of data in a single table and providing faster query efficiency.

Summary

In actual development, the problem of slow database query is unavoidable, but it can be optimized by optimizing query statements, minimizing the number of database queries, adopting reasonable loop methods, and using caching mechanisms. As well as hard disk, CPU, memory upgrade and other methods to solve the problem, thereby improving the efficiency and response speed of the system.

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