Introduction to mysql slow query and EXPLAIN

Redis is a high-performance, scalable memory data structure storage system that is widely used in data caching, message queues, distributed locks and other fields. In Redis application process, slow query is a common performance problem. When the response time of Redis processing requests exceeds the specified threshold, it can be called a slow query. Slow queries may cause Redis performance to degrade and affect application stability and reliability. In order to ensure the high availability and reliability of Redis, we need to troubleshoot slow queries from multiple aspects and

Preface: One of the columns in the result of executing explain in Mysql is key_len. So what is the meaning of key_len? key_len: Indicates the number of bytes used by the index. Based on this value, the usage of the index can be judged. Especially when combining indexes, it is very important to judge how many parts of the index are used. Notes on calculating key_len: Additional information about the index field: it can be divided into variable-length and fixed-length data types for discussion. When the index field is a fixed-length data type, such as char, int, datetime, a mark is required to indicate whether it is empty. This mark Occupies 1 byte (for notnull fields, this 1 byte is not needed); for variable-length data types, such as v

With the rapid development of application systems, how to effectively solve system performance problems has become increasingly important. For applications that use MySql database, behavior logs and slow queries are two important tools for locating performance problems. This article will introduce MySql's behavior logs and slow queries, and discuss how to use these two tools to quickly locate performance problems. 1. MySql behavior log MySql's behavior log is a log that records all operations performed by the database server. By looking at the behavior log, we can learn

1. table The table to be queried 2. type index query type, from best to worst: system>const>eq_ref>ref>range>index>ALL. Generally speaking, ensure that the query reaches at least the range level, and preferably reaches the ref. 3. possible_keys displays one or more indexes that may be applied to this table. If there is an index for the field involved in the query, the index will be listed, but it may not be actually used by the query. 4. The index actually used by the key. If it is NULL, the index is not used. If a covering index is used in the query, the index Only appears in the key list 5. key

This article brings you relevant knowledge about mysql. It mainly introduces a tool pt-query-digest for analyzing mysql slow query logs. Let's take a look at it together. I hope it will be helpful to you.

Database Slow Query Optimization Practice: Application in PHP Programming As a PHP programmer, you 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

With the rapid development of the Internet, reliability and efficiency have become one of the most important issues for developers. For PHP language developers, solving slow queries has become one of the common problems. The emergence of slow queries will cause the website to respond slowly, which will affect the user experience and may even lead to data security issues. To this end, this article will introduce how to avoid slow queries in PHP development. 1. What is slow query? In the MySQL database, the phenomenon of a query being slower than expected is called a slow query. Slow queries not only affect the performance of your website;

Concept 1. Explain is used to analyze the SELECT query statement. Developers can optimize the query statement by analyzing the Explain results. Function 2. Through the explain command, we can learn how the SQL is executed, and then parsing the explain results can help us use better indexes and ultimately optimize it! Through the explain command, we can know the following information: the reading order of the table, the type of data reading operation, which indexes can be used, which indexes are actually used, references between tables, how many rows of each table are queried by the optimizer, etc. information. Example explainselect*fromtable_user;