What are the data monitoring and performance tuning techniques for learning MySQL?

What are the data monitoring and performance tuning techniques for learning MySQL?

With the rapid development of the Internet, databases have always been an indispensable part of applications. As one of the most popular open source databases, MySQL's data monitoring and performance tuning have attracted more and more attention from developers.

In this article, we will introduce some basic skills of MySQL data monitoring and performance tuning, and attach relevant code examples to help readers better understand and practice.

1. Data monitoring

1. Monitoring query performance
   Query is one of the most commonly used operations in the database, so monitoring query performance is very important for optimizing the database. MySQL provides some built-in statements and tools that can help us monitor and analyze query performance.

(1) EXPLAIN statement
The EXPLAIN statement can help us understand how MySQL executes a query statement. It shows how MySQL's query optimizer executes the query plan, including the indexes used, connection types, etc.

Sample code:

EXPLAIN SELECT * FROM customers WHERE age > 30;

(2) SHOW STATUS
SHOW STATUS statement can be used to view various status information of the MySQL server, including the number of query executions, lock conditions, etc. . We can use this status information to determine the load situation and performance bottlenecks of the database.

Sample code:

SHOW STATUS LIKE 'Queries';
SHOW STATUS LIKE 'Table_locks_waited';

2. Monitoring server status
   In addition to query performance, we also need to monitor the overall status of the MySQL server, including CPU utilization, memory usage, and number of connections etc.

(1) SHOW PROCESSLIST
The SHOW PROCESSLIST statement can display information about the query and connection currently being executed. By observing this information, we can learn which queries are executing, along with their status and execution time.

Sample code:

SHOW PROCESSLIST;

(2) SHOW VARIABLES
SHOW VARIABLES statement can display various configuration parameters of the MySQL server. We can check that these configuration parameters are set as we expect and adjust them if necessary.

Sample code:

SHOW VARIABLES LIKE 'innodb_buffer_pool_size';
SHOW VARIABLES LIKE 'max_connections';

2. Performance tuning

1. Using indexes
   Index is one of the key factors to improve query performance. MySQL provides multiple types of indexes, including B-tree indexes, hash indexes, etc. We should choose the appropriate index type based on specific query requirements and table characteristics, and ensure that the use of indexes is efficient.

Sample code:

CREATE INDEX idx_age ON customers (age);

2. Optimizing query statements
   Optimizing query statements is an important means to improve database performance. We can optimize the query execution plan by rewriting the query statement, adjusting the order of the WHERE clause, and using JOIN queries.

Sample code:

SELECT * FROM customers WHERE age > 30 ORDER BY id LIMIT 10;

3. Partitioning and sub-tables
   When the amount of data is large, we can consider using partitions or sub-tables to improve query performance. Partitioning divides a large table into multiple small tables, each table containing only part of the data; table splitting divides a large table into multiple small tables, each table containing complete structure and data.

Sample code:

CREATE TABLE customers (
    id INT,
    name VARCHAR(50),
    age INT,
    ...
) PARTITION BY RANGE(age)(
    PARTITION p0 VALUES LESS THAN (30),
    PARTITION p1 VALUES LESS THAN (60),
    PARTITION p2 VALUES LESS THAN MAXVALUE
);

Summary:

This article introduces some basic techniques for learning MySQL data monitoring and performance tuning, including query performance monitoring, server Status monitoring, index usage, query statement optimization, partitioning and table sharding, etc. By learning and practicing these techniques, we can better understand and optimize the performance of MySQL databases and improve application response speed and user experience. I hope readers can better use and optimize the MySQL database through the guidance of this article.

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