How to perform distributed storage and query of data in MySQL?
As the amount of data continues to grow, the storage and query performance of a single MySQL database may not be able to meet the demand. At this time, you need to consider using distributed storage and query to improve the scalability and performance of the system. This article will introduce how to perform distributed storage and query of data in MySQL and provide sample code.
The following is an example data sharding method. Suppose we have a user table user
, which has user_id
and name
Two fields.
CREATE TABLE `user` ( `user_id` int(11) NOT NULL AUTO_INCREMENT, `name` varchar(255) DEFAULT NULL, PRIMARY KEY (`user_id`) ) ENGINE=InnoDB;
We can store data in shards through the following methods:
-- 创建划分规则 CREATE FUNCTION shard_hash(user_id INT) RETURNS INT BEGIN RETURN user_id % 4; -- 按照 user_id 的哈希值进行划分为4个片段 END; -- 创建辅助表存储分片信息 CREATE TABLE `shard_mapping` ( `user_id` int(11) NOT NULL, `shard_id` int(11) NOT NULL, PRIMARY KEY (`user_id`) ) ENGINE=InnoDB; -- 将数据按照划分规则插入对应的片段 INSERT INTO `user` (name) SELECT name FROM origin_user WHERE shard_hash(user_id) = 0; -- 插入到片段 0 INSERT INTO `user` (name) SELECT name FROM origin_user WHERE shard_hash(user_id) = 1; -- 插入到片段 1 -- ... -- 插入分片信息 INSERT INTO `shard_mapping` (user_id, shard_id) SELECT user_id, shard_hash(user_id) FROM origin_user; -- 查询时需要根据分片信息路由到对应的片段 SELECT u.name FROM user u JOIN shard_mapping m ON u.user_id = m.user_id WHERE m.shard_id = shard_hash(123); -- 根据分片信息查询对应的片段
-- 在每个MySQL实例上创建相同的表结构 CREATE TABLE `user` ( `user_id` int(11) NOT NULL AUTO_INCREMENT, `name` varchar(255) DEFAULT NULL, PRIMARY KEY (`user_id`) ) ENGINE=InnoDB; -- 使用分片映射表查询对应的片段 SELECT u.name FROM user u JOIN shard_mapping m ON u.user_id = m.user_id WHERE m.shard_id = shard_hash(123); -- 根据分片信息查询对应的片段
It should be noted that data consistency is an important issue when using distributed storage and query. Read performance can be improved through horizontal expansion, but write operations need to ensure data consistency. Distributed locks or coordinators can be used to solve data consistency problems.
Summary:
This article introduces how to perform distributed storage and query of data in MySQL. Through data sharding and shard mapping, data can be stored in different MySQL instances, and the data can be routed to the corresponding fragments through the shard mapping table. At the same time, attention needs to be paid to ensuring data consistency. Distributed locks or coordinators can be used to solve this problem. Using this method can improve the scalability and performance of the system and meet the needs of large-scale data storage and query.
Note: The sharding rules and sharding mapping in the sample code may need to be adjusted according to actual business needs.
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