Database performance optimization skills: comparison between MySQL and TiDB

Database performance optimization skills: Comparison between MySQL and TiDB

In recent years, with the continuous growth of data scale and business needs, database performance optimization has become the focus of many enterprises. Among database systems, MySQL has always been favored by developers for its wide application and mature and stable features. TiDB, a new generation of distributed database system that has emerged in recent years, has attracted much attention for its powerful horizontal scalability and high availability. This article will be based on two typical database systems, MySQL and TiDB, to discuss their different characteristics in performance optimization, and give some common performance optimization techniques.

1. Database architecture design
   In the architecture design of the database system, MySQL and TiDB are obviously different. MySQL uses a master-slave architecture, where write operations are performed through the master database and read operations are performed on the slave database to share the load on the database. MySQL performance can be improved by optimizing in terms of read and write separation.

TiDB adopts a distributed architecture, which achieves horizontal expansion of the database by distributing data across multiple nodes. In this way, even if the amount of data increases, the throughput of the system can be improved by adding nodes.

2. Index optimization
   In a database system, indexing is one of the important means to improve query performance. In MySQL, we can use the EXPLAIN command to analyze the query plan to determine whether the query uses indexes. If a query does not use an index or uses an inappropriate index, you can improve query performance by creating an appropriate index.

In TiDB, you can improve query performance by using TiDB's automatic index management and optimization functions. TiDB will automatically create and delete indexes based on the frequency and scale of queries to better adapt to different business scenarios.

The following is sample code for creating indexes using MySQL and TiDB respectively:

MySQL index creation example:

CREATE INDEX index_name ON table_name (column_name);

TiDB index creation example:

ALTER TABLE table_name ADD INDEX index_name (column_name);

3. Partition table and sharding technology
   When the amount of data is large, partition table and sharding technology can effectively improve the query performance and writing capabilities of the database.

MySQL disperses data into multiple physical tables through partition tables, thereby reducing the amount of data in a single table. This allows you to search only specific partitions when querying, improving query performance. Sharding technology divides data into multiple database nodes to achieve the effect of distributed load.

TiDB realizes automatic data sharding and dispersion through its own distributed architecture, eliminating the need for manual configuration. Just add nodes according to your business needs.

The following is sample code for creating partitioned tables and shards using MySQL and TiDB:

MySQL partition table creation example:

CREATE TABLE table_name (
  ...
) PARTITION BY RANGE(column_name) (
  PARTITION p0 VALUES LESS THAN (100),
  PARTITION p1 VALUES LESS THAN (200),
  PARTITION p2 VALUES LESS THAN (MAXVALUE)
);

TiDB shard creation example:

ALTER TABLE table_name ADD PARTITION (PARTITION p0 VALUES LESS THAN (100));
ALTER TABLE table_name ADD PARTITION (PARTITION p1 VALUES LESS THAN (200));

4. Cache Optimization
   Cache is an important means to reduce database reading pressure and improve query performance. In MySQL, query results can be cached by using the query cache. Query performance can be improved by setting appropriate cache sizes and cache invalidation policies.

In TiDB, you can use TiKV's cache to improve query performance. TiKV uses RocksDB as the storage engine and uses cache to speed up queries. At the same time, TiDB also supports using Redis as a cache to improve query performance.

The following is a sample code for optimizing query cache using MySQL and TiDB respectively:

MySQL query cache optimization example:

SET GLOBAL query_cache_size = 1000000;

TiDB cache optimization example:

SET GLOBAL tikv_gc_memory_barrier = 100;

Summary:
By comparing the performance optimization of the two database systems MySQL and TiDB, we can see that they have certain differences in database architecture design, index optimization, partition table and sharding technology, and cache optimization. . In practical applications, we should select appropriate performance optimization techniques based on the characteristics and business needs of the database system to improve the performance and availability of the database.

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