


In today's large-scale Internet application context, with the growth of data volume and the improvement of business needs, stand-alone databases are gradually unable to meet the requirements of business development. The emergence of distributed databases provides new options to solve this problem.
This article will introduce the basic concepts of database distributed architecture design and optimization, and provide some useful suggestions based on the practice in PHP programming.
1. Database distributed architecture design
- Database sharding technology
Database sharding technology is to split data into multiple data according to specific rules. Small databases, each small database is only responsible for storing a part of the sharded data, thereby evenly distributing the load of the database to multiple nodes. Commonly used sharding strategies include the following:
- Sharding by data range: Split the data into multiple fragments for storage based on a certain dimension of the data, such as ID or time range, etc.;
- Sharding by hash: Use hash function to calculate the data, and split the data according to the size of the hash value;
- Sharding by business function: Shard the data according to business needs Split according to functions, such as storing user information and order information in different shards.
- Database master-slave replication technology
Master-slave replication is to synchronously copy the data of the master database to multiple slave databases, thereby providing read-write separation and Disaster recovery and backup functions. The implementation principle of master-slave replication is that the master database records the data operation log in a binary file, and regularly sends the binary file to the slave database, and the slave database updates its own data by parsing the binary file.
- Database cluster technology
Database cluster refers to combining multiple database nodes into a database service to provide higher performance and reliability. Commonly used distributed architecture models for database clusters include the following:
- Master-standby mode: synchronously replicate the data of the primary database to the standby database. When the primary database fails, the standby database will automatically take over the service;
- Multi-master mode: Multiple database nodes form a cluster, and each node can read and write data;
- Read-write separation mode: For read-intensive business scenarios, read operations are Load balancing to multiple read-only nodes can improve the concurrency and performance of the database.
2. Database distributed architecture optimization
- SQL optimization
Query statements are the focus of database performance optimization. The optimization methods mainly include the following Several:
- Index optimization: For frequently queried fields, adding indexes can improve query efficiency;
- SQL statement optimization: Use SQL statements reasonably, such as avoiding the use of SELECT * like this query method, and avoid performing operations such as function calculations in the WHERE clause;
- Data sharding optimization: For databases sharded by data range, avoid using cross-shard query methods.
- Database connection optimization
Database connection pool technology can effectively optimize database connection performance, reduce the creation and destruction of database connections, thereby improving database performance. In PHP programming, you can choose to use PDO connection pool technology, and pay attention to the operation of regularly releasing database connection resources.
- Cache optimization
Cache technology is one of the key technologies to improve database performance. In PHP programming, you can use third-party cache libraries such as Redis to store hot data in the cache, thereby reducing the access pressure on the database.
3. Practice in PHP programming
- Using PDO database connection pool technology
In PHP programming, the PDO database extension provides PDOStatement:: The setAttribute() method can be used to set some connection pool related attributes, such as the maximum number of connections, the minimum number of connections, etc. The code is as follows:
$pdo = new PDO($dsn, $user, $password); $pdo->setAttribute(PDO::ATTR_EMULATE_PREPARES, FALSE); $pdo->setAttribute(PDO::ATTR_ERRMODE, PDO::ERRMODE_EXCEPTION); $pdo->setAttribute(PDO::ATTR_DEFAULT_FETCH_MODE, PDO::FETCH_ASSOC); $pdo->setAttribute(PDO::ATTR_AUTOCOMMIT, FALSE);
- Optimize database query statements
In order to improve database performance, you need to choose indexes reasonably and pay attention to some SQL statement optimization techniques. The following are some commonly used optimization techniques:
- Use indexes: Create indexes for frequently used query columns to avoid full table scans;
- Avoid using select tags: SELECT * without Do not use it if necessary;
- When using LIKE query string, if the query string is static, try to use "=" instead;
- Reduce the use of subqueries.
- Using caching technology
In PHP programming, using caching technology can effectively reduce database access pressure, thereby improving access performance. Third-party cache libraries such as Redis have the characteristics of high-speed reading and writing, high reliability, and can also effectively assist in distributed caching.
4. Summary
The design and optimization of database distributed architecture is a complex issue that requires comprehensive consideration of business needs, system environment, data scale, performance requirements and other factors. This article provides some practical experience based on PHP programming, hoping to provide readers with some useful references in the design and optimization of database distributed architecture.
The above is the detailed content of Database distributed architecture design and optimization: practice in PHP programming. For more information, please follow other related articles on the PHP Chinese website!

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