MySQL and PostgreSQL: How to handle read and write conflicts under high load?

MySQL and PostgreSQL: How to handle read and write conflicts under high load?

With the rapid development of the Internet, databases play a vital role, storing and managing large amounts of data. Under high load conditions, the read and write operations of the database are performed simultaneously, which may cause read and write conflicts. To ensure data consistency and accuracy, we need to take steps to handle these conflicts. This article will introduce in detail how two commonly used relational databases, MySQL and PostgreSQL, handle read and write conflicts under high load conditions, and provide code examples.

1. MySQL
MySQL is an open source relational database management system that is widely used in Web applications and large enterprise-level databases. Under high load conditions, MySQL provides the following methods to handle read and write conflicts.

1. Lock mechanism
   MySQL provides two lock mechanisms: shared lock (read lock) and exclusive lock (write lock). Read operations use shared locks, and multiple transactions can read the same data at the same time. However, write operations use exclusive locks. Only one transaction can write a certain data, and other transactions need to wait. Under high load conditions, read and write conflicts can be effectively reduced by rational use of the lock mechanism.

The following is an example of MySQL code using the lock mechanism:

-- 开始事务
START TRANSACTION;

-- 对数据表加排它锁
LOCK TABLES table_name WRITE;

-- 执行写操作
UPDATE table_name SET column_name = value WHERE condition;

-- 提交事务
COMMIT;

-- 解锁数据表
UNLOCK TABLES;

2. Optimistic concurrency control
   Optimistic concurrency control is a method that uses version numbers or timestamps to handle The mechanism of read-write conflicts. Before the write operation, the version number or timestamp of the data will be checked. If it is found that other transactions have modified the data, the conflict needs to be handled, and you can choose to retry or give up the operation. Optimistic concurrency control can reduce the use of locks and is more suitable in certain scenarios.

The following is a MySQL code example using optimistic concurrency control:

-- 开始事务
START TRANSACTION;

-- 读取数据
SELECT * FROM table_name WHERE condition;

-- 执行写操作，并检查版本号或时间戳
UPDATE table_name SET column_name = new_value, version = new_version WHERE condition AND version = old_version;

-- 判断是否更新成功
IF ROW_COUNT() = 0 THEN
   -- 处理冲突
   ROLLBACK;
ELSE
   -- 提交事务
   COMMIT;
END IF;

2. PostgreSQL
PostgreSQL is a powerful and highly scalable open source relational database management system. Under high load conditions, PostgreSQL provides the following methods to handle read and write conflicts.

1. MVCC (Multi-Version Concurrency Control)
   MVCC is the default concurrency control mechanism of PostgreSQL, which handles read and write conflicts by using multiple versions of data. Data modification does not directly overwrite the original data, but creates a new version. Read operations can read both the old and new versions of data at the same time, and write operations only affect the new version of data. MVCC can provide higher concurrency performance and can effectively handle read and write conflicts.
2. Row-level lock
   PostgreSQL supports a row-level locking mechanism, which can lock at a specific row level. Unlike MySQL, PostgreSQL's row-level locks can be read by multiple transactions simultaneously, and only write operations require exclusive locks. This means that multiple transactions can read the same data at the same time, improving concurrency performance.

The following is a PostgreSQL code example using row-level locks:

-- 开始事务
BEGIN;

-- 加行级锁
LOCK table_name IN ROW EXCLUSIVE MODE;

-- 执行写操作
UPDATE table_name SET column_name = new_value WHERE condition;

-- 提交事务
COMMIT;

To sum up, MySQL and PostgreSQL are two commonly used relational databases. Under high load conditions The approach to handling read-write conflicts is slightly different. MySQL handles conflicts through the locking mechanism and optimistic concurrency control, while PostgreSQL uses MVCC and row-level locks to handle conflicts. In practical applications, we can choose an appropriate database according to specific needs and scenarios, and combine it with corresponding technical means to handle read and write conflicts to ensure data consistency and reliability.

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