Understand the concurrency control and locking mechanisms of MySQL and PostgreSQL

Understand the concurrency control and lock mechanism of MySQL and PostgreSQL

Introduction:
In a database management system (DBMS), database concurrency control and lock mechanism are crucial concepts. They are used to manage data consistency and isolation when multiple users access the database concurrently. This article will explore the implementation mechanisms of concurrency control and lock mechanisms in two common relational database management systems, MySQL and PostgreSQL, and provide corresponding code examples.

1. MySQL’s concurrency control and lock mechanism
MySQL uses two main concurrency control and lock mechanisms to deal with data consistency issues when multiple users access the database. These two mechanisms are Optimistic Concurrency Control (OCC for short) and Pessimistic Concurrency Control (PCC for short).

1. Optimistic Concurrency Control (OCC)
   Optimistic Concurrency Control (OCC) assumes that data access between multiple users will not conflict, and the data is only checked when a transaction is committed. Optimistic concurrency control in MySQL is mainly implemented through version control. Each transaction will first copy a copy of the data to be modified, and check whether there are conflicts before the transaction is submitted.

Code example for optimistic concurrency control:

'''
START TRANSACTION;

SELECT * FROM table WHERE id = 1 FOR UPDATE;

-- Subsequent read and write operations

COMMIT;
'''

In this example, by using the FOR UPDATE clause with the SELECT statement, we can Lock the specified record to prevent other transactions from modifying the record. This approach not only ensures data consistency but also reduces unnecessary lock competition.

2. Pessimistic Concurrency Control (PCC)
   Pessimistic Concurrency Control (PCC) assumes that data access between multiple users may conflict, and directly locks during the transaction operation, blocking other users Access to data. Pessimistic concurrency control in MySQL is mainly implemented through row-level locks, ensuring the isolation between transactions.

Code example for pessimistic concurrency control:

'''
START TRANSACTION;

SELECT * FROM table WHERE id = 1 FOR UPDATE;

-- Subsequent read and write operations

COMMIT;
'''

In this example, by using the FOR UPDATE clause with the SELECT statement, we can Lock the specified record to prevent other transactions from modifying the record. This approach ensures data consistency, but may lead to more lock contention and blocking.

2. PostgreSQL’s concurrency control and locking mechanism
PostgreSQL is an open source relational database management system that uses Multi-Version Concurrency Control (MVCC) to achieve data access. Concurrency control and locking mechanism.

1. Multi-version Concurrency Control (MVCC)
   Multi-version Concurrency Control (MVCC) uses data version control to achieve isolation and consistency of concurrent access. Each transaction can see a certain historical version of the data without being affected by update operations of other transactions. When concurrent operations occur, PostgreSQL assigns a unique transaction ID to each transaction and uses that ID to tag each data version.

Code example for multi-version concurrency control:

'''
BEGIN TRANSACTION;

SELECT * FROM table WHERE id = 1;

-- Subsequent read and write operations

COMMIT;
'''

In this example, we can perform read operations and write operations within a transaction without displaying Ground locked. PostgreSQL handles concurrent access and conflict issues internally to ensure data consistency.

Conclusion:
MySQL and PostgreSQL are two widely used relational database management systems. They adopt different implementation mechanisms in terms of concurrency control and locking mechanisms. MySQL uses optimistic concurrency control (OCC) and pessimistic concurrency control (PCC), while PostgreSQL uses multi-version concurrency control (MVCC). Developers need to choose a suitable database management system based on specific application scenarios and needs, and rationally use concurrency control and lock mechanisms to ensure data consistency and isolation.

(Note: The above code examples are for illustration only. The specific implementation may be different and need to be adjusted according to the specific database version and syntax.)

References:

1. MySQL official documentation: https://dev.mysql.com/doc/
2. PostgreSQL official documentation: https://www.postgresql.org/docs/

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