Deeply understand the principles of MySQL MVCC and improve query efficiency

In-depth understanding of MySQL MVCC principles and improved query efficiency

In the database, effectively handling concurrent transactions has always been an important challenge. Multi-Version Concurrency Control (MVCC) in MySQL is a mechanism for handling concurrent transactions, which can improve query efficiency and reduce the possibility of data conflicts. This article will delve into the principles of MySQL MVCC and provide some code examples to illustrate its implementation details.

MVCC is a multi-version control technology that achieves the isolation of concurrent transactions by maintaining multiple versions of data in the database. In MVCC, when each transaction reads data, it will see a version that is completely isolated from other transactions, which can prevent read and write conflicts of data.

MVCC in MySQL is implemented through the following two important concepts: Undo Log and Read View.

Undo Log is a log used for rollback operations. Before each transaction modifies the data, a copy of the original data will be written to the Undo Log. When a transaction needs to be rolled back, the data can be restored to the state before modification through Undo Log. At the same time, in order to prevent the Undo Log from being too large, MySQL uses the InnoDB storage engine to automatically generate the Undo Log.

Read View is used to determine the data that a transaction can see. Each transaction generates a Read View when it starts, which represents the database state when the transaction starts. Read View will record active transactions in the database and their corresponding Undo Log, so that when querying, MySQL can use Read View to determine which data is visible to the current query, and which data needs to be restored based on Undo Log.

In order to better understand how MVCC works, we will illustrate it through a simple code example below.

The sample code is as follows:

// 第一个事务
START TRANSACTION;
SELECT * FROM table1 WHERE id = 1;
// 当前事务中看到的数据：
// id = 1, name = "Alice"
// id = 2, name = "Bob"

// 第二个事务
START TRANSACTION;
UPDATE table1 SET name = "Jack" WHERE id = 1;
COMMIT;

// 第一个事务继续查询
SELECT * FROM table1 WHERE id = 1;
// 当前事务中看到的数据：
// id = 1, name = "Alice"

COMMIT;

In the above example, the first transaction obtained two records when querying the database, and then the second transaction modified the id of 1 Change the name field of the record to "Jack". Then, the first transaction continues the query and finds that the record with id 1 still has the name "Alice" in the current transaction. This is because the Read View of the first transaction has already determined the state of the database at startup, and the modification of the record with id 1 by the second transaction is not visible in the Read View of the first transaction.

The above example clearly shows how MVCC works. When MySQL queries, it will determine the visible data based on the Read View of each transaction. For uncommitted data, that is, data modified by other transactions, the current transaction cannot see it. Only when a transaction commits can other transactions see its modifications to the data.

The implementation principle of MVCC involves many details, such as transaction isolation level, lock mechanism and version chain management. Understanding these details can help us better utilize MVCC to improve query efficiency and reduce data conflicts.

To sum up, MySQL's MVCC is a mechanism for handling concurrent transactions, which improves query efficiency by maintaining multiple versions of data and controlling concurrent read and write operations. In actual use, we need to understand the principles of MVCC and choose the appropriate isolation level to balance concurrency and data consistency according to the specific situation.

The above is an introduction to in-depth understanding of MySQL MVCC principles and improving query efficiency. I hope it can inspire readers. At the same time, I hope readers can flexibly use MVCC in actual projects to improve database concurrency and performance.

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