Home Database Mysql Tutorial How to implement MySQL underlying optimization: performance optimization of transaction locks and methods to avoid deadlocks

How to implement MySQL underlying optimization: performance optimization of transaction locks and methods to avoid deadlocks

Nov 08, 2023 pm 12:57 PM
mysql optimization deadlock transaction lock

How to implement MySQL underlying optimization: performance optimization of transaction locks and methods to avoid deadlocks

How to achieve MySQL underlying optimization through transaction lock performance optimization and deadlock avoidance

Introduction:
In the MySQL database, transaction locks play a crucial role important role. If the performance of transaction locks is poor or there is a deadlock, it will seriously affect the performance and stability of the database. Therefore, this article will focus on how to achieve the underlying optimization of MySQL by optimizing the performance of transaction locks and avoiding deadlocks.

1. Performance optimization method of transaction lock

  1. Use appropriate transaction isolation level

MySQL provides a variety of transaction isolation levels, including read Commit, read committed, repeatable read, and serialize. Different isolation levels have different effects on the performance of transaction locks. Typically, repeatable read is a good choice because it provides good concurrency performance and avoids some common concurrency problems.

Sample code:

SET SESSION TRANSACTION ISOLATION LEVEL REPEATABLE READ;
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  1. Reasonable use of transactions

When using transactions, try to reduce the execution time of the transaction and the lock holding time. The longer the transaction execution time, the higher the probability of lock conflict, thus affecting concurrency performance. Properly splitting transactions and splitting multiple operations into multiple small transactions can improve concurrency performance.

Sample code:

BEGIN;
UPDATE table1 SET column1 = value1 WHERE id = 1;
COMMIT;
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  1. Minimize the number of locks in a transaction

Use the granularity of locks reasonably and minimize the scope of locks, which can improve Concurrency performance. For example, when performing a large number of read operations, you can use read locks (shared locks) instead of write locks (exclusive locks) to reduce the locking of data.

Sample code:

SELECT * FROM table1 FOR SHARE;
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  1. Use indexes to speed up lock operations

When performing lock operations, using appropriate indexes can greatly improve performance. Indexes can speed up locking scope and reduce lock contention.

Sample code:

CREATE INDEX idx_column1 ON table1(column1);
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2. Methods to avoid deadlock

  1. Locating deadlock

MySQL provides a SHOW ENGINE The INNODB STATUS command can be used to view the current deadlock situation. Deadlock problems can be located and resolved based on this information.

Sample code:

SHOW ENGINE INNODB STATUS;
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  1. Optimize transaction order

If a deadlock occurs, you can try to adjust the order of transactions to reduce the probability of deadlock. For example, database tables can be accessed in the same order to avoid deadlocks.

Sample code:

BEGIN;
SELECT * FROM table1 FOR UPDATE;
SELECT * FROM table2 FOR UPDATE;
COMMIT;
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  1. Use appropriate lock granularity

When using locks, choosing the lock granularity reasonably can reduce the probability of deadlock. . If the lock granularity is too large, it can easily lead to deadlock. If the lock granularity is too small, lock contention may occur.

Sample code:

SELECT * FROM table1 WHERE id = 1 FOR UPDATE;
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  1. Set the timeout period

In order to avoid deadlock from continuing, you can set an appropriate timeout period. When a transaction holds a lock for more than the set timeout, it will be actively terminated by MySQL, thereby releasing the lock resources.

Sample code:

SET SESSION innodb_lock_wait_timeout = 10;
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Conclusion:
By optimizing the performance of transaction locks and avoiding deadlocks, the underlying optimization of MySQL can be achieved. Reasonable use of transaction isolation levels, minimizing the number of locks in transactions, and using indexes to speed up lock operations can improve the concurrency performance of the database. At the same time, the occurrence of deadlocks can be reduced by locating deadlocks, optimizing transaction order, using appropriate lock granularity, and setting timeouts.

Of course, the above optimization methods are just some common examples, and specific optimization methods need to be adjusted and implemented according to the actual situation. To sum up, by optimizing the performance of transaction locks and avoiding deadlocks, we can optimize the underlying MySQL and improve the performance and stability of the database.

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