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Table of Contents
1. Understand common causes of deadlocks
2. How to view and analyze deadlock logs
3. Practical strategies to avoid deadlocks
4. How to deal with deadlocks
Home Database Mysql Tutorial Resolving deadlocks in concurrent MySQL transactions

Resolving deadlocks in concurrent MySQL transactions

Jul 07, 2025 am 12:26 AM
mysql Deadly locked business

Resolving deadlocks in concurrent MySQL transactions

MySQL deadlock is a common problem in concurrent operations, especially when multiple transactions modify multiple tables or the same set of records at the same time. Once a deadlock occurs, it will cause transaction blockage, system responses to slow down, and even affect user experience. The key to solving MySQL deadlocks is to understand its causes and avoid and deal with them by rationally designing transaction logic.

Resolving deadlocks in concurrent MySQL transactions

1. Understand common causes of deadlocks

The essence of deadlock is "looping for resources". When two or more transactions each hold part of the resources and try to obtain the resources held by the other party, it will enter a deadlock. When MySQL detects this, it will roll back one of the transactions and throw a deadlock error.

Resolving deadlocks in concurrent MySQL transactions

Common causes include:

  • Multiple transactions access the same resources (such as tables, rows) in different orders
  • Transaction execution time is too long and the occupied resources are not released in time
  • The missing index causes the lock range to expand, increasing the probability of conflict

For example:
Transaction A updates the id=1 record of user table user, and then tries to update the id=100 of order table order;
Transaction B first updated order.id=100, and then tried to update user.id=1.
At this time, a deadlock may be formed.

Resolving deadlocks in concurrent MySQL transactions

2. How to view and analyze deadlock logs

MySQL provides the SHOW ENGINE INNODB STATUS command to view the latest deadlock information. Although this part of the output is detailed, it requires some experience to interpret it clearly.

Key concerns include:

  • SQL statements that each transaction is executing
  • The lock mode held by each
  • The requested lock type and the waiting object

Usually, deadlock logs show the dependencies between transactions, helping you locate which SQLs are causing the problem.

Suggested practices:

  • Crawl the log as soon as possible after a deadlock occurs
  • Save the log for subsequent analysis
  • Track specific business logic paths in combination with application code

3. Practical strategies to avoid deadlocks

To reduce the occurrence of deadlocks, the focus is on unifying access order, shortening transaction life cycle, and optimizing index usage . Here are some specific practices:

  • Unified access order : Ensure that all transactions access data objects in the same order. For example, always operate the user table first and then the order table.
  • Reduce transaction granularity : minimize the number of operations involved in a transaction and do not do too much in one transaction.
  • Use appropriate indexes : Ensure that WHERE conditions have good index support and avoid gap lock conflicts caused by full table scanning.
  • Avoid interactive transactions : Do not wait for user input or other external events during the transaction.
  • Retry mechanism : Catch deadlock exceptions (such as 1213 error) at the application layer and retry the transaction appropriately.

For example, if you find that a certain type of business operations frequently experiences deadlocks, you can consider combining these operations into a stored procedure, or adding lock control sequences at the application layer.


4. How to deal with deadlocks

Deadlock itself cannot be completely avoided, but it can be quickly restored through reasonable mechanisms. Once MySQL rolls back one transaction, the other transaction can continue to execute.

Coping methods include:

  • Capture deadlock error codes (such as ER_LOCK_DEADLOCK) in the application and automatically retry the transaction
  • Record the time, SQL, and context of deadlocks for subsequent analysis
  • Reconstruct or split the business process of high-frequency deadlock

It should be noted that the number of retry times should not be too many to prevent infinite loops or increase the burden on the database.


Basically that's it. As long as you pay attention to transaction order, optimize SQL execution efficiency, and use indexes reasonably, you can greatly reduce deadlock problems.

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