Solution to Optimistic Lock Failure

It is an exception thrown when the data is modified by other transactions before the transaction is committed when using the optimistic locking strategy in the Spring framework, resulting in the update operation of the current transaction that cannot be successful. Optimistic locks are usually implemented through mechanisms such as version number and timestamp to avoid conflicts when updating data.

Problem analysis

When encounteringOptimisticLockingFailureException, it means that your application is using an optimistic lock mechanism to protect concurrent updates of data, but when trying to update the data, it is found that the data has been modified by other transactions. This usually means that there are multiple transactions trying to modify the same copy of data at the same time.

Reason for the error

• Concurrent conflict: Two or more transactions attempt to update the same record at the same time.
• Improper configuration of optimistic lock mechanism: Optimistic lock fields or update logic may not be configured correctly.
• Business logic issues: Business logic may lead to frequent data update conflicts.

Solution

• Analyze concurrent conflicts: Determine which operations or transactions may cause concurrent conflicts and consider whether they can be optimized or adjusted.
• Optimized optimistic lock configuration: Ensure that optimistic lock fields and update logic are configured correctly.
• Adjust business logic: Consider whether it is possible to reduce unnecessary concurrent update operations, or adopt other concurrency control strategies (such as pessimistic locks).

Solution

1. Analyze concurrent conflicts

First, you need to analyze which operations or transactions are most likely to cause concurrent conflicts. You can view database logs, application logs, or use performance analysis tools to help you locate problems.

2. Optimize optimistic lock configuration

Make sure your entity class correctly uses optimistic lock annotations (e.g.@Version) and your DAO or Repository layer correctly handles optimistic lock fields when updating data.

Example：

@Entity
public class MyEntity {
    // ... Other fields ...
    @Version
    private Long version;

    // ... getter and setter ...}

// In your Repository or DAO layer, use Spring Data JPA's save method to automatically handle optimistic locks@Repository
public interface MyEntityRepository extends JpaRepository<MyEntity, Long> {
    // ...Other methods ...}

// In your service layer, just call the save method@Service
public class MyEntityService {
    @Autowired
    private MyEntityRepository myEntityRepository;

    public void updateMyEntity(MyEntity entity) {
        (entity); // If other transactions modify the entity during this period, an OptimisticLockingFailureException will be thrown here    }
}

3. Adjust business logic

If concurrent conflicts occur frequently and cannot be resolved by optimizing optimistic lock configurations, you may want to consider adjusting your business logic. For example, you can try to reduce unnecessary concurrent update operations, or use other concurrency control strategies (such as pessimistic locks).

Things to note

• Optimistic locks are suitable for scenarios where more reads, less writes. If there are a large number of concurrent writes in your application, you may want to consider using other concurrent control strategies.
• Make sure your application can be handled properly when using optimistic locks.OptimisticLockingFailureException. For example, you can catch the exception and try the operation again, or show an error message to the user and ask them to try again.
• Regularly monitor and evaluate the performance and effectiveness of your concurrency control strategies to ensure they meet your application needs.

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