Imagine you are developing a multi-threaded application for a bank. How would you ensure that when multiple threads are trying to update the same account, the account data remains consistent?
- Employing optimistic locking techniques such as versioning, where each thread checks a version number before updating the account.
- Implementing thread-safe data structures like ConcurrentHashMap to store account information.
- Using synchronized methods or blocks to lock access to the account data when it's being updated.
- Utilizing atomic operations provided by classes like AtomicInteger to ensure atomic updates of account data.
In a multi-threaded bank application, consistency can be achieved by using synchronized methods or blocks to ensure that only one thread can access and update the account data at a time. This prevents race conditions and data corruption. Other options, like using thread-safe data structures or atomic operations, can help with performance but may not guarantee consistency in complex scenarios. Optimistic locking with versioning can also be used to handle concurrent updates.
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