pessimistic lock
The basic idea of pessimistic locking is to assume that there will be conflicts between concurrent operations , so the data will be locked and other operations will be blocked.
When updating data, the pessimistic lock will first acquire the lock, and then perform the update operation. Other operations need to wait for the release of the lock before continuing.
Advantages of pessimistic locking
The advantage of pessimistic locking is that it can guarantee data consistency, because other operations cannot modify the data during the update operation.
Disadvantages of pessimistic locking
(1) Performance issues
Pessimistic locks will block other operations and reduce the concurrency performance of the system. If you need to wait for the lock to be released during the operation, it will increase the response time of the operation and affect the user experience.
(2) Deadlock problem
Pessimistic locks may cause deadlock problems, that is, multiple threads wait for each other to release the lock and cannot continue to execute.
(3) Lock granularity problem
The pessimistic lock has a large lock granularity, which may prevent some data from being operated concurrently and affect the concurrent performance of the system.
(4) High programming complexity
When using pessimistic locking, it is necessary to perform lock locking and release operations, and it is necessary to deal with issues such as lock granularity and timeout, and the programming complexity is relatively high.
Pessimistic lock usage scenarios
(1) High concurrency
Pessimistic locking is suitable for use in scenarios with high concurrency because it can ensure data consistency.
(2) Write more and read less
Pessimistic locking is suitable for use in scenarios where more writes are less read, because read operations need to wait for write operations to release the lock before proceeding.
(3) High probability of data conflict
Pessimistic locks are suitable for use in scenarios with a high probability of data conflicts, that is, conflicts between concurrent operations are likely to occur.
(4) Implementation mechanism of pessimistic lock
Pessimistic locks are usually implemented through database row-level locks or distributed locks. When updating data, the data will be locked, and other operations need to wait for the release of the lock before proceeding.
Pessimistic lock implementation
(1) Database row-level locks
The database provides a row-level lock mechanism, which can lock data rows in a transaction.
By using the SELECT ... FOR UPDATE statement in the transaction, you can obtain the pessimistic lock on the data row, and other transactions need to wait for the release of the lock to operate.
(2) Distributed lock
In distributed systems, pessimistic locks can be implemented using distributed locks.
There are many ways to implement distributed locks, such as database-based, cache-based, ZooKeeper-based, etc. By acquiring distributed locks, pessimistic locking of data in a distributed environment can be guaranteed.
(3) Pessimistic read
When reading data, directly use pessimistic lock to lock data, and other operations need to wait for the release of the lock. This method is suitable for scenarios with more writes and less reads to ensure data consistency.
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