1. What is MySQL deadlock?
Deadlock refers to the phenomenon that two or more transactions wait for each other due to competition for lock resources during execution, and they will not be able to continue to execute without external interference. In layman's terms, it means that two or more transactions are waiting for the other party to release the lock, resulting in a stalemate and bringing the entire system to a standstill.
2. Causes of MySQL deadlocks.
1 Sequential execution of transactions
When multiple users access a database concurrently, a deadlock may be triggered if each user executes an SQL statement that needs to wait for other transactions to release resources. For example, if two users perform operations on Table A and Table B at the same time, User 1 locks Table A and User 2 locks Table B first. At this point, User 1 needs to wait for User 2 to release the lock on Table B before proceeding, and vice versa. If both users wait for the other to release the lock, a deadlock will occur.
2 Race conditions for business
When multiple transactions operate on the same data, deadlocks can also occur if they are not in the same order. For example, there are two transactions, t1 and t2, that modify data A and B, respectively. Initially, T1 acquires A's lock and waits for B's lock to be released, while T2 acquires B's lock and waits for A's lock to be released. At this time, a deadlock will also occur.
3. Example of MySQL deadlock.
Consider a bank transfer scenario where there are two users, A and B, both of whom start the transfer operation with an account balance of 100 yuan. Let's say A wants to transfer $100 to B, and B wants to transfer $100 to A. The steps are as follows:
A transaction is executed, lock the balance of account A, and check whether the balance of account A is sufficient to transfer money to B (for example, 100 yuan).
The B transaction is executed, the balance of account B is locked, and the balance of account B is checked to see if the balance of account B is sufficient to transfer to A (also assuming 100 yuan).
Transaction A attempts to reduce the balance of account A to $99 and submits the transaction. At this point, the balance of account A is no longer sufficient to support the transfer to B.
Transaction B attempts to reduce the balance of account B to $99 and submits the transaction. At this time, the balance of account B is no longer enough to support the transfer to A.
Transaction A waits for the lock release of account B, and transaction B waits for the lock release of account A. As a result, none of them can continue to execute, resulting in deadlocks.
4. MySQL deadlock solution.
1 Avoid sequential execution of transactions.
When accessing a database concurrently, you should try to avoid sequential execution of transactions. This can be done by using appropriate indexes, avoiding unnecessary operations in transactions, using row-level locks instead of table-level locks whenever possible, and so on. This reduces the amount of time a transaction waits for other transactions to release the lock, thereby reducing the risk of deadlocks.
2 Avoid race conditions for transactions.
To avoid race conditions for transactions, you can use the following measures: use optimistic locks, use pessimistic locks, use distributed locks, and so on. Optimistic locking assumes that multiple transactions do not operate on the same data at the same time, so they can occur at the same time without interfering with each other. Pessimistic locks assume that multiple transactions will operate on the same data at the same time, so locks need to be used to ensure the exclusivity of the data. Distributed locks enable synchronization and coordination of operations across multiple database nodes.
3 Optimize database structure and workload.
For scenarios where deadlocks may occur, you can optimize the database structure and workload to reduce the risk of deadlocks. For example, accounts that frequently make transfers can use a separate table to store transfer records to reduce the scope of locking on the primary table, use appropriate isolation levels and timeout parameters, and so on. At the same time, ensure that the performance parameters of the database (such as buffer size, number of connections, etc.) are set appropriately to avoid resource contention and excessive concurrent access.