MySQL supports several isolation levels that control the behavior of transactions and how they interact with other transactions. Here are the four isolation levels supported by MySQL, along with examples of how they might behave:
- READ UNCOMMITTED: This is the lowest isolation level and allows transactions to read data that has not yet been committed by other transactions. This can lead to dirty reads, where a transaction reads data that is later rolled back by another transaction.
Example: A transaction reads the balance of a bank account before another transaction has finished transferring money into the account. If the second transaction is rolled back, the first transaction will have read an incorrect balance.
- READ COMMITTED: This isolation level allows transactions to read only data that has been committed by other transactions. This helps to prevent dirty reads, but it can still lead to non-repeatable reads and phantom reads.
Example: A transaction reads the balance of a bank account, and another transaction transfers money into the account and commits the change. If the first transaction reads the balance again, it will see a different value than it did previously.
- REPEATABLE READ: This isolation level prevents non-repeatable reads and phantom reads by locking rows that are read by a transaction until the transaction is committed or rolled back. This can improve consistency, but it can also lead to deadlocks if two transactions attempt to lock the same rows.
Example: A transaction reads the balance of a bank account, and another transaction transfers money out of the account. If the first transaction reads the balance again, it will see the same value as it did previously, because the rows have been locked.
- SERIALIZABLE: This is the highest isolation level and prevents all dirty reads, non-repeatable reads, and phantom reads by locking all rows that are read or modified by a transaction until the transaction is committed or rolled back. This ensures complete consistency, but it can also lead to reduced concurrency and slower performance.
Example: A transaction reads the balance of a bank account, and another transaction attempts to transfer money out of the account. The second transaction will have to wait until the first transaction is committed or rolled back because all rows have been locked.
Overall, different isolation levels offer different trade-offs between consistency and concurrency, and it is important to choose the level that best meets the needs of your application and workload.