The relationship between MySQL locks, transaction isolation levels and applications

MySQL lock transaction isolation level and application
In the database, the transaction isolation level is a very important concept, which determines the degree of isolation between concurrent transactions. MySQL provides four transaction isolation levels: READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, and SERIALIZABLE. Different transaction isolation levels have different locking strategies for data reading and writing, so it is crucial to correctly select and use the appropriate transaction isolation level in your application.

1. READ UNCOMMITTED (read uncommitted): At this level, transactions can read uncommitted data from other transactions. This means that a dirty read may occur, that is, unverified data is read. This level is generally not recommended unless you need to obtain very real-time data under special circumstances.
2. READ COMMITTED (read committed): At this level, transactions can only read submitted data. This avoids dirty read problems, but may cause non-repeatable read problems. Non-repeatable read refers to reading the same data twice in the same transaction, but the results are inconsistent. This is because other transactions may have updated the data during transaction execution.
3. REPEATABLE READ (repeatable read): At this level, a transaction can read the same data multiple times with consistent results. This is achieved by locking the data during the reading process. At the REPEATABLE READ level, the read operation will share the lock on the data rows that meet the conditions, so that other transactions can only read the data but cannot modify the data. However, phantom read problems may still occur. Phantom reading refers to reading data in a range twice in the same transaction, but the results are inconsistent. This is because during transaction execution, other transactions may have inserted or deleted data that meets the conditions.
4. SERIALIZABLE (serialization): At this level, transactions are executed serially. This means that only one transaction can modify the data at the same point in time, and other transactions are waiting for the lock to be released. This level can completely avoid the problems of dirty reads, non-repeatable reads, and phantom reads, but it also has a considerable impact on concurrency performance because you need to wait for other transactions to release the lock.

The following uses specific code examples to demonstrate the locking strategies under different transaction isolation levels:

First create a test table:

CREATE TABLE test_table ( id INT PRIMARY KEY, name VARCHAR(100), age INT );

Then demonstrate different transactions respectively Locking strategy under isolation level:

1. READ UNCOMMITTED:

   -- 执行事务1 SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED; START TRANSACTION; SELECT * FROM test_table WHERE id = 1; -- 执行事务2 START TRANSACTION; UPDATE test_table SET age = 20 WHERE id = 1; COMMIT; -- 继续执行事务1 SELECT * FROM test_table WHERE id = 1; COMMIT;

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   In this example, transaction 1 reads the data modified but not committed by transaction 2.

2. READ COMMITTED:

   -- 执行事务1 SET TRANSACTION ISOLATION LEVEL READ COMMITTED; START TRANSACTION; SELECT * FROM test_table WHERE id = 1; -- 执行事务2 START TRANSACTION; UPDATE test_table SET age = 20 WHERE id = 1; COMMIT; -- 继续执行事务1 SELECT * FROM test_table WHERE id = 1; COMMIT;

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   In this example, transaction 1 can only read the data that transaction 2 has submitted.

3. REPEATABLE READ：

   -- 执行事务1 SET TRANSACTION ISOLATION LEVEL REPEATABLE READ; START TRANSACTION; SELECT * FROM test_table WHERE id = 1; -- 执行事务2 START TRANSACTION; UPDATE test_table SET age = 20 WHERE id = 1; COMMIT; -- 继续执行事务1 SELECT * FROM test_table WHERE id = 1; COMMIT;

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   In this example, transaction 1 adds a shared lock when reading data, and transaction 2 waits for transaction 1 to release the shared lock before it can be executed. .

4. SERIALIZABLE:

   -- 执行事务1 SET TRANSACTION ISOLATION LEVEL SERIALIZABLE; START TRANSACTION; SELECT * FROM test_table WHERE id = 1; -- 执行事务2 START TRANSACTION; UPDATE test_table SET age = 20 WHERE id = 1; COMMIT; -- 继续执行事务1 SELECT * FROM test_table WHERE id = 1; COMMIT;

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   In this example, transaction 1 adds a shared lock when reading data, and transaction 2 waits for transaction 1 to release the shared lock before it can be executed.

   Through the above code examples, we can see how the lock strategy works under different transaction isolation levels. In actual application development, it is very necessary to choose the appropriate transaction isolation level, which can be selected according to specific business scenarios and performance requirements.

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