The ACID characteristics of a transaction refer to atomicity, consistency, isolation and persistence. Atomicity ensures that all operations in a transaction are done or not; consistency ensures that the database is transferred from one consistent state to another; isolation prevents mutual interference when multiple transactions are executed concurrently; persistence ensures that the results of the transaction are permanently saved after the transaction is committed. Transactions ensure data consistency through redo log, undo log and lock mechanisms. Redo Log is used for crash recovery, Undo Log supports rollback and MVCC, and the lock mechanism controls concurrent access to avoid dirty reading, non-repeatable reading and phantom reading. Correct use of transactions requires reasonable control of transaction boundaries and the appropriate isolation level is selected. For example, READ COMMITTED is suitable for most scenarios. REPEATABLE READ can avoid phantom reading but may increase lock overhead. Common misconceptions include the belief that transactions can fully ensure data security, submitting them and ignoring performance problems caused by long transactions. In actual development, transaction granularity should be controlled, fast in and out, and reliability should be improved in combination with master-slave replication and other mechanisms.

A MySQL transaction refers to a set of SQL statements that are executed as a whole. It either succeeds all or fails all rollbacks and does not stay in an intermediate state. This mechanism is a key means to ensure data consistency.

What is the ACID feature of a transaction?

Transactions must meet four characteristics: atomicity, consistency, isolation, and persistence , which is commonly known as ACID.

• Atomicity : All operations in a transaction are either done or not.
• Consistency : The transaction must change the database from one consistent state to another.
• Isolation : When multiple transactions are executed concurrently, the execution of one transaction should not affect other transactions.
• Persistence : Once a transaction is committed, the result is permanent and will not be lost even if the system crashes.

These four features work together to ensure that the data remains correct and consistent in concurrent access or exceptions.

How to ensure data consistency in transactions?

The transaction itself cannot directly "guaranteed" consistency. It indirectly achieves consistency guarantee through the underlying logging mechanism (such as redo log, undo log) and locking mechanism .

• Redo Log : records the physical modifications of the transaction to the data page, and is used to replay the committed transaction during crash recovery.
• Undo Log : Records the status before data change, used for transaction rollback and MVCC (multi-version concurrency control).
• Locking mechanism : includes row-level locks, table-level locks, etc., which are used to control the access of concurrent transactions to the same resource and prevent dirty reading, non-repeatable reading, and fantasy reading.

For example, when two transactions modify the same record at the same time, if there is no locking mechanism, the data may be overwritten or inconsistent. Using the InnoDB engine line locks combined with the transaction isolation level can effectively avoid this type of problem.

How to use transactions correctly?

The key to using transactions is to reasonably control the boundaries of transactions and to select the appropriate transaction isolation level .

A common practice is to explicitly open transactions in your code:

 START TRANSACTION;
-- Perform multiple SQL operations UPDATE accounts SET balance = balance - 100 WHERE user_id = 1;
UPDATE orders SET status = 'paid' WHERE order_id = 1001;
COMMIT;

If an error occurs in the middle, you can execute ROLLBACK to roll back the entire transaction.

Also, note:

• Don't put too many irrelevant operations in one transaction, otherwise it will easily cause locks to wait or even deadlocks.
• Choose the appropriate isolation level according to business needs. For example, read Committed (READ COMMITTED) is suitable for most scenarios, and repeatable reading (REPEATABLE READ) can avoid phantom reading but may bring higher lock overhead.

Common misunderstandings and precautions

Many people think that as long as the transaction is used, the data will be safe, but in fact it is not.

• If there is no lock in the transaction, concurrent write conflicts may still occur.
• After submitting the transaction, the disk is not dropped immediately, but relies on the buffer pool and log mechanism to flush the disk asynchronously. In extreme cases, data may still be lost (such as power outage). At this time, it is necessary to combine dual-machine hot standby, master-slave replication and other mechanisms to improve availability and reliability.
• Long transactions are likely to cause performance problems, such as undo log expansion, intensified lock competition, and excessive MVCC versions.

Therefore, in actual development, we should pay attention to controlling the transaction granularity, avoid processing a large amount of logic in a transaction, and try to achieve "fast in and out".

Basically that's it. Affairs is not a panacea, and it is only effective if you use it well.

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