MySQL concurrency problems are usually caused by improper use of lock mechanisms. Solutions include: 1. Prioritize the InnoDB engine and index the update fields to use row locks; 2. Reasonably set the transaction isolation level according to business needs to avoid being too high or too low; 3. Reduce deadlocks by keeping transactions short, accessing resources in sequence, explicit locking, etc.; 4. Adjust lock priority and parameter configuration according to read and write scenarios.

MySQL's concurrency control and locking mechanism are the key to ensuring data consistency and performance when multiple users operate simultaneously. If you find that the system has slow response, frequent deadlocks or long transaction waiting time under high concurrency, it is likely to be related to the way the lock is used.

The following is a few common perspectives to talk about the actual key points of MySQL locking mechanism and concurrent control.

Table lock vs row lock: it is important to choose the right lock type

MySQL supports multiple lock types, the most common of which are table locks and row locks .

• Table locks are suitable for the MyISAM engine. They lock the entire table and are suitable for scenarios where there are more reads, fewer writes, but have poor concurrent write capabilities.
• Row locks are provided by InnoDB, which only locks the data rows involved, supports higher concurrency, but are also more likely to cause deadlocks.

For example: When you perform UPDATE or DELETE operation, InnoDB will decide whether it is a row lock or a table lock based on whether the query condition hits the index. If there is no proper index, even if you only want to change one row, it may lock the entire table.

So suggestion:

• Try to use the InnoDB storage engine
• Add indexes to fields that are frequently used for updates
• Avoid enlargement of lock range by full table scanning

Transaction isolation level affects concurrent behavior

MySQL supports four transaction isolation levels:

• Read Uncommitted
• Read Committed
• Repeatable Read (default)
• Serializable

Different isolation levels determine what data can be seen between transactions and will also affect the behavior of locks.

for example:

• Under "Read Committed", the consistency view is regenerated every read, and it may see modifications committed by other transactions;
• "Repeatable Read" ensures that the same data is read multiple times in the entire transaction and the result remains unchanged, but gap locks may be used to prevent phantom reading.

Setting too high (such as Serializable) will cause a lot of lock competition, and too low may cause dirty reads or non-repeatable reading problems. It is recommended to make reasonable choices based on business needs.

Deadlock is not the end of the world, but you must be able to check and guard

A deadlock is a situation where two or more transactions are waiting for each other to release the lock. Although InnoDB has a deadlock detection mechanism, frequent deadlocks can affect performance and user experience.

The way to view deadlocks is simple:
Execute SHOW ENGINE INNODB STATUS\G , and you can see the details of the latest deadlock in the LATEST DETECTED DEADLOCK section in the output.

How to avoid deadlocks?

• Keep business short and concise, reduce lock holding time
• When multiple transactions access resources, try to do it in the same order.
• Lock it before operating a batch of data (such as using SELECT ... FOR UPDATE )

A detail is: Sometimes you don't explicitly start a transaction, but if you use FOR UPDATE , MySQL will automatically start an implicit transaction and lock the relevant records.

Writing locks are preferred or reading locks are preferred? Look at your business scenario

By default, InnoDB prefers write locks as write operations are usually more important. But this can also cause read requests to wait in line.

You can control the lock waiting behavior by adjusting parameters such as innodb_lock_wait_timeout and innodb_rollback_on_timeout . However, these are advanced configurations and are recommended to go online after verification of the test environment.

If it is a read-intensive application (such as a report system), you can consider changing some queries READ COMMITTED and using READ ONLY transactions to optimize performance appropriately.

The lock mechanism and concurrent control are actually not complicated, but there are many things that are easy to be ignored, such as missing indexes, too large transactions, and unreasonable SQL execution plan, which will indirectly lead to locking problems. When troubleshooting, you can start from slow query logs and lock waiting logs and gradually locate them.

Basically that's it.

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