Optimistic concurrency control

Posted 2020-10-10 rsapaper

Optimistic concurrency control

 https://en.wikipedia.org/wiki/Optimistic_concurrency_control

 

Optimistic concurrency control (OCC) is a concurrency control method applied to transactional systems such as relational database management systems and software transactional memory. OCC assumes that multiple transactions can frequently complete without interfering with each other. While running, transactions use data resources without acquiring locks on those resources. Before committing, each transaction verifies that no other transaction has modified the data it has read. If the check reveals conflicting modifications, the committing transaction rolls back and can be restarted.^[1] Optimistic concurrency control was first proposed by H.T. Kung.^[2]

 

【无锁，事务不等待】

OCC is generally used in environments with low data contention. When conflicts are rare, transactions can complete without the expense of managing locks and without having transactions wait for other transactions‘ locks to clear, leading to higher throughput than other concurrency control methods. However, if contention for data resources is frequent, the cost of repeatedly restarting transactions hurts performance significantly; it is commonly thought^[who?] that other concurrency control methods have better performance under these conditions.^{[citation needed]} However, locking-based ("pessimistic") methods also can deliver poor performance because locking can drastically limit effective concurrency even when deadlocks are avoided.

 

 

https://www.ibm.com/support/knowledgecenter/en/SSPK3V_7.0.0/com.ibm.swg.im.soliddb.sql.doc/doc/pessimistic.vs.optimistic.concurrency.control.html

 

 

• Pessimistic concurrency control (or pessimistic locking) is called "pessimistic" because the system assumes the worst — it assumes that two or more users will want to update the same record at the same time, and then prevents that possibility by locking the record, no matter how unlikely conflicts actually are.

  The locks are placed as soon as any piece of the row is accessed, making it impossible for two or more users to update the row at the same time. Depending on the lock mode (shared, exclusive, or update), other users might be able to read the data even though a lock has been placed. For more details on the lock modes, see Lock modes: shared, exclusive, and update.

• Optimistic concurrency control (or optimistic locking) assumes that although conflicts are possible, they will be very rare. Instead of locking every record every time that it is used, the system merely looks for indications that two users actually did try to update the same record at the same time. If that evidence is found, then one user‘s updates are discarded and the user is informed.

  For example, if User1 updates a record and User2 only wants to read it, then User2 simply reads whatever data is on the disk and then proceeds, without checking whether the data is locked. User2 might see slightly out-of-date information if User1 has read the data and updated it, but has not yet committed the transaction.

  Optimistic locking is available on disk-based tables (D-tables) only.

 

 

https://docs.jboss.org/jbossas/docs/Server_Configuration_Guide/4/html/TransactionJTA_Overview-Pessimistic_and_optimistic_locking.html

6.1.1. Pessimistic and optimistic locking

Transactional isolation is usually implemented by locking whatever is accessed in a transaction. There are two different approaches to transactional locking: Pessimistic locking and optimistic locking.

The disadvantage of pessimistic locking is that a resource is locked from the time it is first accessed in a transaction until the transaction is finished, making it inaccessible to other transactions during that time. If most transactions simply look at the resource and never change it, an exclusive lock may be overkill as it may cause lock contention, and optimistic locking may be a better approach. With pessimistic locking, locks are applied in a fail-safe way. In the banking application example, an account is locked as soon as it is accessed in a transaction. Attempts to use the account in other transactions while it is locked will either result in the other process being delayed until the account lock is released, or that the process transaction will be rolled back. The lock exists until the transaction has either been committed or rolled back.

With optimistic locking, a resource is not actually locked when it is first is accessed by a transaction. Instead, the state of the resource at the time when it would have been locked with the pessimistic locking approach is saved. Other transactions are able to concurrently access to the resource and the possibility of conflicting changes is possible. At commit time, when the resource is about to be updated in persistent storage, the state of the resource is read from storage again and compared to the state that was saved when the resource was first accessed in the transaction. If the two states differ, a conflicting update was made, and the transaction will be rolled back.

In the banking application example, the amount of an account is saved when the account is first accessed in a transaction. If the transaction changes the account amount, the amount is read from the store again just before the amount is about to be updated. If the amount has changed since the transaction began, the transaction will fail itself, otherwise the new amount is written to persistent storage.

 

 

【事务独立:通过对资源加锁实现】

事务锁：
    悲观锁：因A事务对某资源加锁后，其他事务无法访问该资源，直到该事务访问结束而锁被释放
    乐观锁：因A事务对某资源加锁后，其他事务可以访问该资源；但数据更新时候，如果两事务对数据的更新冲突，则发生数据回滚，资源不被任何一个事务修改；如果不同事务对资源的更新一致，则资源被更新。