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]

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 that other concurrency control methods have better performance under these conditions. However, locking-based ("pessimistic") methods also can deliver poor performance because locking can drastically limit effective concurrency even when deadlocks are avoided.

OCC phases

More specifically, OCC transactions involve these phases:

Web usage

The stateless nature of HTTP makes locking infeasible for web user interfaces. It's common for a user to start editing a record, then leave without following a "cancel" or "logout" link. If locking is used, other users who attempt to edit the same record must wait until the first user's lock times out.

HTTP does provide a form of built-in OCC: The GET method returns an ETag for a resource and subsequent PUTs use the ETag value in the If-Match headers; while the first PUT will succeed, the second will not, as the value in If-Match is based on the first version of the resource.[3]

Some database management systems offer OCC natively - without requiring special application code. For others, the application can implement an OCC layer outside of the database, and avoid waiting or silently overwriting records. In such cases, the form includes a hidden field with the record's original content, a timestamp, a sequence number, or an opaque token. On submit, this is compared against the database. If it differs, the conflict resolution algorithm is invoked.

Examples

See also

References

  1. Johnson, Rohit (2003). "Common Data Access Issues". Expert One-on-One J2EE Design and Development. Wrox Press. ISBN 0-7645-4385-7.
  2. Kung, H.T. (1981). "On Optimistic Methods for Concurrency Control". ACM Transactions on Database Systems.
  3. "Editing the Web - Detecting the Lost Update Problem Using Unreserved Checkout". W3C Note. 10 May 1999.
  4. Help:Edit conflict
  5. "Bugzilla: FAQ: Administrative Questions". MozillaWiki. 11 April 2012.
  6. "Module ActiveRecord::Locking". Rails Framework Documentation.
  7. "Object Relational Mapping (GORM)". Grails Framework Documentation.
  8. "Transaction Processing". GT.M Programmers Guide UNIX Edition.
  9. "Tip 19 – How to use Optimistic Concurrency with the Entity Framework". MSDN Blogs. 19 May 2009.
    • Most revision control systems support the "merge" model for concurrency, which is OCC.
  10. "Transaction Concurrency - Optimistic Concurrency Control". Mimer Developers - Features. 26 February 2010.
  11. "The Datastore". What Is Google App Engine?. 27 August 2010.
  12. "Elasticsearch - Guide - Index API". Elasticsearch Guide. 22 March 2012.
  13. "Transactions - MonetDB". 16 January 2013.
  14. "Transactions in Redis".

External links

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