Optimistic concurrency control: Difference between revisions

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{{Short description|Concurrency control method}}

'''Optimistic concurrency control''' ('''OCC'''), also known as '''optimistic locking''', is a [[Non-lock concurrency control|non-locking 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.<ref>{{cite book | title = Expert One-on-One J2EE Design and Development | first = Rohit | last = Johnson | publisher = Wrox Press | year = 2003 | isbn = 978-0-7645-4385-2 | chapter = Common Data Access Issues | chapterurlchapter-url = http://learning.infocollections.com/ebook%202/Computer/Programming/Java/Expert_One-on-One_J2EE_Design_and_Development/6266final/LiB0080.html | archive-url = https://web.archive.org/web/20111008203709/http://learning.infocollections.com/ebook%202/Computer/Programming/Java/Expert_One-on-One_J2EE_Design_and_Development/6266final/LiB0080.html | archive-date = 8 October 2011}}</ref> Optimistic concurrency control was first proposed in 1979 by [[HT Kung|H. T. Kung]] and John T. Robinson.<ref name="KungRobinson1981">{{Cite news| title = On Optimistic Methods for Concurrency Control | first = J. T. Robinson | last = H. T. Kung | publisher = ACM Transactions on Database Systems | year = 1981 | url = https://apps.dtic.mil/dtic/tr/fulltext/u2/a081452.pdf| archive-url = https://web.archive.org/web/20190831230313/https://apps.dtic.mil/dtic/tr/fulltext/u2/a081452.pdf| url-status = live| archive-date = August 31, 2019}}</ref>

OCC is generally used in environments with low [[Block contention|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;, itin iswhich commonly thought{{who|date=July 2016}} thatcase other [[concurrency control]] methods havemay be better performance under these conditionssuited.{{citation needed|date=July 2016}} However, locking-based ("pessimistic") methods also can deliver poor performance because locking can drastically limit effective concurrency even when deadlocks are avoided.

== Phases of Optimistic concurrency control ==

{{Unreferenced section|date=August 2010}}

More specifically, Optimistic concurrency control transactions involve these phases:

== Phases of Optimisticoptimistic concurrency control ==

More specifically, Optimistic concurrency control transactions involve these phases:<ref name="KungRobinson1981" />

*'''Begin''': Record a timestamp marking the transaction's beginning.

*'''Modify''': Read database values, and tentatively write changes.

*'''Validate''': Check whether other transactions have modified data that this transaction has used (read or written). This includes transactions that completed after this transaction's start time, and optionally, transactions that are still active at validation time.

*'''Commit/Rollback''': If there is no conflict, make all changes take effect. If there is a conflict, resolve it, typically by aborting the transaction, although other resolution schemes are possible. Care must be taken to avoid a [[TOCTTOUtime-of-check to time-of-use]] bug, particularly if this phase and the previous one are not performed as a single [[linearizability|atomic]] operation.

==Web usage==

The [[Stateless server|stateless]] nature of [[HTTP]] makes locking infeasible for web user interfaces. It's is 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 response to an initial GET methodrequest returnscan include an [[HTTP ETag|ETag]] for asubsequent resourcePUT andrequests subsequent PUTsto use the ETag value in the If-Match headers;header. while the firstAny PUT willrequests succeed,with thean secondout-of-date willETag not, asin the value in If-Match isheader basedcan onthen the first version of thebe resourcerejected.<ref>{{cite web | url = http://www.w3.org/1999/04/Editing/ | title = Editing the Web - Detecting the Lost Update Problem Using Unreserved Checkout | work = W3C Note | date = 10 May 1999}}</ref>

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 (web)|form]] includesmay include 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===

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* [[Bugzilla]] uses OCC; [[edit conflict]]s are called "mid-air collisions".<ref>{{cite web | url = https://wiki.mozilla.org/Bugzilla:FAQ#Does_Bugzilla_provide_record_locking_when_there_is_simultaneous_access_to_the_same_bug.3F_Does_the_second_person_get_a_notice_that_the_bug_is_in_use_or_how_are_they_notified.3F | title = Bugzilla: FAQ: Administrative Questions | work = MozillaWiki | date = 11 April 2012}}</ref>

* The [[Ruby on Rails]] framework has an API for OCC.<ref>{{cite web | url = http://api.rubyonrails.org/classes/ActiveRecord/Locking/Optimistic.html | title = Module ActiveRecord::Locking | work = Rails Framework Documentation}}</ref>

* The [[Grails (framework)|Grails]] framework uses OCC in its default conventions.<ref>{{cite web | url = http://grails.org/doc/1.0.x/guide/single.html#5.3.5%20Pessimistic%20and%20Optimistic%20Locking | title = Object Relational Mapping (GORM) | work = Grails Framework Documentation | url-status = dead | archiveurlarchive-url = https://web.archive.org/web/20140815173309/http://grails.org/doc/1.0.x/guide/single.html#5.3.5%20Pessimistic%20and%20Optimistic%20Locking | archivedatearchive-date = 2014-08-15 }}</ref>

* The [[GT.M]] database engine uses OCC for managing transactions<ref>{{cite web | url = http://tinco.pair.com/bhaskar/gtm/doc/books/pg/UNIX_manual/ch05s17.html | title = Transaction Processing | work = GT.M Programmers Guide UNIX Edition}}</ref> (even single updates are treated as mini-transactions).

* [[Microsoft]]'s [[Entity Framework]] (including Code-First) has built-in support for OCC based on a binary timestamp value.<ref>{{cite web | url = httphttps://blogslearn.msdnmicrosoft.com/ben-us/alexjef/archivecore/2009saving/05/20/tip-19-how-to-useconcurrency?tabs=data-annotations#optimistic-concurrency-in-the-entity-framework.aspx | title = TipHandling 19Concurrency –Conflicts How| towork use Optimistic Concurrency with the= Entity Framework |documentation work = MSDN Blogshub | date = 195 MayJuly 20092023}}</ref>

* Most [[revision control]] systems support the "merge" model for concurrency, which is OCC.</ref>{{cn|date=February 2023}}

* [[Mimer SQL]] is a [[DBMS]] that only implements optimistic concurrency control.<ref>{{cite web | url = httphttps://developer.mimer.com/featuresarticle/transaction-concurrency-optimistic-concurrency-control/feature_15.htm | title = Transaction Concurrency - Optimistic Concurrency Control | work = Mimer Developers - Features | date = 26 February 2010 | access-date = 622 May 2013 | archive-url = https://web.archive.org/web/20130321105959/http://developer.mimer.com/features/feature_15.htm | archive-date = 21 March 2013 | url-status = dead | df = dmy-allDec 2023}}</ref>

* [[Pyrrho (RDBMS)|Pyrrho]] is a [[DBMS]] that uses optimistic concurrency control.<ref name="DBTechSQLT">{{cite book|title=SQL Transactions Theory and hands-on exercises|url=http://myy.haaga-helia.fi/~dbms/dbtechnet/download/SQL-Transactions_handbook_EN.pdf|first1=Martti|last1=Laiho|first2=Dimitris A.|last2=Dervos|first3=Kari|last3=Silpiö

|isbn=978-952-93-2420-0|url-status=live|archive-url=https://web.archive.org/web/20170918213513/http://myy.haaga-helia.fi/~dbms/dbtechnet/download/SQL-Transactions_handbook_EN.pdf|archive-date=18 September 2017}}</ref>{{rp|30}}

* [[Google App Engine]] data store uses OCC.<ref>{{cite web | url = http://code.google.com/appengine/docs/whatisgoogleappengine.html | title = The Datastore | work = What Is Google App Engine? | date = 27 August 2010}}</ref>

* The [[Apache Solr]] search engine supports OCC via the {{Mono|_version_}} field.<ref>{{cite web|url=https://lucene.apache.org/solr/guide/6_6/updating-parts-of-documents.html|title=Updating Parts of Documents|access-date=2018-06-28}}</ref>

* The [[Elasticsearch]] search engine supportsupdates OCCits documents via OCC. Each version of a document is assigned a sequence number, and newer versions receive higher sequence numbers. As changes to a document arrive asynchronously, the software can use the sequence number to avoid overriding a newer version attributewith an old one.<ref>{{cite web | urltitle=Optimistic concurrency control | website=Elastic http| url=https://www.elastic.co/guide/en/elasticsearch/reference/current/docsoptimistic-index_concurrency-control.html#index-versioning | title = Elasticsearch access- Guide - Index API | work = Elasticsearch Guide | date = 22 March 20122024-02-05}}</ref>

* [[CouchDB]] implements OCC through [document revisions.<ref>{{cite web | title=Technical Overview | website=Apache CouchDB Documentation | url=https://webdocs.archivecouchdb.org/weben/20170204203059stable/https:intro//wikioverview.apache.org/couchdb/Document_revisionshtml document| revisions].access-date=2024-02-06}}</ref>

* The [[MonetDB]] [[Column-oriented DBMS|column-oriented]] [[database management system]]'s transaction management scheme is based on OCC.<ref>{{cite web | url = http://www.monetdb.org/Documentation/Manuals/SQLreference/Transactions | title = Transactions - MonetDB | date = 16 January 2013}}</ref>

* Most implementations of [[software transactional memory]] use OCC.{{citation needed|reason=Claim initially said optimistic locking, now says OCC, both claims unsourced|date=March 2019}}

* [[Redis]] provides OCC through WATCH command.<ref>{{cite web | url = http://redis.io/topics/transactions | title = Transactions in Redis }}</ref>

* [[Firebird (database server)|Firebird]] uses [[Multiversion concurrency control|Multi-generational architecture]] as an implementation of OCC for data management.{{citation needed|date = November 2020}}

* [[MySQL]] implements OCC in Group Replication configuration

* [[Amazon DynamoDB|DynamoDB]] uses [conditional update as an implementation of OCC.<ref>{{cite web | url = https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html#WorkingWithItems.ConditionalUpdate| title = Working with Items and Attributes - Conditional Update]Writes| asaccess-date implementation= of2 OCC.November 2020}}</ref>

* [[Firebird (database server)|Firebird]] uses [[Multiversion concurrency control|Multi-generational architecture]] as implementation of OCC for data management.

* [[Kubernetes]] uses OCC when [updating resources.<ref>{{cite web | url = https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#resource-operations-update updating| resource].title = API Overview - Resource Operations| access-date = 3 November 2020}}</ref>

*[[Amazon DynamoDB|DynamoDB]] uses [https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html#WorkingWithItems.ConditionalUpdate Conditional Update] as implementation of OCC.

* [[YugabyteDB]] is a cloud-native database that primarily uses OCC.<ref>{{Cite web|last=Yugabyte|first=Team|title=Explicit locking {{!}} YugabyteDB Docs|url=https://docs.yugabyte.com/latest/architecture/transactions/explicit-locking/|access-date=2022-01-04|website=docs.yugabyte.com|language=en-us}}</ref>

* [[Kubernetes]] uses OCC when [https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#resource-operations-update updating resource].

* [[Firestore]] is a NoSQL database by [[Firebase]] that uses OCC in its transactions.

* [[Apache Iceberg]] uses OCC to update tables and run maintenance operations on them.

==See also==

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==External links==

*{{cite journal|title=On optimistic methods for concurrency control|journal=ACM Transactions on Database Systems|date=June 1981|first=H. T.|last=Kung|author2=John T. Robinson|volume=6|issue=2|pages=213–226|doi=10.1145/319566.319567|citeseerx=10.1.1.101.8988|s2cid=61600099 }}

* Enterprise JavaBeans, 3.0, By Bill Burke, Richard Monson-Haefel, Chapter 16. Transactions, Section 16.3.5. Optimistic Locking, Publisher: O'Reilly, Pub Date: May 16, 2006, Print {{ISBN|0-596-00978-X}},

* {{cite conference | first = Andreas | last = Hollmann | title = Multi-Isolation: Virtues and Limitations | booktitlebook-title = Multi-Isolation (what is between pessimistic and optimistic locking) | pages = 8 | publisher = Happy-Guys Software GbR | date = May 2009 | ___location = 01069 Gutzkovstr. 30/F301.2, Dresden | url = http://www.andrej-hollmann.de/images/stories/informatik/multi-isolation-part-1.pdf | format = [[PDF]] | accessdateaccess-date = 2013-05-16 }}{{dead link|date=March 2018 |bot=InternetArchiveBot |fix-attempted=yes }}

{{DEFAULTSORT:Optimistic Concurrency Control}}

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