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https://doi.org/10.1109/comput...
Article . 2009 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY
Data sources: Datacite
DBLP
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Data sources: DBLP
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SQL Access Patterns for Optimistic Concurrency Control

Authors: Fritz Laux; Martti Laiho;

SQL Access Patterns for Optimistic Concurrency Control

Abstract

Transaction processing is of growing importance for mobile and web applications. Booking tickets, flight reservation, e-Banking, e-Payment, and booking holiday arrangements are just a few examples. Due to temporarily disconnected situations the synchronization and consistent transaction processing are key issues. To avoid difficulties with blocked transactions or communication loss several authors and technology providers have recommended to use Optimistic Concurrency Control (OCC) to solve the problem. However most vendors of Relational Database Management Systems (DBMS) implemented only locking schemes for concurrency control which prohibit the immediate use of OCC. We propose Row Version Verifying (RVV) discipline to avoid lost updates and achieve a kind of OCC for those DBMS not providing an adequate non-blocking concurrency control. Moreover, the different mechanisms are categorized as access pattern in order to provide programmers with a general guideline for SQL databases. The proposed SQL access patterns are relevant for all transactional applications with unreliable communication and low conflicting situations. We demonstrate the proposed solution using mainstream database systems like Oracle, DB2, and SQLServer.

5 pages, 1 figure

Keywords

FOS: Computer and information sciences, Computer Science - Databases, Databases (cs.DB)

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    popularity
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green