Implementing Optimistic Concurrency Control for Persistence Middleware Using Row Version Verification

Laiho, Martti; Laux, Fritz

doi:10.1109/dbkda.2010.25

Cited by 3 publications

(7 citation statements)

References 8 publications

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“…HTTP offers ETags [17] in response to allow caching of results, and ETags can be used for validating a step in a transaction. ETags are very similar to the RVV concept [27] or Multi-Version Concurrency Control (MVCC), successfully used in PostgreSQL [28], SQL server [29], Oracle etc. to provide optimistic execution.…”

Section: Related Workmentioning

confidence: 99%

“…The RVV protocol is a type of version control mechanism, which can be used for a form of optimistic concurrency control, alongside or in preference to other versioning measures such as MVCC. The model implementations of RVV in the Laiho/Laux paper [27] envisage a sequence generator to ensure uniqueness of RVV values, so that new values of this sequence are added as a special row-version column in base tables on each INSERT or UPDATE. Some Database Management Systems (DBMSs) include row versioning mechanisms that can be used for this.…”

Section: A Row-version Validationmentioning

confidence: 99%

“…If the RVV model of Laiho/Laux [27] is extended in this way it can be used to validate the results of join queries, or more complex selections where a row in the selection embeds values from rows of other tables.…”

Section: B Rvv and Complex Selectionsmentioning

confidence: 99%

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Data Validation for Big Live Data

Crowe,

Begg,

Laux

et al. 2021

Preprint

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Data Integration of heterogeneous data sources relies either on periodically transferring large amounts of data to a physical Data Warehouse or retrieving data from the sources on request only. The latter results in the creation of what is referred to as a virtual Data Warehouse, which is preferable when the use of the latest data is paramount. However, the downside is that it adds network traffic and suffers from performance degradation when the amount of data is high. In this paper, we propose the use of a readCheck validator to ensure the timeliness of the queried data and reduced data traffic. It is further shown that the readCheck allows transactions to update data in the data sources obeying full Atomicity, Consistency, Isolation, and Durability (ACID) properties.

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Section: Related Workmentioning

confidence: 99%

Section: A Row-version Validationmentioning

confidence: 99%

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Data Validation for Big Live Data

Crowe,

Begg,

Laux

et al. 2021

Preprint

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“…With the dissemination of middleware OCC has been recommended by , [21], [22]) for transactional e-business and m-commerce applications but little concern have been spend on how this can be achieved using commercial SQL databases [7]. Heß [20] simply uses Hibernate's optimistic-lock="version" option but does not mention the risk of legacy applications not under control of Hibernate which could still lead to lost updates.…”

Section: Related Workmentioning

confidence: 99%

“…Heß [20] simply uses Hibernate's optimistic-lock="version" option but does not mention the risk of legacy applications not under control of Hibernate which could still lead to lost updates. Nock [6] uses a timestamp column with Java timestamp resolution ignoring the fact that contemporary database products can produce more than a hundred times the same timestamp [7]. Akbar-Husain [21] believes that demarking the method that checks the version with the required transaction attribute will be sufficient to avoid lost updates.…”

Section: Related Workmentioning

confidence: 99%

SQL Access Patterns for Optimistic Concurrency Control

Laux

Laiho

2009

2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns

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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 synchronisation 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.

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Concurrency control for real‐time and mobile transactions: Historical view, challenges, and evolution of practices

Chaudhry

Yousaf

2021

Concurrency and Computation

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Recently, mobile computing has changed the way that spatial data and GIS are processed. Unlike wired and stand-alone GIS, now the trend has been switched from offline to real-time data processing using location aware services, such as GPS technology. The increased usage of location aware services in multiuser real-time environment has made transaction management incredibly significant. If the simultaneous query operations on the same data item are not handled intelligently then this results in data inconsistency issue. Concurrency control protocol is one of the primary aspects that helps in overcoming this issue a in multiuser environment. To the best of our knowledge, the impact of technological advancements on concurrency control has not been thoroughly studied in the literature. In this article, we explored the literature on concurrency control algorithms in depth with respect to real-time applications and the applications with moving objects. We defined a taxonomy of concurrency control solutions and assessed the maturity of these solutions in the light of characteristics of real-time and mobile environment. We compared the most recent developments made in the literature and presented meaningful insights. Challenges are also identified and discussed, which can assist in doing research in this domain in future. K E Y W O R D S concurrency control, mobile, real time 1 INTRODUCTION IoT (Internet of Things) emerged as a promising technology that has revolutionized the way of living. GPS-based devices and sensors are commonly used in majority of the applications. The convergence of multiple domains such as real-time GIS, mobile computing, and IoT has made it necessary to solve the computing problem considering the requirements of each domain. Mobile GIS domain integrates several technologies: GPS, mobile computing, and GIS. In recent times, the data processing environment deals with varying kinds of sensors. The real-time data collected by sensors need to be processed in timely manner to ensure efficient data management. The sensors can be categorized into two types depending on their mobility: fixed and agile/mobile sensors. Fixed sensors are spatially fixed, whereas mobile sensors change their location with respect to time. Mobile sensors collect data on geographical grounds and this data can be referred to as spatiotemporal data. This has given rise to a new research domain of real-time mobile data processing and management. Thus, real-time processing domain emerged with respect to time depending on the nature of sensor technology and evolution of IoT. The future processing systems are expected to meet the requirements of spatiotemporal and real-time data, leading toward a new domain of real-time GIS. Real-time data can be used for both static and dynamic processing. For example, in the first aspect, mobile sensors can process and analyze the real-time spatiotemporal data for dynamic processing. On the other hand, real-time data can be collected and saved in a log for future offline analysis (static processing).

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Implementing Optimistic Concurrency Control for Persistence Middleware Using Row Version Verification

Cited by 3 publications

References 8 publications

Data Validation for Big Live Data

Data Validation for Big Live Data

SQL Access Patterns for Optimistic Concurrency Control

Concurrency control for real‐time and mobile transactions: Historical view, challenges, and evolution of practices

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