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Multiversion-based view maintenance over distributed data sources

Published: 12 December 2004 Publication History

Abstract

Materialized views can be maintained by submitting maintenance queries to the data sources. However, the query results may be erroneous due to concurrent source updates. State-of-the-art maintenance strategies typically apply compensations to resolve such conflicts and assume all source schemata remain stable over time. In a loosely coupled dynamic environment, the sources may autonomously change not only their data but also their schema or semantics. Consequently, either the maintenance or the compensation queries may be broken. Unlike compensation-based approaches found in the literature, we instead model the complete materialized view maintenance process as a view maintenance transaction (VM_Transaction). This way, the anomaly problem can be rephrased as the serializability of VM_Transactions. To achieve VM_Transaction serializability, we propose a multiversion concurrency control algorithm, called TxnWrap, which is shown to be the appropriate design for loosely coupled environments with autonomous data sources. TxnWrap is complementary to the maintenance algorithms proposed in the literature, since it removes concurrency issues from consideration allowing the designer to focus on the maintenance logic. We show several optimizations of TxnWrap, in particular, (1) space optimizations on versioned data materialization and (2) parallel maintenance scheduling. With these optimizations, TxnWrap even outperforms state-of-the-art view maintenance solutions in terms of refresh time. Further, several design choices of TxnWrap are studied each having its respective advantages for certain environmental settings. A correctness proof based on transaction theory for TxnWrap is also provided. Last, we have implemented TxnWrap. The experimental results confirm that TxnWrap achieves predictable performance under a varying rate of concurrency.

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Online Appendix to: Multiversion-based view maintenance over distributed data sources

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Cited By

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  • (2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
  • (2022)View Materialization for Query Processing in IoT SystemsInternational Journal of Technology Diffusion10.4018/IJTD.30074613:1(1-19)Online publication date: 20-May-2022
  • (2019)Impact of technology evolution on the materialised viewsInternational Journal of Business Information Systems10.1504/ijbis.2019.09930530:4(427-462)Online publication date: 1-Jan-2019
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Reviews

Elizabeth A. Unger

The integration of information from many distributed databases is a challenge of this decade. Success in this endeavor will determine the ability of many organizations to continue in the future. This paper offers one approach to meeting the various challenges of current distributed data organization architectures, based on a model for the complete materialized view maintenance process, by expressing it as a view maintenance problem, and reducing the transaction serialization space. The paper is well written, provides a solution model for the problem of maintaining distributed views of a conceptual database, accounts for differences in the schemas, and describes a physical implementation in terms of its performance against conventional view maintenance algorithms. The single processor algorithm implementation is supplemented by a parallel processor solution, and formal correctness proofs are provided. The major problems of data update and schema change anomalies are shown to be solvable, by reformulating the maintenance problem of data as a virtual transaction model. Reformulated transactions are mapped from the distributed anomalies to the problem of serializability of transactions. Serializability theory provides the formal system in which view maintenance, view adaptation, and view synchronization can be solved for the materialized view maintenance problem. In essence, the concurrency problems of multiple updates for a record value are no longer a component of the problem. This enables simplification of the problem, and also of the conceptualization of it. A pivotal idea for this is the introduction of a local identifier within each data source's scope for version management, and global identifiers for the materialized view. These two types of identifiers are related, in that the global identifier is composed from a vector of the local identifiers. The authors bring an interesting new perspective to the challenge of providing users with a consistent view of the data of an enterprise, by approaching the complex view maintenance problem through the reconceptualization of the transactions into a serialized order. This may or may not be the ultimate solution for the overall problem, but approaching it with this perspective is very thought provoking. This paper is recommended to those interested in integrating distributed databases by providing a view of them. Online Computing Reviews Service

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Published In

cover image ACM Transactions on Database Systems
ACM Transactions on Database Systems  Volume 29, Issue 4
December 2004
250 pages
ISSN:0362-5915
EISSN:1557-4644
DOI:10.1145/1042046
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 December 2004
Published in TODS Volume 29, Issue 4

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  1. View maintenance
  2. transaction processing

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Cited By

View all
  • (2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
  • (2022)View Materialization for Query Processing in IoT SystemsInternational Journal of Technology Diffusion10.4018/IJTD.30074613:1(1-19)Online publication date: 20-May-2022
  • (2019)Impact of technology evolution on the materialised viewsInternational Journal of Business Information Systems10.1504/ijbis.2019.09930530:4(427-462)Online publication date: 1-Jan-2019
  • (2019)Materialized View Maintenance: Issues, Classification, and Open ChallengesInternational Journal of Cooperative Information Systems10.1142/S0218843019300018Online publication date: 25-Jan-2019
  • (2017)Temporal and Evolving Data Warehouse DesignScientific Programming10.1155/2017/73923492017Online publication date: 1-Jan-2017
  • (2015)Delta extraction in a limited collaborative environmentInternational Journal of Intelligent Information and Database Systems10.1504/IJIIDS.2015.0708289:1(54-78)Online publication date: 1-Jul-2015
  • (2015)Using grouping strategy and pattern discovery for delta extraction in a limited collaborative environmentInternational Journal of Business Intelligence and Data Mining10.1504/IJBIDM.2015.07221310:4(378-405)Online publication date: 1-Oct-2015
  • (2014)MesaProceedings of the VLDB Endowment10.14778/2732977.27329997:12(1259-1270)Online publication date: 1-Aug-2014
  • (2013)Live linked dataInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2013.0566058:2(119-133)Online publication date: 1-Sep-2013
  • (2013)Update Management in Decision Support SystemsTransactions on Large-Scale Data- and Knowledge-Centered Systems XII10.1007/978-3-642-45315-1_2(27-53)Online publication date: 2013
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