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A predicate-based caching scheme for client-server database architectures

Published: 01 January 1996 Publication History

Abstract

We propose a new client-side data-caching scheme for relational databases with a central server and multiple clients. Data are loaded into each client cache based on queries executed on the central database at the server. These queries are used to form predicates that describe the cache contents. A subsequent query at the client may be satisfied in its local cache if we can determine that the query result is entirely contained in the cache. This issue is called cache completeness . A separate issue, cache currency , deals with the effect on client caches of updates committed at the central database. We examine the various performance tradeoffs and optimization issues involved in addressing the questions of cache currency and completeness using predicate descriptions and suggest solutions that promote good dynamic behavior. Lower query-response times, reduced message traffic, higher server throughput, and better scalability are some of the expected benefits of our approach over commonly used relational server-side and object ID-based or page-based client-side caching.

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  • (2022)Cache management in MASCARA-FPGA: from coalescing heuristic to replacement policyProceedings of the 18th International Workshop on Data Management on New Hardware10.1145/3533737.3535096(1-5)Online publication date: 12-Jun-2022
  • (2021)Caching Support for Range Query Processing on Bitmap IndicesProceedings of the 33rd International Conference on Scientific and Statistical Database Management10.1145/3468791.3468800(49-60)Online publication date: 6-Jul-2021
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Information

Published In

cover image The VLDB Journal — The International Journal on Very Large Data Bases
The VLDB Journal — The International Journal on Very Large Data Bases  Volume 5, Issue 1
January 1996
95 pages

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 January 1996

Author Tags

  1. Cache completeness
  2. Cache currency
  3. Caching
  4. Multiple clients
  5. Relational databases

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  • (2023)Workload-Aware Cache Management of Bitmap IndicesProceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies10.1145/3632366.3632386(1-10)Online publication date: 4-Dec-2023
  • (2022)Cache management in MASCARA-FPGA: from coalescing heuristic to replacement policyProceedings of the 18th International Workshop on Data Management on New Hardware10.1145/3533737.3535096(1-5)Online publication date: 12-Jun-2022
  • (2021)Caching Support for Range Query Processing on Bitmap IndicesProceedings of the 33rd International Conference on Scientific and Statistical Database Management10.1145/3468791.3468800(49-60)Online publication date: 6-Jul-2021
  • (2021)MASCARA-FPGA cooperation model: Query Trimming through acceleratorsProceedings of the 33rd International Conference on Scientific and Statistical Database Management10.1145/3468791.3468795(203-208)Online publication date: 6-Jul-2021
  • (2018)A new filtering-based query processingProceedings of the 12th International Conference on Intelligent Systems: Theories and Applications10.1145/3289402.3289512(1-6)Online publication date: 24-Oct-2018
  • (2017)Data CanopyProceedings of the 2017 ACM International Conference on Management of Data10.1145/3035918.3064051(557-572)Online publication date: 9-May-2017
  • (2014)Exploring optimization and caching for efficient collection operationsAutomated Software Engineering10.1007/s10515-013-0119-x21:1(3-40)Online publication date: 1-Mar-2014
  • (2013)Optimized data management for e-learning in the clouds towards CloodleProceedings of the 4th Symposium on Information and Communication Technology10.1145/2542050.2542089(320-324)Online publication date: 5-Dec-2013
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