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Query Caching and Answering Using an Atom Based Neuro-Architecture

  • Yehia Kotb
  • Moutaz HaddaraEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 16)

Abstract

The use of materialized views derived from the intermediate results of frequently executed queries is a popular strategy for improving performance in environments with high query workloads, like archival databases and data warehouses. Query reuse depends mainly on caching queries results. Thus, the ability to retrieve these cached results in a short response time and a high throughput are primary objectives in archival databases. In this paper, a query optimization technique based on decomposition is proposed. The decomposition of any complex query yields a set of atoms. An atom is a simple query that accesses a single table. The decomposition set is then cached. When a query is submitted, the query is first assessed to decide whether the query can be fully, partially, or cannot be answered by the cache. To avoid cache growth, a hit ratio is adopted to decide which cached data need to be flushed and which should remain. We then propose a neuro-architecture that answers the queries using VLSI technology.

Keywords

Query optimization Caching 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Faculty of EngineeringAmerican University of the Middle EastEqailaKuwait
  2. 2.Department of TechnologyWesterdals-Oslo School of Arts, Communication and TechnologyOsloNorway

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