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      Query-log aware replicated declustering

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      Author
      Turk, A.
      Oktay, K. Y.
      Aykanat, Cevdet
      Date
      2013
      Source Title
      IEEE Transactions on Parallel and Distributed Systems
      Print ISSN
      1045-9219
      Publisher
      Institute of Electrical and Electronics Engineers
      Volume
      24
      Issue
      5
      Pages
      987 - 995
      Language
      English
      Type
      Article
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      115
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      Abstract
      Data declustering and replication can be used to reduce I/O times related with processing of data intensive queries. Declustering parallelizes the query retrieval process by distributing the data items requested by queries among several disks. Replication enables alternative disk choices for individual disk items and thus provides better query parallelism options. In general, existing replicated declustering schemes do not consider query log information and try to optimize all possible queries for a specific query type, such as range or spatial queries. In such schemes, it is assumed that two or more copies of all data items are to be generated and scheduling of these copies to disks are discussed. However, in some applications, generation of even two copies of all of the data items is not feasible, since data items tend to have very large sizes. In this work, we assume that there is a given limit on disk capacities and thus on replication amounts. We utilize existing query-log information to propose a selective replicated declustering scheme, in which we select the data items to be replicated and decide on their scheduling onto disks while respecting disk capacities. We propose and implement an iterative improvement algorithm to obtain a two-way replicated declustering and use this algorithm in a recursive framework to generate a multiway replicated declustering. Then we improve the obtained multiway replicated declustering by efficient refinement heuristics. Experiments conducted on realistic data sets show that the proposed scheme yields better performance results compared to existing replicated declustering schemes. © 1990-2012 IEEE.
      Keywords
      Declustering
      Iterative improvement heuristics
      Parallel disk architectures
      Replication
      Better performance
      Data declustering
      Declustering
      Declustering scheme
      Iterative improvements
      Parallel disks
      Query parallelism
      Algorithms
      Distributed computer systems
      Iterative methods
      Scheduling
      Information retrieval
      Permalink
      http://hdl.handle.net/11693/21016
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/TPDS.2012.113
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