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Benchmarking Adaptive Indexing

  • Goetz Graefe
  • Stratos Idreos
  • Harumi Kuno
  • Stefan Manegold
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6417)

Abstract

Ideally, realizing the best physical design for the current and all subsequent workloads would impact neither performance nor storage usage. In reality, workloads and datasets can change dramatically over time and index creation impacts the performance of concurrent user and system activity. We propose a framework that evaluates the key premise of adaptive indexing — a new indexing paradigm where index creation and re-organization take place automatically and incrementally, as a side-effect of query execution. We focus on how the incremental costs and benefits of dynamic reorganization are distributed across the workload’s lifetime. We believe measuring the costs and utility of the stages of adaptation are relevant metrics for evaluating new query processing paradigms and comparing them to traditional approaches.

Keywords

Query Processing Physical Design Query Execution Indexing Technique Actual Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Goetz Graefe
    • 2
  • Stratos Idreos
    • 1
  • Harumi Kuno
    • 2
  • Stefan Manegold
    • 1
  1. 1.CWI AmsterdamThe Netherlands
  2. 2.Hewlett-Packard LaboratoriesPalo Alto

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