Advertisement
Published in:
2011 | OriginalPaper | Chapter
Benchmarking Adaptive Indexing
Authors : Goetz Graefe, Stratos Idreos, Harumi Kuno, Stefan Manegold
Published in: Performance Evaluation, Measurement and Characterization of Complex Systems
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.