Optimal Indexing Using Near-Minimal Space

C. Heeren, H. V. Jagadish, L. Pitt

Research output: Contribution to conferencePaperpeer-review

Abstract

We consider the index selection problem. Given either a fixed query workload or an unknown probability distribution on possible future queries, and a bound B on how much space is available to build indices, we seek to build a collection of indices for which the average query response time is minimized. We give strong negative and positive peformance bounds. Let m be the number of queries in the workload. We show how to obtain with high probability a collection of indices using space O(B ln m) for which the average query cost is optB the optimal performance possible for indices using at most B total space. Moreover, this space relaxation is necessary: unless N P ⊆ no(log log n), no polynomial time algorithm can guarantee average query cost less than M1-∈ optB using space αB, for any constant α, where M is the size of the dataset. We quantify the error in performance introduced by running the algorithm on a sample drawn from a query distribution.

Original languageEnglish (US)
Pages244-251
Number of pages8
StatePublished - Dec 1 2003
EventTwenty second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2003 - San Diego, CA, United States
Duration: Jun 9 2003Jun 11 2003

Other

OtherTwenty second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2003
CountryUnited States
CitySan Diego, CA
Period6/9/036/11/03

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture

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