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Answering Joint Queries from Multiple Aggregate OLAP Databases

  • Elaheh Pourabbas
  • Arie Shoshani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2737)

Abstract

Given an OLAP query expressed over multiple source OLAP databases, we study the problem of evaluating the result OLAP target database. The problem arises when it is not possible to derive the result from a single database. The method we use is the linear indirect estimator, commonly used for statistical estimation. We examine two obvious computational methods for computing such a target database, called the “Full-cross-product” (F) and the “Pre-aggregation” (P) methods. We study the accuracy and computational complexity of these methods. While the method F provides a more accurate estimate, it is more expensive computationally than P. Our contribution is in proposing a third new method, called the “Partial-Pre-aggregation” method (PP), which is significantly less expensive than F, but is just as accurate.

Keywords

Category Attribute Statistical Database Average Relative Error Source Database Target Database 
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 2003

Authors and Affiliations

  • Elaheh Pourabbas
    • 1
  • Arie Shoshani
    • 2
  1. 1.Istituto di Analisi dei Sistemi ed Informatica “Antonio Ruberti”CNRRomeItaly
  2. 2.Lawrence Berkeley National LaboratoryBerkeleyUSA

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