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CRB-Tree: An Efficient Indexing Scheme for Range-Aggregate Queries

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Database Theory — ICDT 2003 (ICDT 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2572))

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Abstract

We propose a new indexing scheme, called the CRB-tree, for efficiently answering range-aggregate queries. The range-aggregate problem is defined as follows: Given a set of weighted points in Rd, compute the aggregate of weights of points that lie inside a d-dimensional query rectangle. In this paper we focus on range-COUNT, SUM, AVG aggregates. First, we develop an indexing scheme for answering two-dimensional range-COUNT queries that usesO(N/B) disk blocks and answers a query in O(logN B) I/Os, where N is the number of input points and B is the disk block size. This is the first optimal index structure for the 2D range- COUNT problem. The index can be extended to obtain a near-linear-size structure for answering range-SUM queries using O(logN B) I/Os.We also obtain similar bounds for rectangle-intersection aggregate queries, in which the input is a set of weighted rectangles and a query asks to compute the aggregate of the weights of those input rectangles that overlap with the query rectangle. This result immediately improves a recent result on temporal-aggregate queries. Our indexing scheme can be dynamized and extended to higher dimensions. Finally, we demonstrate the practical efficiency of our index by comparing its performance against kdB-tree. For a dataset of around 100 million points, the CRB-tree query time is 8-10 times faster than the kdB-tree query time. Furthermore, unlike other indexing schemes, the query performance of CRB-tree is oblivious to the distribution of the input points and placement, shape and size of the query rectangle.

The first two authors are supported by Army Research Office MURI grant DAAH04-96-1- 0013, by NSF grants ITR-333-1050, EIA-9870724, EIA-997287, and CCR-9732787, and by a grant from the U.S.-Israeli Binational Science Foundation. The third author is supported by the National Science Foundation through ESS grant EIA-9870734, RI grant EIA-9972879, CAREER grant CCR-9984099, and ITR grant EIA-0112849.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Duke University, 27708, Durham, NC

    Sathish Govindarajan, Pankaj K. Agarwal & Lars Arge

Authors
  1. Sathish Govindarajan
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  2. Pankaj K. Agarwal
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  3. Lars Arge
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Editor information

Editors and Affiliations

  1. Dip. di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, 00198, Roma, Italy

    Diego Calvanese  & Maurizio Lenzerini  & 

  2. Department of Computer Science, Stanford University, Room 474 Gates Computer Science Building 4B, 94305-9045, Stanford, CA, USA

    Rajeev Motwani

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Govindarajan, S., Agarwal, P.K., Arge, L. (2003). CRB-Tree: An Efficient Indexing Scheme for Range-Aggregate Queries. In: Calvanese, D., Lenzerini, M., Motwani, R. (eds) Database Theory — ICDT 2003. ICDT 2003. Lecture Notes in Computer Science, vol 2572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36285-1_10

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  • DOI: https://doi.org/10.1007/3-540-36285-1_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00323-6

  • Online ISBN: 978-3-540-36285-2

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