Paper Info
Title
CRB-Tree: An Efficient Indexing Scheme for Range-Aggregate Queries
Abstract
We propose a newindexing 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 uses O(N/B) disk blocks and answers a query in O(logB N) 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(logB N) 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.
Year
DOI
Venue
2003
10.1007/3-540-36285-1_10
ICDT
Keywords
Field
DocType
range-aggregate queries,range-aggregate query,d-dimensional query rectangle,efficient indexing scheme,query performance,rectangle-intersection aggregate query,kdb-tree query time,crb-tree query time,input point,logb n,query rectangle,indexing scheme,indexation
Block size,Query optimization,Indexation,Database query,Computer science,Rectangle,Sargable,Search engine indexing,Algorithm,Theoretical computer science,Spatial database
Conference
Volume
ISSN
ISBN
2572
0302-9743
3-540-00323-1
Citations 
PageRank 
References 
28
1.35
22
Authors
3
Name
Order
Citations
PageRank
Sathish Govindarajan111012.84
Pankaj K. Agarwal25257593.81
Lars Arge32066255.14