Joining Interval Data in Relational Databases

The increasing use of temporal and spatial data in present-day relational systems necessitates an efficient support of joins on interval-valued attributes. Standard join algorithms do not support those data types adequately, whereas special approaches for interval joins usually require an augmentation of the internal access methods which is not supported by existing relational systems. To overcome these problems we introduce new join algorithms for interval data. Based on the Relational Interval Tree, these algorithms can easily be implemented on top of any relational database system while providing excellent performance on joining intervals. As experimental results on an Oracle9i server show, the new techniques outperform existing relational methods for joining intervals significantly.

Authors: Enderle J., Hampel M., Seidl T.
Published in: Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD 2004), Paris, France
Publisher: ACM - New York,NY,USA
Language: EN
Year: 2004
Additional:

(acceptance rate 16%)

Pages: 683-694
ISBN: 1-58113-859-8
Conference: SIGMOD
DOI:10.1145/1007568.1007645
Url:SIGMOD 2004
Files:
Type: Conference papers (peer reviewed)
Research topic: Fast Access to Complex Data