The hB $^\Pi$ -tree: a multi-attribute index supporting concurrency, recovery and node consolidation

The hB $^\Pi$ -tree: a multi-attribute index supporting concurrency, recovery and node... We propose a new multi-attribute index. Our approach combines the hB-tree, a multi-attribute index, and the $\Pi$ -tree, an abstract index which offers efficient concurrency and recovery methods. We call the resulting method the hB $^\Pi$ -tree. We describe several versions of the hB $^\Pi$ -tree, each using a different node-splitting and index-term-posting algorithm. We also describe a new node deletion algorithm. We have implemented all the versions of the hB $^\Pi$ -tree. Our performance results show that even the version that offers no performance guarantees, actually performs very well in terms of storage utilization, index size (fan-out), exact-match and range searching, under various data types and distributions. We have also shown that our index is fairly insensitive to increases in dimension. Thus, it is suitable for indexing high-dimensional applications. This property and the fact that all our versions of the hB $^\Pi$ -tree can use the $\Pi$ -tree concurrency and recovery algorithms make the hB $^\Pi$ -tree a promising candidate for inclusion in a general-purpose DBMS. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

The hB $^\Pi$ -tree: a multi-attribute index supporting concurrency, recovery and node consolidation

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Publisher
Springer-Verlag
Copyright
Copyright © 1997 by Springer-Verlag Berlin Heidelberg
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s007780050030
Publisher site
See Article on Publisher Site

Abstract

We propose a new multi-attribute index. Our approach combines the hB-tree, a multi-attribute index, and the $\Pi$ -tree, an abstract index which offers efficient concurrency and recovery methods. We call the resulting method the hB $^\Pi$ -tree. We describe several versions of the hB $^\Pi$ -tree, each using a different node-splitting and index-term-posting algorithm. We also describe a new node deletion algorithm. We have implemented all the versions of the hB $^\Pi$ -tree. Our performance results show that even the version that offers no performance guarantees, actually performs very well in terms of storage utilization, index size (fan-out), exact-match and range searching, under various data types and distributions. We have also shown that our index is fairly insensitive to increases in dimension. Thus, it is suitable for indexing high-dimensional applications. This property and the fact that all our versions of the hB $^\Pi$ -tree can use the $\Pi$ -tree concurrency and recovery algorithms make the hB $^\Pi$ -tree a promising candidate for inclusion in a general-purpose DBMS.

Journal

The VLDB JournalSpringer Journals

Published: Feb 1, 1997

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