Order Indexes: supporting highly dynamic hierarchical data in relational main-memory database systems

Order Indexes: supporting highly dynamic hierarchical data in relational main-memory database... Maintaining and querying hierarchical data in a relational database system is an important task in many business applications. This task is especially challenging when considering dynamic use cases with a high rate of complex, possibly skewed structural updates. Labeling schemes are widely considered the indexing technique of choice for hierarchical data, and many different schemes have been proposed. However, they cannot handle dynamic use cases well due to various problems, which we investigate in this paper. We therefore propose Order Indexes—a dynamic representation of the nested intervals encoding—which offer competitive query performance, unprecedented update efficiency, and robustness for highly dynamic workloads. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Order Indexes: supporting highly dynamic hierarchical data in relational main-memory database systems

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Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-016-0436-3
Publisher site
See Article on Publisher Site

Abstract

Maintaining and querying hierarchical data in a relational database system is an important task in many business applications. This task is especially challenging when considering dynamic use cases with a high rate of complex, possibly skewed structural updates. Labeling schemes are widely considered the indexing technique of choice for hierarchical data, and many different schemes have been proposed. However, they cannot handle dynamic use cases well due to various problems, which we investigate in this paper. We therefore propose Order Indexes—a dynamic representation of the nested intervals encoding—which offer competitive query performance, unprecedented update efficiency, and robustness for highly dynamic workloads.

Journal

The VLDB JournalSpringer Journals

Published: Aug 8, 2016

References

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