CCE Faculty Proceedings, Presentations, Speeches and Lectures

Temporal join processing with hilbert curve space mapping

Event Name/Location

Gyeongju, Korea / March 24-28, 2014

Presentation Date

3-24-2014

Document Type

Conference Proceeding

Proceedings Title

Proceedings of the 29th ACM Symposium on Applied Computing

ISBN

978-1-4503-2469-4

Description

Management of data with a time dimension increases the overhead of storage and query processing in large database applications especially with the join operation, which is a commonly used and expensive relational operator. The join evaluation is difficult because temporal data are intrinsically multidimensional. The problem is harder since tuples with longer life spans tend to overlap a greater number of joining tuples thus; they are likely to be accessed more often. The proposed index-based Hilbert-Temporal Join (Hilbert-TJ) join algorithm maps temporal data into Hilbert curve space that is inherently clustered, thus allowing for fast retrieval and storage.

An evaluation and comparison study of the proposed Hilbert-TJ algorithm determined the relative performance with respect to a nested-loop join, a sort-merge, and a partition-based join algorithm that use a multiversion B+ tree (MVBT) index. The metrics include the processing time (disk I/O time plus CPU time) and index storage size. Under the given conditions, the expected outcome was that by reducing index redundancy better performance was achieved. Additionally, the Hilbert-TJ algorithm offers support to both valid-time and transaction-time data.

DOI

10.1145/2554850.2554903

First Page

839

Last Page

844

Comments

Conference Website: http://www.acm.org/conferences/sac/sac2014/

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