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
NSUWorks Citation
Raigoza, Jaime and Sun, Junping, "Temporal join processing with hilbert curve space mapping" (2014). CCE Faculty Proceedings, Presentations, Speeches and Lectures. 66.
https://nsuworks.nova.edu/gscis_facpres/66
Comments
Conference Website: http://www.acm.org/conferences/sac/sac2014/