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Published Articles >> Table of Contents >> Abstract
21st International Conference on Data Engineering (ICDE'05)
pp. 552-563
GPIVOT: Efficient Incremental Maintenance of Complex ROLAP Views
Songting Chen, Worcester Polytechnic Institute
Elke A. Rundensteiner, Worcester Polytechnic Institute
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.71
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| Abstract |
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Data warehousing and on-line analytical processing
(OLAP) are essential for decision support applications.
Common OLAP operations include for example
drill down, roll up, pivot and unpivot. Typically,
such queries are fairly complex and are often executed
over huge volumes of data. The solution in practice
is to use materialized views to reduce the query cost. Utilizing
materialized views that incorporate not just traditional
simple SELECT-PROJECT-JOIN operators but also complex
OLAP operators such as pivot and unpivot is crucial to
improve the OLAP query performance but as of now unexplored
topic. In this work, we demonstrate that the efficient
maintenance of views with pivot and unpivot operators requires
the definition of more generalized operators, which
we call GPIVOT and GUNPIVOT. We propose rewriting
rules, combination rules and propagation rules for such
operators. We also design a novel view maintenance framework
for applying these rules to obtain an efficient maintenance
plan. Our query transformation rules are thus dual
purpose serving both view maintenance and query optimization.
This paves the way for the inclusion of the
GPIVOT and GUNPIVOT into any DBMS engine.
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 Additional Information
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Citation:
Songting Chen, Elke A. Rundensteiner,
"GPIVOT: Efficient Incremental Maintenance of Complex ROLAP Views,"
icde,
pp. 552-563,
21st International Conference on Data Engineering (ICDE'05),
2005
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