Over the years, multidimensional access methods have shown high
potential for significant performance improvements in various
application domains. However, only few approaches have made
their way into commercial products.
In commercial database management systems the B-Tree is still the
prevalent indexing technique. Integrating new indexing methods
into existing database kernels is in general a very complex and
costly task. Exceptions exist, as
our experience of integrating the UB-Tree into TransBase, a commercial
database system, shows. The UB-Tree is a very promising multidimensional
index, which has shown its superiority over traditional access methods
in different scenarios, especially in the OLAP field. In this
presentation we discuss the major issues of a UB-Tree integration.
As we will show, the complexity and cost of this task is reduced
significantly due to the fact that the UB-Tree relies on the classical
B-Tree. Even though commercial database systems provide interfaces
for index extensions, we favor the kernel integration because of the
tight coupling with the query optimizer, which allows for optimal usage
of the UB-Tree in execution plans. Measurements on a real-world data
warehouse show that the kernel integration leads to an additional
performance improvement compared to our prototype implementation,
which has been used for performance comparisons with competing index
methods so far.
BIO of Volker Markl:
Dr. Markl is curently working for the Bavarian Research Center for
Knowledge-Based Systems (FORWISS) in Munich, where he is the deputy
research group manager of the Knowledge-Bases Research group, a
team of 10 researchers. His main project is the international
research effort MISTRAL which aims at investigating with industry
partners the application of multi-dimensional access methods to
relational database systems. The participating commercial partners
are SAP AG, NEC, Hitachi, Teijin Systems Technology, TransAction
Software, GfK, the European Union, Microsoft Research.
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PRESENTATION of Robert Fenk
Title: Management and Query Processing of one dimensional
Intervals with the UB-Tree
Abstract:
The management and query processing of one dimensional intervals is
a special case of extended object handling. One dimensional
intervals play an important role in temporal databases and they can
also be used for fuzzy matching, fuzzy logic and measuring
quality classes, etc. Most existing multidimensional access methods
for extended objects do not address this special problem and most of
them are main memory access methods that do not support efficient
access to secondary storage.
The research in the application of the UB-Tree to extended objects is
part of my doctoral work. The combination of UB-Tree and
transformation of extended objects to parameter space is
an effective solution for this specific problem.
BIO of Mr. Robert Fenk:
Dipl.-Inform. Robert Fenk is a graduate of the Munich
University of Technology, where he acquired a Masters degree
in Computer Science in 1998. He worked in the field of range
query processing, where he finished his thesis in the
MISTRAL project at FORWISS under the supervision of
Dipl. Inform. Stefan Sixl, Dr. Volker Markl and Prof. Rudolf
Bayer, PhD. |