| On the problem of generating common predecessors |
| Full text |
Pdf
(231 KB)
|
| Source
|
Data Warehousing and OLAP
archive
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
table of contents
McLean, Virginia, USA
Pages: 43 - 48
Year of Publication: 2002
ISBN:1-58113-590-4
|
|
Authors
|
|
W. Lehner
|
University of Erlangen-Nuremberg, Erlangen, Germany
|
|
W. Hümmer
|
University of Erlangen-Nuremberg, Erlangen, Germany
|
|
L. Schlesinger
|
University of Erlangen-Nuremberg, Erlangen, Germany
|
|
A. Bauer
|
University of Erlangen-Nuremberg, Erlangen, Germany
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 3, Downloads (12 Months): 25, Citation Count: 0
|
|
|
ABSTRACT
Using common subexpressions to speed up a set of queries is a well known and long studied problem. However, due to the isolation requirement, operating a database in the classic transactional way does not offer many applications to exploit the benefits of simultaneously computing a set of queries. In the opposite, many applications can be identified in the context of data warehousing, e. g. optimizing the incremental maintenance process of multiple dependent materialized views or the generation of application specific data marts. In the paper we discuss the problem whether it is always advisable to generate the most complete common predecessor for a given set of queries or to restrict a predecessor to a subset of all possible base tables. As we will see, this question cannot be answered without having knowledge about the cardinality of queries after aggregation. However, if we can rely on this information, we can come up with an optimal predecessor for a common set of queries.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
Sameet Agarwal , Rakesh Agrawal , Prasad Deshpande , Ashish Gupta , Jeffrey F. Naughton , Raghu Ramakrishnan , Sunita Sarawagi, On the Computation of Multidimensional Aggregates, Proceedings of the 22th International Conference on Very Large Data Bases, p.506-521, September 03-06, 1996
|
| |
2
|
|
| |
3
|
|
 |
4
|
Prasad M. Deshpande , Karthikeyan Ramasamy , Amit Shukla , Jeffrey F. Naughton, Caching multidimensional queries using chunks, Proceedings of the 1998 ACM SIGMOD international conference on Management of data, p.259-270, June 01-04, 1998, Seattle, Washington, United States
|
| |
5
|
Jim Gray , Adam Bosworth , Andrew Layman , Hamid Pirahesh, Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total, Proceedings of the Twelfth International Conference on Data Engineering, p.152-159, February 26-March 01, 1996
|
| |
6
|
|
 |
7
|
Jonathan Goldstein , Per-Åke Larson, Optimizing queries using materialized views: a practical, scalable solution, Proceedings of the 2001 ACM SIGMOD international conference on Management of data, p.331-342, May 21-24, 2001, Santa Barbara, California, United States
|
| |
8
|
|
| |
9
|
|
 |
10
|
Venky Harinarayan , Anand Rajaraman , Jeffrey D. Ullman, Implementing data cubes efficiently, Proceedings of the 1996 ACM SIGMOD international conference on Management of data, p.205-216, June 04-06, 1996, Montreal, Quebec, Canada
|
| |
11
|
|
| |
12
|
|
 |
13
|
|
| |
14
|
|
| |
15
|
|
| |
16
|
|
 |
17
|
Markos Zaharioudakis , Roberta Cochrane , George Lapis , Hamid Pirahesh , Monica Urata, Answering complex SQL queries using automatic summary tables, Proceedings of the 2000 ACM SIGMOD international conference on Management of data, p.105-116, May 15-18, 2000, Dallas, Texas, United States
|
 |
18
|
Yihong Zhao , Prasad M. Deshpande , Jeffrey F. Naughton , Amit Shukla, Simultaneous optimization and evaluation of multiple dimensional queries, Proceedings of the 1998 ACM SIGMOD international conference on Management of data, p.271-282, June 01-04, 1998, Seattle, Washington, United States
|
|