ACM Home Page
Please provide us with feedback. Feedback
Efficient computation of multiple group by queries
Full text PdfPdf (372 KB)
Source International Conference on Management of Data archive
Proceedings of the 2005 ACM SIGMOD international conference on Management of data table of contents
Baltimore, Maryland
SESSION: Research papers: OLAP table of contents
Pages: 263 - 274  
Year of Publication: 2005
ISBN:1-59593-060-4
Authors
Zhimin Chen  Microsoft Research
Vivek Narasayya  Microsoft Research
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 70,   Citation Count: 6
Additional Information:

abstract   references   cited by   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1066157.1066188
What is a DOI?

ABSTRACT

Data analysts need to understand the quality of data in the warehouse. This is often done by issuing many Group By queries on the sets of columns of interest. Since the volume of data in these warehouses can be large, and tables in a data warehouse often contain many columns, this analysis typically requires executing a large number of Group By queries, which can be expensive. We show that the performance of today's database systems for such data analysis is inadequate. We also show that the problem is computationally hard, and develop efficient techniques for solving it. We demonstrate significant speedup over existing approaches on today's commercial database systems.


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
 
2
 
3
4
5
6
 
7
8
 
9
 
10
 
11
 
12
Graefe G. The Cascades Framework for Query Optimization. In Data Engineering Bulletin (Sept 1995), 19--29.
 
13
14
 
15
Hinneburg A., Habich D., and Lehner W. COMBI-Operator -- Database Support for Data Mining Applications. In Proc. of VLDBA 2003, 429--439.
 
16
17
 
18
19
 
20
Protein Information Resource (PIR) web site. <u>http://pir.georgetown.edu/</u>
 
21
Sarawagi S., Agrawal R., and Gupta A. On Compressing the Data Cube. IBM Technical Report.
22
23
 
24
TPC Benchmark H. Decision Support. http://www.tpc.org
 
25

Collaborative Colleagues:
Zhimin Chen: colleagues
Vivek Narasayya: colleagues