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Characterizing memory requirements for queries over continuous data streams
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Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
Madison, Wisconsin
SESSION: Research session 7: queries and views table of contents
Pages: 221 - 232  
Year of Publication: 2002
ISBN:1-58113-507-6
Authors
Arvind Arasu  Stanford University, Stanford, CA
Brian Babcock  Stanford University, Stanford, CA
Shivnath Babu  Stanford University, Stanford, CA
Jon McAlister  Stanford University, Stanford, CA
Jennifer Widom  Stanford University, Stanford, CA
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 9,   Downloads (12 Months): 46,   Citation Count: 29
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ABSTRACT

We consider conjunctive queries with arithmetic comparisons over multiple continuous data streams. We specify an algorithm for determining whether or not a query can be evaluated using a bounded amount of memory for all possible instances of the data streams. When a query can be evaluated using bounded memory, we produce an execution strategy based on constant-sized synopses of the data streams.


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.

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A. Arasu, B. Babcock, S. Babu, J. McAlister, and J. Widom. Characterizing memory requirements for queries over continuous data streams. Technical report, Stanford University Database Group, Nov. 2001. Available at http://dbpubs.stanford.edu/pub/2001-49.
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A. Gupta and I. S. Mumick. Maintenance of materialized views: Problems, techniques, and applications. IEEE Data Engineering Bulletin, 18(2):3-18, June 1995.
 
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J. M. Hellerstein, M. J. Franklin, et al. Adaptive query processing: Technology in evolution. IEEE Data Engineering Bulletin, 23(2):7-18, June 2000.
 
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M. R. Henzinger, P. Raghavan, and S. Rajagopalan. Computing on data streams. Technical Report TR-1998-011, Compaq Systems Research Center, Palo Alto, California, May 1998.
 
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Stanford Stream Data Management (STREAM) Project. http://www-db.stanford.edu/stream.
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Traderbot home page. http://www.traderbot.com.
 
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CITED BY  29
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Arvind Arasu: colleagues
Brian Babcock: colleagues
Shivnath Babu: colleagues
Jon McAlister: colleagues
Jennifer Widom: colleagues

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