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Models and issues in data stream systems
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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: PODS invited talk table of contents
Pages: 1 - 16  
Year of Publication: 2002
ISBN:1-58113-507-6
Authors
Brian Babcock  Stanford University, Stanford, CA
Shivnath Babu  Stanford University, Stanford, CA
Mayur Datar  Stanford University, Stanford, CA
Rajeev Motwani  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
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ABSTRACT

In this overview paper we motivate the need for and research issues arising from a new model of data processing. In this model, data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying data streams. In addition to reviewing past work relevant to data stream systems and current projects in the area, the paper explores topics in stream query languages, new requirements and challenges in query processing, and algorithmic issues.


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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CITED BY  289

Collaborative Colleagues:
Brian Babcock: colleagues
Shivnath Babu: colleagues
Mayur Datar: colleagues
Rajeev Motwani: colleagues
Jennifer Widom: colleagues