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International Conference on Management of Data archive
Proceedings of the 2007 ACM SIGMOD international conference on Management of data table of contents
Beijing, China
SESSION: Approximate and probabilistic processing table of contents
Pages: 713 - 724  
Year of Publication: 2007
ISBN:978-1-59593-686-8
Authors
Lyublena Antova  Saarland University, Saarbrücken, Germany
Christoph Koch  Saarland University, Saarbrücken, Germany
Dan Olteanu  Saarland University, Saarbrücken, Germany
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Incomplete information arises naturally in numerous data management applications. Recently, several researchers have studied query processing in the context of incomplete information. Most work has combined the syntax of a traditional query language like relational algebra with a nonstandard semantics such as certain or ranked possible answers. There are now also languages with special features to deal with uncertainty. However, to the standards of the data management community, to date no language proposal has been made that can be considered a natural analog to SQL or relational algebra for the case of incomplete information.

In this paper we propose such a language, World-set Algebra, which satisfies the robustness criteria and analogies to relational algebra that we expect. The language supports the contemplation on alternatives and can thus map from a complete database to an incomplete one comprising several possible worlds. We show that World-set Algebra is conservative over relational algebra in the sense that any query that maps from a complete database to a complete database (a complete-to-complete query) is equivalent to a relational algebra query. Moreover, we give an efficient algorithm for effecting this translation.

We then study algebraic query optimization of such queries. We argue that query languages with explicit constructs for handling uncertainty allow for the more natural and simple expression of many real-world decision support queries. The results of this paper not only suggest a language for specifying queries in this way, but also allow for their efficient evaluation in any relational database management system.


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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S. Abiteboul, R. Hull, and V. Vianu. Foundations of Databases. Addison-Wesley, 1995.
 
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P. Andritsos, A. Fuxman, and R. J. Miller. Clean answers over dirty databases: A probabilistic approach. In Proc. ICDE, 2006.
 
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L. Antova, C. Koch, and D. Olteanu. 10<sup>10</sup><sup>6</sup> worlds and beyond: Efficient representation and processing of incomplete information. In Proc. ICDE, 2007.
 
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L. Antova, C. Koch, and D. Olteanu. World-set decompositions: Expressiveness and efficient algorithms. In Proc. ICDT, 2007.
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O. Benjelloun, A. D. Sarma, C. Hayworth, and J. Widom. An Introduction to ULDBs and the Trio System. IEEE Data Engineering Bulletin, 29(1):5--16, Mar. 2006.
 
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T. J. Green and V. Tannen. "Models for Incomplete and Probabilistic Information". In International Workshop on Incompleteness and Inconsistency in Databases (IIDB), 2006.
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R. Rantzau and C. Mangold. Laws for rewriting queries containing division operators. In Proc. ICDE, 2006.
 
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Stanford Trio Project. TriQL-The Trio Query Language, Oct. 2006. http://infolab.stanford.edu/~widom/triql.html.
 
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Transaction Processing Performance Council. TPC Benchmark H (Decision Support), revision 2.6.0 edition, 2006. http://www.tpc.org/tpch/spec/tpch2.6.0.pdf.


Collaborative Colleagues:
Lyublena Antova: colleagues
Christoph Koch: colleagues
Dan Olteanu: colleagues