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Materializing views with minimal size to answer queries
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Source Symposium on Principles of Database Systems archive
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
San Diego, California
Pages: 38 - 48  
Year of Publication: 2003
ISBN:1-58113-670-6
Authors
Rada Chirkova  North Carolina State University, Raleigh, NC
Chen Li  University of California, Irvine, Irvine, CA
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGMOD: ACM Special Interest Group on Management of Data
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 1,   Downloads (12 Months): 27,   Citation Count: 1
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ABSTRACT

In this paper we study the following problem. Given a database and a set of queries, we want to find, in advance, a set of views that can compute the answers to the queries, such that the size of the viewset (i.e., the amount of space, in bytes, required to store the viewset) is minimal on the given database. This problem is important for many applications such as distributed databases, data warehousing, and data integration. We explore the decidability and complexity of the problem for workloads of conjunctive queries. We show that results differ significantly depending on whether the workload queries have self-joins. If queries can have self-joins, then a disjunctive viewset can be a better solution than any set of conjunctive views. We show that the problem of finding a minimal-size disjunctive viewset is decidable, and give an upper bound on its complexity. If workload queries cannot have self-joins, there is no need to consider disjunctive viewsets, and we show that the problem is in NP. We describe a very compact search space of conjunctive views, which contains all views in at least one optimal disjunctive viewset. We give a dynamic-programming algorithm for finding minimal-size disjunctive viewsets for queries without self-joins, and discuss heuristics to make the algorithm efficient.


REFERENCES

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