Algebraic Query Optimization for Distributed Top-k Queries

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Algebraic Query Optimization for Distributed Top-k Queries
: Distributed top-k query processing is increasingly becoming an essential functionality in a large number of emerging application classes. This paper addresses the efficient algebraic optimization of top-k queries in wide-area distributed data repositories where the index lists for the attribute values (or text terms) of a query are distributed across a number of data peers and the computational costs include network latency, bandwidth consumption, and local peer work. We use a dynamic programming approach to find the optimal execution plan using compact data synopses for selectivity estimation that is the basis for our cost model. The optimized query is executed in a hierarchical way involving a small and fixed number of communication phases. We have performed experiments on real web data that show the benefits of distributed top-k query optimization both in network resource consumption and query response time.
Thomas Neumann, Sebastian Michel
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where BTW
Authors Thomas Neumann, Sebastian Michel
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