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SIGMOD
2010
ACM

Threshold query optimization for uncertain data

10 years 2 months ago
Threshold query optimization for uncertain data
The probabilistic threshold query (PTQ) is one of the most common queries in uncertain databases, where all results satisfying the query with probabilities that meet the threshold requirement are returned. PTQ is used widely in nearest-neighbor queries, range queries, ranking queries, etc. In this paper, we investigate the general PTQ for arbitrary SQL queries that involve selections, projections and joins. The uncertain database model that we use is one that combines both attribute and tuple uncertainty as well as correlations between arbitrary attribute sets. We address the PTQ optimization problem that aims at improving the efficiency of PTQ query execution by enabling alternative query plan enumeration for optimization. We propose general optimization rules as well as rules specifically for selections, projections and joins. We introduce a threshold operator (τ-operator) to the query plan and show it is generally desirable to push down the τ-operator as much as possible. Our P...
Yinian Qi, Rohit Jain, Sarvjeet Singh, Sunil Prabh
Added 18 Jul 2010
Updated 18 Jul 2010
Type Conference
Year 2010
Where SIGMOD
Authors Yinian Qi, Rohit Jain, Sarvjeet Singh, Sunil Prabhakar
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