Threshold query optimization for uncertain data

Authors:
Yinian Qi;Rohit Jain;Sarvjeet Singh;Sunil Prabhakar
Affiliations:
Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, and Google Inc., Mountain View, CA, USA;Purdue University, West Lafayette, IN, USA
Venue:
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Year:
2010

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Abstract

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.