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VLDB
1999
ACM

Evaluating Top-k Selection Queries

11 years 9 months ago
Evaluating Top-k Selection Queries
In many applications, users specify target values for certain attributes, without requiring exact matches to these values in return. Instead, the result to such queries is typically a rank of the “top k” tuples that best match the given attribute values. In this paper, we study the advantages and limitations of processing a top-k query by translating it into a single range query that traditional relational DBMSs can process efficiently. In particular, we study how to determine a range query to evaluate a top-k query by exploiting the statistics available to a relational DBMS, and the impact of the quality of these statistics on the retrieval efficiency of the resulting scheme.
Surajit Chaudhuri, Luis Gravano
Added 05 Aug 2010
Updated 05 Aug 2010
Type Conference
Year 1999
Where VLDB
Authors Surajit Chaudhuri, Luis Gravano
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