Abstract

This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this information to significantly improve average query performance. Results from simulation experiments demonstrate that the proposed generalized partial indexing strategies perform well compared to the traditional approach to indexing. 1 Introduction In traditional database systems, indexes are used primarily for the efficient associative retrieval of data. The database administrator (DBA) chooses to build indexes on selected columns of tuples in an RDBMS (or members of objects in an OODBMS) to speed up queries that apply predicates to those columns 1 . The choice of indexes is influenced by the number ...

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