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Overview:

In a NESUG 2007 paper with Shuguang Zhang, The author demonstrated a compressed index (termed "Condensed index" in that paper) which provided significant performance gains (about 33% elapsed time and cpu time) in retrieving subsets from sorted datasets in which each level of the sort variables(s) has many observations, and the sort variable was used as the selection criterion. This paper extends the compressed index in two ways: replication of a SAS composite index, and further performance gains (up to 50%) by selectively replacing direct access (i.e. POINT=) techniques with sequential access (FIRSTOBS and LASTOBS). This paper demonstrates, with sample DATA steps, how to create and use a compressed index, and compares its performance to SAS indices, and to the previous results.

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Format:PDFSize:289 KB
Date:Feb 2009
Pages:9

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