Publication View

Adaptive segmentation for scientific databases (2009)

Abstract
In this paper we explore database segmentation in the context of a column-store DBMS targeted at a scientific database. We present a novel hardware- and scheme-oblivious segmentation algorithm, which learns and adapts to the workload immediately. The approach taken is to capitalize on (intermediate) query results, such that future queries benefit from a more appropriate data layout. The algorithm is implemented as an extension of a complete DBMS and evaluated against a real-life workload. It demonstrates significant performance gains without DBA assistance.

Publication details
Download http://dare.uva.nl/record/297099
Publisher IEEE
Repository Publications of the Universiteit van Amsterdam (Netherlands)
Type Article in monograph or in proceedings