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Adaptive OLAP Caching - Towards a Better Quality of Service in Analytical Systems

Authors:
Pedro Marques
Orlando Belo

Keywords: on-line analytical processing; analytical servers; caching; association rules mining; cache content prediction.

Abstract:
Nowadays, the use of Multidimensional Data Systems has become a part of everyday actions in medium and large companies. These systems, which concern mainly in aiding their users in the process of decision-making, have a large flexibility in data exploration and high performance response levels to queries. Despite all the existing techniques, it is sometimes very hard to maintain such levels of performance that the user demands. With the purpose of tackling eventual performance losses, other techniques where developed trying to reduce data servers load. One of such mechanisms is the creation of OLAP caches maintaining previous queries and serving them upon subsequent requests without having to ask to the server. Due to OLAP systems organization, it is possible to identify the characteristics of its users and its exploration patterns – what queries will a user submit during a session, their frequency and resources involved. However, it is possible to go one step further, and to predict exactly what data will be requested by a specific user and, especially, the sequence of those requests. This is called the prediction phase and is followed by the pre-materialization of views that correspond to the user’s requests in the future. These views are then stored in the cache and served to the user in the appropriate time. The technique we propose here consists in maintaining a positive ratio between the time spent to predict and materialize the most relevant views to users, and the time that would be spent if no prediction had been done.

Pages: 42 to 47

Copyright: Copyright (c) IARIA, 2012

Publication date: July 22, 2012

Published in: conference

ISSN: 2308-4391

ISBN: 978-1-61208-223-3

Location: Nice, France

Dates: from July 22, 2012 to July 27, 2012