In the second half of the chapter, we discuss query
routing algorithms and freshness-aware scheduling. This protocol enables users to
seamlessly decide how fresh the data analysed should be by allowing for different
degrees of freshness of the online analytical processing (OLAP) nodes. In particular
it becomes then possible to trade freshness of data for query performance.
OLAP with a Database Cluster 2
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of Idea Group Inc. is prohibited.
Introduction
Online analytical processing (OLAP) systems must cope with huge volumes of data
and at the same time must allow for short response times to facilitate interactive
usage. They must also be capable to scale, meaning to be easily extensible with the
increasing data volumes accumulated. Furthermore, the requirement that the data
analysed should be up-to-date is becoming more and more important. However, not
only are these contrary requirements, but they also run counter to the performance
needs of the day-to-day business.
Most OLAP systems nowadays are kept separated from mission critical systems.
This means that they offer a compromise between ???up-to-dateness,??? that is, freshness
(or currency) of data, and query response times. The data needed are propagated
into the OLAP system on a regular basis, preferably when not slowing down
day-to-day business, for example, during nights or weekends.
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