High frequency batch-oriented computations over large sliding time windows (original) (raw)

Future Generation Computer Systems, 2015

Abstract

ABSTRACT Today’s business workflows are very likely to include batch computations that periodically analyze subsets of data within specific time ranges to provide strategic information for stakeholders and other interested parties. The frequency of these batch computations provides an effective measure of data analytics freshness available to decision makers. Nevertheless, the typical amounts of data to elaborate in a batch are so large that a computation can take very long. Considering that usually a new batch starts when the previous one has completed, the frequency of such batches can thus be very low.

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