EXPLOITING PARALLELISM IN EXPONENTIAL SMOOTHING OF LARGE-SCALE DISCRETE DATASETS

摘要

A system, and computer program product for large-scale data transformations. Embodiments include a smoothing engine within an R environment to configure at least one master task and at least two worker tasks. A chunk calculator receives a series of data values and divides the series of data values into portions of data values which are in turn assigned as workloads to at least two worker tasks. The worker tasks serve to calculate a first state value of a first one of the portions of data values, and calculate a second state value of a second one of the portions of data values. The workloads are selected such that calculating a second state value does not depend on the first state value. The results of the workload calculations are used to calculate a smoothing factor used to predict a trend.