Scaling of complex calculations over big data-sets

Abstract

This article introduces a novel approach to scale complex calculations in extensive IT infrastructures and presents significant case studies in SONCA and DISESOR projects. Described system is enabling parallelism of calculations by providing dynamic data sharding without necessity of direct integration with storage repositories. Presented solution doesn't require to complete a single phase of processing before starting the next one, hence it is suitable for supporting many dependent calculations and can be used to provide scalability and robustness of whole data processing pipelines. Introduced mechanism is designed to support case of still emerging data, thereby it is suitable for data streams e.g. transformation and analysis of data collected from multiple sensors. As will be shown in this article, this approach scales well and is very attractive because can be easily applied to data processing between heterogeneous systems. © 2014 Springer International Publishing.