A Systematic Study for Big Data Stream Processing Frameworks
The choice of the most effective stream processing framework (SPF) for Big Data has been an important issue among the researchers and practioners. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, these technologies used in each SPF might better them, it is still difficult to conclude which framework berforms better under different scenarios and conditions. In this paper, we aim to show trends and differences about several SPFs for Big Data by using the so called Systematic Mapping (SM) approach using the related research outcomes. To achieve this objective, nine research questions (RQs) were raised, in which 91 studies that were conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can direct researchers in getting an state-of-art overview of the field.
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