Understanding and Improving the Cost of Scaling Distributed Event Processing

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Provided by: Association for Computing Machinery
Topic: Big Data
Format: PDF
Building scalable back-end infrastructures for data-centric applications is becoming important. Applications used in data centers have complex, multilayer software stacks and are required to scale to a large number of nodes. Today, there is increased interest in improving the efficiency of such software stacks. In this paper, the authors examine the efficiency of such a stack used for distributed stream processing, an important application domain. They use a specific streaming system, Borealis and extensively hand-tune the end-to-end data path.
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