Thursday 19th June, 2014
9:00am to 10:30am
Processing ever-increasing amounts of information and providing a meaningful analysis of large datasets (Big Data) has become a significant computing challenge in the Enterprise environment. New tools, frameworks, and systems have been proposed for Big Data processing. They target a variety of data (everything from business transactions to sensor data to tweets) and aim to offer new useful insights via advanced real-time analytics and/or batch-driven data analysis. The common theme of these underlying systems is that they represent a scale-out approach on commodity machines. Using a MapReduce framework I will present and analyze challenges in performance management of such systems. I will talk about the community and enterprise efforts to design unified and/or integrated data processing frameworks that aim to simplify application development and enhance data analytics. Finally, I will discuss hardware and resource usage patterns imposed by modern and emerging scale-out applications and their possible impact on the future system design.
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