Applying stratosphere for big data analytics
Analyzing big data sets as they occur in modern business and science applications requires query languages that allow for the specification of complex data processing tasks. Moreover, these ideally declarative query specifications have to be optimized, parallelized and scheduled for processing on massively parallel data processing platforms. This paper demonstrates the application of Stratosphere to different kinds of Big Data Analytics tasks. Using examples from different application domains, we show how to formulate analytical tasks as Meteor queries and execute them with Stratosphere. These examples include data cleansing and information extraction tasks, and a correlation analysis of microblogging and stock trade volume data that we describe in detail in this paper.
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