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Applying Stratosphere for Big Data Analytics (2013)
| Venue: | In BTW |
| Citations: | 3 - 3 self |
BibTeX
@INPROCEEDINGS{Leich13applyingstratosphere,
author = {Marcus Leich and Jochen Adamek and Moritz Schubotz and Arvid Heise and Astrid Rheinländer and Volker Markl},
title = {Applying Stratosphere for Big Data Analytics},
booktitle = {In BTW},
year = {2013}
}
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Abstract
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 showhow to formulate analytical tasks as Meteor queries and execute them with Stratosphere. These examples include data cleansing and information extraction tasks, and acorrelation analysis of microblogging and stock trade volume data that we describe in detail in this paper. 1
Keyphrases
big data analytics meteor query big data analytics task query language acorrelation analysis information extraction task declarative query specification stock trade volume data different kind parallel data processing platform complex data processing task different application domain analytical task
