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Miguel Liroz-Gistau 1 Reza Akbarinia 1 Patrick Valduriez 1 
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : FP-Hadoop makes the reduce side of Hadoop MapReduce more parallel and efficiently deals with the problem of data skew in the reduce side. In FP-Hadoop, there is a new phase, called intermediate reduce (IR), in which blocks of intermediate values, constructed dynamically, are processed by intermediate reduce workers in parallel. Our experiments using FP-Hadoop using synthetic and real benchmarks have shown excellent performance gains compared to native Hadoop, e.g. more than 10 times in reduce time and 5 times in total execution time.
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Submitted on : Monday, April 8, 2019 - 3:45:23 PM
Last modification on : Friday, August 5, 2022 - 3:03:28 PM


Miguel Liroz-Gistau, Reza Akbarinia, Patrick Valduriez. FP-Hadoop. 2019. ⟨hal-02093002⟩



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