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Improving Data Locality of MapReduce by Scheduling in Homogeneous Computing Environments

https://doi.org/10.1109/ispa.2011.14

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Dynamic Proportional Share Scheduling in Hadoop

inferredcites →https://doi.org/10.1109/cit.2010.458openalex-snapshot

SAMR: A Self-adaptive MapReduce Scheduling Algorithm in Heterogeneous Environment

inferredcites →https://doi.org/10.1109/clustr.2009.5289171openalex-snapshot

HPMR: Prefetching and pre-shuffling in shared MapReduce computation environment

inferredcites →https://doi.org/10.1109/gcc.2009.16openalex-snapshot

Spatial Queries Evaluation with MapReduce

inferredcites →https://doi.org/10.1109/i-span.2008.24openalex-snapshot

A Taxonomy of Data Prefetching Mechanisms

inferredcites →https://doi.org/10.1109/icdmw.2009.34openalex-snapshot

Toolkit-Based High-Performance Data Mining of Large Data on MapReduce Clusters

inferredcites →https://doi.org/10.1109/icppw.2009.37openalex-snapshot

Biodoop: Bioinformatics on Hadoop

inferredcites →https://doi.org/10.21276/ijre.2018.5.5.4openalex-snapshot

MapReduce: Simplified Data Processing on Large Cluster

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Matchmaking: A New MapReduce Scheduling Technique

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A Fine-Grained and Dynamic MapReduce Task Scheduling Scheme for the Heterogeneous Cloud Environment

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Enhance Performance of Mapreduce Job on Hadoop Framework using Setup and Cleanup

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