Benchmarking MapReduce Implementations for Application Usage Scenarios

Provided by: Binghamton University
Topic: Big Data
Format: PDF
The MapReduce paradigm provides a scalable model for large scale data-intensive computing and associated fault-tolerance. With data production increasing daily due to ever growing application needs, scientific endeavors, and consumption, the MapReduce model and its implementations need to be further evaluated, improved, and strengthened. Several MapReduce frameworks with various degrees of conformance to the key tenets of the model are available today, each, optimized for specific features. HPC application and middleware developers must thus understand the complex dependencies between MapReduce features and their application.

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