Abstract: The MapReduce programming model has introduced simple interfaces to a large class of applications. Its easy-to-use APIs and autonomic parallelization are attracting attentions from ...

Abstract: As a powerful distributed computing model, MapReduce has been widely used in many domains to process massive amounts of data. To ensure its correctness, one of the appropriate ways is formal ...

Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that goodness to go around. This article gets you started with Hadoop, ...

MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

This project is all about making big data processing faster and more efficient. By leveraging the power of multi-threading, our framework breaks down large datasets into manageable chunks, processes ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day on ...

In MapReduce, what does the Record Reader component do? It reads the configuration files for the job It converts the physical representation of the input data into key-value pairs for the mapper It ...

ABSTRACT: This paper introduces MapReduce as a distributed data processing model using open source Hadoop framework for manipulating large volume of data. The huge volume of data in the modern world, ...