MapReduce and Spark are two very popular open source cluster computing frameworks for
large scale data analytics. These frameworks hide the complexity of task parallelism and …

Apache Spark is an open-source cluster computing framework for big data processing. It has
emerged as the next generation big data processing engine, overtaking Hadoop …

Data analysis is an important functionality in cloud computing which allows a huge amount
of data to be processed over very large clusters. MapReduce is recognized as a popular …

The past few years have seen a major change in computing systems, as growing data
volumes and stalling processor speeds require more and more applications to scale out to …

MapReduce is a highly-popular paradigm for high-performance computing over large data
sets in large-scale platforms. However, when the source data is widely distributed and the …

MapReduce is a programming model and an associated implementation for processing and
generating large datasets that is amenable to a broad variety of real-world tasks. Users …

In the last two decades, the continuous increase of computational power has produced an
overwhelming flow of data which has called for a paradigm shift in the computing …

A prominent parallel data processing tool MapReduce is gaining significant momentum from
both industry and academia as the volume of data to analyze grows rapidly. While …

" Big Data" computing increasingly utilizes the MapReduce programming model for scalable
processing of large data collections. Many MapReduce jobs are I/O-bound, and so …

MapReduce and its variants have been highly successful in implementing large-scale data-
intensive applications on commodity clusters. However, most of these systems are built …