The MapReduce model uses a barrier between the Map and Reduce stages. This provides simplicity in both programming and implementation. However, in many situations, this barrier hurts performance because it is overly restrictive. Thus, we develop a method to break the barrier in MapReduce in a way that improves efficiency. Careful design of our barrier-less MapReduce framework results in equivalent generality and retains ease of programming. We motivate our case with, and experimentally study our barrier-less techniques in, a wide variety of MapReduce applications divided into seven classes. Our experiments show that our approach can achieve better performance times than a traditional MapReduce framework. We achieve a reduction in job comp...
International audienceThe MapReduce programming model is widely acclaimed as a key solution to desig...
This is a post-peer-review, pre-copyedit version of an article published in International Conference...
MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and d...
The MapReduce model uses a barrier between the Map and Re-duce stages. This provides simplicity in b...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
AbstractMapReduce simplifies parallel programming, abstracting the programmer responsibilities as sy...
Over the last ten years MapReduce has emerged as one of the staples of distributed computing both in...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is a programming model for data-parallel programs originally intended for data centers. Ma...
AbstractIn this paper, we propose methods for the improvement of performance of a MapReduce program ...
MapReduce is a programming model from Google forcluster-based computing in domains such as searcheng...
AbstractThe MapReduce framework has been generating a lot of interest in a wide range of areas. It h...
International audienceMapReduce is a programming model which allows the processing of vast amounts o...
This paper describes how Hadoop Frame work was used to process large vast of data., in real time fau...
We investigate the problem of MapReduce and coded MapReduce. MapReduce is a programming model for th...
International audienceThe MapReduce programming model is widely acclaimed as a key solution to desig...
This is a post-peer-review, pre-copyedit version of an article published in International Conference...
MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and d...
The MapReduce model uses a barrier between the Map and Re-duce stages. This provides simplicity in b...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
AbstractMapReduce simplifies parallel programming, abstracting the programmer responsibilities as sy...
Over the last ten years MapReduce has emerged as one of the staples of distributed computing both in...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is a programming model for data-parallel programs originally intended for data centers. Ma...
AbstractIn this paper, we propose methods for the improvement of performance of a MapReduce program ...
MapReduce is a programming model from Google forcluster-based computing in domains such as searcheng...
AbstractThe MapReduce framework has been generating a lot of interest in a wide range of areas. It h...
International audienceMapReduce is a programming model which allows the processing of vast amounts o...
This paper describes how Hadoop Frame work was used to process large vast of data., in real time fau...
We investigate the problem of MapReduce and coded MapReduce. MapReduce is a programming model for th...
International audienceThe MapReduce programming model is widely acclaimed as a key solution to desig...
This is a post-peer-review, pre-copyedit version of an article published in International Conference...
MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and d...