In the thesis work was illustrated MapReduce is attractive because it abstracts parallel and distributed concepts in such a way that it allows novice programmers to take advantage of cluster computing without needing to be familiar with associated complexities such as data dependency, mutual exclusion, replication, and reliability. However, the challenge is that problems must be expressed in such a way that they can be solved using MapReduce. This often involves carefully designing inputs and outputs of MapReduce problems as often outputs of one MapReduce are used as inputs to another
MapReduce is a programming model for data-parallel programs originally intended for data centers. Ma...
В статье анализируется и рассматривается модель распределённых вычислений MapReduce, используемая дл...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is a software framework that allows certain kinds of parallelizable or distributable probl...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
MapReduce是由Google提出的并行计算框架,具备高可扩展性、高可用性和良好的容错性,现已广泛应用于处理大规模数据。连接操作是大数据分析中的一个常见运算,随着数据规模的进一步增大,如何有效处理...
Parallel programming languages have sought out many dif-ferent means by which many numbers of cores ...
MapReduce is a programming model from Google for cluster-based computing in domains such as search e...
In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogene...
The load balancing. Algorithms for information distribution in a cluster of servers and their use in...
MapReduce[2] is a two-step approach to distributing large computations over multiple servers, in whi...
This paper considers a way of parallel implementation of an algorithm of formal con-cept analysis fo...
DISTRIBUTED COMPUTING WITH MapReduce MODEL ON MOBILE PLATFORM This article explain the use of the n...
随着现有数据体量的迅速增长,超大规模中高维数据集的聚类问题变得越来越重要;而现有的子空间聚类算法大多是单机串行执行,处理此类问题效率极低.讨论了利用MapReduce对这类数据集进行并行聚类的方法,提...
MapReduce is a programming model for data-parallel programs originally intended for data centers. Ma...
В статье анализируется и рассматривается модель распределённых вычислений MapReduce, используемая дл...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is a software framework that allows certain kinds of parallelizable or distributable probl...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
MapReduce是由Google提出的并行计算框架,具备高可扩展性、高可用性和良好的容错性,现已广泛应用于处理大规模数据。连接操作是大数据分析中的一个常见运算,随着数据规模的进一步增大,如何有效处理...
Parallel programming languages have sought out many dif-ferent means by which many numbers of cores ...
MapReduce is a programming model from Google for cluster-based computing in domains such as search e...
In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogene...
The load balancing. Algorithms for information distribution in a cluster of servers and their use in...
MapReduce[2] is a two-step approach to distributing large computations over multiple servers, in whi...
This paper considers a way of parallel implementation of an algorithm of formal con-cept analysis fo...
DISTRIBUTED COMPUTING WITH MapReduce MODEL ON MOBILE PLATFORM This article explain the use of the n...
随着现有数据体量的迅速增长,超大规模中高维数据集的聚类问题变得越来越重要;而现有的子空间聚类算法大多是单机串行执行,处理此类问题效率极低.讨论了利用MapReduce对这类数据集进行并行聚类的方法,提...
MapReduce is a programming model for data-parallel programs originally intended for data centers. Ma...
В статье анализируется и рассматривается модель распределённых вычислений MapReduce, используемая дл...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...