论文标题
Hadoop MapReduce的替代基于C ++的HPC系统
An Alternative C++ based HPC system for Hadoop MapReduce
论文作者
论文摘要
MapReduce是一种用于大大改善数据分布式处理的技术，并可以大大加快计算加速。 Hadoop及其MapReduce依赖于JVM和Java，这在内存上很昂贵。可以使用基于高性能计算的MAPREDUCE框架，该框架可以比标准MAPREDUCE更快，更快地执行内存。本文探讨了一种完全基于C ++的MAPREDUCE方法及其对开发人员友好，部署界面，效率和可扩展性等多种因素的可行性。本文还引入了延迟的减少和部署技术，这些技术可以加快编译环境中的MapReduce。
MapReduce is a technique used to vastly improve distributed processing of data and can massively speed up computation. Hadoop and its MapReduce relies on JVM and Java which is expensive on memory. High Performance Computing based MapReduce framework could be used that can perform more memory-efficiently and faster than the standard MapReduce. This paper explores an entirely C++ based approach to the MapReduce and its feasibility on multiple factors like developer friendliness, deployment interface, efficiency and scalability. This paper also introduces Delayed Reduction and deployment techniques that can speed up MapReduce in a compiled environment.
