Studies on the Large Scale Data Processing Technologies Used in Servers for Cloud Computing

陈康

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Studies on the Large Scale Data Processing Technologies Used in Servers for Cloud Computing

更新时间：2026-04-20

- Studies on the Large Scale Data Processing Technologies Used in Servers for Cloud Computing
- Vol. 22, Issue 11, Pages: 12-16(2009)
- 作者机构：
  
  清华大学计算机科学与技术系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.05
- Published：2009
- 稿件说明：
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[1]陈康.云计算后台大规模数据处理技术探讨[J].电信工程技术与标准化,2009,22(11):12-16.

陈康. Studies on the Large Scale Data Processing Technologies Used in Servers for Cloud Computing[J]. 2009, 22(11): 12-16.
[1]陈康.云计算后台大规模数据处理技术探讨[J].电信工程技术与标准化,2009,22(11):12-16. DOI：

陈康. Studies on the Large Scale Data Processing Technologies Used in Servers for Cloud Computing[J]. 2009, 22(11): 12-16. DOI：

摘要

云计算的后台处理技术是云计算系统的总体保障。本文主要介绍当前云计算中的后台大规模数据处理技术。大规模数据处理技术对于云计算的后台数据收集与整理起着关键的作用。在云计算中的大规模数据处理技术主要解决三个问题

即可靠性

可扩展性以及易编程性。本文结合Google的MapReduce编程方式

以及微软的Dryad编程方式

着重介绍在实践中

如何达到上述的目标。

Abstract

Data processing technologies used in servers are the critical foundations for the cloud computing systems.This paper introduces the large scale data processing technologies used in the current cloud computing implementations.Such technologies are quite important for the data collections as well as processing.There are three key goals for processing the large scale data i.e.reliability

scalability and easy to program.Based on the Map Reduce programming paradigm from Google and Dryad model from Microsoft

how to achieve the goals in practice are discussed in detail.

关键词

Keywords

references

Interpreting the data: Parallel analysis with Sawzall [J] . Carlos A. Varela,Paolo Ciancarini,Kenjiro Taura,Rob Pike,Sean Dorward,Robert Griesemer,Sean Quinlan. Scientific Programming . 2005 (4)

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