Big Data Stream Computing:Features and Challenges

Dawei Sun

doi:10.11959/j.issn.2096-0271.2015032

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Big Data Stream Computing:Features and Challenges

STUDY | 更新时间：2024-06-03

- Big Data Stream Computing:Features and Challenges
- BIG DATA RESEARCH Vol. 1, Issue 3, Pages: 92-98(2015)
- 作者机构：
  
  中国地质大学信息工程学院北京 100083
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2015032
  CLC： TP311.13
- Online First：2015-06，
  
  Published：20 June 2015
- 稿件说明：
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Dawei Sun. Big Data Stream Computing:Features and Challenges[J]. BIG DATA RESEARCH, 2015, 1(3): 92-98.
DOI：

Dawei Sun. Big Data Stream Computing:Features and Challenges[J]. BIG DATA RESEARCH, 2015, 1(3): 92-98. DOI： 10.11959/j.issn.2096-0271.2015032.

摘要

在大数据时代，数据的时效性日益突出，数据的流式特征更加明显，越来越多的应用场景需要部署在流式计算平台中。大数据流式计算作为大数据计算的一种形态，其重要性也不断提升。针对大数据环境中流式计算应用所呈现出的诸多鲜明特征进行了系统化的分析，并从系统架构的角度，给出了大数据流式计算系统构建的原则性策略。结合当前比较典型的流式计算平台，重点研究了当前大数据流式计算在在线环境下的资源调度和节点依赖环境下的容错策略等方面的技术挑战。

Abstract

In big data era

the timeliness of data has become one of the most important factors

and the streaming feature of data has become more obvious.More and more applications need to be deployed in stream computing platforms.Big data stream computing as a major form of big data computing has become more and more important.The features of big data stream computing application were systematically analyzed.The principle strategies to build a big data stream computing system were given from the perspective of system architecture.Combined with some typical big data stream computing systems

some technology challenges in big data stream computing environments were focused

such as resource scheduling in online environments

fault tolerance strategy in node-dependence environments.

关键词

Keywords

references

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