Big Graph Processing in MapReduce

MapReduce 中的大图处理

• 批准号: DE140100999
• 负责人: Prof Lu Qin
• 金额: $ 26.33万
• 依托单位: University of Technology Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE140100999
• 关键词: Big; Graph; Processing; MapReduce

As a large branch of big data processing, big graph processing is becoming increasingly important in both industry and academia, due to the large expressive power of graphs to model complex relationships among entities in the real world. This project will find highly scalable solutions to process big graphs using MapReduce. MapReduce is a big data processing framework that is shown to be scalable to handle structured query language-styled queries but is still open when it is used to process big graphs. Most of the problems studied in this project are fundamental graph problems that are not well studied in MapReduce. This project will enhance big graph processing which is beneficial for both science and society.

作为大数据处理的一个重要分支，大图处理在工业界和学术界都变得越来越重要，因为图具有强大的表达能力来建模现实世界中实体之间的复杂关系。该项目将找到高度可扩展的解决方案来使用 MapReduce 处理大图。 MapReduce 是一个大数据处理框架，它被证明是可扩展的，可以处理结构化查询语言风格的查询，但在用于处理大图时仍然是开放的。该项目研究的大多数问题都是基本的图问题，在 MapReduce 中没有得到很好的研究。该项目将增强大图处理，这对科学和社会都有好处。