Big Graph Processing in MapReduce

大图处理作为大数据处理的一个大分支，由于其强大的表达能力可以描述现实世界中实体之间的复杂关系，因此在工业界和学术界都变得越来越重要。该项目将找到高度可伸缩的解决方案，以处理大型图表使用MapReduce.MapReduce是一个大数据处理框架，它被证明是可伸缩的，可以处理结构化查询语言风格的查询，但当它用于处理大型图表时，它仍然是开放的。本项目中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。该项目将增强大图形处理，这对科学和社会都是有益的。

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.