The Big Data Analysis of Two-degree Contacts on Hadoop
Hao Wu, Xiongfei Li
Available Online August 2016.
- https://doi.org/10.2991/cset-16.2016.41How to use a DOI?
- MapReduce, two-degree contacts, Hadoop
- The social network has undergone a rapid development along of the popularity of the Internet. In face of the huge social data increasingly, the common processing methods or algorithm is difficult to deal with it. With its technology maturing gradually, Hadoop has been popularized and used to the different categories. For its characteristics of the lower cost and the higher efficiency to deal with the huge amounts of data, Hadoop is able to analyze two-degree contacts quickly, so as to obtain the information of contacts faster and to build better contacts. It designs the configuration on Hadoop, one is the master host, and the others are slavers. Through the configuration in the network, these parts are able to communicate with each other and ensure that the master host can control the slaves. This system adopts mainly the core frameworks which are the Hadoop distributed file system (HDFS) and the MapReduce algorithm. According to the statistical support and combining with the theory of two-degree contacts and Hadoop, it shows the degree of recommending contacts and realizes the analysis of two-degree contacts on Hadoop finally. Through the big data analysis technology on Hadoop and the process optimized of two-degree contacts, the efficiency of the system can be improved significantly.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hao Wu AU - Xiongfei Li PY - 2016/08 DA - 2016/08 TI - The Big Data Analysis of Two-degree Contacts on Hadoop BT - 2016 International Conference on Computer Science and Electronic Technology PB - Atlantis Press SP - 167 EP - 171 SN - 2352-538X UR - https://doi.org/10.2991/cset-16.2016.41 DO - https://doi.org/10.2991/cset-16.2016.41 ID - Wu2016/08 ER -