A MapReduce Model to Process Massive Switching Center Data Set
Wen Chuan Yang, Rui Li, Zhi Dong Shang · Applied Mechanics and Materials · 2014
Accompany the widely use of smart phone in China, all inputs and routes packets streams to the Telecommunication Content Distribution Service Switching Centers (TSC). There is a tendency to put more capability into the switch, such as retain or query passing by data. Thus we definitely need to think about what can be kept in working storage and how to analysis it. Obviously, the ordinary database cannot handle the massive dataset and complex ad-hoc query. In this paper, we propose MRTSC, a MapReduce deep service analysis system based on Hive/Hadoop frameworks. A distributed file system HDFS is used in MRTSC for fast data sharing and query. MRTSC also optimizes scheduling for switch analysis jobs and supports fault tolerance for the entire workflow. Our results show that the model achieves a higher efficiency.