HVPI: Extending Hadoop to Support Video Analytic Applications
Xiaomeng Zhao, Huadóng Ma, Haitao Zhang, Yi Ping Tang, Yue Kou · 2015
Hadoop is widely deployed distributed computing framework and makes creating distributed applications much easier. However, unlike text data, there is no existing video r/w interface for Hadoop, and many existing video analytic applications implemented in C/C++ are not compatible with Hadoop framework. In this paper, we propose an open source Hadoop video processing interface HVPI to extend Hadoop to support video analytic applications. It provides easy-to-use video r/w interface for developers to quickly build large-scale video analytic applications based on Hadoop, and native processing interface to help users easily port existing video analytic applications written in C/C++ into Hadoop platform. We also present two typical use cases of HVPI and do experiments based on them. Experimental results demonstrate that the applications built based on HVPI are both scalable and efficient.