Title :
Stream processing with BigData: SSS-MapReduce
Author :
Nakada, Hidemoto ; Ogawa, Hiroyo ; Kudoh, T.
Author_Institution :
Nat. Inst. of Adv. Ind. Sci. & Technol., Tsukuba, Japan
Abstract :
We propose a Map Reduce based stream processing system, called SSS, which is capable of processing stream along with large scale static data. Unlike the existing stream processing systems that can work only on the relatively small on-memory data-set, SSS can process incoming streamed data consulting the stored data. SSS processes streamed data with continuous Mappers and Reducers, which are periodically invoked by the system. It also supports merge operation on two sets of data, which enables stream data processing with large static data. This poster shows overview of SSS stream processing and preliminary evaluation results.
Keywords :
distributed processing; merging; BigData; Mappers; Reducer; SSS-MapReduce based stream processing system; data merge operation; large scale static data; on-memory data-set; Cloud computing; Conferences; Data processing; Databases; Servers; Throughput; USA Councils;
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4673-4511-8
Electronic_ISBN :
978-1-4673-4509-5
DOI :
10.1109/CloudCom.2012.6427499