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In-Memory Based Incremental Processing Method for Stream Query Processing in Big Data Environments
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 Title & Authors
In-Memory Based Incremental Processing Method for Stream Query Processing in Big Data Environments
Bok, Kyoungsoo; Yook, Misun; Noh, Yeonwoo; Han, Jieun; Kim, Yeonwoo; Lim, Jongtae; Yoo, Jaesoo;
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Recently, massive amounts of stream data have been studied for distributed processing. In this paper, we propose an incremental stream data processing method based on in-memory in big data environments. The proposed method stores input data in a temporary queue and compare them with data in a master node. If the data is in the master node, the proposed method reuses the previous processing results located in the node chosen by the master node. If there are no previous results of data in the node, the proposed method processes the data and stores the result in a separate node. We also propose a job scheduling technique considering the load and performance of a node. In order to show the superiority of the proposed method, we compare it with the existing method in terms of query processing time. Our experimental results show that our method outperforms the existing method in terms of query processing time.
Big Data;In-memory;Distribute Processing;Real-time Processing;Streaming Data;
 Cited by
빅데이터의 효과적인 처리 및 활용을 위한 클라이언트-서버 모델 설계,박대서;김화종;

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