Multi-way Windowed Streams θ-Joins Using Cluster

	Multi-way Windowed Streams θ-Joins Using Cluster
	Xinchun Liu; Jing Li; Xiaopeng Fan; Jun Chen
刊名	International Journal of Grid and Distributed Computing
	2016
英文摘要	Recent years have witnessed an increasing interesting in data stream processing, such as network monitoring, the e-business, advertising system and etc. Join is applied to explore the correlation among the tuples from multiple streams. In this paper, we present a general method named Distributed Streams Join (DSJ) to process multi-way windowed streams θ-joins using a shared-nothing cluster. DSJ contains a distribution method named Time-Slice Distribution Method (TDM) and a join method named Transfer Join Method (TJM). Different from previous work, DSJ can (1) process multi-way θ-joins under arbitrary predicates; (2) preserve the integrity of results and load balance while distributing tuples to different nodes for parallel joining; (3) carry out the join operation in a local optimum order according to the histograms maintained in a real-time way. We have built DSJ on our own stream processing cluster to deal with multi-way streams joins and the experiments demonstrate that our DSJ can not only guarantee the load balance among all the computing nodes but also improve the throughput effectively.
收录类别	其他
原文出处	http://www.earticle.net/Article.aspx?sn=271592
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/10237]
专题	深圳先进技术研究院_数字所
作者单位	International Journal of Grid and Distributed Computing
推荐引用方式 GB/T 7714	Xinchun Liu,Jing Li,Xiaopeng Fan,et al. Multi-way Windowed Streams θ-Joins Using Cluster[J]. International Journal of Grid and Distributed Computing,2016.
APA	Xinchun Liu,Jing Li,Xiaopeng Fan,&Jun Chen.(2016).Multi-way Windowed Streams θ-Joins Using Cluster.International Journal of Grid and Distributed Computing.
MLA	Xinchun Liu,et al."Multi-way Windowed Streams θ-Joins Using Cluster".International Journal of Grid and Distributed Computing (2016).