Load shedding for window joins over streams

被引:0
|
作者
Han, Donghong [1 ]
Xiao, Chuan [1 ]
Zhou, Rui [1 ]
Wang, Guoren [1 ]
Huo, Huan [1 ]
Hui, Xiaoyun [1 ]
机构
[1] Northeastern Univ, Shenyang 110004, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a novel load shedding technique over sliding window joins. We first construct a dual window architectural model including join-windows and aux-windows. With the statistics built on aux-windows, an effective load shedding strategy is developed to produce maximum subset join outputs. For the streams with high arrival rates, we propose an approach incorporating front-shedding and rear-shedding, and then address the problem of how to cooperate these two shedding processes through a series of calculations. Based on extensive experimentation with synthetic data and real life data, we show that our load shedding strategy delivers superb join output performance, and dominates the existing strategies.
引用
收藏
页码:472 / 483
页数:12
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