Processing high data rate streams in System S

被引：22

作者：

Andrade, H. ^{[1
]}

Gedik, B. ^{[1
]}

Wu, K-L. ^{[1
]}

Yu, P. S. ^{[2
]}

机构：

[1] IBM Corp, Thomas J Watson Res Ctr, Hawthorne, NY 10532 USA

[2] Univ Illinois, Dept Comp Sci, Chicago, IL 60607 USA

来源：

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING | 2011年 / 71卷 / 02期

关键词：

Data stream processing; Scale-up strategies; Workload balancing; Split/aggregate/join architectural pattern;

D O I：

10.1016/j.jpdc.2010.08.007

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

High-performance stream processing is critical in many sense-and-respond application domains from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high-rate live streams. The central tenets of this work are the programming model, the workload splitting mechanisms, the code generation framework, and the underlying System S middleware and SPADE programming model. We demonstrate considerable scalability behavior coupled with low processing latency in a real-world financial trading application. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：145 / 156

页数：12

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