The design of the borealis stream processing engine

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The design of the borealis stream processing engine (2005)

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by Daniel J. Abadi , Yanif Ahmad , Magdalena Balazinska , Mitch Cherniack , Jeong-hyon Hwang , Wolfgang Lindner , Anurag S. Maskey , Er Rasin , Esther Ryvkina , Nesime Tatbul , Ying Xing , Stan Zdonik

Venue:	In CIDR
Citations:	250 - 10 self

BibTeX

@INPROCEEDINGS{Abadi05thedesign,
    author = {Daniel J. Abadi and Yanif Ahmad and Magdalena Balazinska and Mitch Cherniack and Jeong-hyon Hwang and Wolfgang Lindner and Anurag S. Maskey and Er Rasin and Esther Ryvkina and Nesime Tatbul and Ying Xing and Stan Zdonik},
    title = {The design of the borealis stream processing engine},
    booktitle = {In CIDR},
    year = {2005},
    pages = {277--289}
}

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Abstract

Borealis is a second-generation distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Borealis inherits core stream processing functionality from Aurora [14] and distribution functionality from Medusa [51]. Borealis modifies and extends both systems in non-trivial and critical ways to provide advanced capabilities that are commonly required by newly-emerging stream processing applications. In this paper, we outline the basic design and functionality of Borealis. Through sample real-world applications, we motivate the need for dynamically revising query results and modifying query specifications. We then describe how Borealis addresses these challenges through an innovative set of features, including revision records, time travel, and control lines. Finally, we present a highly flexible and scalable QoS-based optimization model that operates across server and sensor networks and a new fault-tolerance model with flexible consistency-availability trade-offs.

Keyphrases

borealis stream processing engine brown university flexible consistency-availability trade-off basic design core stream sensor network stream processing engine newly-emerging stream processing application revision record new fault-tolerance model brandeis university query result sample real-world application innovative set control line critical way distribution functionality borealis modifies scalable qos-based optimization model advanced capability query specification time travel

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