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The design of the Borealis stream processing engine

  • Daniel J. Abadi
  • , Yanif Ahmad
  • , Magdalena Balazinska
  • , Uǧur Çetintemel
  • , Mitch Cherniack
  • , Jeong Hyon Hwang
  • , Wolfgang Lindner
  • , Anurag S. Maskey
  • , Alexander Rasin
  • , Esther Ryvkina
  • , Nesime Tatbul
  • , Ying Xing
  • , Stan Zdonik
  • Massachusetts Institute of Technology
  • Brown University
  • Brandeis University

Research output: Contribution to conferencePaperpeer-review

1012 Scopus citations

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.

Original languageEnglish
Pages277-289
Number of pages13
StatePublished - 2005
Event2nd Biennial Conference on Innovative Data Systems Research, CIDR 2005 - Asilomar, CA, United States
Duration: Jan 4 2005Jan 7 2005

Conference

Conference2nd Biennial Conference on Innovative Data Systems Research, CIDR 2005
Country/TerritoryUnited States
CityAsilomar, CA
Period01/4/0501/7/05

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