B
Brian Babcock
Researcher at Stanford University
Publications - 21
Citations - 8127
Brian Babcock is an academic researcher from Stanford University. The author has contributed to research in topics: Data stream mining & Data stream. The author has an hindex of 18, co-authored 21 publications receiving 7979 citations.
Papers
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Proceedings ArticleDOI
Models and issues in data stream systems
TL;DR: The need for and research issues arising from a new model of data processing, where data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying data streams are motivated.
Proceedings Article
STREAM: The Stanford Stream Data Manager.
Arvind Arasu,Brian Babcock,Shivnath Babu,Mayur Datar,Keith Ito,Itaru Nishizawa,Justin Rosenstein,Jennifer Widom +7 more
Book ChapterDOI
STREAM: The Stanford Data Stream Management System
Arvind Arasu,Brian Babcock,Shivnath Babu,John Cieslewicz,Mayur Datar,Keith Ito,Rajeev Motwani,Utkarsh Srivastava,Jennifer Widom +8 more
TL;DR: A general-purpose prototype Data Stream Management System (DSMS), also called STREAM, is built that supports a large class of declarative continuous queries over continuous streams and traditional stored data sets.
Proceedings ArticleDOI
Distributed top-k monitoring
Brian Babcock,Christopher Olston +1 more
TL;DR: This work shows that transmitting entire data streams is unnecessary to support top-k monitoring queries and presents an alternative approach that reduces communication significantly, and empirically through extensive simulation on real-world data that this approach reduces overall communication cost by an order of magnitude.
Query Processing, Resource Management, and Approximation ina Data Stream Management System
Rajeev Motwani,Jennifer Widom,Arvind Arasu,Brian Babcock,Shivnath Babu,Mayur Datar,Gurmeet Singh Manku,Christopher Olston,Justin Rosenstein,Rohit Varma +9 more
TL;DR: This paper describes the ongoing work developing the Stanford Stream Data Manager (STREAM), a system for executing continuous queries over multiple continuous data streams that supports a declarative query language.