TelegraphCQ: Continuous Dataflow Processing for an Uncertan World

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TelegraphCQ: Continuous Dataflow Processing for an Uncertan World (2003)

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by Sirish Chandrasekaran , Owen Cooper , Amol Deshpande , Michael J. Franklin , Joseph M. Hellerstein , Wei Hong , Sailesh Krishnamurthy , Sam Madden , Vijayshankar Raman , Fred Reiss , Mehul Shah

Citations:

490 - 23 self

BibTeX

@MISC{Chandrasekaran03telegraphcq:continuous,
    author = {Sirish Chandrasekaran and Owen Cooper and Amol Deshpande and Michael J. Franklin and Joseph M. Hellerstein and Wei Hong and Sailesh Krishnamurthy and Sam Madden and Vijayshankar Raman and Fred Reiss and Mehul Shah},
    title = {TelegraphCQ: Continuous Dataflow Processing for an Uncertan World},
    year = {2003}
}

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Abstract

Increasingly pervasive networks are leading towards a world where data is constantly in motion. In such a world, conventional techniques for query processing, which were developed under the assumption of a far more static and predictable computational environment, will not be sufficient. Instead, query processors based on adaptive dataflow will be necessary. The Telegraph project has developed a suite of novel technologies for continuously adaptive query processing. The next generation Telegraph system, called TelegraphCQ, is focused on meeting the challenges that arise in handling large streams of continuous queries over high-volume, highly-variable data streams. In this paper, we describe the system architecture and its underlying technology, and report on our ongoing implementation effort, which leverages the PostgreSQL open source code base. We also discuss open issues and our research agenda.

Keyphrases

uncertan world continuous dataflow processing adaptive query processing large stream underlying technology continuous query telegraph project open issue conventional technique system architecture predictable computational environment ongoing implementation effort postgresql open source code base novel technology next generation telegraph system query processor highly-variable data stream pervasive network adaptive dataflow research agenda query processing

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