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Flexible and Scalable Storage Management for Data-intensive Stream Processing

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    Publication properties
    Title: Flexible and Scalable Storage Management for Data-intensive Stream Processing
    Rating: (2)
    Discussion: 0 comments
    Date: 2009
    Publication type: Conference paper
    Authors:
    No. First name Last name Show
    1. Irina Botan
    2. Gustavo Alonso
    3. Nesime Tatbul
    4. Donald Kossmann
    5. Peter M. Fischer
    Download (from PubZone): Download
    Download (by DOI): 10.1145/1516360.1516467
    BibTeX: conf/edbt/BotanAFKT09
    DBLP: db/conf/edbt/edbt2009.html#BotanAFKT09
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    Conference Track
    Conference Name: EDBT 2009, 12th International Conference on Extending Database Technology, Saint Petersburg, Russia, March 24-26, 2009 2009
    Track Name: Research
    URL: http://www.edbt.org/Proceedings/2009-StPetersburg/edbt/sessions/research.html

    Abstract
           Data Stream Management Systems (DSMS) operate under strict
           performance requirements. Key to meeting such requirements is to
           efficiently handle time-critical tasks such as managing internal
           states of continuous query operators, traffic on the queues
           between operators, as well as providing storage support for
           shared computation and archived data. In this paper, we
           introduce a general purpose storage management framework for
           DSMSs that performs these tasks based on a clean,
           loosely-coupled, and flexible system design that also
           facilitates performance optimization. An important contribution
           of the framework is that, in analogy to buffer management
           techniques in relational database systems, it uses information
           about the access patterns of streaming applications to tune and
           customize the performance of the storage manager. In the paper,
           we first analyze typical application requirements at different
           granularities in order to identify important tunable parameters
           and their corresponding values. Based on these parameters, we
           define a general-purpose storage management interface. Using the
           interface, a developer can use our SMS (Storage Manager for
           Streams) to generate a customized storage manager for streaming
           applications. We explore the performance and potential of SMS
           through a set of experiments using the Linear Road
           benchmark.