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Towards an Industry Standard for Benchmarking Big Data Systems

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Advancing Big Data Benchmarks (WBDB 2013, WBDB 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8585))

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Abstract

Big Data is one of most talked about topics across major industry verticals, research and, governments. Many enterprises are adapting Big Data analytics for improving operational efficiency, customer experience, and to drive new business opportunities. But they are challenged with tools, techniques and metrics to characterize and compare hardware and software systems that can optimally meet their requirements. In this paper the author looks at the industry treads, the role that well established industry standard consortia like the TPC can play in developing standards, and a status update from the TPC.

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References

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Acknowledgements

The author thanks the past and present members of the TPC.

Author information

Authors and Affiliations

  1. Cisco Systems, Inc., 275 East Tasman Drive, San Jose, CA, 95134, USA

    Nambiar Raghunath

Authors
  1. Nambiar Raghunath
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Corresponding author

Correspondence to Nambiar Raghunath .

Editor information

Editors and Affiliations

  1. University of Toronto, Toronto, Ontario, Canada

    Tilmann Rabl

  2. Cisco Systems, Inc., San José, USA

    Nambiar Raghunath

  3. Oracle Corporation, Redwood Shores, USA

    Meikel Poess

  4. Pivotal Software, Inc., Palo Alto, USA

    Milind Bhandarkar

  5. University of Toronto, Toronto, Canada

    Hans-Arno Jacobsen

  6. University of California at San Diego, La Jolla, USA

    Chaitanya Baru

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Raghunath, N. (2014). Towards an Industry Standard for Benchmarking Big Data Systems. In: Rabl, T., Raghunath, N., Poess, M., Bhandarkar, M., Jacobsen, HA., Baru, C. (eds) Advancing Big Data Benchmarks. WBDB WBDB 2013 2013. Lecture Notes in Computer Science(), vol 8585. Springer, Cham. https://doi.org/10.1007/978-3-319-10596-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-10596-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10595-6

  • Online ISBN: 978-3-319-10596-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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