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Lessons Learned from the Industry’s First TPC Benchmark DS (TPC-DS)

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Performance Evaluation and Benchmarking for the Era of Artificial Intelligence (TPCTC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11135))

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Abstract

The TPC Benchmark DS (TPC-DS) is a decision support benchmark that models several generally applicable aspects of a decision support system, including queries and data maintenance, which is representative of modern decision support and big data applications. TPC-DS was initially designed for Relational Database Management Systems (RDBMS), later extended support for Apache Hadoop. This paper provides the lessons learned including hardware and software tuning parameters from the first TPC-DS publication which was on Cisco UCS® Integrated Infrastructure with Transwarp Data Hub.

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References

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Author information

Authors and Affiliations

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

    Manan Trivedi

  2. Transwarp Technology (Shanghai) Co., Ltd., 11F&12F, Bld B, No. 88 Hongcao RD, Shanghai, China

    Zhenqiang Chen

Authors
  1. Manan Trivedi
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  2. Zhenqiang Chen
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Corresponding authors

Correspondence to Manan Trivedi or Zhenqiang Chen .

Editor information

Editors and Affiliations

  1. Advanced Micro Systems, Inc., Santa Clara, CA, USA

    Raghunath Nambiar

  2. Oracle Corporation, Redwood Shores, CA, USA

    Meikel Poess

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Trivedi, M., Chen, Z. (2019). Lessons Learned from the Industry’s First TPC Benchmark DS (TPC-DS). In: Nambiar, R., Poess, M. (eds) Performance Evaluation and Benchmarking for the Era of Artificial Intelligence. TPCTC 2018. Lecture Notes in Computer Science(), vol 11135. Springer, Cham. https://doi.org/10.1007/978-3-030-11404-6_11

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  • DOI: https://doi.org/10.1007/978-3-030-11404-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11403-9

  • Online ISBN: 978-3-030-11404-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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