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Benchmarking Big Data Systems: Introducing TPC Express Benchmark HS

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Big Data Benchmarking (WBDB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8991))

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Abstract

As Big Data becomes an integral part of enterprise IT ecosystem, many organizations are challenged with metrics and methodologies to benchmark various hardware and software technologies in terms of performance, price-performance and energy efficiency. Continuing its commitment to bring relevant benchmarks to industry, the Transaction Processing Performance (TPC) formed the Big Data committee to develop set of industry standards, and announced its first standard, the TPC Express benchmark HS (TPCx-HS) in August 2014. TPCx-HS enables measurement of both hardware and software including Hadoop Runtime, Hadoop file system API compatible systems and MapReduce layers. The TPCx-HS can be used to asses a broad range of system topologies and implementation methodologies, in a technically rigorous and directly comparable, vendor-neutral manner.

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References

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Acknowledgement

Developing an industry standard benchmark for a new environment like Big Data has taken the dedicated efforts of experts across many companies. The author thank the contributions of Andrew Bond (Red Hat), Andrew Masland (NEC), Avik Dey (Intel), Brian Caufield (IBM), Chaitanya Baru (SDSC), Da Qi Ren (Huawei), Dileep Kumar (Cloudera), Jamie Reding (Microsoft), John Poelman (IBM), Karthik Kulkarni (Cisco), Meikel Poess (Oracle), Mike Brey (Oracle), Mike Crocker (SAP), Paul Cao (HP), Reza Taheri (VMware), Simon Harris (IBM), Tariq Magdon-Ismail (VMware), Wayne Smith (Intel), Yanpei Chen (Cloudera), Michael Majdalany (L&M), Forrest Carman (Owen Media) and Andreas Hotea (Hotea Solutions).

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Correspondence to Raghunath Nambiar .

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Nambiar, R. (2015). Benchmarking Big Data Systems: Introducing TPC Express Benchmark HS. In: Rabl, T., Sachs, K., Poess, M., Baru, C., Jacobson, HA. (eds) Big Data Benchmarking. WBDB 2014. Lecture Notes in Computer Science(), vol 8991. Springer, Cham. https://doi.org/10.1007/978-3-319-20233-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-20233-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20232-7

  • Online ISBN: 978-3-319-20233-4

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