Skip to main content
SpringerLink
Log in
Book cover

Workshop on Big Data Benchmarks

Workshop on Big Data Benchmarks

WBDB 2013, WBDB 2013: Advancing Big Data Benchmarks pp 179–192Cite as

MPP SQL Engines: Architectural Choices and Their Implications on Benchmarking

  • Conference paper
  • First Online:

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

Abstract

One approach to big data benchmarking is to study the implications of the underlying computing platform, both hardware and software. The software stack for big data analytics comprises a suite of technology solutions including MPP SQL Engines. This paper provides an overview of the architectural choices in the underlying hardware infrastructure, the architectural choices in the design of parallel SQL Engines, and the implications of both on benchmarking. A benchmark suite developed at XtremeData for internal engineering use is also described.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Double Data Rate.

  2. 2.

    Quad Data Rate.

  3. 3.

    Storage Area Network.

  4. 4.

    Network Attached Storage.

References

  1. Big data: The next frontier for innovation, competition, and productivity, McKinsey&Company. http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation

  2. Cloudera-Hadoop. http://www.cloudera.com/content/cloudera/en/products-and-services/cdh.html

  3. Apache CouchDB. http://couchdb.apache.org

  4. MongoDB: A Document Oriented Database. http://www.mongodb.org/about/

  5. NoSQL Distilled. http://martinfowler.com/books/nosql.html

  6. Amazon Web Services. https://aws.amazon.com/products/

  7. Google Compute Engine:Quickstart: Creating an instance and launching Apache - Google Developers. https://developers.google.com/compute/docs/quickstart

  8. VMware 10GE QoS Design Deep Dive with Cisco UCS, Nexus. http://bradhedlund.com/2010/09/15/vmware-10ge-qos-designs-cisco-ucs-nexus/

  9. OpenStack Open Source Cloud Computing Software. https://www.openstack.org/

  10. PostgreSQL: The world’s most advanced open source database. http://www.postgresql.org/

  11. TPC – Homepage. http://www.tpc.org/default.asp

  12. Seng, J.-L., Yao, S.B., Hevner, A.R.: Requirements-driven database systems benchmark method. Decis. Support Syst. 38(4), 629–648 (2005). doi:10.1016/j.dss.2003.06.002, http://dx.doi.org/10.1016/j.dss.2003.06.002

  13. Darmont, J., Bentayeb, F., Boussaid, O.: Benchmarking data warehouses. Int. J. Bus. Intell. Data Min. 2(1), 79–104 (2007). doi:10.1504/IJBIDM.2007.012947, http://dx.doi.org/10.1504/IJBIDM.2007.012947

Download references

Author information

Authors and Affiliations

  1. XtremeData, Inc., Schaumburg, IL, USA

    Ravi Chandran

  2. XtremeData Technologies Ltd., Bangalore, India

    K. T. Sridhar & M. A. Sakkeer

Authors
  1. Ravi Chandran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. T. Sridhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. A. Sakkeer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ravi Chandran .

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

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Chandran, R., Sridhar, K.T., Sakkeer, M.A. (2014). MPP SQL Engines: Architectural Choices and Their Implications on Benchmarking. 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_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10596-3_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10595-6

  • Online ISBN: 978-3-319-10596-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation