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Big Data Benchmarking : 5th International Workshop, WBDB 2014, Potsdam, Germany, August 5-6- 2014, Revised Selected Papers / edited by Tilmann Rabl, Kai Sachs, Meikel Poess, Chaitanya Baru, Hans-Arno Jacobson.

Contributor(s): Material type: TextTextLanguage: İngilizce Series: Information Systems and Applications, incl. Internet/Web, and HCI ; 8991Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319202334
Subject(s): LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Benchmark Specifications and Proposals -- Hadoop and MapReduce -- In-Memory, Data Generation and Graphs.
Summary: This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Big Data Benchmarking, WBDB 2014, held in Potsdam, Germany, in August 2014. The 13 papers presented in this book were carefully reviewed and selected from numerous submissions and cover topics such as benchmarks specifications and proposals, Hadoop and MapReduce - in the different context such as virtualization and cloud - as well as in-memory, data generation, and graphs.
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Item type Current library Home library Collection Call number Status Notes Date due Barcode
E-Book E-Book Merkez Kütüphane Merkez Kütüphane E-Kitap Koleksiyonu QA76.9.D3EBK (Browse shelf(Opens below)) Geçerli değil-e-Kitap / Not applicable-e-Book EBK00146

Benchmark Specifications and Proposals -- Hadoop and MapReduce -- In-Memory, Data Generation and Graphs.

This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Big Data Benchmarking, WBDB 2014, held in Potsdam, Germany, in August 2014. The 13 papers presented in this book were carefully reviewed and selected from numerous submissions and cover topics such as benchmarks specifications and proposals, Hadoop and MapReduce - in the different context such as virtualization and cloud - as well as in-memory, data generation, and graphs.

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