License: Creative Commons Attribution 3.0 Germany license (CC BY 3.0 DE)
When quoting this document, please refer to the following
DOI: 10.4230/DARTS.3.1.1
URN: urn:nbn:de:0030-drops-71392
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Zhang, Bo ; Krikava, Filip ; Rouvoy, Romain ; Seinturier, Lionel

Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)

DARTS-3-1-1.pdf (0.7 MB)


Arising with the popularity of Hadoop, optimizing Hadoop executions has grabbed lots of attention from research community.
Many research contributions are proposed to elevate Hadoop performance, particularly in the domain of self-adaptive software systems.
However, due to the complexity of Hadoop operation and the difficulty to reproduce experiments, the efforts of these Hadoop-related research are hard to be evaluated.

To address this limitation, we propose a research acceleration platform for rapid prototyping and evaluation of self-adaptive behavior in Hadoop clusters.
It provides an automated manner to quickly and easily provision reproducible Hadoop environments and execute acknowledged benchmarks.
This platform is based on the state-of-the-art container technology that supports both distributed configurations as well as standalone single-host setups.
We demonstrate the approach on a complete implementation of a concrete Hadoop self-adaptive case study.

BibTeX - Entry

  author =	{Bo Zhang and Filip Krikava and Romain Rouvoy and Lionel Seinturier},
  title =	{{Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)}},
  pages =	{1:1--1:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-71392},
  doi =		{10.4230/DARTS.3.1.1},
  annote =	{Keywords: Hadoop, Docker, Rapid Prototyping, Benchmark}

Keywords: Hadoop, Docker, Rapid Prototyping, Benchmark
Collection: DARTS, Volume 3, Issue 1
Related Scholarly Article:
Issue Date: 2017
Date of publication: 16.05.2017
Supplementary Material:

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