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Apache Mahout Essentials

You're reading from Apache Mahout Essentials

Product type Book

Published in Jun 2015

Publisher

ISBN-13 9781783554997

Pages 164 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Jayani Withanawasam

Table of Contents (13) Chapters

Apache Mahout Essentials

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

1. Introducing Apache Mahout

2. Clustering

3. Regression and Classification

4. Recommendations

5. Apache Mahout in Production

6. Visualization

Index

Monitoring Hadoop

Apache Hadoop daemons can be monitored using different mechanisms.

Commands/scripts

The running JVMs related to Hadoop can be displayed using the following command (use the correct Java installation location):

/usr/lib/jvm/java-7-oracle/bin/jps

The outcome of the preceding command is given in the following figure:

Data nodes

Active data nodes in the cluster can be displayed using the following command:

[Hadoop installation directory]/bin/hdfs dfsadmin –report

The outcome of the preceding command for a cluster with two data nodes is shown in the following figure:

Node managers

Active node managers can be monitored using the following command:

 [Hadoop installation directory]/bin /yarn node –list

The outcome of the preceding command for a cluster with two node managers is shown in the following figure:

Web UIs

Apache Hadoop has provided Web UIs to monitor MapReduce job processing details.

As shown in the following figure, NameNode operations in HDFS can be monitored at http://localhost...

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Authors (1)

Jayani Withanawasam

Jayani Withanawasam is R&D engineer and a senior software engineer at Zaizi Asia, where she focuses on applying machine learning techniques to provide smart content management solutions. She is currently pursuing an MSc degree in artificial intelligence at the University of Moratuwa, Sri Lanka, and has completed her BE in software engineering (with first class honors) from the University of Westminster, UK. She has more than 6 years of industry experience, and she has worked in areas such as machine learning, natural language processing, and semantic web technologies during her tenure. She is passionate about working with semantic technologies and big data.

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