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You're reading from Monitoring Hadoop

Product typeBook

Published inApr 2015

Publisher

ISBN-139781783281558

Edition1st Edition

Tools

Hadoop

Concepts

Data Processing

Author (1)

Aman Singh

Metrics contexts

Metrics are more relevant to the maintainers of the Hadoop clusters than its users. There might be many users who run MapReduce jobs on a cluster; they are concerned about MapReduce Counters and not the metrics, which are daemon specific. MapReduce counters talk about the number of mappers or reducers, number of bytes read or written to the HDFS and non-HDFS File System, how many spills happened, information about the shuffle phase, etc. However, for Hadoop administrators, metrics about the daemons are of more concern, in order to better understand the cluster.

Named contexts

Each of the daemons has a group of contexts for it. Some of the contexts, which are supported or rather available, are listed in the following table:

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Monitoring Hadoop

Published in: Apr 2015Publisher: ISBN-13: 9781783281558

Author (1)

Aman Singh

Gurmukh Singh is a seasoned technology professional with 14+ years of industry experience in infrastructure design, distributed systems, performance optimization, and networks. He has worked in big data domain for the last 5 years and provides consultancy and training on various technologies. He has worked with companies such as HP, JP Morgan, and Yahoo. He has authored Monitoring Hadoop by Packt Publishing
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Hadoop 1.x	Hadoop 2.x
jvm: for Java Virtual Machine	yarn: for the YARN components
dfs: for Distributed File System	jvm: for Java Virtual Machine
mapred: for JobTracker and TaskTracker	dfs: for Distributed File System
rpc: for Remote Procedure...

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Metrics contexts

Named contexts

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