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Real-Time Big Data Analytics

You're reading from   Real-Time Big Data Analytics Design, process, and analyze large sets of complex data in real time

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781784391409
Length 326 pages
Edition 1st Edition
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Author (1):
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Shilpi Saxena Shilpi Saxena
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Shilpi Saxena
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Table of Contents (17) Chapters Close

Real-Time Big Data Analytics
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
1. Introducing the Big Data Technology Landscape and Analytics Platform FREE CHAPTER 2. Getting Acquainted with Storm 3. Processing Data with Storm 4. Introduction to Trident and Optimizing Storm Performance 5. Getting Acquainted with Kinesis 6. Getting Acquainted with Spark 7. Programming with RDDs 8. SQL Query Engine for Spark – Spark SQL 9. Analysis of Streaming Data Using Spark Streaming 10. Introducing Lambda Architecture Index

Understanding the Storm UI


The Storm UI depicts some very vital and important aspects of the Storm cluster and topology. Some of the aspects that Storm depicts form the cardinal rules for optimizing the performance. But, before we talk about the performance, let's befriend the Storm UI and its parameters through series of captures from the Storm UI and descriptions of the same.

Storm UI landing page

The landing page on Storm UI first talks about Cluster Summary, as shown in the following screenshot:

A brief description of the columns available in Cluster Summary, is as follows:

  • Version: As the name suggests, this captures the version of Storm on the UI node. One of the prerequisites for a cluster is that the version of Storm should be same on all the nodes. Thus, this clearly denotes the version of Storm in the cluster.

  • Nimbus uptime: This denotes the duration (in days, hours, minutes, and seconds) for which the Nimbus instance has been running. Nimbus being the coordinator daemon that essentially...

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