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Big Data Analytics

You're reading from   Big Data Analytics Real time analytics using Apache Spark and Hadoop

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781785884696
Length 326 pages
Edition 1st Edition
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Author (1):
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Venkat Ankam Venkat Ankam
Author Profile Icon Venkat Ankam
Venkat Ankam
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Table of Contents (12) Chapters Close

Preface 1. Big Data Analytics at a 10,000-Foot View 2. Getting Started with Apache Hadoop and Apache Spark FREE CHAPTER 3. Deep Dive into Apache Spark 4. Big Data Analytics with Spark SQL, DataFrames, and Datasets 5. Real-Time Analytics with Spark Streaming and Structured Streaming 6. Notebooks and Dataflows with Spark and Hadoop 7. Machine Learning with Spark and Hadoop 8. Building Recommendation Systems with Spark and Mahout 9. Graph Analytics with GraphX 10. Interactive Analytics with SparkR Index

Starting Spark daemons

If you are planning to use a standalone cluster manager, you need to start the Spark master and worker daemons which are the core components in Spark's architecture. Starting/stopping daemons varies slightly from distribution to distribution. Hadoop distributions such as Cloudera, Hortonworks, and MapR provide Spark as a service with YARN as the default resource manager. This means that all Spark applications will run on the YARN framework by default. But, we need to start spark master and worker roles to use Spark's standalone resource manager. If you are planning to use the YARN resource manager, you don't need to start these daemons. Please follow the following procedure depending on the type of distribution you are using. Downloading and installation instructions can be found in Chapter 2, Getting Started with Apache Hadoop and Apache Spark, for all these distributions.

Working with CDH

Cloudera Distribution for Hadoop (CDH) is an open source distribution...

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