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Apache Spark for Data Science Cookbook

You're reading from  Apache Spark for Data Science Cookbook

Product type Book
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Pages 392 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Padma Priya Chitturi Padma Priya Chitturi
Profile icon Padma Priya Chitturi
LinkedIn
Padma Priya Chitturi is Analytics Lead at Fractal Analytics Pvt Ltd and has over five years of experience in Big Data processing. Currently, she is part of capability development at Fractal and responsible for solution development for analytical problems across multiple business domains at large scale. Prior to this, she worked for an Airlines product on a real-time processing platform serving one million user requests/sec at Amadeus Software Labs. She has worked on realizing large-scale deep networks (Jeffrey deans work in Google brain) for image classification on the big data platform Spark. She works closely with Big Data technologies such as Spark, Storm, Cassandra and Hadoop. She was an open source contributor to Apache Storm.
See other products by Padma Priya Chitturi

Table of Contents (17) Chapters

Apache Spark for Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Big Data Analytics with Spark Tricky Statistics with Spark Data Analysis with Spark Clustering, Classification, and Regression Working with Spark MLlib NLP with Spark Working with Sparkling Water - H2O Data Visualization with Spark Deep Learning on Spark Working with SparkR

Interactive analysis with the SparkR shell

The entry point into SparkR is the SparkContext which connects the R program to a Spark Cluster. When working with the SparkR shell, SQLContext and SparkContext are already available. SparkR's shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively.

Getting ready

To step through this recipe, you will need a running Spark Cluster either in pseudo distributed mode or in one of the distributed modes, that is, standalone, YARN, or Mesos.

How to do it…

In this recipe, we’ll see how to start SparkR interactive shell using Spark 1.6.0:

  1. Start the SparkR shell by running the following in the SparkR package directory:

          /bigdata/spark-1.6.0-bin-hadoop2.6$ ./bin/sparkR --master
      spark://192.168.0.118:7077
  R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
  Copyright (C) 2015 The R Foundation for Statistical Computing
  Platform: x86_64-pc-linux-gnu (64-bit)
  R is free software and comes with...
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Authors (1)

Profile icon Padma Priya Chitturi
LinkedIn
Padma Priya Chitturi is Analytics Lead at Fractal Analytics Pvt Ltd and has over five years of experience in Big Data processing. Currently, she is part of capability development at Fractal and responsible for solution development for analytical problems across multiple business domains at large scale. Prior to this, she worked for an Airlines product on a real-time processing platform serving one million user requests/sec at Amadeus Software Labs. She has worked on realizing large-scale deep networks (Jeffrey deans work in Google brain) for image classification on the big data platform Spark. She works closely with Big Data technologies such as Spark, Storm, Cassandra and Hadoop. She was an open source contributor to Apache Storm.
Read more
See other products by Padma Priya Chitturi

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