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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

Machine learning with H2O and Spark


H2O is an open source system for machine learning. It offers a rich set of machine learning algorithms and a web-based data processing user interface. It offers the ability to develop machine learning applications in Java, Scala, Python, and R. It also has the ability to interface with Spark, HDFS, Amazon S3, SQL, and NoSQL databases. H2O also provides an H2O Flow, which is an IPython-like notebook that allows you to combine code execution, text, mathematics, plots, and rich media into a single document. Sparkling Water is a product of H2O on Spark.

Why Sparkling Water?

Sparkling Water combines the best of both worlds of Spark and H2O:

  • Spark provides the best APIs, RDDs, and multitenant contexts

  • H2O provides speed, columnar-compression, machine learning, and deep learning algorithms

  • Both Spark and H2O Contexts reside in a shared executor JVM and shared Spark RDDs and H2O RDDs

An application flow on YARN

The steps involved in a Sparkling Water application submitted...

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