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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

Summary

Big Data analytics with Hadoop and Spark is broadly classified into two major categories: data analytics and data science. While data analytics focuses on past and present statistics, data science focuses on future statistics. While data science projects are iterative in nature, data analytics projects are not iterative.

Apache Hadoop provides you with distributed storage and resource management and Spark provides you with in-memory performance for Big Data analytics. A variety of tools and techniques are used in Big Data analytics depending on the type of use cases and their feasibility.

The next chapter will help you get started with Hadoop and Spark.

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