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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


Machine learning is the science of making machines work without programming predefined rules and learn from data. It is used to build regression, classification, clustering, anomaly detection, and recommender-based systems. It involves training or fitting a model on historical data and using the trained model to make predictions for new data.

Spark provides you with the MLlib library which is a RDD based API and ML pipelines which is a DataFrames based API to build machine learning applications. MLlib is in maintenance mode from version 2.0 and it will be deprecated and discontinued in upcoming releases. ML pipelines will be the mainstream API. Apache Mahout was a machine learning library built on top of Hadoop, which is now integrated with Spark to provide in-memory performance and avoid scalability issues. H2O is an open source project that has powerful machine learning and deep learning algorithms that provide integration with Spark as a Sparkling Water product.

Both Hadoop and...

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