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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 on Spark and Hadoop


MLlib is a machine learning library on top of Spark that provides major machine learning algorithms and utilities. It is divided into two separate packages:

  • spark.mllib: This is the original machine learning API built on top of Resilient Distributed Datasets (RDD). As of Spark 2.0, this RDD-based API is in maintenance mode and is expected to be deprecated and removed in upcoming releases of Spark.

  • spark.ml: This is the primary machine learning API built on top of DataFrames to construct machine learning pipelines and optimizations.

spark.ml is preferred over spark.mllib because it is based on the DataFrames API that provides higher performance and flexibility.

Apache Mahout was a general machine learning library on top of Hadoop. Mahout started out primarily as a Java MapReduce package to run machine learning algorithms. As machine learning algorithms are iterative in nature, MapReduce had major performance and scalability issues. So, Mahout stopped...

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