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Mastering Apache Spark 2.x

You're reading from Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781786462749

Length 354 pages

Edition 2nd Edition

Languages

Scala

Tools

Apache Spark

Concepts

Big Data

Author (1):

Romeo Kienzler

View More author details

Table of Contents (15) Chapters

Preface

1. A First Taste and What’s New in Apache Spark V2

2. Apache Spark SQL FREE CHAPTER

3. The Catalyst Optimizer

4. Project Tungsten

5. Apache Spark Streaming

6. Structured Streaming

7. Apache Spark MLlib

8. Apache SparkML

9. Apache SystemML

10. Deep Learning on Apache Spark with DeepLearning4j and H2O

11. Apache Spark GraphX

12. Apache Spark GraphFrames

13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience

14. Apache Spark on Kubernetes

Who this book is for

This book is an extensive guide to Apache Spark from the programmer's and data scientist's perspective. It covers Apache Spark in depth, but also supplies practical working examples for different domains. Operational aspects are explained in sections on performance tuning and cloud deployments. All the chapters have working examples, which can be replicated easily.

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Authors (1)

Romeo Kienzler

Romeo Kienzler

Romeo Kienzler works as the chief data scientist in the IBM Watson IoT worldwide team, helping clients to apply advanced machine learning at scale on their IoT sensor data. He holds a Master's degree in computer science from the Swiss Federal Institute of Technology, Zurich, with a specialization in information systems, bioinformatics, and applied statistics.

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