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Mastering Apache Spark 2.x - Second Edition

You're reading from  Mastering Apache Spark 2.x - Second Edition

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Pages 354 pages
Edition 2nd Edition
Languages
Concepts

Table of Contents (21) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. A First Taste and What’s New in Apache Spark V2 2. Apache Spark SQL 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

Chapter 9. Apache SystemML

So far, we have only covered components that came along with the standard distribution of Apache Spark (except HDFS, Kafka and Flume, of course). However, Apache Spark can also serve as runtime for third-party components, making it as some sort of operating system for big data applications. In this chapter, we want to introduce Apache SystemML, an amazing piece of technology initially developed by the IBM Almaden Research Lab in California. Apache SystemML went through many transformation stages and has now become an Apache top level project.

In this chapter, we will cover the following topics to get a greater insight into the subject:

  • Using SystemML for your own machine learning applications on top of Apache Spark
  • Learning the fundamental differences between SystemML and other machine learning libraries for Apache Spark
  • Discovering the reason why another machine library exists for Apache Spark
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