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Hands-On Deep Learning with Apache Spark

You're reading from   Hands-On Deep Learning with Apache Spark Build and deploy distributed deep learning applications on Apache Spark

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788994613
Length 322 pages
Edition 1st Edition
Languages
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Author (1):
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Guglielmo Iozzia Guglielmo Iozzia
Author Profile Icon Guglielmo Iozzia
Guglielmo Iozzia
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Table of Contents (19) Chapters Close

Preface 1. The Apache Spark Ecosystem FREE CHAPTER 2. Deep Learning Basics 3. Extract, Transform, Load 4. Streaming 5. Convolutional Neural Networks 6. Recurrent Neural Networks 7. Training Neural Networks with Spark 8. Monitoring and Debugging Neural Network Training 9. Interpreting Neural Network Output 10. Deploying on a Distributed System 11. NLP Basics 12. Textual Analysis and Deep Learning 13. Convolution 14. Image Classification 15. What's Next for Deep Learning? 16. Other Books You May Enjoy Appendix A: Functional Programming in Scala 1. Appendix B: Image Data Preparation for Spark

Streaming data with Kafka and Spark

Spark Streaming with Kafka is a common combination of technologies in data pipelines. This section will present some examples of streaming Kafka with Spark.

Apache Kakfa

Apache Kafka (http://kafka.apache.org/) is an open source message broker written in Scala. Originally, it was developed by LinkedIn, but it was then released as open source in 2011 and is currently maintained by the Apache Software Foundation.

Here are some of the reasons why you might prefer Kafka to a traditional JMS message broker:

  • It's fast: A single Kafka broker running on commodity hardware can handle hundreds of megabytes of reads and writes per second from thousands of clients
  • Great scalability: It can be easily...
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