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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

Training data ingestion from a database with Spark

Sometimes data has been previously ingested and stored into a database by some other application, so you would need to connect to a database in order to use it for training or testing purposes. This section describes how to get data from a relational database and a NoSQL database. In both cases, Spark would be used.

Data ingestion from a relational database

Suppose the data is stored in a table called sparkexample in a MySQL (https://dev.mysql.com/) schema with the name sparkdb. This is the structure of that table:

mysql> DESCRIBE sparkexample;
+-----------------------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default...
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