You're reading from Machine Learning with Spark. - Second Edition

Product typeBook

Published inApr 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781785889936

Edition2nd Edition

Languages

Scala

Tools

Apache Spark

Concepts

Machine Learning

Authors (2):

Rajdeep Dua

Manpreet Singh Ghotra

View More author details

Summary

In this chapter, we covered how to set up Spark locally on our own computer as well as in the cloud as a cluster running on Amazon EC2. You learned how to run Spark on top of Amazon's Elastic Map Reduce (EMR). You also learned how to use Google Compute Engine's Spark Service to create a cluster and run a simple job. We discussed the basics of Spark's programming model and API using the interactive Scala console, and we wrote the same basic Spark program in Scala, Java, R, and Python. We also compared the performance metrics of Hadoop versus Spark for different machine learning algorithms as well as SORT benchmark tests.

In the next chapter, we will consider how to go about using Spark to create a machine learning system.

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Machine Learning with Spark. - Second Edition

Published in: Apr 2017Publisher: PacktISBN-13: 9781785889936

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Authors (2)

Rajdeep Dua

Rajdeep Dua has over 18 years experience in the cloud and big data space. He has taught Spark and big data at some of the most prestigious tech schools in India: IIIT Hyderabad, ISB, IIIT Delhi, and Pune College of Engineering. He currently leads the developer relations team at Salesforce India. He has also presented BigQuery and Google App Engine at the W3C conference in Hyderabad. He led the developer relations teams at Google, VMware, and Microsoft, and has spoken at hundreds of other conferences on the cloud. Some of the other references to his work can be seen at Your Story and on ACM digital library. His contributions to the open source community relate to Docker, Kubernetes, Android, OpenStack, and Cloud Foundry.
Read more about Rajdeep Dua

Manpreet Singh Ghotra

Manpreet Singh Ghotra has more than 15 years experience in software development for both enterprise and big data software. He is currently working at Salesforce on developing a machine learning platform/APIs using open source libraries and frameworks such as Keras, Apache Spark, and TensorFlow. He has worked on various machine learning systems, including sentiment analysis, spam detection, and anomaly detection. He was part of the machine learning group at one of the largest online retailers in the world, working on transit time calculations using Apache Mahout, and the R recommendation system, again using Apache Mahout. With a master's and postgraduate degree in machine learning, he has contributed to, and worked for, the machine learning community.
Read more about Manpreet Singh Ghotra

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