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  • Book Overview & Buying Mastering Apache Spark 2.x
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Mastering Apache Spark 2.x

Mastering Apache Spark 2.x - Second Edition

By : Romeo Kienzler
4.5 (2)
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Mastering Apache Spark 2.x

Mastering Apache Spark 2.x

4.5 (2)
By: Romeo Kienzler

Overview of this book

Apache Spark is an in-memory, cluster-based Big Data processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and more. This book will take your knowledge of Apache Spark to the next level by teaching you how to expand Spark’s functionality and build your data flows and machine/deep learning programs on top of the platform. The book starts with a quick overview of the Apache Spark ecosystem, and introduces you to the new features and capabilities in Apache Spark 2.x. You will then work with the different modules in Apache Spark such as interactive querying with Spark SQL, using DataFrames and DataSets effectively, streaming analytics with Spark Streaming, and performing machine learning and deep learning on Spark using MLlib and external tools such as H20 and Deeplearning4j. The book also contains chapters on efficient graph processing, memory management and using Apache Spark on the cloud. By the end of this book, you will have all the necessary information to master Apache Spark, and use it efficiently for Big Data processing and analytics.
Table of Contents (15 chapters)
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10
Deep Learning on Apache Spark with DeepLearning4j and H2O

Apache Spark with Jupyter Notebooks on IBM DataScience Experience

When talking about the cloud, nearly everybody has a different view. Some think of virtual machines, which you can start and stop instantaneously, while some others think of file storage. But the cloud is more than that. In this chapter, we will talk about using Apache Spark in the cloud. But this is, of course, more than provisioning some virtual machines and installing an Apache Spark cluster on it.

We are talking about the so-called Platform as a service clouds (PaaS), where everything is a service, ready to be consumed, and the operation of components is done by the cloud provider. Therefore, on PaaS clouds, Apache Spark is pre-installed. This is done in a way that workers can be added to and removed from the cluster on-the-fly. But not only is Apache Spark pre-installed, the required tooling around it is also...

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Mastering Apache Spark 2.x
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