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Apache Spark 2: Data Processing and Real-Time Analytics

You're reading from   Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789959208
Length 616 pages
Edition 1st Edition
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Authors (7):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Romeo Kienzler Romeo Kienzler
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Romeo Kienzler
Siamak Amirghodsi Siamak Amirghodsi
Author Profile Icon Siamak Amirghodsi
Siamak Amirghodsi
Broderick Hall Broderick Hall
Author Profile Icon Broderick Hall
Broderick Hall
Md. Rezaul Karim Md. Rezaul Karim
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Md. Rezaul Karim
Meenakshi Rajendran Meenakshi Rajendran
Author Profile Icon Meenakshi Rajendran
Meenakshi Rajendran
Shuen Mei Shuen Mei
Author Profile Icon Shuen Mei
Shuen Mei
+3 more Show less
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Table of Contents (23) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
1. A First Taste and What's New in Apache Spark V2 FREE CHAPTER 2. Apache Spark Streaming 3. Structured Streaming 4. Apache Spark MLlib 5. Apache SparkML 6. Apache SystemML 7. Apache Spark GraphX 8. Spark Tuning 9. Testing and Debugging Spark 10. Practical Machine Learning with Spark Using Scala 11. Spark's Three Data Musketeers for Machine Learning - Perfect Together 12. Common Recipes for Implementing a Robust Machine Learning System 13. Recommendation Engine that Scales with Spark 14. Unsupervised Clustering with Apache Spark 2.0 15. Implementing Text Analytics with Spark 2.0 ML Library 16. Spark Streaming and Machine Learning Library 1. Other Books You May Enjoy Index

Cloud-based deployments


There are three different abstraction levels of cloud systems--Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). We will see how to use and install Apache Spark on all of these.

The new way to do IaaS is Docker and Kubernetes as opposed to virtual machines, basically providing a way to automatically set up an Apache Spark cluster within minutes. The advantage of Kubernetes is that it can be used among multiple different cloud providers as it is an open standard and also based on open source.

You even can use Kubernetes, in a local data center and transparently and dynamically move workloads between local, dedicated, and public cloud data centers. PaaS, in contrast, takes away from you the burden of installing and operating an Apache Spark cluster because this is provided as a service.

There is an ongoing discussion, whether Docker is IaaS or PaaS but, in our opinion, this is just a form of a lightweight preinstalled virtual machine.This is particularly interesting because the offering is completely based on open source technologies, which enables you to replicate the system on any other data center.

One of the open source components, we'll introduce is Jupyter notebooks; a modern way to do data science, in a cloud-based collaborative environment.

You have been reading a chapter from
Apache Spark 2: Data Processing and Real-Time Analytics
Published in: Dec 2018
Publisher: Packt
ISBN-13: 9781789959208
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