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Stream Analytics with Microsoft Azure

You're reading from  Stream Analytics with Microsoft Azure

Product type Book
Published in Dec 2017
Publisher Packt
ISBN-13 9781788395908
Pages 322 pages
Edition 1st Edition
Languages
Authors (2):
Ryan Murphy Ryan Murphy
Profile icon Ryan Murphy
Manpreet Singh Manpreet Singh
Profile icon Manpreet Singh
View More author details
Toc

Table of Contents (18) Chapters close

Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Introducing Stream Processing and Real-Time Insights 2. Introducing Azure Stream Analytics and Key Advantages 3. Designing Real-Time Streaming Pipelines 4. Developing Real-Time Event Processing with Azure Streaming 5. Building Using Stream Analytics Query Language 6. How to achieve Seamless Scalability with Automation 7. Integration of Microsoft Business Intelligence and Big Data 8. Designing and Managing Stream Analytics Jobs 9. Optimizing Intelligence in Azure Streaming 10. Understanding Stream Analytics Job Monitoring 11. Use Cases for Real-World Data Streaming Architectures

Summary


In this chapter, we learnt about how to scale and parallelize Stream Analytics workloads. We explored how to deploy Azure Stream Analytics using ARM templates. Finally, we examined Out of order and late arriving events.

Now that we know how to deploy Azure Stream Analytics and scale it, we will turn to the next chapter to look into other features and functionalities of Azure Stream Analytics.

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