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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

Time management and event delivery guarantees


Windowing is an important query language extension that Stream Analytics provides to group events by time intervals, enabling aggregations of data streams. Other language extensions help with additional temporal aspects of stream data processing, including the source of the timestamp on which windows will be calculated, and the settings governing potential timestamp conflicts.

In a streaming system, a timestamp is the most fundamental data element in an event, and thus every event must have one in order to be processed or queried. In a simple streaming system, we can guarantee this by defining the moment each event arrives in the event stream as its identifying timestamp. (For Stream Analytics, the event stream is either Event Hub or IoT Hub.) Arrival Time is the default identifying timestamp of events. However, Stream Analytics provides a mechanism to choose a timestamp, known as Application Time, based on a column in the payload instead. Furthermore...

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