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Azure Data Engineer Associate Certification Guide

You're reading from  Azure Data Engineer Associate Certification Guide

Product type Book
Published in Feb 2022
Publisher Packt
ISBN-13 9781801816069
Pages 574 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Newton Alex Newton Alex
Profile icon Newton Alex

Table of Contents (23) Chapters

Preface Part 1: Azure Basics
Chapter 1: Introducing Azure Basics Part 2: Data Storage
Chapter 2: Designing a Data Storage Structure Chapter 3: Designing a Partition Strategy Chapter 4: Designing the Serving Layer Chapter 5: Implementing Physical Data Storage Structures Chapter 6: Implementing Logical Data Structures Chapter 7: Implementing the Serving Layer Part 3: Design and Develop Data Processing (25-30%)
Chapter 8: Ingesting and Transforming Data Chapter 9: Designing and Developing a Batch Processing Solution Chapter 10: Designing and Developing a Stream Processing Solution Chapter 11: Managing Batches and Pipelines Part 4: Design and Implement Data Security (10-15%)
Chapter 12: Designing Security for Data Policies and Standards Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
Chapter 13: Monitoring Data Storage and Data Processing Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing Part 6: Practice Exercises
Chapter 15: Sample Questions with Solutions Other Books You May Enjoy

Transformations using streaming analytics

One of the common themes that you might notice in streaming queries is that if there is any kind of transformation involved, there will always be windowed aggregation that has to be specified. Let's take the example of counting the number of distinct entries in a time frame.

The COUNT and DISTINCT transformations

This type of transformation can be used to count the number of distinct events that have occurred in a time window. Here is an example to count the number of unique trips in the last 10 seconds:

SELECT
    COUNT(DISTINCT tripId) AS TripCount,
    System.TIMESTAMP() AS Time
INTO [Output]
FROM [Input] TIMESTAMP BY createdAt
GROUP BY TumblingWindow(second, 10)

Next, let's look at an example where we can cast the type of input in a different format.

CAST transformations

The CAST transformation can be used to convert the data type on the fly. Here is an example to convert...

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