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Scalable Data Analytics with Azure Data Explorer

You're reading from  Scalable Data Analytics with Azure Data Explorer

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801078542
Pages 364 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Jason Myerscough Jason Myerscough
Profile icon Jason Myerscough

Table of Contents (18) Chapters

Preface Section 1: Introduction to Azure Data Explorer
Chapter 1: Introducing Azure Data Explorer Chapter 2: Building Your Azure Data Explorer Environment Chapter 3: Exploring the Azure Data Explorer UI Section 2: Querying and Visualizing Your Data
Chapter 4: Ingesting Data in Azure Data Explorer Chapter 5: Introducing the Kusto Query Language Chapter 6: Introducing Time Series Analysis Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data Chapter 8: Data Visualization with Azure Data Explorer and Power BI Section 3: Advanced Azure Data Explorer Topics
Chapter 9: Monitoring and Troubleshooting Azure Data Explorer Chapter 10: Azure Data Explorer Security Chapter 11: Performance Tuning in Azure Data Explorer Chapter 12: Cost Management in Azure Data Explorer Chapter 13: Assessment Other Books You May Enjoy

Ingesting data from Blob storage using Azure Event Grid

In our final example of data ingestion, we will enable streaming on our cluster and use Azure Event Grid and Event Hubs so we can ingest data whenever new files are placed in our storage account's blob container. A blob container is a location on the storage account used to store our data.

For this section, we need to create the following Azure resources:

  • A storage account for storing files
  • An event grid to emit blob creation events
  • An event hub deliver the notification to Azure Data Explorer

Using JSON data, we will demonstrate how to create JSON-based mapping schemas.

When a file is uploaded to the storage account, a blob created event is generated and received by the event grid. The event grid then updates Azure Data Explorer to pull information from the storage account. In our example, the information is a JSON file.

This path of data ingestion is shown in the following figure:

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