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Cloud Scale Analytics with Azure Data Services

You're reading from   Cloud Scale Analytics with Azure Data Services Build modern data warehouses on Microsoft Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781800562936
Length 520 pages
Edition 1st Edition
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Author (1):
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Patrik Borosch Patrik Borosch
Author Profile Icon Patrik Borosch
Patrik Borosch
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Data Warehousing and Considerations Regarding Cloud Computing
2. Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses FREE CHAPTER 3. Chapter 2: Connecting Requirements and Technology 4. Section 2: The Storage Layer
5. Chapter 3: Understanding the Data Lake Storage Layer 6. Chapter 4: Understanding Synapse SQL Pools and SQL Options 7. Section 3: Cloud-Scale Data Integration and Data Transformation
8. Chapter 5: Integrating Data into Your Modern Data Warehouse 9. Chapter 6: Using Synapse Spark Pools 10. Chapter 7: Using Databricks Spark Clusters 11. Chapter 8: Streaming Data into Your MDWH 12. Chapter 9: Integrating Azure Cognitive Services and Machine Learning 13. Chapter 10: Loading the Presentation Layer 14. Section 4: Data Presentation, Dashboarding, and Distribution
15. Chapter 11: Developing and Maintaining the Presentation Layer 16. Chapter 12: Distributing Data 17. Chapter 13: Introducing Industry Data Models 18. Chapter 14: Establishing Data Governance 19. Other Books You May Enjoy

Monitoring your MDWH

Monitoring your workloads with different services on Azure might be a challenging idea when you consider the isolated service. But as mentioned in other chapters already, all Azure services that we have touched on integrate with Azure Monitor. Their logs and metrics can be sent to Log Analytics and can be analyzed together with other services at a higher level.

When we check the Azure Synapse-dedicated SQL pools, for example, you will have the option to select and push from the following log information to Log Analytics (and two other options; see the following):

  • SQLRequests: These are insights about the queries run in the pool, especially the distribution of the steps.
  • RequestSteps: Here, you will find the details about the query steps.
  • ExecRequests: High-level information about the queries.
  • DmsWorkers: Insights about the worker nodes that are executing steps during query execution.
  • Waits: Wait states during query runs; you will also...
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