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Azure Data Engineer Associate Certification Guide

You're reading from   Azure Data Engineer Associate Certification Guide A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam

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Product type Paperback
Published in Feb 2022
Publisher Packt
ISBN-13 9781801816069
Length 574 pages
Edition 1st Edition
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Author (1):
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Newton Alex Newton Alex
Author Profile Icon Newton Alex
Newton Alex
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Azure Basics
2. Chapter 1: Introducing Azure Basics FREE CHAPTER 3. Part 2: Data Storage
4. Chapter 2: Designing a Data Storage Structure 5. Chapter 3: Designing a Partition Strategy 6. Chapter 4: Designing the Serving Layer 7. Chapter 5: Implementing Physical Data Storage Structures 8. Chapter 6: Implementing Logical Data Structures 9. Chapter 7: Implementing the Serving Layer 10. Part 3: Design and Develop Data Processing (25-30%)
11. Chapter 8: Ingesting and Transforming Data 12. Chapter 9: Designing and Developing a Batch Processing Solution 13. Chapter 10: Designing and Developing a Stream Processing Solution 14. Chapter 11: Managing Batches and Pipelines 15. Part 4: Design and Implement Data Security (10-15%)
16. Chapter 12: Designing Security for Data Policies and Standards 17. Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
18. Chapter 13: Monitoring Data Storage and Data Processing 19. Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing 20. Part 6: Practice Exercises
21. Chapter 15: Sample Questions with Solutions 22. Other Books You May Enjoy

Monitoring cluster performance

Since services such as Synapse and ADF are platform-as-a-service (PaaS) services where you will not have explicit control over the clusters, the one place where we can control each and every aspect of a cluster is the Azure HDInsight service. In HDInsight, you can create your own Hadoop, Spark, Hive, HBase, and other clusters and control every aspect of the cluster. You can use Log Analytics to monitor cluster performance, as with the other examples we saw earlier in the chapter. You can learn more about using Log Analytics in HDInsight here: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-oms-log-analytics-tutorial.

Apart from the Log Analytics approach, there are four main areas of the HDInsight portal that help monitor cluster performance. Let's look at them.

Monitoring overall cluster performance

The HDInsight Ambari dashboard is the first place to check for cluster health. If you see very high heap usage, disk usage...

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