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Azure Data Engineer Associate Certification Guide

You're reading from   Azure Data Engineer Associate Certification Guide Ace the DP-203 exam with advanced data engineering skills

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781805124689
Length 548 pages
Edition 2nd Edition
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Authors (3):
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Newton Alex Newton Alex
Author Profile Icon Newton Alex
Newton Alex
Giacinto Palmieri Giacinto Palmieri
Author Profile Icon Giacinto Palmieri
Giacinto Palmieri
Mr. Surendra Mettapalli Mr. Surendra Mettapalli
Author Profile Icon Mr. Surendra Mettapalli
Mr. Surendra Mettapalli
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Azure Basics FREE CHAPTER
2. Chapter 1: Introducing Azure Basics 3. Part 2: Data Storage
4. Chapter 2: Implementing a Partition Strategy 5. Chapter 3: Designing and Implementing the Data Exploration Layer 6. Part 3:Data Processing
7. Chapter 4: Ingesting and Transforming Data 8. Chapter 5: Developing a Batch Processing Solution 9. Chapter 6: Developing a Stream Processing Solution 10. Chapter 7: Managing Batches and Pipelines 11. Part 4:Secure, Monitor, and Optimize Data Storage and Processing
12. Chapter 8: Implementing Data Security 13. Chapter 9: Monitoring Data Storage and Data Processing 14. Chapter 10: Optimizing and Troubleshooting Data Storage and Data Processing 15. Chapter 11: Accessing the Online Practice Resources 16. Other Books You May Enjoy

Reading from and Writing to a Delta Lake

In Chapter 3, Designing and Implementing the Data Exploration Layer, you first encountered the concept of a Delta Lake. This is a layer of relational tables, called delta tables, on top of the files stored in a data lake. While the ability to see data in a tabular format and use SQL to query is also offered by creating an external table over CSV or Parquet files, creating a delta table adds extra benefits, such as versioning and transaction support.

Note

This section primarily focuses on the Read from and write to a delta lake concept of the DP-203: Data Engineering on Microsoft Azure exam.

In Synapse, aside from creating delta tables from templates, as shown in Chapter 3, Designing and Implementing the Data Exploration Layer, you can also create custom tables, as shown in Figure 5.35:

Figure 5.35 – The image illustrates the Synapse live interface showing the process of creating a custom delta table named “Customer” with columns “CustomerId,” “FirstName,” and “LastName” in “Database1.” The “Customer” table is displayed with the “CustomerId” column marked as a primary key. The interface includes tabs for “SQL script 4”, “Table” creation, and options for validation and “publish” changes.

Figure 5.35 – Creating a custom delta table in Synapse

Alternatively, you can create a delta table from an existing...

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