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Azure Databricks Cookbook

You're reading from Azure Databricks Cookbook

Product type Book

Published in Sep 2021

Publisher Packt

ISBN-13 9781789809718

Pages 452 pages

Edition 1st Edition

Languages

Concepts

Authors (2):

Phani Raj

Vinod Jaiswal

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Creating an Azure Databricks Service

2. Chapter 2: Reading and Writing Data from and to Various Azure Services and File Formats

3. Chapter 3: Understanding Spark Query Execution

4. Chapter 4: Working with Streaming Data

5. Chapter 5: Integrating with Azure Key Vault, App Configuration, and Log Analytics

6. Chapter 6: Exploring Delta Lake in Azure Databricks

7. Chapter 7: Implementing Near-Real-Time Analytics and Building a Modern Data Warehouse

8. Chapter 8: Databricks SQL

9. Chapter 9: DevOps Integrations and Implementing CI/CD for Azure Databricks

10. Chapter 10: Understanding Security and Monitoring in Azure Databricks

11. Other Books You May Enjoy

Constraints in Delta tables

Delta tables support constraints to ensure data integrity and quality. When the constraint conditions are not met by the data then InvariantViolationException is thrown, and data is not added to the table.

The following types of constraints are supported by the Delta table:

CHECK: Evaluate a given Boolean expression for each input row.
NOT NULL: Check that the column under constraint does not have a null value.

Getting ready

Before starting we need to ensure that we have a valid subscription with contributor access, a Databricks workspace, and an ADLS Gen2 storage account.

You can follow along by running the steps in the 6_6.Constraints notebook in the https://github.com/PacktPublishing/Azure-Databricks-Cookbook/blob/main/Chapter06/6_6.Constraints.ipynb. Upload the file to Customer folder in the rawdata container in your ADLS Gen-2 account which is mounted.

CustomerwithNullCName.csv file has 4 rows and one row has C_NAME as...

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Authors (2)

Phani Raj

Phani Raj is an experienced data architect and a product manager having 15 years of experience working with customers on building data platforms on both on-prem and on cloud. Worked on designing and implementing large scale big data solutions for customers on different verticals. His passion for continuous learning and adapting to the dynamic nature of technology underscores his role as a trusted advisor in the realm of data architecture ,data science and product management.

See other products by Phani Raj

Vinod Jaiswal

Vinod Jaiswal is an experienced data engineer, excels in transforming raw data into valuable insights. With over 8 years in Databricks, he designs and implements data pipelines, optimizes workflows, and crafts scalable solutions for intricate data challenges. Collaborating seamlessly with diverse teams, Vinod empowers them with tools and expertise to leverage data effectively. His dedication to staying updated on the latest data engineering trends ensures cutting-edge, robust solutions. Apart from technical prowess, Vinod is a proficient educator. Through presentations and mentoring, he shares his expertise, enabling others to harness the power of data within the Databricks ecosystem.

Read more

See other products by Vinod Jaiswal

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