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Azure Databricks Cookbook

You're reading from   Azure Databricks Cookbook Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781789809718
Length 452 pages
Edition 1st Edition
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Authors (2):
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Vinod Jaiswal Vinod Jaiswal
Author Profile Icon Vinod Jaiswal
Vinod Jaiswal
Phani Raj Phani Raj
Author Profile Icon Phani Raj
Phani Raj
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Toc

Table of Contents (12) Chapters Close

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 FREE CHAPTER 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

Versioning in Delta tables

In today's world, data is growing day by day and sometimes we need to access the historical data. To access the data for a particular period, data needs to be saved at a point in time, meaning a snapshot of the data at an interval of time. Having such a snapshot will make it easy to audit data changes and perform rollbacks for bad writes or accidentally deleted data.

When the data is written into Delta Lake, every transaction is versioned, and it can be accessed at any point in time. This is called Time Travel. It provides the flexibility to travel back to a previous time and access the data of the current Delta table as it was then. The transaction log contains the versioning information of the Delta table.

Delta Lake always provides backward compatibility, but sometimes suffers from forward-compatibility breaks, meaning a lower version of the Databricks runtime may not be able to read and write data that was written using a higher version of...

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