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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

Handling concurrency

One of the most common problems in big data systems is that they are not compliant with ACID properties, or to put it more simply, let's say they only support some properties of ACID transactions between reads and writes, and even then, they still have a lot of limitations. But with Delta Lake, ACID compliance is possible, and you can now leverage the features of ACID transactions that you used to get in Relational Database Management Systems (RDBMSes). Delta Lake uses optimistic concurrency control for handling transactions.

Optimistic concurrency control provides a mechanism to handle concurrent transactions that are changing data in the table. It ensures that all the transactions are completed successfully. A Delta Lake write operation is performed in three stages:

  1. Read – The latest version of the table in which the file needs to be modified is read.
  2. Write – New data files are written.
  3. Validate and commit – Validate...
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