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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

Understanding offsets and checkpoints

In this recipe, you will learn how a Spark Streaming query recovers from failure or any unexpected server crash using checkpointing, where it stores the process and the state of the query as and when it is executing. The information that the checkpointing stores is the range of offsets that are processed in each trigger (you can refer to the Understanding trigger options recipe to learn more about triggers).

Getting ready

We will be using Event Hubs for Kafka as the source for streaming data.

You can use the Python script available at https://github.com/PacktPublishing/Azure-Databricks-Cookbook/blob/main/Chapter04/PythonCode/KafkaEventHub_Windows.py, which will push the data to Event Hubs for Kafka as the streaming data producer. Change the topic name in the Python script to kafkaenabledhub2.

You can refer to the Reading data from Kafka-enabled Event Hubs recipe to understand how to get the bootstrap server details and other configuration...

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