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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
Authors (2):
Phani Raj Phani Raj
Profile icon Phani Raj
Vinod Jaiswal Vinod Jaiswal
Profile icon Vinod Jaiswal
View More author details
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 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

Reading streaming data from Apache Kafka

In this recipe, you will learn how to use Apache Kafka connectors for structured streaming in Azure Databricks to read data from Apache Kafka and write the streaming data to Delta tables and to Parquet files in the default DBFS location.

Getting ready

Before you start working on this recipe, please ensure you have gone through all the following points.

  • Creating an Azure HD Insight Apache Kafka cluster (version 3.6 or later) that has Kafka version Kafka 0.10+. Perform the steps mentioned in the following document:

    https://docs.microsoft.com/en-us/azure/hdinsight/kafka/apache-kafka-get-started#:~:text=Table%201%20%20%20%20Property%20%20,a%20region%20...%20%205%20more%20rows

  • You can use the following Python script, https://github.com/PacktPublishing/Azure-Databricks-Cookbook/blob/main/Chapter04/PythonCode/Kafka_producer.py, which will push the data to the Apache Kafka cluster as a streaming data producer.
  • To run the Python...
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