Book Image

Azure Databricks Cookbook

By : Phani Raj, Vinod Jaiswal
Book Image

Azure Databricks Cookbook

By: Phani Raj, Vinod Jaiswal

Overview of this book

Azure Databricks is a unified collaborative platform for performing scalable analytics in an interactive environment. The Azure Databricks Cookbook provides recipes to get hands-on with the analytics process, including ingesting data from various batch and streaming sources and building a modern data warehouse. The book starts by teaching you how to create an Azure Databricks instance within the Azure portal, Azure CLI, and ARM templates. You’ll work through clusters in Databricks and explore recipes for ingesting data from sources, including files, databases, and streaming sources such as Apache Kafka and EventHub. The book will help you explore all the features supported by Azure Databricks for building powerful end-to-end data pipelines. You'll also find out how to build a modern data warehouse by using Delta tables and Azure Synapse Analytics. Later, you’ll learn how to write ad hoc queries and extract meaningful insights from the data lake by creating visualizations and dashboards with Databricks SQL. Finally, you'll deploy and productionize a data pipeline as well as deploy notebooks and Azure Databricks service using continuous integration and continuous delivery (CI/CD). By the end of this Azure book, you'll be able to use Azure Databricks to streamline different processes involved in building data-driven apps.
Table of Contents (12 chapters)

Streaming data from log files

Nowadays, most enterprises are maintaining a lot of applications and each application has its log files. Extracting the required information from log files or monitoring the log file data is becoming a cumbersome task for administrators. To salvage some of the workloads from the shoulders of administrators, Azure Databricks is a great help. Using Databricks, you can process the log files and interactively query the log data to extract the required information.

Getting ready

You can follow along by running the steps in the "4-4.StreamingLogFiles" notebook in your local cloned repository in the Chapter04 folder (https://github.com/PacktPublishing/Azure-Databricks-Cookbook/tree/main/Chapter04).

Upload the LogFiles folder in the Common/LogData folder to the ADLS Gen-2 account in the rawdata filesystem under the Log Files folder.

In this recipe, the use case that we are going to examine is the application logs being generated in the ADLS...