Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Sp…

English | 2021 | ISBN: ‎ 1789809711 | 452 pages | pdf, epub | 79.86 MB

Get to grips with building and productionizing end-to-end big data solutions in Azure and learn best practices for working with large datasets
Key Features

Integrate with Azure Synapse Analytics, Cosmos DB, and Azure HDInsight Kafka Cluster to scale and analyze your projects and build pipelines
Use Databricks SQL to run ad hoc queries on your data lake and create dashboards
Productionize a solution using CI/CD for deploying notebooks and Azure Databricks Service to various environments

Book Description

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.
What you will learn

Read and write data from and to various Azure resources and file formats
Build a modern data warehouse with Delta Tables and Azure Synapse Analytics
Explore jobs, stages, and tasks and see how Spark lazy evaluation works
Handle concurrent transactions and learn performance optimization in Delta tables
Learn Databricks SQL and create real-time dashboards in Databricks SQL
Integrate Azure DevOps for version control, deploying, and productionizing solutions with CI/CD pipelines
Discover how to use RBAC and ACLs to restrict data access
Build end-to-end data processing pipeline for near real-time data analytics

Who this book is for

This recipe-based book is for data scientists, data engineers, big data professionals, and machine learning engineers who want to perform data analytics on their applications. Prior experience of working with Apache Spark and Azure is necessary to get the most out of this book.
Table of Contents

Creating an Azure Databricks Service
Reading and Writing Data from and to Various Azure Services and File Formats
Understanding Spark Query Execution
Working with Streaming Data
Integrating with Azure Key-Vault, App Configuration and Log Analytics
Exploring Delta Lake in Azure Databricks
Implementing Near-Real-Time Analytics and Building Modern Data Warehouse
Azure Databricks SQL Analytics
DevOps Integrations and Implementing CI/CD for Azure Databricks
Understanding Security and Monitoring in Azure Databricks