Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service

Length: 452 pages
Edition: 1
Language: English
Publisher: Packt Publishing
Publication Date: 2021-09-17
ISBN-10: 1789809711
ISBN-13: 9781789809718
Sales Rank: #313109 (See Top 100 Books)

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.

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

Azure Databricks Cookbook
Contributors
About the authors
About the reviewers
Preface
    Who this book is for
    What this book covers
    To get the most out of this book
        Download the example code files
    Download the color images
    Conventions used
    Sections
        Getting ready
        How to do it…
        How it works…
        There's more…
        See also
    Get in touch
    Share Your Thoughts
Chapter 1: Creating an Azure Databricks Service
    Technical requirements
    Creating a Databricks workspace in the Azure portal 
        Getting ready
        How to do it…
        How it works…
    Creating a Databricks service using the Azure CLI (command-line interface)
        Getting ready
        How to do it…
        How it works…
        There's more…
    Creating a Databricks service using Azure Resource Manager (ARM) templates
        Getting ready
        How to do it…
        How it works…
    Adding users and groups to the workspace
        Getting ready
        How to do it…
        How it works…
        There's more…
    Creating a cluster from the user interface (UI)
        Getting ready
        How to do it…
        How it works…
        There's more…
    Getting started with notebooks and jobs in Azure Databricks
        Getting ready
        How to do it…
         How it works…
    Authenticating to Databricks using a PAT
        Getting ready
        How to do it…
        How it works…
        There's more…
Chapter 2: Reading and Writing Data from and to Various Azure Services and File Formats
    Technical requirements
    Mounting ADLS Gen2 and Azure Blob storage to Azure DBFS
        Getting ready
        How to do it…
        How it works…
        There's more…
    Reading and writing data from and to Azure Blob storage
        Getting ready
        How to do it…
        How it works…
        There's more…
    Reading and writing data from and to ADLS Gen2
        Getting ready
        How to do it…
        How it works…
    Reading and writing data from and to an Azure SQL database using native connectors
        Getting ready
        How to do it…
        How it works…
    Reading and writing data from and to Azure Synapse SQL (dedicated SQL pool) using native connectors 
        Getting ready
        How to do it…
        How it works…
    Reading and writing data from and to Azure Cosmos DB 
        Getting ready
        How to do it…
        How it works…
    Reading and writing data from and to CSV and Parquet 
        Getting ready
        How to do it…
        How it works…
    Reading and writing data from and to JSON, including nested JSON 
        Getting ready
        How to do it…
        How it works…
Chapter 3: Understanding Spark Query Execution
    Technical requirements
    Introduction to jobs, stages, and tasks
        Getting ready
        How to do it…
        How it works…
    Checking the execution details of all the executed Spark queries via the Spark UI
        Getting ready
        How to do it…
        How it works…
    Deep diving into schema inference
        Getting ready
        How to do it…
        How it works…
        There's more…
    Looking into the query execution plan
        Getting ready
        How to do it…
        How it works…
    How joins work in Spark 
        Getting ready
        How to do it…
        How it works…
        There's more…
    Learning about input partitions 
        Getting ready
        How to do it…
        How it works…
    Learning about output partitions 
        Getting ready
        How to do it…
        How it works…
    Learning about shuffle partitions
        Getting ready
        How to do it…
        How it works…
    Storage benefits of different file types
        Getting ready
        How to do it…
        How it works…
Chapter 4: Working with Streaming Data
    Technical requirements
    Reading streaming data from Apache Kafka
        Getting ready
        How to do it…
        How it works…
    Reading streaming data from Azure Event Hubs
        Getting ready
        How to do it…
        How it works…
    Reading data from Event Hubs for Kafka
        Getting ready
        How to do it…
        How it works…
    Streaming data from log files
        Getting ready
        How to do it…
        How it works…
    Understanding trigger options
        Getting ready
        How to do it…
        How it works…
    Understanding window aggregation on streaming data
        Getting ready
        How to do it…
        How it works…
    Understanding offsets and checkpoints
        Getting ready
        How to do it…
        How it works…
Chapter 5: Integrating with Azure Key Vault, App Configuration, and Log Analytics
    Technical requirements
    Creating an Azure Key Vault to store secrets using the UI
        Getting ready
        How to do it…
        How it works…
    Creating an Azure Key Vault to store secrets using ARM templates
        Getting ready
        How to do it…
        How it works…
    Using Azure Key Vault secrets in Azure Databricks
        Getting ready
        How to do it…
        How it works…
    Creating an App Configuration resource
        Getting ready
        How to do it…
        How it works…
    Using App Configuration in an Azure Databricks notebook
        Getting ready
        How to do it…
        How it works…
    Creating a Log Analytics workspace
        Getting ready
        How to do it…
        How it works…
    Integrating a Log Analytics workspace with Azure Databricks
        Getting ready
        How to do it…
        How it works…
Chapter 6: Exploring Delta Lake in Azure Databricks
    Technical requirements
    Delta table operations – create, read, and write
        Getting ready
        How to do it…
        How it works…
        There's more…
    Streaming reads and writes to Delta tables
        Getting ready
        How to do it…
        How it works…
    Delta table data format
        Getting ready
        How to do it…
        How it works…
        There's more…
    Handling concurrency
        Getting ready
        How to do it…
        How it works…
    Delta table performance optimization
        Getting ready
        How to do it…
        How it works…
    Constraints in Delta tables
        Getting ready
        How to do it…
        How it works…
    Versioning in Delta tables
        Getting ready
        How to do it…
        How it works…
Chapter 7: Implementing Near-Real-Time Analytics and Building a Modern Data Warehouse 
    Technical requirements
    Understanding the scenario for an end-to-end (E2E) solution
        Getting ready
        How to do it…
        How it works…
    Creating required Azure resources for the E2E demonstration
        Getting ready
        How to do it…
        How it works…
    Simulating a workload for streaming data
        Getting ready
        How to do it…
        How it works…
    Processing streaming and batch data using Structured Streaming
        Getting ready
        How to do it… 
        How it works…
    Understanding the various stages of transforming data
        Getting ready
        How to do it…
        How it works…
    Loading the transformed data into Azure Cosmos DB and a Synapse dedicated pool
        Getting ready
        How to do it…
        How it works…
    Creating a visualization and dashboard in a notebook for near-real-time analytics
        Getting ready
        How to do it…
        How it works…
    Creating a visualization in Power BI for near-real-time analytics
        Getting ready
        How to do it…
        How it works…
    Using Azure Data Factory (ADF) to orchestrate the E2E pipeline 
        Getting ready
        How to do it…
        How it works…
Chapter 8: Databricks SQL 
    Technical requirements
    How to create a user in Databricks SQL
        Getting ready
        How to do it…
        How it works…
    Creating SQL endpoints  
        Getting ready
        How to do it…
        How it works…
    Granting access to objects to the user 
        Getting ready
        How to do it…
        How it works…
    Running SQL queries in Databricks SQL
        Getting ready
        How to do it… 
        How it works…
    Using query parameters and filters
        Getting ready
        How to do it…
        How it works…
    Introduction to visualizations in Databricks SQL
        Getting ready
        How to do it…
    Creating dashboards in Databricks SQL
        Getting ready
        How to do it…
        How it works…
    Connecting Power BI to Databricks SQL
        Getting ready
        How to do it…
Chapter 9: DevOps Integrations and Implementing CI/CD for Azure Databricks
    Technical requirements
    How to integrate Azure DevOps with an Azure Databricks notebook
        Getting ready
        How to do it…
    Using GitHub for Azure Databricks notebook version control 
        Getting ready
        How to do it…
        How it works…
    Understanding the CI/CD process for Azure Databricks
        Getting ready
        How to do it…
        How it works…
    How to set up an Azure DevOps pipeline for deploying notebooks
        Getting ready
        How to do it… 
        How it works…
    Deploying notebooks to multiple environments
        Getting ready
        How to do it…
        How it works…
    Enabling CI/CD in an Azure DevOps build and release pipeline
        Getting ready
        How to do it…
    Deploying an Azure Databricks service using an Azure DevOps release pipeline
        Getting ready
        How to do it…
Chapter 10: Understanding Security and Monitoring in Azure Databricks
    Technical requirements
    Understanding and creating RBAC in Azure for ADLS Gen-2
        Getting ready
        How to do it…
    Creating ACLs using Storage Explorer and PowerShell
        Getting ready
        How to do it…
        How it works…
    How to configure credential passthrough
        Getting ready
        How to do it…
    How to restrict data access to users using RBAC
        Getting ready
        How to do it… 
    How to restrict data access to users using ACLs
        Getting ready
        How to do it…
    Deploying Azure Databricks in a VNet and accessing a secure storage account
        Getting ready
        How to do it…
        There's more…
    Using Ganglia reports for cluster health
        Getting ready
        How to do it…
    Cluster access control
        Getting ready
        How to do it…
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Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service

Key Features

Book Description

What you will learn

Who this book is for

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