70 recipes to learn how to implement reliable data pipelines with Apache Spark, optimally store and process structured and unstructured data in Delta Lake, and use Databricks to orchestrate and govern your data. Key Features Learn data ingestion, data transformation, and data management techniques using Apache Spark and Delta Lake Gain practical guidance on using Delta Lake tables and orchestrating data pipelines Implement reliable DataOps and DevOps practices, and enforce data governance policies on Databricks Book DescriptionApache Spark is a powerful open source distributed computing system that enables fast and flexible data processing and Delta Lake is an open-source storage layer that provides reliability, performance, and scale for data lakes. Data Engineering with Databricks Cookbook will show you recipes for effectively using Apache Spark, Delta Lake, and Databricks for data engineering, beginning with an introduction to data ingestion and loading with Apache Spark. You will be introduced to various data manipulation and data transformation solutions that can be applied to data. You'll discover how to manage and optimize Delta tables, as well as how to ingest and process streaming data. You'll learn how to improve the performance problems of Apache Spark apps and Delta Lake. Later chapters will teach you how to use Databricks to implement DataOps and DevOps practices. You'll then learn how to orchestrate and schedule data pipelines using Databricks Workflows. Finally, you will go over how to set up and configure Unity Catalog for data governance. By the end of this book, you’ll learn how to build reliable data pipelines with modern data engineering technologies as well as have a comprehensive understanding of how to build efficient and scalable data pipelines.What you will learn Perform data loading, ingestion, and processing with Apache Spark Discover data transformation techniques and custom UDFs in Apache Spark Manage and optimize Delta tables with Apache Spark and Delta Lake APIs Use Spark Structured Streaming for real-time data processing Optimize Apache Spark application and Delta table query performance Implement DataOps and DevOps practices on Databricks Orchestrate data pipelines with Delta Live Tables and Databricks Workflows Implement data governance policies with Unity Catalog Who this book is forThis book is for data engineers, data scientists, and data practitioners who want to learn how to build efficient and scalable data pipelines using Apache Spark, Delta Lake, and Databricks. To get the most out of this book, you should have basic knowledge of data architecture, SQL, and Python.

Book Information
ISBN 9781837633357
Author Pulkit Chadha
Format Paperback
Page Count 454
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited