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Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

By : Pulkit Chadha
4.4 (7)
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Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

4.4 (7)
By: Pulkit Chadha

Overview of this book

Written by a Senior Solutions Architect at Databricks, Data Engineering with Databricks Cookbook will show you how to effectively use Apache Spark, Delta Lake, and Databricks for data engineering, starting with comprehensive introduction to data ingestion and loading with Apache Spark. What makes this book unique is its recipe-based approach, which will help you put your knowledge to use straight away and tackle common problems. You’ll be introduced to various data manipulation and data transformation solutions that can be applied to data, find out how to manage and optimize Delta tables, and get to grips with ingesting and processing streaming data. The book will also show you how to improve the performance problems of Apache Spark apps and Delta Lake. Advanced recipes later in the book will teach you how to use Databricks to implement DataOps and DevOps practices, as well as how to orchestrate and schedule data pipelines using Databricks Workflows. You’ll also go through the full process of setup and configuration of the Unity Catalog for data governance. By the end of this book, you’ll be well-versed in building reliable and scalable data pipelines using modern data engineering technologies.
Table of Contents (16 chapters)
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1
Part 1 – Working with Apache Spark and Delta Lake
9
Part 2 – Data Engineering Capabilities within Databricks

Triggering jobs based on file arrival

File arrival triggers can be used to start your Databricks Workflow when new files show up in an external location such as Amazon S3 or Azure storage. This feature is useful when new data does not come regularly and a scheduled job would not work well. Every minute, file arrival triggers look for new files. They do not have any extra cost except for the cloud provider costs for listing files in the storage location.

In this recipe, you will learn how to set up file arrival triggers to run Databricks Workflows.

Getting ready

Before you can use file arrival triggers, you need to meet the following conditions:

  • Your workspace should have Unity Catalog activated. Unity Catalog is a unified governance solution for data and AI assets on the lakehouse.
  • An external location that belongs to the Unity Catalog metastore is recommended. This is an object that has both a cloud storage path and a storage credential that allows access to that...

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