Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Modern Data Architectures with Python

You're reading from   Modern Data Architectures with Python A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python

Arrow left icon
Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Length 318 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture FREE CHAPTER 3. Chapter 2: Understanding Data Analytics 4. Part 2: Data Engineering Toolset
5. Chapter 3: Apache Spark Deep Dive 6. Chapter 4: Batch and Stream Data Processing Using PySpark 7. Chapter 5: Streaming Data with Kafka 8. Part 3:Modernizing the Data Platform
9. Chapter 6: MLOps 10. Chapter 7: Data and Information Visualization 11. Chapter 8: Integrating Continous Integration into Your Workflow 12. Chapter 9: Orchestrating Your Data Workflows 13. Part 4:Hands-on Project
14. Chapter 10: Data Governance 15. Chapter 11: Building out the Groundwork 16. Chapter 12: Completing Our Project 17. Index 18. Other Books You May Enjoy

Practical lab

Our cloud team will be triggering an AWS Lambda and passing the path to the data being delivered from our ingestion tool. They have asked for a Lambda that will pass that information to your workflow, which should be parameterized. This type of request is very common and allows Databricks to be interacted with using a variety of tooling, such as AWS Step Functions and Jenkins, among others.

Solution

In this solution, we will walk you through the Python code needed to complete the tasks. There are two ways to access Databricks via the REST API – using the requests package, as shown previously, and using the Python package provided by Databricks. In my solution, I am using the Databricks package to keep things simple. I have not come across a case where the package doesn’t meet my needs, but if it’s not good enough, you can always access the REST API directly.

Lambda code

Here, I am importing all my Python libraries. Take note of the databricks_cli...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image