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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

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Length 318 pages
Edition 1st Edition
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Author (1):
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Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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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

Setting up your environment

Before we begin this chapter, let’s take some time to set up our working environment.

Python, AWS, and Databricks

As in the previous chapter, this chapter assumes you have a working version of Python 3.6+ installed in your development environment. It also assumes you have set up an AWS account and have set up Databricks with that AWS account.

Databricks CLI

The first step is to install the databricks-cli tool using the pip Python package manager:

pip install databricks-cli

Let’s validate that everything has been installed correctly. If the following command produces the tool version, then everything is working correctly:

databricks –v

Now, let’s set up authentication. First, go into the Databricks UI and generate a personal access token. The following command will ask for the host that’s been created for your Databricks instance, as well as the created token:

databricks configure –token...
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