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Modern Data Architectures with Python

You're reading from  Modern Data Architectures with Python

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Pages 318 pages
Edition 1st Edition
Languages
Author (1):
Brian Lipp Brian Lipp
Profile icon Brian Lipp

Table of Contents (19) Chapters

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture 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

Tips and tricks with Databricks notebooks

Since we will go through notebooks, it makes sense to mention a few tricks you can do with Databricks notebooks.

Magic

Databricks notebooks can use magic, which involves mixing in some type of non-Python component using the % syntax.

Markdown

Markdown is an advantageous way to format text, much like HTML, but it’s much simpler to write and learn. To invoke a Markdown cell, simply type %md at the start of your cell.

Other languages

When working with notebooks, it can be handy to run a command in a language other than what the notebook is set up to run. The language magic works by typing %[language] at the start of the notebook cell. For example, you can invoke %sql, %r, %scala, and %python using the language magically. Keep in mind that it is impossible to pass variables between languages, and the context of the language magic is limited to the cell itself.

Terminal

To gain terminal access to the driver node, use...

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