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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

Databricks Workflows

Now that we’ve gone through the YAML deployment of workflows in dbx, next, we will look at the web console. Here, we have the main page for workflows. We can create a new workflow by clicking the Create job button at the top left:

Figure 9.1: Create job

Figure 9.1: Create job

When you create a workflow, you will be presented with a diagram of the workflow and a menu for each step:

Figure 9.2: My_workflow

Figure 9.2: My_workflow

Be sure to match the package name and entry point with what is defined in setup.py if you’re using a package:

Figure 9.3: Workflow diagram

Figure 9.3: Workflow diagram

When you run your workflow, you will see each instance run, its status, and its start time:

Figure 9.4: Workflow run

Figure 9.4: Workflow run

Here is an example of a two-step workflow that has failed:

Figure 9.5: Workflow flow

Figure 9.5: Workflow flow

You can see your failed runs individually in the console:

Figure 9.6: Workflow run failed
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