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Data Engineering with Python

You're reading from  Data Engineering with Python

Product type Book
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Pages 356 pages
Edition 1st Edition
Languages
Author (1):
Paul Crickard Paul Crickard
Profile icon Paul Crickard

Table of Contents (21) Chapters

Preface 1. Section 1: Building Data Pipelines – Extract Transform, and Load
2. Chapter 1: What is Data Engineering? 3. Chapter 2: Building Our Data Engineering Infrastructure 4. Chapter 3: Reading and Writing Files 5. Chapter 4: Working with Databases 6. Chapter 5: Cleaning, Transforming, and Enriching Data 7. Chapter 6: Building a 311 Data Pipeline 8. Section 2:Deploying Data Pipelines in Production
9. Chapter 7: Features of a Production Pipeline 10. Chapter 8: Version Control with the NiFi Registry 11. Chapter 9: Monitoring Data Pipelines 12. Chapter 10: Deploying Data Pipelines 13. Chapter 11: Building a Production Data Pipeline 14. Section 3:Beyond Batch – Building Real-Time Data Pipelines
15. Chapter 12: Building a Kafka Cluster 16. Chapter 13: Streaming Data with Apache Kafka 17. Chapter 14: Data Processing with Apache Spark 18. Chapter 15: Real-Time Edge Data with MiNiFi, Kafka, and Spark 19. Other Books You May Enjoy Appendix

Deploying your data pipelines

There are many ways to handle the different environments—development, testing, production—and how you choose to do that is up to what works best with your business practices. Having said that, any strategy you take should involve using the NiFi registry.

Using the simplest strategy

The simplest strategy would be to run NiFi over the network and split the canvas into multiple environments. When you have promoted a process group, you would move it in to the next environment. When you needed to rebuild a data pipeline, you would add it back to development and modify it, then update the production data pipeline to the newest version. Your NiFi instance would look like the following screenshot:

Figure 10.11 – A single NiFi instance working as DEV, TEST, and PROD

Notice in the preceding screenshot that only PROD has a green checkmark. The DEV environment created the processor group, then changes were committed...

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