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Data Engineering with Python

You're reading from   Data Engineering with Python Work with massive datasets to design data models and automate data pipelines using Python

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Building Data Pipelines – Extract Transform, and Load
2. Chapter 1: What is Data Engineering? FREE CHAPTER 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

Managing the distributed data pipeline

The preceding data pipeline runs on each node. To compensate for that, you had to create the same path on both nodes for the PutFile processor to work. Earlier, you learned that there are several processors that can result in race conditions – trying to read the same file at the same time – which will cause problems. To resolve these issues, you can specify that a processor should only run on the Primary Node – as an isolated process.

In the configuration for the PutFile processor, select the Scheduling tab. In the dropdown for Scheduling Strategy, choose On primary node, as shown in the following screenshot:

Figure 16.6 – Running a processor on the Primary Node only

Now, when you run the data pipeline, the files will only be placed on the Primary Node. You can schedule processors such as GetFile or ExecuteSQL to do the same thing.

To see the load of the data pipeline on each node, you...

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