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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

Kafka architecture

Kafka is an open source distributed streaming platform designed to scale to impressive levels. Kafka can store as much data as you have storage for, but it shouldn’t be used as a database. Kafka’s core architecture is composed of five main ideas – topics, brokers, partitions, producers, and consumers.

Topics

For a developer, a Kafka topic is the most important concept to understand. Topics are where data is “stored.” Topics hold data often called events, which means that the data has a key and a value. Keys in this context are not related to a database key that defines uniqueness, but they can be used for organizational purposes. The value is the data itself, which can be in a few different formats such as strings, JSON, Avro, and Protobuf. When your data is written to Kafka, it will have metadata; the most important will be the timestamp.

Working with Kafka can be confusing because the data isn’t stored in a database...

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