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Graph Data Modeling in Python

You're reading from   Graph Data Modeling in Python A practical guide to curating, analyzing, and modeling data with graphs

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618035
Length 236 pages
Edition 1st Edition
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Authors (2):
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Gary Hutson Gary Hutson
Author Profile Icon Gary Hutson
Gary Hutson
Matt Jackson Matt Jackson
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Matt Jackson
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Getting Started with Graph Data Modeling
2. Chapter 1: Introducing Graphs in the Real World FREE CHAPTER 3. Chapter 2: Working with Graph Data Models 4. Part 2: Making the Graph Transition
5. Chapter 3: Data Model Transformation – Relational to Graph Databases 6. Chapter 4: Building a Knowledge Graph 7. Part 3: Storing and Productionizing Graphs
8. Chapter 5: Working with Graph Databases 9. Chapter 6: Pipeline Development 10. Chapter 7: Refactoring and Evolving Schemas 11. Part 4: Graphing Like a Pro
12. Chapter 8: Perfect Projections 13. Chapter 9: Common Errors and Debugging 14. Index 15. Other Books You May Enjoy

From relational to graph databases

Due to the poor performance of our relational database in answering graph-like questions, we may want to move our tabular data into a graph format.

First, we will consider a sensible graph schema for our data, based on the information we have available, before writing a pipeline to move data from MySQL into a Python igraph network. By doing this, we can benchmark how a graphical approach to our path-based question performs, in comparison to the same question we answered with SQL.

Schema design

In our tables, we have two types of entities, users and games, which have different properties. Because of this, it is wise to consider users and games as different node types.

For users, we only have a unique ID for each user. To add data to an igraph graph, we will need to add an increasing integer igraph node ID for each distinct node, as we learned in Chapter 1, Introducing Graphs in the Real World, and Chapter 2, Working with Graph Data Models...

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