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Optimizing Databricks Workloads

You're reading from   Optimizing Databricks Workloads Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781801819077
Length 230 pages
Edition 1st Edition
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Authors (3):
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Anshul Bhatnagar Anshul Bhatnagar
Author Profile Icon Anshul Bhatnagar
Anshul Bhatnagar
Sarthak Sarbahi Sarthak Sarbahi
Author Profile Icon Sarthak Sarbahi
Sarthak Sarbahi
Anirudh Kala Anirudh Kala
Author Profile Icon Anirudh Kala
Anirudh Kala
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Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: Introduction to Azure Databricks
2. Chapter 1: Discovering Databricks FREE CHAPTER 3. Chapter 2: Batch and Real-Time Processing in Databricks 4. Chapter 3: Learning about Machine Learning and Graph Processing in Databricks 5. Section 2: Optimization Techniques
6. Chapter 4: Managing Spark Clusters 7. Chapter 5: Big Data Analytics 8. Chapter 6: Databricks Delta Lake 9. Chapter 7: Spark Core 10. Section 3: Real-World Scenarios
11. Chapter 8: Case Studies 12. Other Books You May Enjoy

Learning about graph analysis in Databricks

Graph analysis is the study of graphs to help deliver actionable insights and make decisions based on relationships between entities. A graph is a visual depiction of data with vertices and edges that helps in establishing relationships between entities. Let's learn more about this with an example, as follows:

Figure 3.7 – An example of a graph

In the preceding screenshot, we can see an example of a typical graph. Here, the entities in the circles are called vertices. Each vertex is treated as an object that has its own properties called attributes. Every vertex has a relationship with another vertex in a graph. This is called an edge.

For instance, let's say vertex a represents a person named Mark and vertex b represents a person named Thomas. Mark has an attribute that states he is 32 years old. Similarly, Thomas is 30 years old. An edge between these two vertices states friend. This defines...

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