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You're reading from  Graph Data Science with Neo4j

Product typeBook
Published inJan 2023
Reading LevelIntermediate
PublisherPackt
ISBN-139781804612743
Edition1st Edition
Languages
Python
Tools
Neo4j
Concepts
Mobile Application Development
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Author (1)
Estelle Scifo
Estelle Scifo
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Estelle Scifo

Estelle Scifo possesses over 7 years experience as a data scientist, after receiving her PhD from the Laboratoire de lAcclrateur Linaire, Orsay (affiliated to CERN in Geneva). As a Neo4j certified professional, she uses graph databases on a daily basis and takes full advantage of its features to build efficient machine learning models out of this data. In addition, she is also a data science mentor to guide newcomers into the field. Her domain expertise and deep insight into the perspective of the beginners needs make her an excellent teacher.
Read more about Estelle Scifo

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Introducing the Pregel API

Neo4j allows you to write plugins: following some API, you can write code in Java, which can then be used from Cypher through, for instance, the CALL statement, given that the JAR file containing your code has been placed in the plugins folder and your code has been properly annotated so that Neo4j can find the relevant information. That’s how APOC and GDS are implemented. Thanks to the Pregel API, we can extend not only Neo4j but GDS itself, leveraging its main features.

In this section, we will cover these GDS features and the basic principles behind the Pregel API.

GDS’s features

GDS allows users to extend it while taking advantage of many common functionalities, such as the following:

  • In-memory projected graph: We won’t have to write code to create a projected graph – we can directly work on an existing projected graph in the GDS graph catalog.
  • Stream/write/mutate procedures: The execution modes are automatically...
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Graph Data Science with Neo4j
Published in: Jan 2023Publisher: PacktISBN-13: 9781804612743
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Estelle Scifo

Estelle Scifo possesses over 7 years experience as a data scientist, after receiving her PhD from the Laboratoire de lAcclrateur Linaire, Orsay (affiliated to CERN in Geneva). As a Neo4j certified professional, she uses graph databases on a daily basis and takes full advantage of its features to build efficient machine learning models out of this data. In addition, she is also a data science mentor to guide newcomers into the field. Her domain expertise and deep insight into the perspective of the beginners needs make her an excellent teacher.
Read more about Estelle Scifo

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