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Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

By : Scifo
4.6 (9)
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Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

4.6 (9)
By: Scifo

Overview of this book

Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data.
Table of Contents (18 chapters)
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1
Section 1: Graph Modeling with Neo4j
5
Section 2: Graph Algorithms
10
Section 3: Machine Learning on Graphs
14
Section 4: Neo4j for Production

Understanding GraphQL APIs by example GitHub API v4

While in the previous section we used Python to build a full web application whose backend database is Neo4j, in this section, we will remove the dependency on Python and build an API directly accessible from the Neo4j server.

When building APIs, a very popular framework is Representational State Transfer (REST). Even though this approach is still possible with a graph database (check, for instance, the gREST project), a different approach is becoming more and more popular GraphQL, a query language for API.

In order to understand GraphQL, we will again use the GitHub API. In previous chapters, we used the REST version (v3). However, v4 uses GraphQL, so we should build a few queries. To do so, we can go to https://developer.github.com/v4/explorer/, which is the traditional GraphQL playground. After providing GitHub login credentials, there is a two-part window; the left panel is where we will write the query, while the...

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