Book Image

Learning Neo4j 3.x - Second Edition

By : Jerome Baton
Book Image

Learning Neo4j 3.x - Second Edition

By: Jerome Baton

Overview of this book

Neo4j is a graph database that allows traversing huge amounts of data with ease. This book aims at quickly getting you started with the popular graph database Neo4j. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases along with data modeling techniques for graph databases. You'll gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. Furthermore, you'll also learn to create awesome procedures using APOC and extend Neo4j's functionality, enabling integration, algorithmic analysis, and other advanced spatial operation capabilities on data. Through the course of the book you will come across implementation examples on the latest updates in Neo4j, such as in-graph indexes, scaling, performance improvements, visualization, data refactoring techniques, security enhancements, and much more. By the end of the book, you'll have gained the skills to design and implement modern spatial applications, from graphing data to unraveling business capabilities with the help of real-world use cases.

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Table of Contents (24 chapters)
Title Page
Title Page
Credits
Credits
About the Authors
About the Authors
Acknowledgement
Acknowledgement
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Graph Theory and Databases
Graph Theory and Databases
Introducing Neo4j 3.x and a history of graphs
Definition and usage of the graph theory
Background
The Property Graph model of graph databases
Why use graph databases, or not
Test questions
Summary
2
Getting Started with Neo4j
Getting Started with Neo4j
Key concepts and characteristics of Neo4j
Sweet spot use cases of Neo4j
The features
The license conditions
Installing Neo4j
Using Neo4j in a cloud environment
Sandbox
Using Neo4j in a Docker container
Test questions
Summary
3
Modeling Data for Neo4j
Modeling Data for Neo4j
The four fundamental data constructs
How to start modeling for graph databases
A graph model – a simple, high-fidelity model of reality
Graph modeling – best practices and pitfalls
Test questions
Summary
4
Getting Started with Cypher
Getting Started with Cypher
Writing the Cypher syntax
Key attributes of Cypher
Being crude with the data
Key operative words in Cypher
Syntax norms
More that you need to know
The Cypher refcard
The openCypher project
Summary
5
Awesome Procedures on Cypher - APOC
Awesome Procedures on Cypher - APOC
Installing APOC
Verifying APOC installation
Functions and procedures
My preferred usages 
Several key usages
Test questions
Summary
6
Extending Cypher
Extending Cypher
Building an extension project
Custom aggregators
Unmanaged extensions
Summary
7
Query Performance Tuning
Query Performance Tuning
Explain and profile instructions
Indexes
Rules of thumb
Summary
8
Importing Data into Neo4j
Importing Data into Neo4j
LOAD CSV
Importing from a JSON source
Importing from a JDBC source
Importing from an XML source 
Summary
9
Going Spatial
Going Spatial
What is spatial?
What is so spatial then?
Neo4j spatial
Removing all the geo data
Summary
10
Security
Security
Authentication and authorization
Roles
Users management
Linking Neo4j to an LDAP directory
Configuring Neo4j to use LDAP
Test questions
Summary
11
Visualizations for Neo4j
Visualizations for Neo4j
The power of graph visualizations
Open source visualization libraries
Closing remarks on visualizations - pitfalls and issues
Cytoscape example
Questions and answers
Summary
12
Data Refactoring with Neo4j
Data Refactoring with Neo4j
Preliminary step
Simple changes
Great changes
Consequences
Summary
13
Clustering
Clustering
Why set up a cluster?
Concepts
Building a cluster
Disaster recovery
Summary
14
Use Case Example - Recommendations
Use Case Example - Recommendations
Recommender systems dissected
Using a graph model for recommendations
Specific query examples for recommendations
Business variations on recommendations
Fraud detection systems
Access control systems
Social networking systems
Questions and answers
Summary
15
Use Case Example - Impact Analysis and Simulation
Use Case Example - Impact Analysis and Simulation
Impact analysis systems dissected
Impact simulation in a cost calculation environment
Questions and answers
Summary
16
Tips and Tricks
Tips and Tricks
Reset password
Enabling SSH on a Raspberry Pi
Creating guides for the Neo4j browser
Data backup and restore
Tools
Community projects
Online documentation
Community
More proverbs

About the Reviewers

Taffy Brecknock has worked in the IT industry for more than 20 years. During his career, he has worked as a software developer, managed development teams, and has been responsible for application design and more recently systems architecture.

He has held roles with both public and private sector organizations. While working with the Australian Government, Taffy got first-hand exposure to the use of connected data in law enforcement. After using relational database systems as the data repository, he is experienced in the short comings of using this paradigm to model such systems.

After learning about graph databases, specifically Neo4j, he has become extremely interested in the many different applications of this technology. He feels that there are few problems in today's business world that cannot benefit from being modeled in a graph.

 

 

 

Jose Ernesto Echeverria started working with relational databases in the 90s, and has been working with Neo4j since 2014. He prefers graph databases over others, given their capabilities for real-world modeling and their adaptability to change. As a polyglot programmer, he has used languages such as Java, Ruby, and R with Neo4j in order to solve data management problems of multinational corporations. He is a regular attendee of GraphConnect, OSCON, and RailsConf. When not working, he enjoys spending time with family, road trips, Minecraft projects with his children, as well as reading and drinking craft beers.

 

 

 

Adriano Longo is a freelance data analyst based in the Netherlands with a passion for Neo4j's relationship-oriented data model.

He is specialized in querying, processing, and modeling data with Cypher, R, Python, and SQL and has worked on climate prediction models at UEA's Climatic Research Unit before focusing on analytical solutions for the private sector.

Today, Adriano uses Neo4j and Linkurious.js to explore the complex web of relationships that nefarious actors use to obfuscate their abuse of environmental and financial regulations--making dirty secrets less transparent, one graph at a time.

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