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Home > Data > Databases > Neo4j Graph Data Modelling
Neo4j Graph Data Modelling
Neo4j Graph Data Modelling

Neo4j Graph Data Modelling: Design efficient and flexible databases by optimizing the power of Neo4j

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Neo4j Graph Data Modelling

Chapter 2. Modeling Flights and Cities

We looked at what graphs are and what domains they might be suited for. Now, it is time to dive deeper into concepts that are related to graph databases and how we can go ahead and create our data in a graph. In this chapter, we will look at:

  • How graphs can be used outside the social context modeling flights and cities for creating an itinerary
  • Adding nodes, labels, properties, relationships, uniqueness constraints, and indices

Before we dive deep into modeling, we recommend that you download the code samples that you will need to run the examples in this chapter. The code can be downloaded from https://github.com/maheshlal2910/neo4j_graph_data_modelling.

Graphs are more than social

Often, when we talk about graph databases and their most suited use cases, people point out that social networks are a good use case for graphs. While this is true, in a way, it pigeonholes graph databases. Graph databases are versatile tools that can be used to model various domains and problems. In this book, we pick up a nonsocial example—travel, and explain how we can model data for various subsystems that would be used in a travel website using Neo4j.

Designing a system to get a travel itinerary

The travel domain is interesting in terms of data modeling challenges. Throughout this book, we will be modeling systems that work together in a website that can be used for planning flight travel. Travelers would like to look at the options for an itinerary before booking any particular set of flights, especially if there is no direct flight from the traveler's current city to the destination city. Normally, an itinerary includes total duration, layover duration, and the number of hops it takes to reach the destination. We cannot, however, derive the itinerary without modeling cities and flights, which brings us to our first data modeling problem.

Introduction to modeling flights and cities

If we were to explain the problem of cities and the number of flights between them, we could start with drawing cities as nodes. In case two cities have two or more direct flights between them, we connect those two cities with an undirected relationship...

Introduction to modeling nodes and relationships

We looked at the data models in Figure 2.2. Without delving into technical details, we can say that "A person can fly from New York to London on carrier X". With this statement, we can start exploring possibilities in which this data can be modelled. A preliminary approach would be to mark cities as nodes and flights as relationships, as shown in the following figure:

Introduction to modeling nodes and relationships

Figure 2.3: A preliminary model with flights and cities—the property graph

This might seem to be a fair model, however, there are a few problems with the approach. Relationships, in graphs, are used to model how the entities' nodes are related to each other. As discussed earlier, flights are one of the two core entities in our model. Flights don't relate cities to each other, instead, they are a means to get from one city to another. Modeling flights as relationships, can work out in presenting a flight plan, but if we have to allow flight bookings in...

Using Cypher to operate on Neo4j

Operations on Neo4j are generally performed using a query language called Cypher. Cypher is a simple, expressive, SQL-like language that allows us to create, read, update, and delete nodes and relationships in Neo4j. To retrieve data from a Neo4j store, we write Cypher queries, which specify which nodes and which relationships to traverse.

Cypher is a declarative graph query language. Each query is built of clauses and each clause pipes/feeds the next clause with data. Cypher is designed to be a humane query language suitable for developers and operations professionals, and hence, elegantly combines simplicity, expressiveness. and efficiency.

Note

There are ways in which you can, and should influence efficiency from a user perspective, particularly by writing queries that utilize and are sympathetic to the graph structure. However, each query is planned, costed, and executed by the query engine that tries to optimize queries. This allows users to focus on better...

Creating cities in Neo4j

We will model cities as nodes, as shown in Figure 2.4, with the city's name and country as properties. Cities should have unique names. For this, we can add a constraint before we start creating cities in our graph.

The query is as follows:

neo4j-sh (?)$ CREATE CONSTRAINT ON (city: City) ASSERT city.name IS UNIQUE;

The output of the preceding query is as shown:

+-------------------+
| No data returned. |
+-------------------+
Constraints added: 1

This adds a constraint on all nodes that will henceforth be created with the label City to have a unique name property. The city in (city: City) is a placeholder, like a variable, for any node with label City. Note that the addition of a uniqueness constraint is idempotent—it can be repeated multiple times without throwing an error or changing the constraint after it first gets added.

It's a good practice to add a uniqueness constraint, like we did, before we start adding nodes that have a particular label. While...

Graphs are more than social

Often, when we talk about graph databases and their most suited use cases, people point out that social networks are a good use case for graphs. While this is true, in a way, it pigeonholes graph databases. Graph databases are versatile tools that can be used to model various domains and problems. In this book, we pick up a nonsocial example—travel, and explain how we can model data for various subsystems that would be used in a travel website using Neo4j.

Designing a system to get a travel itinerary

The travel domain is interesting in terms of data modeling challenges. Throughout this book, we will be modeling systems that work together in a website that can be used for planning flight travel. Travelers would like to look at the options for an itinerary before booking any particular set of flights, especially if there is no direct flight from the traveler's current city to the destination city. Normally, an itinerary includes total duration, layover duration, and the number of hops it takes to reach the destination. We cannot, however, derive the itinerary without modeling cities and flights, which brings us to our first data modeling problem.

Introduction to modeling flights and cities

If we were to explain the problem of cities and the number of flights between them, we could start with drawing cities as nodes. In case two cities have two or more direct flights between them, we connect those two cities with an undirected relationship, as...

Introduction to modeling nodes and relationships

We looked at the data models in Figure 2.2. Without delving into technical details, we can say that "A person can fly from New York to London on carrier X". With this statement, we can start exploring possibilities in which this data can be modelled. A preliminary approach would be to mark cities as nodes and flights as relationships, as shown in the following figure:

Figure 2.3: A preliminary model with flights and cities—the property graph

This might seem to be a fair model, however, there are a few problems with the approach. Relationships, in graphs, are used to model how the entities' nodes are related to each other. As discussed earlier, flights are one of the two core entities in our model. Flights don't relate cities to each other, instead, they are a means to get from one city to another. Modeling flights as relationships, can work out in presenting a flight plan, but if we have to allow flight bookings in the future, then we need to...

Using Cypher to operate on Neo4j

Operations on Neo4j are generally performed using a query language called Cypher. Cypher is a simple, expressive, SQL-like language that allows us to create, read, update, and delete nodes and relationships in Neo4j. To retrieve data from a Neo4j store, we write Cypher queries, which specify which nodes and which relationships to traverse.

Cypher is a declarative graph query language. Each query is built of clauses and each clause pipes/feeds the next clause with data. Cypher is designed to be a humane query language suitable for developers and operations professionals, and hence, elegantly combines simplicity, expressiveness. and efficiency.

Note

There are ways in which you can, and should influence efficiency from a user perspective, particularly by writing queries that utilize and are sympathetic to the graph structure. However, each query is planned, costed, and executed by the query engine that tries to optimize queries. This allows users to focus on better...

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Description

If you are a developer who wants to understand the fundamentals of modeling data in Neo4j and how it can be used to model full-fledged applications, then this book is for you. Some understanding of domain modeling may be advantageous but is not essential.

Who is this book for?

If you are a developer who wants to understand the fundamentals of modeling data in Neo4j and how it can be used to model full-fledged applications, then this book is for you. Some understanding of domain modeling may be advantageous but is not essential.

What you will learn

  • Translate a problem domain from a whiteboard to your database
  • Make design decisions based on the nature of data and how it is going to be used
  • Use Cypher to create and query data
  • Evolve your database in stages
  • Optimize the performance of your application with data design
  • Design paradigms to ensure flexibility, ease of querying, and performance
  • Move from an existing model to a new model without losing consistency

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Publication date : Jul 27, 2015
Length: 138 pages
Edition : 1st
Language : English
ISBN-13 : 9781784397302
Category :
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Concepts :
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Publication date : Jul 27, 2015
Length: 138 pages
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Language : English
ISBN-13 : 9781784397302
Category :
Data
Concepts :
Databases
Tools :
Neo4j

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Table of Contents

10 Chapters
1. Graphs Are Everywhere Chevron down icon Chevron up icon
1. Graphs Are Everywhere
Graphs in mathematics
The property graph model
Storage – native graph storage versus non-native graph storage
Reasons to use graph databases
What to use a graph database for
Choosing Neo4j for exploring graph databases
The structure of the book
Summary
2. Modeling Flights and Cities Chevron down icon Chevron up icon
2. Modeling Flights and Cities
Graphs are more than social
Designing a system to get a travel itinerary
Introduction to modeling nodes and relationships
Using Cypher to operate on Neo4j
Creating cities in Neo4j
Indices
Adding flights to Neo4j
Traversing relationships
Summary
3. Formulating an Itinerary Chevron down icon Chevron up icon
3. Formulating an Itinerary
Creating an itinerary from flights and cities
Business logic should lie in code
Summary
4. Modeling Bookings and Users Chevron down icon Chevron up icon
4. Modeling Bookings and Users
Building a data model for booking flights
A simple model of the bookings ecosystem
Modeling bookings in an RDBMS
Creating bookings and users in Neo4j
Queries to find journeys and bookings
Queries to find the booking history of a user
Summary
5. Refactoring the Data Model Chevron down icon Chevron up icon
5. Refactoring the Data Model
Capturing information about hotels at airports
Modeling airports and hotels
Extracting airport information from flights
Reasons for not migrating using a single query
Adding hotels to airports
Fetching hotels
Summary
6. Modeling Communication Chains Chevron down icon Chevron up icon
6. Modeling Communication Chains
Capturing traveler reviews for hotels
A model for reviews and comments
Adding reviews to Neo4j
Adding comments to Neo4j
Summary
7. Modeling Access Control Chevron down icon Chevron up icon
7. Modeling Access Control
Controlling access for content change
Modeling hierarchies
Modeling access control groups and employees
Querying the data model to find what is accessible to an employee
Summary
8. Recommendations and Analysis of Historical Data Chevron down icon Chevron up icon
8. Recommendations and Analysis of Historical Data
Recommending cities to travelers
Recommending hotels to travelers
Analysis of the historical data
Summary
9. Wrapping Up Chevron down icon Chevron up icon
9. Wrapping Up
There is no correct model
Further reading and exploration
What to watch out for while using Neo4j
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
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G. A. Patino Aug 17, 2015
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If you are looking for a book to give you a quick overview of the capabilities of graph databases, or how to think in terms of developing a graph database this is a good book to start. The explanations on how to decide whether something should be a node or a property are clear, and the example of a flight and hotel booking application make them very relatable to a wide array of users. The way business considerations are integrated in the modelling decisions will be great guidance for somebody getting into this field.It is also good if you want to get the basics of Neo4j very quickly, as the book is only 109 pages long. However, I think that only people with some programming experience and that are comfortable deducing language syntax rules from example code will be able to do it. This is because the authors rely too much on the declarative nature of Neo4j/Cypher and don't go into any details about syntax rules.The book could have benefited from an initial chapter explaining the Neo4j ecosystem better, as is not clear how to switch from the shell to the browser, or in what conditions to use each. Also, as mentioned above, an explanation of the language syntax would have greatly improved he accessibility of the text. There is no mention either of saving and loading databases either in the shell or the browser. Finally, expanding the last chapter to explain the main limitations of Neo4j, as opposed to graph databases, and what other open-source packages could be used to complement the language would have been very useful.
Amazon Verified review Amazon

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About the author

Profile icon Mahesh K Lal
Mahesh K Lal
Mahesh Lal is a developer who has experience with various technologies. In 2011, while working on a social network for a client, he discovered the power of graphs, specifically Neo4j. Since then, he has been working with multiple clients across various domains for modeling their data as a graph. Currently working for ThoughtWorks, India, he is trying to help his clients look at their search problems in the form of a graph.
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