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Home > Data > Database Administration > Neo4j Cookbook
Neo4j Cookbook
Neo4j Cookbook

Neo4j Cookbook: Harness the power of Neo4j to perform complex data analysis over the course of 75 easy-to-follow recipes

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eBook May 2015 226 pages 1st Edition
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Neo4j Cookbook

Chapter 2. Connecting to Neo4j

In this chapter, we will cover the following recipes:

  • Accessing Neo4j from the command line using the Neo4j shell
  • Accessing Neo4j from the command line using curl
  • Accessing Neo4j from the Java libraries
  • Accessing Neo4j using the Java REST bindings
  • Mapping Neo4j to Java-annotated classes using Spring Data Neo4j
  • Accessing the embedded Neo4j from Python
  • Accessing Neo4j from Python using the REST bindings
  • Annotate the Python object model to the Neo4j graph database
  • Accessing the embedded Neo4j from Ruby
  • Accessing Neo4j from Ruby using the REST bindings
  • Accessing Neo4j from Scala
  • Accessing Neo4j from .NET
  • Accessing Neo4j from PHP
  • Accessing Neo4j from Node.js

Introduction

In this chapter, we will take a look at the various ways in which you can connect to Neo4j. Neo4j is a high-performance graph database, which gives the flexibility to access it from various languages and in different options. The two most popular ones being the embedded option and the server mode. The embedded mode gives the user the power to embed it within the application to get high performance with low latency, whereas the server mode gives the user the flexibility to access the services using the REST endpoint, making it (virtually) language-neutral. Let's briefly discuss both the modes:

  • The embedded mode: The Neo4j graph database can be directly embedded into the application, making it look like a single binary executable file. It can be accessed using the appropriate Java binding.
  • The server mode: The Neo4j graph database can run in the server mode, in which its services can be accessed from any host, using the REST endpoints that are exposed by the Neo4j server...

Accessing Neo4j from the command line using the Neo4j shell

Often, you will find yourself in the need of firing simple Neo4j operations, either to create a node or delete a node, query the total number of nodes, or to poke into the Neo4j graph database. With Neo4j, this can easily be done through the command-line interface.

Neo4j can also be accessed from the command line like the Unix shell. Although it is less likely that this mode is going to be used in production, it's very handy when it comes to development and debugging. In this recipe and the next recipe, we will explore the two ways to connect to Neo4j from the command-line interface, which are using the Neo4j shell and curl.

In this recipe, we will learn how to connect to Neo4j from the command-line interface.

Getting ready

Neo4j ships with a command-line client called the Neo4j shell. The Neo4j shell is a fully featured interactive shell that supports line editing, history, and various help options. Using man followed by a Neo4j...

Accessing Neo4j from the command line using curl

Curl is a popular command-line tool used to access and transfer the data using various protocols. Because the REST API uses the HTTP protocol to transfer data, the curl tool becomes a command-line tool that is used to access the REST API, which is exposed by the Neo4j graph database server.

In this recipe, we will learn how to access the Neo4j graph database server using curl.

Getting ready

The service root endpoint by default is http://host:port/db/data/, which can also be seen through the web interface by opening the endpoint URL in the browser. You will see something similar to this:

Getting ready

How to do it...

Let's access the Neo4j graph database server using the REST endpoint via the curl command-line tool:

  1. Start the Neo4j graph database server using the following command:
    $ ./neo4j start

    To check whether things are running fine, open http://localhost:7474/db/data/ in a browser.

    The browser sends the text/HTML as the accepted encoding, but in curl...

Accessing Neo4j from the Java libraries

Java is at the sweet spot when it comes to the Neo4j language bindings, as Neo4j itself is implemented in Java. Most of the other language bindings, which access Neo4j as an embedded application, have been built on Java. In this recipe, we will take a look at the various ways to connect to Neo4j in Java.

In this recipe, we will learn how to access Neo4j in the most powerful way.

Getting ready

Neo4j can be embedded into the Java application, which can provide you with high-performance query results. Follow these steps to embed it into the application:

  1. Neo4j JAR files can be found in the lib directory of the source code. Include all the JAR files present in this directory. Alternatively, the JAR files are also present in the Maven repository.
  2. Add Neo4j to the build path and also add it as a dependency. Detailed information on this can be found at http://docs.neo4j.org/chunked/milestone/tutorials-java-embedded-setup.html.

How to do it...

Let's create our...

Accessing Neo4j using the Java REST bindings

Neo4j can also be accessed using the Java REST bindings, which allows it to be accessed from remote nodes easily. In this recipe, we will take a look at the ways of accessing Neo4j from Java using the REST bindings.

Getting ready

The Neo4j REST interface provides an easy way to access Neo4j graph database remotely.

Follow these instructions to go through this recipe:

Start the Neo4j graph database server using the following command:

$ ./neo4j start

To check whether the REST interface is running fine, open http://localhost:7474/db/data/ in a browser.

How to do it...

This problem can be dealt with in two ways, which are described as follows:

Developing your own Neo4j REST client

There are many REST Java client libraries that can be utilized to write your own REST API client for Neo4j. The bad part is that you have to deal with all the possible scenarios and error cases. One example is using the Jersey client, which is shown in the following code:

final String...

Mapping Neo4j to Java-annotated classes using Spring Data Neo4j

Spring Data Neo4j can increase the productivity of Java by many folds when dealing with Neo4j. It provides a Plain Old Java Objects (POJO) based programming model that significantly reduces the amount of boilerplate code needed to develop Neo4j-based applications. It helps the developer to think in terms of an object-oriented approach, which is easily extendible to add new data models and enhance existing ones (properties, entities, and relationships).

In this recipe, we will learn the use of Neo4j with Spring Data Neo4j.

Getting ready

To step through this recipe, we will need the following configurations to be set before:

The following is the Maven configuration:

<dependency>
  <groupId>org.springframework.data</groupId>
  <artifactId>spring-data-neo4j</artifactId>
  <version>2.3.1.RELEASE</version>
</dependency>
<repositories>
  <repository>
    <id>spring-neo4j...

Introduction

In this chapter, we will take a look at the various ways in which you can connect to Neo4j. Neo4j is a high-performance graph database, which gives the flexibility to access it from various languages and in different options. The two most popular ones being the embedded option and the server mode. The embedded mode gives the user the power to embed it within the application to get high performance with low latency, whereas the server mode gives the user the flexibility to access the services using the REST endpoint, making it (virtually) language-neutral. Let's briefly discuss both the modes:

  • The embedded mode: The Neo4j graph database can be directly embedded into the application, making it look like a single binary executable file. It can be accessed using the appropriate Java binding.

  • The server mode: The Neo4j graph database can run in the server mode, in which its services can be accessed from any host, using the REST endpoints that are exposed by the Neo4j server and various...

Accessing Neo4j from the command line using the Neo4j shell

Often, you will find yourself in the need of firing simple Neo4j operations, either to create a node or delete a node, query the total number of nodes, or to poke into the Neo4j graph database. With Neo4j, this can easily be done through the command-line interface.

Neo4j can also be accessed from the command line like the Unix shell. Although it is less likely that this mode is going to be used in production, it's very handy when it comes to development and debugging. In this recipe and the next recipe, we will explore the two ways to connect to Neo4j from the command-line interface, which are using the Neo4j shell and curl.

In this recipe, we will learn how to connect to Neo4j from the command-line interface.

Getting ready

Neo4j ships with a command-line client called the Neo4j shell. The Neo4j shell is a fully featured interactive shell that supports line editing, history, and various help options. Using man followed by a Neo4j command...

Accessing Neo4j from the command line using curl

Curl is a popular command-line tool used to access and transfer the data using various protocols. Because the REST API uses the HTTP protocol to transfer data, the curl tool becomes a command-line tool that is used to access the REST API, which is exposed by the Neo4j graph database server.

In this recipe, we will learn how to access the Neo4j graph database server using curl.

Getting ready

The service root endpoint by default is http://host:port/db/data/, which can also be seen through the web interface by opening the endpoint URL in the browser. You will see something similar to this:

How to do it...

Let's access the Neo4j graph database server using the REST endpoint via the curl command-line tool:

  1. Start the Neo4j graph database server using the following command:

    $ ./neo4j start

    To check whether things are running fine, open http://localhost:7474/db/data/ in a browser.

    The browser sends the text/HTML as the accepted encoding, but in curl, we...

Accessing Neo4j from the Java libraries

Java is at the sweet spot when it comes to the Neo4j language bindings, as Neo4j itself is implemented in Java. Most of the other language bindings, which access Neo4j as an embedded application, have been built on Java. In this recipe, we will take a look at the various ways to connect to Neo4j in Java.

In this recipe, we will learn how to access Neo4j in the most powerful way.

Getting ready

Neo4j can be embedded into the Java application, which can provide you with high-performance query results. Follow these steps to embed it into the application:

  1. Neo4j JAR files can be found in the lib directory of the source code. Include all the JAR files present in this directory. Alternatively, the JAR files are also present in the Maven repository.

  2. Add Neo4j to the build path and also add it as a dependency. Detailed information on this can be found at http://docs.neo4j.org/chunked/milestone/tutorials-java-embedded-setup.html.

How to do it...

Let's create our first...

Accessing Neo4j using the Java REST bindings

Neo4j can also be accessed using the Java REST bindings, which allows it to be accessed from remote nodes easily. In this recipe, we will take a look at the ways of accessing Neo4j from Java using the REST bindings.

Getting ready

The Neo4j REST interface provides an easy way to access Neo4j graph database remotely.

Follow these instructions to go through this recipe:

Start the Neo4j graph database server using the following command:

$ ./neo4j start

To check whether the REST interface is running fine, open http://localhost:7474/db/data/ in a browser.

How to do it...

This problem can be dealt with in two ways, which are described as follows:

Developing your own Neo4j REST client

There are many REST Java client libraries that can be utilized to write your own REST API client for Neo4j. The bad part is that you have to deal with all the possible scenarios and error cases. One example is using the Jersey client, which is shown in the following code:

final String...

Mapping Neo4j to Java-annotated classes using Spring Data Neo4j

Spring Data Neo4j can increase the productivity of Java by many folds when dealing with Neo4j. It provides a Plain Old Java Objects (POJO) based programming model that significantly reduces the amount of boilerplate code needed to develop Neo4j-based applications. It helps the developer to think in terms of an object-oriented approach, which is easily extendible to add new data models and enhance existing ones (properties, entities, and relationships).

In this recipe, we will learn the use of Neo4j with Spring Data Neo4j.

Getting ready

To step through this recipe, we will need the following configurations to be set before:

The following is the Maven configuration:

<dependency>
  <groupId>org.springframework.data</groupId>
  <artifactId>spring-data-neo4j</artifactId>
  <version>2.3.1.RELEASE</version>
</dependency>
<repositories>
  <repository>
    <id>spring-neo4j...

Accessing the embedded Neo4j from Python

Python is getting increasingly popular nowadays, and, in this recipe, we will learn how to connect to the Neo4j embedded graph server from the Python client.

Getting ready

Embedded Neo4j is an excellent binding module available in Python to access the Neo4j embedded database. The following steps describe the use of this module:

  1. Install the JPype Python module, as shown in the following command:

    $ sudo apt-get install python-jpype

    It can also be installed from the source available at http://sourceforge.net/projects/jpype/files/JPype/.

  2. Install Neo4j embedded using either pip or easy_install, as follows:

    $ pip install neo4j-embedded
$ easy_install neo4j-embedded

How to do it...

Perform the following steps in order to access Neo4j from Python:

  1. Let's create our first node using the following code:

    import neo4j
db_obj =  neo4j.GraphDatabase(DB_PATH)
# All write operations on graph database happens in transaction
with db_obj.transaction:
  node = db_obj.node(name...

Accessing Neo4j from Python using the REST bindings

The REST interface is widely used and in this recipe, we will learn how to access Neo4j from Python using the REST Bindings.

Getting ready

The py2neo module (http://py2neo.org/2.0/) is an excellent Python binding module used to connect to the Neo4j REST API server.

The py2neo module can be installed from both pip and easy_install, as shown here:

$ pip install py2neo
$ easy_install py2neo

How to do it...

The following steps will get you started with this recipe:

  1. First, we will create our first node assuming the default installation, as shown in the following code:

    from py2neo import neo4j
graph = neo4j.GraphDatabaseService(ENDPOINT_URL)
graph.create(node(name="A")

  2. Next, let's create our first relation using the py2neo module:

    from py2neo import neo4j
graph = neo4j.Graph(ENDPOINT_URL)
graph.create(node(name="A"),
             node(name="B"))
rel(1, "PLAYS WITH", 2)
rel(2, "FATHER OF", 1)

Annotate the Python object model to the Neo4j graph database

In this recipe, we will learn how to map the Python object model to the Neo4j graph database server.

Getting ready

Neomodel is an excellent binding module used for mapping an object model to the Neo4j graph database, thinking in terms of objects and further enhancing properties, relationships, and so on.

Neomodel can be installed from both via pip and easy_install:

$ pip install neomodel
$ easy_install neomodel

Now, set the location of Neo4j via the environment variable:

export NEO4J_REST_URL="http://<ip:port>/db/data"

How to do it...

Let's create our first relationship model using Neomodel, as shown in the following code:

from neomodel import (StructuredNode, StringProperty, IntegerProperty,RelationshipTo, RelationshipFrom)
class Movie(StructuredNode):
    name = StringProperty(unique_index=True, required=True)
    actors = RelationshipFrom('Actor', 'ACTED_IN')
class Actor(StructuredNode):
    name = StringProperty(unique_index...
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Description

If you are already using Neo4j in your application and want to learn more about data analysis or database graphs, this is the book for you. This book also caters for your needs if you are looking to migrate your existing application to Neo4j in the future. We assume that you are already familiar with any general purpose programming language and have some familiarity with Neo4j.

Who is this book for?

If you are already using Neo4j in your application and want to learn more about data analysis or database graphs, this is the book for you. This book also caters for your needs if you are looking to migrate your existing application to Neo4j in the future. We assume that you are already familiar with any general purpose programming language and have some familiarity with Neo4j.

What you will learn

  • Access the Neo4j graph database from any language of your choice, whether it is Java, Python, Scala, or .Net
  • Understand how to migrate data from different types of data stores such as SQL and NoSQL with ease
  • Utilize and learn data modeling best practices
  • Use and mine social data, whether it be from Facebook, Twitter, or LinkedIn
  • Deal with geospatial data and build services such as bounding box queries and nearest point of interest
  • Visualize Neo4j graphs by customizing available tools or writing your own tool
  • Scale Neo4j with up to billions of nodes and edges

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : May 28, 2015
Length: 226 pages
Edition : 1st
Language : English
ISBN-13 : 9781783287260
Category :
Data
Languages :
Java
Concepts :
Database Administration
Tools :
Neo4j

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Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
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Product feature icon DRM FREE - Read whenever, wherever and however you want
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Product Details

Publication date : May 28, 2015
Length: 226 pages
Edition : 1st
Language : English
ISBN-13 : 9781783287260
Category :
Data
Languages :
Java
Concepts :
Database Administration
Tools :
Neo4j

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Table of Contents

11 Chapters
1. Getting Started with Neo4j Chevron down icon Chevron up icon
1. Getting Started with Neo4j
Introduction
Single node installation of Neo4j over Linux
Single node installation of Neo4j over Windows
Single node installation of Neo4j over Mac OS X
Creating your first graph with Neo4j
Importing data from the CSV format to Neo4j
Importing data from RDBMS to Neo4j
Importing data from the Geoff format to Neo4j
Importing data from OrientDB to Neo4j
Importing data from InfiniteGraph to Neo4j
Importing data from the DEX graph database to Neo4j
Common configurations of Neo4j
Running multiple instances of Neo4j over a single machine
Building Neo4j from the source
2. Connecting to Neo4j Chevron down icon Chevron up icon
2. Connecting to Neo4j
Introduction
Accessing Neo4j from the command line using the Neo4j shell
Accessing Neo4j from the command line using curl
Accessing Neo4j from the Java libraries
Accessing Neo4j using the Java REST bindings
Mapping Neo4j to Java-annotated classes using Spring Data Neo4j
Accessing the embedded Neo4j from Python
Accessing Neo4j from Python using the REST bindings
Annotate the Python object model to the Neo4j graph database
Accessing the embedded Neo4j from Ruby
Accessing Neo4j from Ruby using the REST Bindings
Accessing Neo4j from Scala
Accessing Neo4j from .NET
Accessing Neo4j from PHP
Accessing Neo4j from Node.js
3. The Cypher Query Language Chevron down icon Chevron up icon
3. The Cypher Query Language
Introduction
Creating your first node and relationship using Cypher
Querying nodes and relationships using Cypher
Deleting data from Neo4j using the Cypher query
Boolean operators with Cypher
Changing the order of results with Cypher
Limiting and skipping results with Cypher
Regular expressions with Cypher
Aggregation with Cypher
Combining results with Cypher
Finding paths in Cypher along with their shortest route
4. Data Modeling and Leveraging with Neo4j Chevron down icon Chevron up icon
4. Data Modeling and Leveraging with Neo4j
Introduction
Data modeling with Neo4j – moving away from traditional SQL
Aggregate versus connected data models
Creating a binary search tree with Neo4j
Healthcare data modeling with Neo4j
Travel data modeling with Neo4j
Social data modeling with Neo4j
Retail data modeling with Neo4j
5. Mining the Social Treasure Chevron down icon Chevron up icon
5. Mining the Social Treasure
Introduction
Finding mutual friends with Neo4j
Finding friends of friends with Neo4j
Activity streaming with Neo4j
Finding user similarity with Neo4j
Network reachability with Neo4j
6. Developing Location-based Services with Neo4j Chevron down icon Chevron up icon
6. Developing Location-based Services with Neo4j
Introduction
Installing the Neo4j Spatial extension
Importing the Esri shapefiles
Importing the OpenStreetMap files
Importing data using the REST API
Creating a point layer using the REST API
Finding geometries within the bounding box
Finding geometries within a distance
Finding geometries within a distance using Cypher
7. Visualization of Graphs Chevron down icon Chevron up icon
7. Visualization of Graphs
Introduction
Visualization using the Neo4j console
Viewing your graph with Linkurious
The Neo4j graph with Gephi
Visualization with Neoeclipse
8. Industry Usages of Neo4j Chevron down icon Chevron up icon
8. Industry Usages of Neo4j
Introduction
Healthcare with Neo4j
The social networking industry with Neo4j
The travel industry with Neo4j
E-commerce with Neo4j
9. Neo4j Administration and Maintenance Chevron down icon Chevron up icon
9. Neo4j Administration and Maintenance
Introduction
Deploying Neo4j over the Amazon EC2 Cloud
Deploying Neo4j over the Heroku Cloud
Deploying Neo4j over the Microsoft Azure Cloud
Backups with Neo4j
Upgrading Neo4j to the latest version
Neo4j's remote debugging setup
Configuring secure access to your Neo4j instance
10. Scaling Neo4j Chevron down icon Chevron up icon
10. Scaling Neo4j
Introduction
A bulk upload of the initial large dataset
The high availability setup
Handling high read loads
Handling high write loads
Optimizing the Cypher query for performance
Index Chevron down icon Chevron up icon
Index

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RAG-Driven Generative AI
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Hands-On Reinforcement Learning with Python
Hands-On Reinforcement Learning with Python
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LLM Engineer's Handbook
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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(3 Ratings)
5 star 0%
4 star 66.7%
3 star 0%
2 star 0%
1 star 33.3%
CS Oct 10, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
If you have previous knowledge on making graph database applications using Neo4j, this book will help you increase your skills with good examples it have. You can learn to scale your application to more nodes, and lot more with these examples. One of the good books for enhancing your Neo4j skills.
Amazon Verified review Amazon
Sumit Pal Oct 08, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This is a pretty comprehensive book - that almost covers everything you would like to know about Neo4J and how to solve business and technical problems with it. This is one place the reader can go and have an extremely very good idea about Neo4J its capabilities and featuresFor anyone working with Neo4J this is the single reference one needs to go to solve their problems.Most of the examples work as it is out of the box. I have worked pretty extensively with GraphDBs and I love Neo4J.This book could have been 5* had it covered the following - 1) Comparisons with other GraphDBs in the market. 2) Performance improvements 3) Some more treatment of the Basic Graph Algorithms - like TSP and Graph Centrality 4) How Neo4J achieves its speed in terms of the internal data structures2) and 4) are pretty advanced topics.Overall I would highly recommend this book for anyone who wants to start and get going with Neo4J and then run with itEnjoyed the book
Amazon Verified review Amazon
Andrew F. Lee Nov 22, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
If you could not figure this information out from the documentation, the book is not going to help.Pro Tip: can be used as kindling.
Amazon Verified review Amazon

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About the author

Profile icon Ankur Goel
Ankur Goel
Ankur Goel has been passionate about software development for a long time. He is particularly interested in exploring upcoming technologies in the areas of big data, artificial intelligence, and machine learning. He started his career with CDAC High Performance Computing Lab, where he worked on the PARAM series of supercomputers and built real-world use cases around them. He has been working for start-up companies and research labs for most of his career. He also enjoys working with start-ups that are in the stealth mode stage, and helps them with their technology stack. He lives in the beautiful city of Chandigarh, India, with his pretty wife and cute newborn daughter.
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