Mastering Neo4jA Graph Database

Data Masters

Special Thanks To…

Planet Linux Caffehttp://planetlinuxcaffe.com

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John Jadvani954-527-0090

Short bio about me… Andrew Simkovsky 15 years working with database technology

Oracle, MySQL/MariaDB, SQL Server, Postgres

Redis, MongoDB, CouchDB, Cassandra, Neo4j Worked across many industries

Consulting, Retail, Telecommunications, Energy

Data, Marketing, Gaming, Health care

DBTekPro

www.dbtekpro.com

andrew@dbtekpro.com@asimkovsky

Graph Databases

Graph Databases

What is a graph database? Based on graph theory Data is stored as “nodes”, and

relationships as “edges” Nodes have attributes. Relationships have attributes

Relational vs Graph

Relational Relationships are used to join entities together to get

results Data integrity is enforced through constraints

Graph Relationships are considered data Can easily “walk” from node to node using

relationships Can “walk” the graph in multiple directions in

parallel

Relational Model

actor movieactor_movie

1, Keanu Reeves2, Carrie-Ann Moss3, Lawrence Fishburne

actor_idname

movie_idtitlerelease_date

actor_idmovie_idrole

1, The Matrix2, The Matrix Reloaded3, The Matrix Revolutions

1, 1, Neo1, 2, Neo1, 3, Neo2, 1, Trinity2, 2, Trinity2, 3, Trinity3, 1, Morpheus3, 2, Morpheus3, 3, Morpheus

Graph Model

The Matrix

The Matrix 2

The Matrix 3

Keanu Reeves

Carrie-Ann Moss

Lawrence

Fishburne

Graph Model - Detailed

type: Actorname: “Keanu Reeves”

type: Movietitle:

“Matrix” :ACTS_IN

type: Role, role: “Neo”

NodeRelationship

Property Value

Property

Path

Example Graphs

Example Graphs

Example Graphs

Graph Databases – Examples Uses

Social relationships

Actor / movie relationships

Medicine interactions

Just some of the many possibilities!

CypherA Graph Query Language

Queries

START[MATCH][WITH][WHERE]RETURN

[ORDER BY] [SKIP] [LIMIT]

Starting node(s)

Matching pattern (except properties)

Filter on properties

Properties to return

Further conditions / calculations

Query Example

START user=node:nodeIndexName(name={“Bob”})MATCH (user)-[:FRIEND]->(friend)WITH user, count(friend) as friendsWHERE friends > 10RETURN friend.nameORDER BY friend.nameLIMIT 100

Query Parts

START user=node:nodeIndexName(name={“Bob”})made-

up identifi

er

object type

node property identifier

index name

property

value

Query Parts

MATCH (user)-[:FRIEND]->(friend)

node node

relationship definition(including direction)

Another made-up identifier

Query Parts

WITH user, count(friend) as friends

grouping node

calculation

alias

Query Parts

WHERE friends > 10

property filter

Query Parts

RETURN friend.nameORDER BY friend.nameLIMIT 100

Query Example – All Together

START user=node:nodeIndexName(name={“Bob”})MATCH (user)-[:FRIEND]->(friend)WITH user, count(friend) as friendsWHERE friends > 10RETURN friend.nameORDER BY friend.nameLIMIT 100

This will return all nodes where they are friends with Bob, and that Bob has more than 10 friends, but limit to the first 100 found.

Query Example – Matching

START user=node:nodeIndexName(name={“Bob”})MATCH (user)-[:FRIEND {since: “2001-01-01”} ]->(friend)RETURN friend.name

Since relationships have properties, we can search on them too!!

Creating Data

CREATE [UNIQUE]*[SET | DELETE | FOREACH]*[RETURN [ORDER BY][SKIP][LIMIT]]

Creating Data - Examples

CREATE (n {name: “Bob”})

made-up identifier

again

property

value

Creating Data - Examples

CREATE (b {name: “Bob”}), (m {name: “Mary”}), (b)-[:KNOWS]->(m)

Creates two nodes with a relationship between them.This is called creating a path.

Creating Data - Examples

You can combine queries with create options! This allows you to create parts of the graph starting from a particular node (or nodes)!

START b=node:nodeIndexName(name={“Bob”}), m=node:nodeIndexName(name={“Mary”})MATCH (b)-[:KNOWS]->(m)CREATE (b)-[:LOVES]->(m)

Live Demo!

Where Do I Get It?

www.neo4j.org

Thank You For Coming!

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Check out my blog and forums:www.dbtekpro.com

After Party!!Miller’s Ale House

Miracle Mile