graph and rdf databases context : course of advanced databases prepared by : nassim bahri nabila...

Graph and RDF Databases

Context : Course of Advanced Databases

Prepared by : Nassim BAHRI Nabila HOSNI

February 19th, 2015

Table of contents

I. Introduction :Overview of BIG DATA & NOSQL

II. Graph Databases

III. RDF Databases

IV. Application example

V. Scientific article

VI. Conclusion and Q&A

Introduction

3

Not Only SQL

Storing data inmemory

Distributeddatabases

Introduction : Data Model

4

Documents Databases

(Voldemort, Riak)

Big Table Column

(Hbase, cassandra, Hypertable)

Key-Value

(MongoDB)

Graph Databases

(Neo4J)

Introduction : Data Model

5

Data complexity

Data

size Key-Value Stores

Column Family

Document Databases

Graph Databases

90% of use cases

This is what we are interested

Source : Neo Technology webinar

Graph Databases

What is Graph Database?

A graph database is a databases whose specific purpose is the storage of graph-oriented data structures.

Is simply an object oriented database based on Graph theory.

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Graph Databases

Representation

• Nodes

• Relationships between nodes

• Properties on both

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2

3

1

Name : JohnAge : 43

Name : Google

Type : FordColor : blue

Work inSince : 2013

Graph DatabasesThe power of Graph Databases

Performance Flexibility

Agility8

Graph VS Relational DatabasesRelational Database Modeling

ID Name

1 Larry Page

2 Sergey Brin

3 Larry Elisson

N …

ID Name

1 Google

2 Oracle

… …

N …

PersonID CompanyID Since

1 1 1998

2 1 2001

3 2 2010

Person

Company

WorksIn

SELECT Person.NameFROM Person,Company,WorksInWHERE Company.Name='Google'AND WorksIn.CompanyID=Company.IDAND WorksIn.PersonId=Person.ID;

Google's employees?

Lookup

Lookup

Lookup

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Graph VS Relational DatabasesGraph Database Modeling

Name : Larry Page Name : Google

Name : Sergey Brin

Name : Oracle

Name : Larry Elisson

Person 1

Person 2

Company 1

Company 2

Person 3

WorksIN

WorksIN

WorksInSince : 2001

Since : 2010

Since : 1998

Lookup

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Graph DatabasesGraph storage and graph processing

1. The underlying storage• Some databases use native graph storage,• The other databases use relational database, an object-oriented database,…

2. The processing engine• The nodes are physically connected to each other in database,• index-free adjacency

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Graph DatabasesGraph Database Management System

12Source [1]

Graph Databases : ExampleVisual Modeling

13

Name : JohnAge : 27 FRIEND_OF

Name : SallyAge : 32

Title : Graph DatabasesAuthors : Ian Robinson,

Jim Webber

Since : 01/09/2013

Since : 01/09/2013

On : 02/09/2013Rating : 4

On : 02/03/2013Rating : 5

FRIEND_OF

HAS_READ HAS_READ

Graph Databases : ExampleCreate a simple dataset// Create SallyCREATE (sally:Person { name: 'Sally', age: 32 })

// Create JohnCREATE (john:Person { name: 'John', age: 27 })

// Create Graph Databases bookCREATE (gdb:Book { title: 'Graph Databases', authors: ['Ian Robinson', 'Jim Webber'] })

// Connect Sally and John as friendsCREATE (sally)-[:FRIEND_OF { since: 1357718400 }]->(john)

// Connect Sally to Graph Databases bookCREATE (sally)-[:HAS_READ { rating: 4, on: 1360396800 }]->(gdb)

// Connect John to Graph Databases bookCREATE (john)-[:HAS_READ { rating: 5, on: 1359878400 }]->(gdb) 14

Graph Databases : Example

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Graph Databases : ExampleSimple selection from node:

Query 1 : How old are Sally?MATCH (sally:Person { name: 'Sally' })RETURN sally.age as sally_age

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Graph Databases : ExampleSimple selection from node:

Query 2 : Who are the authors of Graph Databases?MATCH (gdb:Book { title: 'Graph Databases' }) RETURN gdb.authors as authors

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Graph Databases : ExampleSelection using relationship:

Query 3 : Who are sally's friends?MATCH (sally:Person { name: 'Sally' }) MATCH (sally)-[r:FRIEND_OF]-(person) RETURN person.name as sally_friend

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Graph Databases : ExampleSelection using relationship and group function:

Query 4 : What is the average rating of Graph Databases?MATCH (gdb:Book { title: 'Graph Databases' })MATCH (gdb)<-[r:HAS_READ]-()RETURN avg(r.rating) as average_rating

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Graph Databases : ExampleUsing order and limit in query:

Query 5 : Who Read Graph Databases First, Sally or John?MATCH (people:Person) WHERE people.name = 'John' OR people.name = 'Sally'MATCH (people)-[r:HAS_READ]->(gdb:Book { title: 'Graph Databases' })RETURN people.name as first_reader ORDER BY r.on LIMIT 1

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Graph Databases : ExampleVisual Modeling

21

Name : JohnAge : 27 FRIEND_OF

Name : SallyAge : 32

Name : AlainAge : 19

Since : 01/09/2013

Since : 01/09/2013

FRIEND_OF

FRIEND_OF

Since : 01/11/2014

Graph Databases : ExampleCompleting our schema// Create AlainCREATE (alain:Person { name: 'Alain', age: 19 })

// Connect Sally and Alain as friendsMATCH (alain:Person { name: 'Alain' })MATCH (sally:Person { name: 'Sally' })CREATE (sally)-[:FRIEND_OF { since: 1358818400 }]->(alain)

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Alain

Sally

John

GDB book

Graph Databases : ExampleNode / relationship navigation:

Query 6 : Which is shared between Alain and John Friend?MATCH (alain:Person { name: 'Alain' })MATCH (john:Person { name: 'John' })MATCH (alain)-[:FRIEND_OF]-(person)-[:FRIEND_OF]-(john)RETURN person.name as friend

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Graph Databases : ExampleUpdate node’s properties:

Query 7 : Change Alain name to LarryMATCH (n { name: 'Alain' })SET n.name = 'Larry'

Query 8 : Remove propertyMATCH (n { name: 'Larry' })SET n.name = NULL

Query 9 : Add propertyMATCH (n { name: 'John' })SET n += { hungry: TRUE , position: 'Entrepreneur' }

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RDF DatabasesThe principle of the web

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HTTP Request

HTTP Response

URL : http://website.com

Communication protocol : HTTP

Representation language : HTML

RDF DatabasesChanging status

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URL URI IRI

Uniform ResourceLocator

Uniform ResourceIdentifier

International ResourceIdentifier

http://website.com http://animals.com#lion http://الحيوانات.tn#lion

RDF DatabasesW3C Standards

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Identification

Representation

Query Reasoning

RDF Databases

RDFResource

Description

Framework

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means

: pages, person, animalsIdea,…

: attributes, characteristics,Relationship,…

: Model, language and syntax to build description

RDF DatabasesData model & syntax

Description : (Subject, Predicate, object)

“example : doc.html is created by John and belongs to the music theme”

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Doc.html is created by JohnDoc.html belongs to music theme

RDF DatabasesData model & syntax

(Subject, Predicate, object)

(Vertex, edge, Vertex)

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John

Doc.html

Music

Author

Theme

RDF DatabasesLabeled graph with URI and literals

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http://www.website.com/john#me

http://www.website.com/doc.html

Music

http://www.website.com/schema#author

http://www.website.com/schema#theme

RDF DatabasesRDF SyntaxesXML, Turtle, TriG, JSON-LD,…

Turtle syntax

@prefix rdf : <http://www.w3.org/1999/02/22-rdf-syntax-ns#>@prefix site : <http://www.website.com/schema#><http://www.website.com/doc.html>

site:author <http://www.website.com/john#me>;site:theme "Music".

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RDF DatabasesSPARQL Protocol And RDF Query Language

• Syntax similar to SQL

SELECT data,FROM data sourceWHERE { conditions }

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RDF DatabasesSPARQL Protocol And RDF Query Language

?x rdf:type ex:PersonGet all person

SELECT ?subject ?property ?valueWHERE { ?subject ?property ?value }

Get the full Graph database

SELECT ?x WHERE{ ?x rdf:type ex:Person . ?x :name ?name . }

Get all person who have a name 34

RDF DatabasesSPARQL Protocol And RDF Query Language

Declaring prefixes

PREFIX esen : <http://esen.tn#>SELECT ?studentWHERE {

?student esen:registeredAt ?x.}

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RDF DatabasesSPARQL Protocol And RDF Query Language

Optional pattern

PREFIX foaf : <http://xmlns.com/foaf/0.1>SELECT ?person ?nameWHERE {

?person foaf:homepage <http://john.info> .OPTIONAL { ?person foaf:name ?name .}

}name : unbound

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RDF DatabasesSPARQL Protocol And RDF Query Language

Union

PREFIX foaf : <http://xmlns.com/foaf/0.1>SELECT ?nameWHERE {

?person foaf:name ?name .{

{?person foaf:homepage <http://john.info> .} UNION {?person foaf:homepage <http://paul.info> .}

}} 37

RDF DatabasesSPARQL Protocol And RDF Query Language

Minus

PREFIX ex : <http://website.com#>SELECT ?personWHERE {

{ ?person rdf:type ?type }MINUS { ?person rdf:type ex:student }

}

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RDF DatabasesUse case : rich snippets Google

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<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Person"> My name is <span property="v:name">Pierre Dumoulin</span>. My personal homepage: <a href="http://www.example.com" rel="v:url" > www.homepage.com</a>I’m living is <span rel="v:address" typeof="v:address"> <span property="v:street-address">12 street name</span> <span property="v:locality">city name</span> ,<span property="v:region">XY</span> <span property="v:postal-code">12345</span>. <span></div>

Application example (RDF)Data storage# Default graph (stored at http://example.org/foaf/aliceFoaf) @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" .. _:b foaf:mbox <mailto:bob@work.example> .. _:a foaf:mbox <mailto:alice@work.example> .

QueryPREFIX foaf: <http://xmlns.com/foaf/0.1/>SELECT ?nameFROM <http://example.org/foaf/aliceFoaf>WHERE { ?x foaf:name ?name }

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NameAlice

Result

Application example (Neo4J)Question : Who is older, Sally or John?

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Name : JohnAge : 27 FRIEND_OF

Name : SallyAge : 32

Name : AlainAge : 19

Since : 01/09/2013

Since : 01/09/2013

FRIEND_OF

FRIEND_OF

Since : 01/11/2014

Application example (Neo4J)Who is older, Sally or John?

MATCH (people:Person)WHERE people.name = 'John' OR people.name = 'Sally'RETURN people.name as oldestORDER BY people.age DESCLIMIT 1

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Scientific article

Title : Querying RDF Data from a Graph Database PerspectiveBook title : The Semantic Web: Research and ApplicationsPages : 346-360Online ISBN : 978-3-540-31547-6Series Volume : 3532Publisher : Springer Berlin HeidelbergCopyright : 2005Authors : Renzo Angles

Claudio Gutierrez

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Scientific articleMODEL LEVEL DATA

COMPLEXITYCONNECTIVITY TYPE OF DATA

Network physical simple high homogeneous

Relational logical simple low homogeneous

Semantic user simple/medium high homogeneous

Object-O logical/physical complex Medium heterogeneous

XML logical medium medium heterogeneous

RDF logical medium high heterogeneous

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Table 1 : Summary of comparison among different database models

Scientific articlePROPERTY G G+ GraphLog Gram GraphDB Lorel F-G

Adjacent nodes +/- √ √ √ +/- √ +/-

Adjacent edges +/- √ √ √ +/- √ +/-

Degree of a node X √ √ x ? X x

Path √ √ √ √ √ √ √

Fixed-length Path √ √ √ √ √ √ √

Distance between two nodes X √ √ X ? x x

Diameter x √ √ X ? x X

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Table 2 : Support of some graph database query languages for the example graph properties

Scientific articlePROPERTY RQL SeRQL RDQL Triple N3 Versa RxPath

Adjacent nodes +/- +/- +/- +/- +/- +/- X

Adjacent edges +/- +/- +/- +/- X x X

Degree of a node +/- x x x x x X

Path x x x x X x +/-

Fixed-length Path +/- +/- +/- +/- +/- X +/-

Distance between two nodes x x x x x x X

Diameter x x x x x x x

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Table 3 : Support of some current RDF query languages for some example graph properties

Conclusion

• Using Graph database for storing data in graph form or in hierarchical tree structure.

• Graph database : Performance, Agility, Flexibility

• The shortest path

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Thanks for your attention

Bibliography[1] Ian Robinson, Jim Webber, and Emil Eifrem.«Graph Databases».O’REILLY, 2013.[2] Serge Miranda, Fabien Gandon. «Des Bases de Données à Big Data». Course at Nice Sophia university, MOOC, 2015.[3] Michel Domenjoud. «Bases de données graphes : un tour d’horizon». Available on <http://blog.octo.com/bases-de-donnees-graphes-un-tour-dhorizon> (consulted 18/02/2015).[4] Neo4J community. «Cypher Query Language». Available on <http://neo4j.com/developer/data-modeling/> (consulted 18/02/2015).[5] Frank Manola, Eric Miller, Brian McBride. «RDF 1.1 Primer». Available on <http://www.w3.org/TR/2014/NOTE-rdf11-primer-20140225/> (consulted 18/02/2015).[6] Eric Prud'hommeaux, Andy Seaborne. «SPARQL Query Language for RDF». Available on <http://www.w3.org/TR/rdf-sparql-query/> (consulted 18/02/2015).[7] Neo4J community. «Introduction to graph databases webinar». Available on <http://www.neo4j.org/learn/videos_webinar> (consulted 18/02/2015).

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