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Graph db: time for serious stuff @ codemotion 23/03/2012

This document discusses graph databases, focusing on their structure, advantages, and use cases. It explains the concepts of vertices and edges, emphasizes when to use graph databases, and compares them with traditional databases. Additionally, it covers specific graph database technologies such as OrientDB and provides examples of their implementations and benefits.

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Graph databases: time for serious stuff David Funaro Alessandro Nadalin 1
Agenda •Theory •When to use a graph? •Why graphDB? •The graphDB community •OrientDB •Orient PHP library 2
Essential (Theory) G = (V, E) Vertex Graph Edge A 3
Binary Relation Hates A B Itchy Scratchy 4
Binary Relation Edge A B Vertex Vertex 4
Graph B E F A D G 5
Undirected Graph B E A D F Example: Friendship 6
Directed Edge Edge A B Vertex Vertex 7
Directed Graph A B A F D Example: Followee 8
Path B E F A D G 9
Path A B D G E F 10
Graph -> GraphDB A GraphDB is a database that use the graph as its primary data structure 11
... when to use a graph ?
Recommendations lives in John type shows Mr Fun Cinema B Bean loca tion lik Rome es shows Cinema A location type Thriller Se7en s ho ws location Milan Cinema C 14
Recommendations lives in John x x x Fun type Mr Bean shows Cinema B loca tion lik ✓ Rome es type shows ✓ Cinema A location ✓ ✓ shows x x ✓ Thriller Se7en location Milan Cinema C 22
Your data is a graph 23
a tree is a graph 24
parent_id is a graph 25
Solve decision problems
Maximum flow
Given a dataset, calculate how to best organize it maximum flow
travelling salesman problem
The pizza guy needs to deliver on A, B,C.
Decision base on distance, traffic, time and so on.
Shortest path
Identify "special" nodes of the graph
Given your dataset, organize some clusters Are there some nodes which cannot belong to a cluster? They probably have some properties different from the average
Given your dataset, organize some clusters Are there some nodes which cannot belong to a cluster? They probably have some properties different from the average ACHTUNG! TERRORISTEN!
but ... why graphDB? 36
Representing a Graph in: http://www.slideshare.net/slidarko/problemsolving-using-graph-traversals-searching- scoring-ranking-and-recommendation# ✓ Relational Database (mysql, oracle) ✓ Document Oriented DB (mongodb, couchdb) ✓ XML Database (MarkLogic, eXist-db) 37
where is the difference ? 38
GraphDB A graph database is any storage system that provides index-free adjacency. http://www.slideshare.net/slidarko/problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation
Step by step example Given a list of people, find their homepages 40
Tree-based DB WAY David Funaro put in the Search Engine 2 find 3 1 http://davidfunaro.com 41
Tree-based DB WAY David Funaro The cost to find Search Engine friend HP put in the a single 2 grows as the friends HP tables grows find 3 1 http://davidfunaro.com 41
GraphDB WAY 1 get the embedded information(index) www.odino.org it’s like that the GraphDB has an additional information (the ancor <a>) 42
GraphDB WAY The Anchor work as a local index to reach the document = index-free adjacency <a href=”http://odino.org”> Alessandro Nadalin </a> 43
Local cost The local cost is O(k) = Constant 44
Local cost The local cost is O(k) = Constant 45
Local cost Thus, as the graph grows in size, the cost of a local step remain the same 46
any database can implicity represent a graph BUT only a graph database make the graph structure explicit 47
Benchmark Deph RDBMS Graph 1 100ms 30ms • 1 Million Vertex • 4 Million Edge 2 1000ms 500ms • Scale Free Tolopogy 3 10000ms 3000ms • MySql VS Neo4J 4 100000m 50000ms s • Both Hash and BTree 5 N/A 100000m s 48 http://markorodriguez.com/2011/02/18/mysql-vs-neo4j-on-a-large-scale-graph-traversal/
How ? PREFIX geospecies: <http://rdf.geospecies.org/ont/ geospecies#> PREFIX lycopodiophyta: <http://lod.geospecies.org/phyla/Pc2> PREFIX door_county: <http://sws.geonames.org/5250768/> PREFIX dcterms: <http://purl.org/dc/terms/> SELECT DISTINCT ?family_name ?canonicalName ?commonName ? identifier ?wikipedia_url WHERE { ?x geospecies:hasFamilyName ?family_name; geospecies:hasCanonicalName ?canonicalName; geospecies:hasCommonName ?commonName; dcterms:identifier ?identifier; geospecies:inPhylum lycopodiophyta:; geospecies:isUSDA_ExpectedIn door_county:. OPTIONAL { ?x geospecies:hasCommonName ?commonName; geospecies:hasWikipediaArticle ?wikipedia_url} } ORDER BY ?family_name ?canonicalName 49
50
NoSPARQL http://blog.acaro.org/entry/somebody-is-going-to-hate-me-nosparql
community that is building and feeding the GraphDB ecosystem NoSPARQL ThinkerPop Stack Databases
data model and their implementation Blueprints is a collection of interfaces, implementations, ouplementations, and test suites for the property graph data model. Blueprints is analogous to the JDBC, but for graph databases. https://github.com/tinkerpop/blueprints/wiki/
a data flow Framework using Process Graph provide a collection of "pipes" that are connected togheter to from processing pipelines
a graph-based programming language. a Turing-Complete graph-base programming language that compiles Gremlin syntax down to Pipes
a REST-full graph shell. Allow blueprints graph to be exposed through a RESTful API (HTTP)
What's hot
OrientDB
Glossary RID <10:05> Cluster Position CLASS 59
Main features
Inheritance
class Vehicle class Car class Bike
class Vehicle class Car class Bike SELECT FROM Vehicle WHERE owner = 1:1
class Vehicle class Car class Bike can return records of class Bike or Car
Traversal
SELECT FROM fellas WHERE any() traverse(0,-1) ( @rid = [Michelle @rid] ) 68
SELECT FROM fellas WHERE any() traverse(0,2) ( @rid = [Michelle @rid] )
SQL synthax
beyond SQL
SELECT FROM authors WHERE book.title = ...
ACID
speaks JSON
{ "schema": { "name": "Address" }, "result": [{ "@type": "d", "@rid": "#13:0", "@version": 6, "@class": "Address", "type": "Residence", "street": "Piazza Navona, 1", "city": "#14:0", "nick": "Luca2" }, { ... ...
Double Protocol
HTTP Universal
HTTP Easy to interact with
binary Blazing fast
on-record SELECTs
SELECT FROM cats
SELECT FROM 11:0
SELECT FROM [11:0,11:1]
SELECT FROM [11:0,12:0]
stress-free setup
2 Mb
./orient/bin/server.sh 94
in-memory DB
or disk-persisted
Supports standards Supports standards 97
•Inheritance •Traversal •SQL-like syntax •ACID OrientDB •Speak JSON •Double protocol •on-record Select •ThinkerPop Compliant
Language Bindings http://code.google.com/p/orient/wiki/ProgrammingLanguageBindings 99
Orient = PHP Library to work with OrientDB https://github.com/congow/Orient 101
Data Mapper Query Builder HTTP Binding
HTTP Binding
use CongowOrient; use CongowOrientFoundationBinding; $driver   = new OrientHttpClientCurl(); $orient   = new Binding($driver, '127.0.0.1', '2480', 'admin', 'admin', 'demo'); $response = $orient->query("SELECT FROM Address"); $output   = json_decode($response->getBody()); foreach ($output->result as $address) {   var_dump($address->street); }
apart from ->query($SQL)
->get|delete|postClass($class)
->post|delete|put|getDocument($rid)
...and much more! (connect, disconnect, ...)
Query Builder
use CongowOrientQuery; $query = new Query(); $query->from(array('users'))->where('username = ?', "admin"); echo $query->getRaw();  // SELECT FROM users WHERE username = "admin"
   $query->select(array('name', 'username', 'email'), false)     ->from(array('12:0', '12:1'), false)     ->where('any() traverse ( any() like "%danger%" )')     ->orWhere("1 = ?", 1)     ->andWhere("links = ?", 1)     ->limit(20)     ->orderBy('username')     ->orderBy('name', true, true)     ->range("12:0", "12:1");   SELECT name, username, email    FROM [12:0, 12:1]    WHERE any() traverse ( any() like "%danger%" )   OR 1 = "1" AND links = "1"    ORDER BY name, username    LIMIT 20    RANGE 12:0 12:1
Data Mapper
namespace PolandPHPConEntity; use CongowOrientODMMapperAnnotations as ODM; /** * @ODMDocument(class="Person") */ class Speaker {     /**      * @ODMProperty( type="string")      */     protected $name;     public function setName($name)     {         $this->name = $name;     }
Domain Driven Design
{ "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "David Coallier" }, { ... ...
{ "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "David Coallier" }, { ... ... $david = $mapper->hydrate(json_decode($speaker));
{ "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "Martin Fowler" }, { ... ... $david instanceOf PolandPHPConEntitySpeaker
Repository Pattern $repo = $manager->getRepository('Speaker')
$speakers = $repo->findAll();
$speaker = $repo->find($rid);
$criteria = array('Name' => 'Martin'); $lornas = $repo->findBy($criteria);
$criteria = array( 'Name' => 'Martin', 'last_name' => 'Fowler' ); $lornaJ = $repo->findOneBy($criteria);
https://github.com/doctrine/common/tree/master/lib/Doctrine/Common/Persistence 134
135
That’s all, folks! David Funaro Alessandro Nadalin @ingdavidino @_odino_ http://davidfunaro.com http://odino.org 136
Credits http://www.flickr.com/photos/sayamindu/5677281218/sizes/l/in/photostream/ http://farm1.static.flickr.com/182/471383865_79d04aec36_o.png http://farm1.static.flickr.com/134/318947873_12028f1b66_b.jpg http://www.flickr.com/photos/atomdocs/3275758118/sizes/o/in/photostream/ http://www.flickr.com/photos/pattipics/5229478393/sizes/o/in/photostream/ http://www.flickr.com/photos/kongharald/366597251/sizes/o/in/photostream/ http://www.everaldo.com/ http://www.flickr.com/photos/tusnelda/6140792529/sizes/l/in/photostream/ http://www.flickr.com/photos/mondi/5368644355/sizes/l/in/photostream/ http://www.flickr.com/photos/jayneandd/4191106566/sizes/l/in/photostream/ http://www.flickr.com/photos/jooon/2093253534/sizes/l/in/photostream/ http://www.flickr.com/photos/bluedharma/89186151/sizes/o/in/photostream/ http://www.flickr.com/photos/exfordy/2747089295/sizes/l/in/photostream/ http://www.flickr.com/photos/nostri-imago/3137422976/sizes/o/in/photostream/ http://www.flickr.com/photos/fionasjournal/379587818/sizes/z/in/photostream/ http://www.flickr.com/photos/nperlapro/1297392267/ http://www.flickr.com/photos/fastphive/28428808/sizes/m/in/photostream/ http://www.flickr.com/photos/rnugraha/2003147365/sizes/o/in/photostream/ http://www.flickr.com/photos/zigazou76/4412946911/sizes/l/in/photostream/ http://www.flickr.com/photos/greatnet/4667555436/sizes/l/in/photostream/ http://www.flickr.com/photos/mnsc/2768391365/sizes/l/in/photostream/ http://www.flickr.com/photos/christmaswithak/4675962453/sizes/l/in/photostream/ http://www.amazon.com/Trainspotting-Irvine-Welsh/dp/0393314804 http://www.flickr.com/photos/franconadalin59/5778176872/sizes/l/in/photostream/ http://farm6.static.flickr.com/5176/5474445627_875d621689_b.jpg http://farm3.static.flickr.com/2243/2189435082_a16d3c89ae_b.jpg http://farm3.static.flickr.com/2647/3816311930_ac52cff491_o.jpg http://i130.photobucket.com/albums/p266/feike1977/PES6-4-3-3defencesettings.jpg http://images.usatoday.com/life/_photos/2006/11/30/numb3rs-topper.jpg http://www.flickr.com/photos/jakecaptive/3205277810/sizes/l/in/photostream/

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Graph db: time for serious stuff @ codemotion 23/03/2012

  • 1.
    Graph databases: time forserious stuff David Funaro Alessandro Nadalin 1
  • 2.
    Agenda •Theory •When to usea graph? •Why graphDB? •The graphDB community •OrientDB •Orient PHP library 2
  • 3.
    Essential (Theory) G =(V, E) Vertex Graph Edge A 3
  • 4.
    Binary Relation Hates A B Itchy Scratchy 4
  • 5.
    Binary Relation Edge A B Vertex Vertex 4
  • 6.
    Graph B E F A D G 5
  • 7.
    Undirected Graph B E A D F Example: Friendship 6
  • 8.
    Directed Edge Edge A B Vertex Vertex 7
  • 9.
    Directed Graph A B A F D Example: Followee 8
  • 10.
    Path B E F A D G 9
  • 11.
    Path A B D G E F 10
  • 12.
    Graph -> GraphDB AGraphDB is a database that use the graph as its primary data structure 11
  • 13.
    ... when touse a graph ?
  • 14.
    Recommendations lives in John type shows Mr Fun Cinema B Bean loca tion lik Rome es shows Cinema A location type Thriller Se7en s ho ws location Milan Cinema C 14
  • 15.
    Recommendations lives in John x x x Fun type Mr Bean shows Cinema B loca tion lik ✓ Rome es type shows ✓ Cinema A location ✓ ✓ shows x x ✓ Thriller Se7en location Milan Cinema C 22
  • 16.
    Your data isa graph 23
  • 17.
    a tree isa graph 24
  • 18.
  • 19.
  • 20.
  • 21.
    Given a dataset,calculate how to best organize it maximum flow
  • 22.
  • 23.
    The pizza guyneeds to deliver on A, B,C.
  • 24.
    Decision base ondistance, traffic, time and so on.
  • 25.
  • 26.
  • 27.
    Given your dataset,organize some clusters Are there some nodes which cannot belong to a cluster? They probably have some properties different from the average
  • 28.
    Given your dataset,organize some clusters Are there some nodes which cannot belong to a cluster? They probably have some properties different from the average ACHTUNG! TERRORISTEN!
  • 29.
    but ... whygraphDB? 36
  • 30.
    Representing a Graphin: http://www.slideshare.net/slidarko/problemsolving-using-graph-traversals-searching- scoring-ranking-and-recommendation# ✓ Relational Database (mysql, oracle) ✓ Document Oriented DB (mongodb, couchdb) ✓ XML Database (MarkLogic, eXist-db) 37
  • 31.
    where is thedifference ? 38
  • 32.
    GraphDB A graph database is any storage system that provides index-free adjacency. http://www.slideshare.net/slidarko/problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation
  • 33.
    Step by stepexample Given a list of people, find their homepages 40
  • 34.
    Tree-based DB WAY David Funaro put in the Search Engine 2 find 3 1 http://davidfunaro.com 41
  • 35.
    Tree-based DB WAY David Funaro The cost to find Search Engine friend HP put in the a single 2 grows as the friends HP tables grows find 3 1 http://davidfunaro.com 41
  • 36.
    GraphDB WAY 1 get the embedded information(index) www.odino.org it’s like that the GraphDB has an additional information (the ancor <a>) 42
  • 37.
    GraphDB WAY The Anchor work as a local index to reach the document = index-free adjacency <a href=”http://odino.org”> Alessandro Nadalin </a> 43
  • 38.
    Local cost The localcost is O(k) = Constant 44
  • 39.
    Local cost The localcost is O(k) = Constant 45
  • 40.
    Local cost Thus, as the graph grows in size, the cost of a local step remain the same 46
  • 41.
    any database canimplicity represent a graph BUT only a graph database make the graph structure explicit 47
  • 42.
    Benchmark Deph RDBMS Graph 1 100ms 30ms • 1 Million Vertex • 4 Million Edge 2 1000ms 500ms • Scale Free Tolopogy 3 10000ms 3000ms • MySql VS Neo4J 4 100000m 50000ms s • Both Hash and BTree 5 N/A 100000m s 48 http://markorodriguez.com/2011/02/18/mysql-vs-neo4j-on-a-large-scale-graph-traversal/
  • 43.
    How ? PREFIX geospecies: <http://rdf.geospecies.org/ont/ geospecies#> PREFIX lycopodiophyta: <http://lod.geospecies.org/phyla/Pc2> PREFIX door_county: <http://sws.geonames.org/5250768/> PREFIX dcterms: <http://purl.org/dc/terms/> SELECT DISTINCT ?family_name ?canonicalName ?commonName ? identifier ?wikipedia_url WHERE { ?x geospecies:hasFamilyName ?family_name; geospecies:hasCanonicalName ?canonicalName; geospecies:hasCommonName ?commonName; dcterms:identifier ?identifier; geospecies:inPhylum lycopodiophyta:; geospecies:isUSDA_ExpectedIn door_county:. OPTIONAL { ?x geospecies:hasCommonName ?commonName; geospecies:hasWikipediaArticle ?wikipedia_url} } ORDER BY ?family_name ?canonicalName 49
  • 44.
  • 45.
    NoSPARQL http://blog.acaro.org/entry/somebody-is-going-to-hate-me-nosparql
  • 46.
    community that isbuilding and feeding the GraphDB ecosystem NoSPARQL ThinkerPop Stack Databases
  • 47.
    data model andtheir implementation Blueprints is a collection of interfaces, implementations, ouplementations, and test suites for the property graph data model. Blueprints is analogous to the JDBC, but for graph databases. https://github.com/tinkerpop/blueprints/wiki/
  • 48.
    a data flowFramework using Process Graph provide a collection of "pipes" that are connected togheter to from processing pipelines
  • 49.
    a graph-based programminglanguage. a Turing-Complete graph-base programming language that compiles Gremlin syntax down to Pipes
  • 50.
    a REST-full graphshell. Allow blueprints graph to be exposed through a RESTful API (HTTP)
  • 51.
  • 52.
  • 53.
    Glossary RID <10:05> Cluster Position CLASS 59
  • 54.
  • 55.
  • 56.
    class Vehicle class Car class Bike
  • 57.
    class Vehicle class Car class Bike SELECT FROM Vehicle WHERE owner = 1:1
  • 58.
    class Vehicle class Car class Bike can return records of class Bike or Car
  • 59.
  • 60.
    SELECT FROM fellasWHERE any() traverse(0,-1) ( @rid = [Michelle @rid] ) 68
  • 61.
    SELECT FROM fellasWHERE any() traverse(0,2) ( @rid = [Michelle @rid] )
  • 62.
  • 63.
  • 64.
  • 65.
  • 66.
  • 67.
    { "schema": { "name": "Address" }, "result": [{ "@type": "d", "@rid": "#13:0", "@version": 6, "@class": "Address", "type": "Residence", "street": "Piazza Navona, 1", "city": "#14:0", "nick": "Luca2" }, { ... ...
  • 68.
  • 69.
  • 70.
  • 71.
  • 72.
  • 73.
  • 74.
  • 75.
  • 76.
  • 77.
  • 78.
  • 79.
  • 80.
  • 81.
  • 82.
    Supports standards Supports standards 97
  • 83.
    •Inheritance •Traversal •SQL-like syntax •ACID OrientDB •Speak JSON •Double protocol •on-record Select •ThinkerPop Compliant
  • 84.
    Language Bindings http://code.google.com/p/orient/wiki/ProgrammingLanguageBindings 99
  • 86.
    Orient = PHPLibrary to work with OrientDB https://github.com/congow/Orient 101
  • 87.
  • 88.
  • 89.
    use CongowOrient; use CongowOrientFoundationBinding; $driver  = new OrientHttpClientCurl(); $orient   = new Binding($driver, '127.0.0.1', '2480', 'admin', 'admin', 'demo'); $response = $orient->query("SELECT FROM Address"); $output   = json_decode($response->getBody()); foreach ($output->result as $address) {   var_dump($address->street); }
  • 90.
  • 91.
  • 92.
  • 93.
  • 94.
  • 95.
    use CongowOrientQuery; $query =new Query(); $query->from(array('users'))->where('username = ?', "admin"); echo $query->getRaw();  // SELECT FROM users WHERE username = "admin"
  • 96.
       $query->select(array('name', 'username', 'email'), false)     ->from(array('12:0', '12:1'), false)     ->where('any() traverse ( any() like "%danger%" )')     ->orWhere("1 = ?", 1)     ->andWhere("links = ?", 1)     ->limit(20)     ->orderBy('username')     ->orderBy('name', true, true)     ->range("12:0", "12:1");   SELECT name, username, email    FROM [12:0, 12:1]    WHERE any() traverse ( any() like "%danger%" )   OR 1 = "1" AND links = "1"    ORDER BY name, username    LIMIT 20    RANGE 12:0 12:1
  • 97.
  • 98.
    namespace PolandPHPConEntity; use CongowOrientODMMapperAnnotationsas ODM; /** * @ODMDocument(class="Person") */ class Speaker {     /**      * @ODMProperty( type="string")      */     protected $name;     public function setName($name)     {         $this->name = $name;     }
  • 99.
  • 100.
    { "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "David Coallier" }, { ... ...
  • 101.
    { "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "David Coallier" }, { ... ... $david = $mapper->hydrate(json_decode($speaker));
  • 102.
    { "schema": { "name": "Speaker" }, "result": [{ "@type": "d", "@rid": "#1:0", "@version": 6, "@class": "Speaker", "name": "Martin Fowler" }, { ... ... $david instanceOf PolandPHPConEntitySpeaker
  • 103.
    Repository Pattern $repo =$manager->getRepository('Speaker')
  • 104.
  • 105.
  • 106.
    $criteria = array('Name'=> 'Martin'); $lornas = $repo->findBy($criteria);
  • 107.
    $criteria = array( 'Name' => 'Martin', 'last_name' => 'Fowler' ); $lornaJ = $repo->findOneBy($criteria);
  • 108.
  • 109.
  • 110.
    That’s all, folks! DavidFunaro Alessandro Nadalin @ingdavidino @_odino_ http://davidfunaro.com http://odino.org 136
  • 111.
    Credits http://www.flickr.com/photos/sayamindu/5677281218/sizes/l/in/photostream/ http://farm1.static.flickr.com/182/471383865_79d04aec36_o.png http://farm1.static.flickr.com/134/318947873_12028f1b66_b.jpg http://www.flickr.com/photos/atomdocs/3275758118/sizes/o/in/photostream/ http://www.flickr.com/photos/pattipics/5229478393/sizes/o/in/photostream/ http://www.flickr.com/photos/kongharald/366597251/sizes/o/in/photostream/ http://www.everaldo.com/ http://www.flickr.com/photos/tusnelda/6140792529/sizes/l/in/photostream/ http://www.flickr.com/photos/mondi/5368644355/sizes/l/in/photostream/ http://www.flickr.com/photos/jayneandd/4191106566/sizes/l/in/photostream/ http://www.flickr.com/photos/jooon/2093253534/sizes/l/in/photostream/ http://www.flickr.com/photos/bluedharma/89186151/sizes/o/in/photostream/ http://www.flickr.com/photos/exfordy/2747089295/sizes/l/in/photostream/ http://www.flickr.com/photos/nostri-imago/3137422976/sizes/o/in/photostream/ http://www.flickr.com/photos/fionasjournal/379587818/sizes/z/in/photostream/ http://www.flickr.com/photos/nperlapro/1297392267/ http://www.flickr.com/photos/fastphive/28428808/sizes/m/in/photostream/ http://www.flickr.com/photos/rnugraha/2003147365/sizes/o/in/photostream/ http://www.flickr.com/photos/zigazou76/4412946911/sizes/l/in/photostream/ http://www.flickr.com/photos/greatnet/4667555436/sizes/l/in/photostream/ http://www.flickr.com/photos/mnsc/2768391365/sizes/l/in/photostream/ http://www.flickr.com/photos/christmaswithak/4675962453/sizes/l/in/photostream/ http://www.amazon.com/Trainspotting-Irvine-Welsh/dp/0393314804 http://www.flickr.com/photos/franconadalin59/5778176872/sizes/l/in/photostream/ http://farm6.static.flickr.com/5176/5474445627_875d621689_b.jpg http://farm3.static.flickr.com/2243/2189435082_a16d3c89ae_b.jpg http://farm3.static.flickr.com/2647/3816311930_ac52cff491_o.jpg http://i130.photobucket.com/albums/p266/feike1977/PES6-4-3-3defencesettings.jpg http://images.usatoday.com/life/_photos/2006/11/30/numb3rs-topper.jpg http://www.flickr.com/photos/jakecaptive/3205277810/sizes/l/in/photostream/