Graph databases are not widespread in the development communities, although they are a swiss-army knife for problem that the relational model can't simple handle well. In this talk we're gonna talk for a few minutes about the graph theory, see how to easily solve a few relational anti-patterns with graph databases and how to integrate them in your next project. At the end we will take a practical look to OrientDB, "next big thing" of the NoSQL ecosystem, through its PHP Data Mapper, "Orient".

1. Graph databases:
time for serious stuff
David Funaro
Alessandro Nadalin
1

2. Agenda
•Theory
•When to use a 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
A GraphDB is a database that use the
graph as its primary data structure
11

13. ... when to use 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 is a graph
23

17. a tree is a graph
24

18. parent_id is a graph
25

19. Solve decision problems

20. Maximum flow

21. Given a dataset, calculate how to best organize it
maximum flow

22. travelling salesman problem

23. The pizza guy needs to deliver on A, B,C.

24. Decision base on distance, traffic, time and so on.

25. Shortest path

26. Identify "special" nodes of the graph

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 ... why graphDB?
36

30. 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

31. where is the difference ?
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 step example
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 local cost is O(k) = Constant
44

39. Local cost
The local cost 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 can implicity 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. 50

45. NoSPARQL
http://blog.acaro.org/entry/somebody-is-going-to-hate-me-nosparql

46. community that is building and feeding the GraphDB ecosystem
NoSPARQL
ThinkerPop
Stack
Databases

47. 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/

48. a data flow Framework using Process Graph
provide a collection of "pipes" that are
connected togheter to from processing
pipelines

49. a graph-based programming language.
a Turing-Complete graph-base programming language
that compiles Gremlin syntax down to Pipes

50. a REST-full graph shell.
Allow blueprints graph to be exposed
through a RESTful API (HTTP)

51. What's hot

52. OrientDB

53. Glossary
RID
<10:05>
Cluster Position
CLASS
59

54. Main features

55. Inheritance

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. Traversal

60. SELECT FROM fellas WHERE any() traverse(0,-1) ( @rid = [Michelle @rid] )
68

61. SELECT FROM fellas WHERE any() traverse(0,2) ( @rid = [Michelle @rid] )

62. SQL synthax

63. beyond SQL

64. SELECT FROM authors WHERE book.title = ...

65. ACID

66. speaks JSON

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. Double Protocol

69. HTTP
Universal

70. HTTP
Easy to interact with

71. binary
Blazing fast

72. on-record SELECTs

73. SELECT FROM cats

74. SELECT FROM 11:0

75. SELECT FROM [11:0,11:1]

76. SELECT FROM [11:0,12:0]

77. stress-free setup

78. 2 Mb

79. ./orient/bin/server.sh
94

80. in-memory DB

81. or disk-persisted

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 = PHP Library to work with OrientDB
https://github.com/congow/Orient
101

87. Data Mapper
Query Builder
HTTP Binding

88. HTTP Binding

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. apart from ->query($SQL)

91. ->get|delete|postClass($class)

92. ->post|delete|put|getDocument($rid)

93. ...and much more!
(connect, disconnect, ...)

94. Query Builder

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. Data Mapper

98. namespace PolandPHPConEntity;
use CongowOrientODMMapperAnnotations as ODM;
/**
* @ODMDocument(class="Person")
*/
class Speaker
{
/**
* @ODMProperty( type="string")
*/
protected $name;
public function setName($name)
{
$this->name = $name;
}

99. Domain Driven Design

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. $speakers = $repo->findAll();

105. $speaker = $repo->find($rid);

106. $criteria = array('Name' => 'Martin');
$lornas = $repo->findBy($criteria);

107. $criteria = array(
'Name' => 'Martin',
'last_name' => 'Fowler'
);
$lornaJ = $repo->findOneBy($criteria);

108. https://github.com/doctrine/common/tree/master/lib/Doctrine/Common/Persistence
134

109. 135

110. That’s all, folks!
David Funaro 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/