Graph databases and a use case with Drupal.

1. Drupal &
Graphs

3. • The “problem”
• Graph databases
• Neo4J
• Examples
• Drupal & graph
• Future

4. The problem

5. too many joins

6. query is unknown

7. tricks only graphs can
solve

8. 1M nodes, ~50 rel/node
Depth RDBMS Neo4J
Returned
records
2 0.016 0.01 ~2’500
3 30.267 0.168 ~110’000
4 1543.505 1.359 ~600’000
5 unfinished 2.132 ~800’000

9. Such speed
So wow
Very graph

10. Examples

12. • Business Intelligence
• Content Management
• Fraud Detection
• Geo
• Graph Search
• Identity & Access
Management
• Impact Analysis
• Logistics
• Master Data Management
• Network and Data Center
Management
• Product Catalog
• Recommendation Engine
• Resource Authorization &
Access Control
• Social Network

13. http://gist.neo4j.org/

14. Graph databases

15. Node Node
Relationship

16. Jim Lisa
:COOK_FOR

17. Jim:PERSON Lisa:PERSON
:COOK_FOR
city: London
gender: male
city: San Francisco
gender: female
meal: Jalfrezi
score: 9.8
user_index::uid::3 user_index::uid::8

18. Jim:PERSON Lisa:PERSON
:COOK_FOR
city: London
gender: male
city: San Francisco
gender: female
meal: Jalfrezi
score: 9.8
:LOVE
user_index::uid::3 user_index::uid::8

19. hop
hop
hop
?
N hops

20. Start

22. designing graph db

23. John
Visit
Paris
Eiffel Louvre
VisitVisit

24. John
Visit
Paris
Eiffel Louvre
HasHas

25. John
Attended
ParisEiffel Louvre
Include
Travel
Include
City

26. 1973
Jan JuneMarch
12 245
1986
3 11

27. Node
Term
Italy
Node!
{t:Italy}
vs
:HAS_TERM
:TERM_NAME

31. Neo4J

32. Server:
embedded - server mode
low latency network
low level API REST API
better control better scaling
JVM only languages

33. Backend

34. db
labels nodes
propsrels

35. Node
inUse nextRelId nextPropId

36. Relationship
inUse
firstNode
secondNode
relType
firstPrevRelId
firstNextRelId
secondPrevRelId
secondNextRelId
nextPropId

37. Disks
Record files
File system cache
Object cache
Traversal API Cypher
Transaction log
Transaction management
Core API

38. Core API

39. Traversal API

40. Cypher

41. MATCH (n)-[r]->(m)

42. • MATCH (n)-[r]->(m)
• MATCH (n:USER)-[:EAT]->(m:FOOD)
• MATCH p = (n)--(m)
• MATCH (n{name:’Jim’})-[r]->(m)
• MATCH (o)-->(n)<-[*1..3]-(m)
• MATCH [:TRAVEL{by:”bus”}]->(n)

43. START n=node(*)

44. • START n=node(12)
• START n=node({12, 3, 7})
• START n=node:user_index(uid=“12”)
• START n=node(3), m=node(12)

45. • WHERE n.name = ‘Jim’
• WHERE n.has(“name”)
• WITH count(n) AS all WHERE all > 10

46. • RETURN n
• RETURN collect(n), o.name
• RETURN length(p)

47. I want a good party this Friday.
Show me my foaf who has at least 20 close
friends - so I can avoid awkward parties.
And they don’t know my ex.

48. START n=node(12)
MATCH
p = (n)-[:FRIEND*]->(m),
(m)<-[:FRIEND*1..2]-(o)
WHERE
any(p IN collect(o) WHERE p.name != ‘Liz’)
WITH count(o) AS total
WHERE total >= 20
RETURN m.name, p, total, collect(o)

49. CREATE
(jim:USER{hair:’green’}),
(erica:USER{hair:’brown’}),
jim-[:REPORTS_TO{type:’TPS’}]->erica;
!
MATCH (n) SET n.name = ‘Walter’;
!
MATCH (n) DELETE n;

50. Drupal <3 Neo4J

51. https://drupal.org/
project/neo4j_connector

52. Neo4JNeo4J-PHP
Neo4J!
Drupal!
Connector
REST API

53. • Pluggable indexes
• Dynamic labels, properties and relationships
• “smart” indexing

54. DEMO

55. Future?
• Cypher builder
• Views integration
• More field support
• Embedded graph display

56. Thank You
Questions?