Meetup di Luglio

1. Graph Analytics sulla Community #Aperitech

2. Marco Liberati
@dej611
Enrico Risa
@wolf4ood

3. Graphs
G = (V,E)

4. Simple Graph
A B
Edge
Vertex

5. Directed Graph
A B
Edge
Vertex

6. Element Can Have Labels
Person City
Lives

7. Name : John
Surname : Reese
Element Can Have Properties
Person City
Lives

8. since : 2007
Name : Steve
Surname : Murphy
Name : RomeName : John
Surname : Reese
Property Graph
Person
City
Person
Lives
Knows
Lives

9. Why Graph and Why Now?
● Everything is Connected
● Relationships are important
● Natural way of modeling data
KV Column Document Relational Graph
Data and Relationship Complexity

10. Graphs are trendy

11. Graph Use Cases
● Recommendation Engine
● Fraud Detection
● Social Network
● Network Analysis
● GeoSpatial Analysis
● Master Data Management
● Internet of Things
● …..

12. Graph Technologies
AWS Neptune

13. Graph Standards
- Gremlin
- PGQL
- Open Cypher
- GQL
- G-CORE

14. Meetup Data Model
- Meetup
- User
- Tag
- Event
- Users join meetups
- Users participate to single events
- Meetups have tags
- Meetups have an organizer

15. ER Model

16. Property Graph Model

17. A Graph Database creates the
relationship just once
(when the edge is created)
VS
RDBMS computes the
relationship every time
you query a database

18. With a RDBMS
traversing a relationship require JOINS
that are computed at query time
With a Graph Database, the
traversing time is
not affected by database size!

19. #Aperitech graph
-[:LOAD]->

20. ● Graph database (written in Java)
● Schema-less
● Cypher query language
○ ASCII art as query
○ Pattern matching

21. (user :USER { name: “Marco” })
Cypher Node
Variabile
Label
Property
Value

22. -[action:TAGGED {when: 130… }] ->
Cypher Link/Relationship
Variabile
Label
Property
Value

23. MATCH (u:User)-[r:JOINED]->(m:Meetup)
WHERE u.name = “Marco”
RETURN u, r, m;
Cypher Query
Applica delle
condizioni alle
variabili
dichiarate sopra
Con return si
descrive cosa
mettere su
ogni riga dei
risultati
PATTERN MATCHING:
Descrivi uno o piu percorsi del
grafo in ASCII art.
Tutti i percorsi che rispettano il
criterio di forma (e non solo…)
verranno presi da Neo4J a questo
punto

24. Get all users Get all meetups

25. Get all users Get all meetups

26. Get all meetups and their tags

27. Get all meetups and their tags

28. Show top 5 Meetups by popularity

29. Show top 5 Meetups by popularity

30. Show top 10 users by participation

31. Show top 10 users by participation

32. Find all Meetup events “Enrico R.” didn’t go!

33. Find all Meetup events “Enrico R.” didn’t go!

34. Analytics mean Trend. Let’s find out
Show GraphRM meetup trends

35. Analytics mean Trend. Let’s find out
Show GraphRM meetup trends

36. As a community manager I’m curious to know who
are the members that join a group but won’t come

37. As a community manager I’m curious to know who
are the members that join a group but won’t come

38. As a community manager I’m curious to know who
are the members that join a group but won’t come

39. Build a recommendation engine with

40. What meetup should we suggest to tommaso based
on topics he likes?

41. What meetup should we suggest to tommaso based
on topics he likes?

42. What meetup should we suggest to tommaso based
on topics he likes?

43. What other metric can we use to recommend to
tommaso a new meetup?

44. What other metric can we use to recommend to
tommaso a new meetup?

45. What other metric can we use to recommend to
tommaso a new meetup?
tommaso

46. What other metric can we use to recommend to
tommaso a new meetup?
tommaso

47. Let’s go deeper:
● let’s look at the people he met at events
● and based on that see at what events these
people are going
● then see what meetups these events belong to
● And weight everything

51. Grazie :)
Marco Liberati
@dej611
Enrico Risa
@wolf4ood

52. Cypher cheatsheet
https://neo4j.com/docs/cypher-refcard/current/