Learn what Neo4j is and why you should use it. Two examples illustrate its utility: a friend-of-a-friend prediction example, and one using flight delays to predict taxi waits at airports.

1. Neo4j Introduction
the basic stuff

2. Agenda
● What / Why
● Learn through an FoF example
● More involved problem: Which airport
performans better
● Advance modeling topics

3. What is it?
A Graph Database

4. A Graph Database

5. Relational Model

6. In Graph

7. Why Graph Database

8. ● Wicked fast on a type of problem
● Scale up independent of amount of data
● Intuitive modeling
● Fun and Freedom (embedded mode)

9. Setup (on a mac)
$> brew update
$> brew install neo4j
$> neo4j start
$> open http://localhost:7474

10. 3 way to use
* Standalone with Cypher *
* Server plugin
* Embedded

11. Cypher
is the way get stuff out from Neo4j graph

12. A FoF example covers
Create
Match
Where
Count
Order by

13. Create node/relationship
create(joe:Person {name: Joe” })
create(sara:Person {name: “Sara” })
create joe-[:knows]->sara

14. Who is Joe’s friend?
MATCH (joe { name: 'Joe' })-[:knows]-(friends)
RETURN joe, friends

15. Joe’s friends of friends
MATCH (joe { name: 'Joe' })-[:knows*2..2]-(fof)
RETURN fof

16. Wait, Joe already knows sara
MATCH (joe { name: 'Joe' })-[:knows*2..2]-(fof)
WHERE NOT(joe-[:knows]-fof)
RETURN fof

17. Who is more likely to be Joe's
friend?
MATCH (joe { name: 'Joe' })-[:knows*2..2]-(fof)
WHERE NOT(joe-[:knows]-fof)
RETURN fof.name, count(*)
ORDER BY count(*) DESC, fof.name

18. A flight/airport example
http://gist.neo4j.org/?6619085

19. Data From
http://www.transtats.bts.gov/DL_SelectFields.a
sp?Table_ID=236&DB_Short_Name=On-Time

20. Data model

21. Ask questions
● How many flight canceled
● How many flight delayed
● Average taxi waiting time
● Shortest path between

22. Other way to use neo4j
● Embedded (CTA)
● Server plugin (Grok)

23. Neo4j modeling tips
● Understand the performance character
○ Traversing is fast
○ IO is slow
○ Node properties are lazy loaded/cached
● Normalization verse denormalization in
relational database performance tuning