Introduction to the applications of graph databases

2. sergeyenin@gmail.com
Sergey
Enin
/pankrat
/sergeyenin

3. AGENDA
GRAPH
NOSQL
DBs
APP
NEO4J

4. Graph
Databases
Graph
Databases

5. Graph Databases: HISTORY
Leonhard Euler (1707 –1783)
Swiss mathematician

6. Graph Databases: HISTORY

7. What is
Graph?

8. Graph Databases: GRAPH
A
B
Ver%ce
(Node)
C
Edge
(Rela%onship)
D

9. Graph Databases: WHAT IS IT?

10. Graph Databases: WHAT IS IT?
Joins
VS
Traversals

11. Graph Databases: CHARACTERISTICS
1
Good for semistructured
connected
data
Index
freeadjacency
2
3
The
underlying
storage
The
processing
engine
4

12. APPs

13. ApplicaFon:
social
graphs

14. Application: PAGE RANK

15. APP: Collaborative filtering

17. Neo4J: CHARACTERISTICS
true
ACID
transac%ons;
scales
to
billions
of
nodes
and
rela%onships;
high
speed
querying
through
traversals;
declara%ve
graph
query
language;

18. Neo4J:
who
use
Neo4J: WHO USE
it

19. Neo4J:
who
use
Neo4J: NETWORK ARCHITECTURE
it
Neo4J:
network
architecture

20. Neo4J:
architecture
Neo4J: ARCHITECTURE

21. Neo4J:
architecture
Neo4J: Internal storage
Node
Rela%onship

22. Neo4J:
architecture
Neo4J: Internal storage

23. APP: Collaborative filtering
Neo4J: CF

24. APP: Collaborative filtering
Neo4J: CF

25. Neo4J: CYPHER
MATCH
(p1:Person)-­‐[x:RATED]-­‐>(m:PRODUCT)<-­‐[y:RATED]-­‐
(p2:Person)
WITH
SUM(x.ra%ng
*
y.ra%ng)
AS
xyDotProduct,
SQRT(REDUCE(xDot
=
0,
a
IN
COLLECT(x.ra%ng)
|
xDot
+
a^2))
AS
xLength,
SQRT(REDUCE(yDot
=
0,
b
IN
COLLECT(y.ra%ng)
|
yDot
+
b^2))
AS
yLength,
p1,
p2
CREATE
UNIQUE
(p1)-­‐[s:SIMILARITY]-­‐(p2)
SET
s.similarity
=
xyDotProduct
/
(xLength
*
yLength)

27. sergeyenin@gmail.com
Thank
you!
/pankrat
/sergeyenin