Graph Search: The Power of Connected Data
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The document discusses the advantages of graph databases, specifically Neo4j, highlighting their ability to manage and query complex interconnected data effectively. It outlines how graph databases handle semi-structured data with benefits like high performance, scalability, and ease of use in querying. Additionally, it provides examples of querying and creating graph structures, showcasing practical applications in areas like network analysis and recommendations.
![Recommenda]ons](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-10-320.jpg)
![Logis]cs](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-11-320.jpg)
![Securi]es
and
Debt
Image:
orgnet.com](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-14-320.jpg)
![The
Power
of
Rela]onships
Connectedness
• Pre-‐computed
joins
• Several
million
joins
per
second
per
thread
per
core
Variable
Structure
• Defined
with
regard
to
node
instances,
not
classes
of
nodes
– Contrast
with
rela]onal
schemas,
where
foreign
key
rela]onships
apply
to
all
rows
in
a
table](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-19-320.jpg)
![Graph
Database
Benefits
“Minutes
to
milliseconds”
performance
• Millions
of
‘joins’
per
second
• Consistent
query
]mes
as
dataset
grows
Fit
for
the
domain
• Lots
of
join
tables?
Connectedness
• Lots
of
sparse
tables?
Semi-‐structure
Business
responsiveness
• Easy
to
evolve](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-20-320.jpg)
![Querying
Graph
Data
• Describing
graphs
• Crea]ng
nodes,
rela]onships
and
proper]es
• Querying
graphs](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-21-320.jpg)
![Cypher
Padern
(rest)<-[:HAS_SKILL]-(ben)-[:HAS_SKILL]->(neo4j),
(ben)-[:WORKS_FOR]->(acme)](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-23-320.jpg)
![Create
Some
Data
CREATE (ben:Person { name:'Ben' }),
(acme:Company { name:'Acme' }),
(rest:Skill { name:'REST' }),
(neo4j:Skill= { name:'Neo4j' }),
(ben)-[:WORKS_FOR]->(acme),
(ben)-[:HAS_SKILL]->(rest),
(ben)-[:HAS_SKILL]->(graphs)
RETURN ben](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-24-320.jpg)
![Create
Nodes
CREATE (ben:Person { name:'Ben' }),
(acme:Company { name:'Acme' }),
(rest:Skill { name:'REST' }),
(neo4j:Skill= { name:'Neo4j' }),
(ben)-[:WORKS_FOR]->(acme),
(ben)-[:HAS_SKILL]->(rest),
(ben)-[:HAS_SKILL]->(graphs)
Iden]fier
Proper]es
RETURN ben
Label](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-25-320.jpg)
![Create
Rela]onships
CREATE (ben:Person { name:'Ben' }),
Iden]fier
Iden]fier
(acme:Company { name:'Acme' }),
Rela]onship
(rest:Skill { name:'REST' }),
(neo4j:Skill= { name:'Neo4j' }),
(ben)-[:WORKS_FOR]->(acme),
(ben)-[:HAS_SKILL]->(rest),
(ben)-[:HAS_SKILL]->(graphs)
RETURN ben](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-26-320.jpg)
![Return
Node
CREATE (ben:Person { name:'Ben' }),
(acme:Company { name:'Acme' }),
(rest:Skill { name:'REST' }),
(neo4j:Skill= { name:'Neo4j' }),
(ben)-[:WORKS_FOR]->(acme),
(ben)-[:HAS_SKILL]->(rest),
(ben)-[:HAS_SKILL]->(graphs)
RETURN ben](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-27-320.jpg)
![Cypher
Padern
(company)<-[:WORKS_FOR]-(me)-[:HAS_SKILL]->(skill),
(company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill)](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-31-320.jpg)
![Cypher
Query
Which
people,
who
work
for
the
same
company
as
me,
have
similar
skills
to
me?
MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill),
(company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill)
WHERE me.name = 'ian'
RETURN colleague.name AS name,
count(skill) AS score,
collect(skill.name) AS skills
ORDER BY score DESC](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-32-320.jpg)
![Graph
Padern
Which
people,
who
work
for
the
same
company
as
me,
have
similar
skills
to
me?
MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill),
(company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill)
WHERE me.name = 'ian'
RETURN colleague.name AS name,
count(skill) AS score,
collect(skill.name) AS skills
ORDER BY score DESC](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-33-320.jpg)
![Anchor
Padern
in
Graph
Which
people,
who
work
for
the
same
company
as
me,
have
similar
skills
to
me?
MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill),
(company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill)
WHERE me.name = 'ian'
RETURN colleague.name AS name,
count(skill) AS score,
collect(skill.name) AS skills
ORDER BY score DESC
Search
nodes
labelled
‘Person’,
matching
on
‘name’
property](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-34-320.jpg)
![Create
Results
Which
people,
who
work
for
the
same
company
as
me,
have
similar
skills
to
me?
MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill),
(company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill)
WHERE me.name = 'ian'
RETURN colleague.name AS name,
count(skill) AS score,
collect(skill.name) AS skills
ORDER BY score DESC](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-35-320.jpg)
![Results
+--------------------------------------+
| name
| score | skills
|
+--------------------------------------+
| "Ben"
| 2
| ["Neo4j","REST"] |
| "Charlie" | 1
| ["Neo4j"]
|
+--------------------------------------+
2 rows](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-37-320.jpg)
![Asset
Management
&
Access
Control
• Which
assets
can
an
admin
control?
• Who
can
change
my
subscrip]on?](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-40-320.jpg)
![Logis]cs
• What’s
the
quickest
delivery
route
for
this
parcel?](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-41-320.jpg)
![Social
Network
&
Recommenda]ons
• Which
assets
can
I
access?
• Who
shares
my
interests?](https://image.slidesharecdn.com/graphsearch-131209034142-phpapp02/85/Graph-Search-The-Power-of-Connected-Data-42-320.jpg)
Graph Search: The Power of Connected Data
- 1. Ian Robinson, Neo Technology Graph Search: The Power of Connected Data Twi$er @iansrobinson #neo4j
- 2. Outline • Data complexity • Graph databases – features and benefits • Querying graph data
- 3. Data Complexity complexity = f(size, semi-structure, connectedness)
- 4. Data Complexity complexity = f(size , semi-structure, connectedness)
- 6. Semi-‐Structure USER_ID FIRST_NAME LAST_NAME 315 Ian Robinson EMAIL_1 EMAIL_2 ian@neotechnology.com iansrobinson@gmail.com Email: ian@neotechnology.com Email: iansrobinson@gmail.com Twi$er: @iansrobinson Skype: iansrobinson 0..n USER FACEBOOK NULL TWITTER SKYPE @iansrobinson iansrobinson CONTACT CONTACT_TYPE
- 10. Recommenda]ons
- 11. Logis]cs
- 12. Access Control
- 13. Fraud Analysis
- 14. Securi]es and Debt Image: orgnet.com
- 16. Graph Databases • Store • Manage • Query data
- 17. Neo4j is a Graph Database
- 19. The Power of Rela]onships Connectedness • Pre-‐computed joins • Several million joins per second per thread per core Variable Structure • Defined with regard to node instances, not classes of nodes – Contrast with rela]onal schemas, where foreign key rela]onships apply to all rows in a table
- 20. Graph Database Benefits “Minutes to milliseconds” performance • Millions of ‘joins’ per second • Consistent query ]mes as dataset grows Fit for the domain • Lots of join tables? Connectedness • Lots of sparse tables? Semi-‐structure Business responsiveness • Easy to evolve
- 21. Querying Graph Data • Describing graphs • Crea]ng nodes, rela]onships and proper]es • Querying graphs
- 22. How to Describe a Graph?
- 24. Create Some Data CREATE (ben:Person { name:'Ben' }), (acme:Company { name:'Acme' }), (rest:Skill { name:'REST' }), (neo4j:Skill= { name:'Neo4j' }), (ben)-[:WORKS_FOR]->(acme), (ben)-[:HAS_SKILL]->(rest), (ben)-[:HAS_SKILL]->(graphs) RETURN ben
- 25. Create Nodes CREATE (ben:Person { name:'Ben' }), (acme:Company { name:'Acme' }), (rest:Skill { name:'REST' }), (neo4j:Skill= { name:'Neo4j' }), (ben)-[:WORKS_FOR]->(acme), (ben)-[:HAS_SKILL]->(rest), (ben)-[:HAS_SKILL]->(graphs) Iden]fier Proper]es RETURN ben Label
- 26. Create Rela]onships CREATE (ben:Person { name:'Ben' }), Iden]fier Iden]fier (acme:Company { name:'Acme' }), Rela]onship (rest:Skill { name:'REST' }), (neo4j:Skill= { name:'Neo4j' }), (ben)-[:WORKS_FOR]->(acme), (ben)-[:HAS_SKILL]->(rest), (ben)-[:HAS_SKILL]->(graphs) RETURN ben
- 27. Return Node CREATE (ben:Person { name:'Ben' }), (acme:Company { name:'Acme' }), (rest:Skill { name:'REST' }), (neo4j:Skill= { name:'Neo4j' }), (ben)-[:WORKS_FOR]->(acme), (ben)-[:HAS_SKILL]->(rest), (ben)-[:HAS_SKILL]->(graphs) RETURN ben
- 29. Querying a Graph Graph Local • Find one or more start nodes • Explore surrounding graph • Millions of hops per second
- 30. Which people, who work for the same company as me, share my skills?
- 32. Cypher Query Which people, who work for the same company as me, have similar skills to me? MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill), (company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill) WHERE me.name = 'ian' RETURN colleague.name AS name, count(skill) AS score, collect(skill.name) AS skills ORDER BY score DESC
- 33. Graph Padern Which people, who work for the same company as me, have similar skills to me? MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill), (company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill) WHERE me.name = 'ian' RETURN colleague.name AS name, count(skill) AS score, collect(skill.name) AS skills ORDER BY score DESC
- 34. Anchor Padern in Graph Which people, who work for the same company as me, have similar skills to me? MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill), (company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill) WHERE me.name = 'ian' RETURN colleague.name AS name, count(skill) AS score, collect(skill.name) AS skills ORDER BY score DESC Search nodes labelled ‘Person’, matching on ‘name’ property
- 35. Create Results Which people, who work for the same company as me, have similar skills to me? MATCH (company)<-[:WORKS_FOR]-(me:Person)-[:HAS_SKILL]->(skill), (company)<-[:WORKS_FOR]-(colleague)-[:HAS_SKILL]->(skill) WHERE me.name = 'ian' RETURN colleague.name AS name, count(skill) AS score, collect(skill.name) AS skills ORDER BY score DESC
- 37. Results +--------------------------------------+ | name | score | skills | +--------------------------------------+ | "Ben" | 2 | ["Neo4j","REST"] | | "Charlie" | 1 | ["Neo4j"] | +--------------------------------------+ 2 rows
- 38. Case Studies
- 39. Network Impact Analysis • Which parts of network does a customer depend on? • Who will be affected if we replace a network element?
- 40. Asset Management & Access Control • Which assets can an admin control? • Who can change my subscrip]on?
- 41. Logis]cs • What’s the quickest delivery route for this parcel?
- 42. Social Network & Recommenda]ons • Which assets can I access? • Who shares my interests?
- 43. graphdatabases.com ts gy en lo i m no pl h m ec Co eo T N of Graph h Databases Ian Robinson, Jim Webber & Emil Eifrem Thank you @ianSrobinson ian@neotechnology.com