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Maria Scharin
maria.scharin@neo4j.com
Introduction to Cypher
Information Developer 

IT Project Manager

Oracle DBA
About Me
maria.scharin@neo4j.com
• A brief history of graph databases
• Graph thinking
• Graph data modelling
• Importing data
• How to get started
Agenda
A brief history of graph databases
Everything and Everyone is Connected
• people, places, events
• companies, markets
• countries, history, politics
• sciences, art, teaching
• technology, networks, machines, applications, users
• software, code, dependencies, architecture, deployments
• criminals, fraudsters and their behavior

Seven Bridges of Königsberg
C
34,3%B
38,4%A
3,3%
D
3,8%
1,8%
1,8%
1,8%
1,8%
1,8%
E
8,1%
F
3,9%
Static world Connected World
Native Graph Platform
Neo4j is an internet-scale,
native graph database which
executes connected workloads
faster than any other database
management system.
Neo4j
Ecosystem
Neo4j Professional Services
300+ partners
47,000 group members
61,000 trained engineers
3.5M downloads
Mindset
“Graph Thinking” is all about
considering connections in
data as important as the data
itself.
Native Graph Platform
Neo4j is an internet-scale,
native graph database which
executes connected workloads
faster than any other database
management system.
Neo4j
Graph thinking
Graph thinking: A modern Swedish family
Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm
Maria
OscarThomas
Ann
FRIEND OF
MOTHER OFMOTHER OF
FRIEND OF
Cody
EX OF
FATHER OF
Graph thinking: A modern Swedish family
Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm
FRIEND OF
MOTHER OF
FRIEND OF
Thomas
Ann
Cody
EX OFMARRIED TO
Dan
Graph thinking: A modern Swedish family
Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm
Karl Ben
Chris Carrie
Elizabeth
EX OF
FRIEND OF
MOTHER OF
FRIEND OF
Thomas
Ann
Cody
EX OFMARRIED TO
Dan
Graph thinking
AnnDan LOVES
The property graph model
since: Jan 10, 2011
brand: “Volvo”
model: “V70”
D
R
IVES
O
W
NS
Car
LIVES_WITH
LOVES
name:”Dan”
born: May 29, 1970
twitter:”@dan”
name:”Ann”
born: Dec 5, 1975
LOVES
Person Person
The property graph model
Cypher: The Graph Query Language
• The “SQL for graphs”: An open language (http://www.opencypher.org/)

• The formal semantics are in the process of being defined: collaboration
with the University of Edinburgh, UK
• Declarative
• Focus on pattern matching
• Intuitive and easy to learn (ASCII-Art)
Cypher: The Graph Query Language
CREATE
LABEL PROPERTYLABEL PROPERTY RELATIONSHIP
TYPE
(:Person { name:“Dan”} ) - [:LOVES]-> (:Person { name:“Ann”} )
NODE NODERELATIONSHIP
name:”Dan” name:”Ann”
LOVES
Person Person
MERGE
Index-free adjacency
Credit: Dan McCreary
https://medium.com/@dmccreary/how-to-explain-index-free-adjacency-to-your-manager-1a8e68ec664a
Maria’s

house
Ann’s

house
Index-free adjacency
Credit: Dan McCreary
https://medium.com/@dmccreary/how-to-explain-index-free-adjacency-to-your-manager-1a8e68ec664a
Relational and
Other NoSQL
Databases
ResponseTime
Connectedness and Size of Data Set
0 to 2 hops
0 to 3 degrees
Few connections
5+ hops
3+ degrees
Thousands of connections
Neo4j
Real-Time Query Performance
Graph data modelling
Graph data modeling
• Relational to graph
• Different ways of modelling
• Refactoring
• Inference
• A social recommendation example
Relational to Graph
select restaurant.name

from person join review on (...) join restaurant on(…)

where person.name = “Maria”
reviewperson business
Maria
Sushi Lovers
The Burger Joint
Pedro’s Pizza
reviewperson business
Relational model
Rows
Joins
Table names
Columns
Graph model
Nodes
Relationships
Labels
Properties
Maria
Sushi Lovers
Pedro’s

Pizza
The

Burger

Joint
Relational to Graph
Arrow tool: http://www.apcjones.com/arrows/#
Graph data modelling
Graph data modelling: refactoring
Arrow tool: http://www.apcjones.com/arrows/#
Graph data modelling: inference
Arrow tool: http://www.apcjones.com/arrows/#
A Social Recommendation
Maria
Ann
Diana
FRIEND OF
FRIEND OF
LIKES
LIKES
iSushi
:Restaurant
New York
:Location
Sushi
:Cuisine
SERVES
SERVES
LOCATED_IN
LOCATED_IN
Sushi Lovers
:Restaurant
Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm
A Social Recommendation
Some icons designed by Freepik
www.freepik.com/free-vector/people-icons-collection_1024244.htm
Maria Ann
Diana
FRIEND OF
FRIEND OF
LIKES
LIKES
iSushi
New York
Sushi
SERVES
SERVES
LOCATED_IN
LOCATED_IN
:Restaurant
:Location
:Cuisine
:Restaurant
Sushi Lovers
A Social Recommendation
Some icons designed by Freepik
www.freepik.com/free-vector/people-icons-collection_1024244.htm
Maria Ann
Diana
FRIEND OF
FRIEND OF
LIKES
LIKES
iSushi
New York
Sushi
SERVES
SERVES
LOCATED_IN
LOCATED_IN
:Restaurant
:Location
:Cuisine
:Restaurant
Sushi Lovers
https://neo4j.com/docs/developer-manual/current/cypher/query-tuning/
A Social Recommendation
Some icons designed by Freepik
www.freepik.com/free-vector/people-icons-collection_1024244.htm
Maria Ann
Diana
FRIEND OF
FRIEND OF
LIKES
LIKES
iSushi
New York
Sushi
SERVES
SERVES
LOCATED_IN
LOCATED_IN
:Restaurant
:Location
:Cuisine
Sushi Lovers
:Restaurant
Import data
Download and install Neo4j Desktop
https://neo4j.com/download/
Download and install Neo4j Desktop
The Yelp dataset
https://www.yelp.com/dataset
The Yelp dataset
https://www.yelp.com/dataset
json format
Convert json files to csv format: 

https://github.com/johnymontana/neo4j-datasets/tree/master/yelp
https://www.yelp.com/dataset
The Yelp dataset
(Also available in sql)
https://www.yelp.com/dataset
The Yelp dataset
Import data: LOAD CSV
Cypher-Based LOAD CSV Capability
• Transactional (ACID) writes
• Initial and incremental loads of up to 10 million nodes and relationships
• From HTTP and Files
• Power of Cypher:
• Create and update graph structures
• Data conversion, filtering, aggregation
• De-structuring of input data
• Transaction size control
• Via Neo4j Browser or cypher-shell
• https://neo4j.com/docs/cypher-refcard/current/
Import data: LOAD CSV
line
["yelping_since", "useful", "compliment_photos", "compliment_list", "compliment_funny", "funny", "review_count", "friends", "fans", "compliment_note", "compliment_plain",
"compliment_writer", "compliment_cute", "average_stars", "user_id", "compliment_more", "elite", "compliment_hot", "cool", "name", "compliment_profile", "compliment_cool"]
["2014-11-03", "0", "0", "0", "0", "0", "8",
"cvVMmlU1ouS3I5fhutaryQ;nj6UZ8tdGo8YJ9lUMTVWNw;RTtdEVhAmeWqCSp0IgJ99w;t3UKA1sl4e6LY_xsjuvI0A;s057_BvOfnKNvQquJf7VNg;VYrdepCgdzJ4WaxP7dBGpg;XXLSk6s
QQDyr3dZ4zE-O0g;Py8ThfExQaXF2Woqr7kWUw;233YNvzVtZ1ObkaNkUzNIw;L6iE9NpmHHJQTk0JQlRlSA;Y7XTMgZ_q5Bj5f9KhK1R4Q", "[u'cvVMmlU1ouS3I5fhutaryQ',
u'nj6UZ8tdGo8YJ9lUMTVWNw', u'RTtdEVhAmeWqCSp0IgJ99w', u't3UKA1sl4e6LY_xsjuvI0A', u's057_BvOfnKNvQquJf7VNg', u'VYrdepCgdzJ4WaxP7dBGpg',
u'XXLSk6sQQDyr3dZ4zE-O0g', u'Py8ThfExQaXF2Woqr7kWUw', u'233YNvzVtZ1ObkaNkUzNIw', u'L6iE9NpmHHJQTk0JQlRlSA', u'Y7XTMgZ_q5Bj5f9KhK1R4Q']", "0", "0", "1", "0", "0",
"4.67", "oMy_rEb0UBEmMlu-zcxnoQ", "0", "", "[]", "0", "0", "Johnny", "0", "0"]
https://neo4j.com/docs/cypher-refcard/current/
Import data: LOAD CSV
https://neo4j.com/docs/cypher-refcard/current/
Import data: LOAD CSV
http://markhneedham.com/blog/2014/07/10/neo4j-load-csv-processing-hidden-arrays-in-your-csv-documents/

https://neo4j.com/docs/cypher-refcard/current/
Import data: LOAD CSV
https://neo4j.com/docs/cypher-refcard/current/
Import data: LOAD CSV
https://neo4j.com/docs/cypher-refcard/current/
Use JDBC with your sql database
Use JDBC with your sql database
apoc.load.jdbc 
Access any database that provides a JDBC driver
Execute queries whose results are turned into streams of rows
Use the rows to update or create graph structures
https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
Use JDBC with your sql database
CALL apoc.load.jdbc(“jdbc:mysql://localhost:3306/yelp_db?
user=user&password=pwd", “business") 

YIELD row 

RETURN row
https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
Use JDBC with your sql database
CALL apoc.load.jdbc("jdbc:mysql://localhost:3306/yelp_db?
user=user&password=pwd", “business")
YIELD row
RETURN row.id, row.name, row.address, row.state
https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
Use JDBC with your sql database
CALL apoc.load.jdbc("jdbc:mysql://localhost:3306/yelp_db?
user=user&password=pwd", “business")
YIELD row
MERGE (:Business {id: row.id, name:row.name, address:row.address,
state:row.state})
https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
Import data: neo4j-admin import
Command line bulk loader neo4j-admin import
• For initial database population
• Scale across CPUs and disk performance
• Efficient RAM usage
• Split- and compressed file support
• For loads up to 10B+ records
• Up to 1M records per second
https://neo4j.com/docs/operations-manual/3.3/tutorial/import-tool/
• Neo4j Desktop - Free for download
• Neo4j Browser (included in Neo4j Desktop)
• Sandbox: neo4j.com/sandbox
• Drivers - Official Drivers and Community Supported Drivers
• Webinars and Tutorials
• Community and Meetups
Get started with Neo4j
Neo4j Sandbox
https://neo4j.com/sandbox-v2/
Thank you!
maria.scharin@neo4j.com

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[Webinar] Introduction to Cypher

  • 2. Information Developer IT Project Manager Oracle DBA About Me maria.scharin@neo4j.com
  • 3. • A brief history of graph databases • Graph thinking • Graph data modelling • Importing data • How to get started Agenda
  • 4. A brief history of graph databases
  • 5. Everything and Everyone is Connected • people, places, events • companies, markets • countries, history, politics • sciences, art, teaching • technology, networks, machines, applications, users • software, code, dependencies, architecture, deployments • criminals, fraudsters and their behavior

  • 6. Seven Bridges of Königsberg
  • 7. C 34,3%B 38,4%A 3,3% D 3,8% 1,8% 1,8% 1,8% 1,8% 1,8% E 8,1% F 3,9% Static world Connected World Native Graph Platform Neo4j is an internet-scale, native graph database which executes connected workloads faster than any other database management system. Neo4j
  • 8. Ecosystem Neo4j Professional Services 300+ partners 47,000 group members 61,000 trained engineers 3.5M downloads Mindset “Graph Thinking” is all about considering connections in data as important as the data itself. Native Graph Platform Neo4j is an internet-scale, native graph database which executes connected workloads faster than any other database management system. Neo4j
  • 10. Graph thinking: A modern Swedish family Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm Maria OscarThomas Ann FRIEND OF MOTHER OFMOTHER OF FRIEND OF Cody EX OF FATHER OF
  • 11. Graph thinking: A modern Swedish family Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm FRIEND OF MOTHER OF FRIEND OF Thomas Ann Cody EX OFMARRIED TO Dan
  • 12. Graph thinking: A modern Swedish family Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm Karl Ben Chris Carrie Elizabeth EX OF FRIEND OF MOTHER OF FRIEND OF Thomas Ann Cody EX OFMARRIED TO Dan
  • 15. since: Jan 10, 2011 brand: “Volvo” model: “V70” D R IVES O W NS Car LIVES_WITH LOVES name:”Dan” born: May 29, 1970 twitter:”@dan” name:”Ann” born: Dec 5, 1975 LOVES Person Person The property graph model
  • 16. Cypher: The Graph Query Language • The “SQL for graphs”: An open language (http://www.opencypher.org/)
 • The formal semantics are in the process of being defined: collaboration with the University of Edinburgh, UK • Declarative • Focus on pattern matching • Intuitive and easy to learn (ASCII-Art)
  • 17. Cypher: The Graph Query Language CREATE LABEL PROPERTYLABEL PROPERTY RELATIONSHIP TYPE (:Person { name:“Dan”} ) - [:LOVES]-> (:Person { name:“Ann”} ) NODE NODERELATIONSHIP name:”Dan” name:”Ann” LOVES Person Person MERGE
  • 18. Index-free adjacency Credit: Dan McCreary https://medium.com/@dmccreary/how-to-explain-index-free-adjacency-to-your-manager-1a8e68ec664a Maria’s
 house Ann’s
 house
  • 19. Index-free adjacency Credit: Dan McCreary https://medium.com/@dmccreary/how-to-explain-index-free-adjacency-to-your-manager-1a8e68ec664a
  • 20. Relational and Other NoSQL Databases ResponseTime Connectedness and Size of Data Set 0 to 2 hops 0 to 3 degrees Few connections 5+ hops 3+ degrees Thousands of connections Neo4j Real-Time Query Performance
  • 22. Graph data modeling • Relational to graph • Different ways of modelling • Refactoring • Inference • A social recommendation example
  • 23. Relational to Graph select restaurant.name
 from person join review on (...) join restaurant on(…)
 where person.name = “Maria” reviewperson business Maria Sushi Lovers The Burger Joint Pedro’s Pizza
  • 24. reviewperson business Relational model Rows Joins Table names Columns Graph model Nodes Relationships Labels Properties Maria Sushi Lovers Pedro’s
 Pizza The
 Burger
 Joint Relational to Graph
  • 26. Graph data modelling: refactoring Arrow tool: http://www.apcjones.com/arrows/#
  • 27. Graph data modelling: inference Arrow tool: http://www.apcjones.com/arrows/#
  • 28. A Social Recommendation Maria Ann Diana FRIEND OF FRIEND OF LIKES LIKES iSushi :Restaurant New York :Location Sushi :Cuisine SERVES SERVES LOCATED_IN LOCATED_IN Sushi Lovers :Restaurant Icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm
  • 29. A Social Recommendation Some icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm Maria Ann Diana FRIEND OF FRIEND OF LIKES LIKES iSushi New York Sushi SERVES SERVES LOCATED_IN LOCATED_IN :Restaurant :Location :Cuisine :Restaurant Sushi Lovers
  • 30. A Social Recommendation Some icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm Maria Ann Diana FRIEND OF FRIEND OF LIKES LIKES iSushi New York Sushi SERVES SERVES LOCATED_IN LOCATED_IN :Restaurant :Location :Cuisine :Restaurant Sushi Lovers https://neo4j.com/docs/developer-manual/current/cypher/query-tuning/
  • 31. A Social Recommendation Some icons designed by Freepik www.freepik.com/free-vector/people-icons-collection_1024244.htm Maria Ann Diana FRIEND OF FRIEND OF LIKES LIKES iSushi New York Sushi SERVES SERVES LOCATED_IN LOCATED_IN :Restaurant :Location :Cuisine Sushi Lovers :Restaurant
  • 33. Download and install Neo4j Desktop https://neo4j.com/download/
  • 34. Download and install Neo4j Desktop
  • 36. The Yelp dataset https://www.yelp.com/dataset json format Convert json files to csv format: 
 https://github.com/johnymontana/neo4j-datasets/tree/master/yelp https://www.yelp.com/dataset
  • 37. The Yelp dataset (Also available in sql) https://www.yelp.com/dataset
  • 39. Import data: LOAD CSV Cypher-Based LOAD CSV Capability • Transactional (ACID) writes • Initial and incremental loads of up to 10 million nodes and relationships • From HTTP and Files • Power of Cypher: • Create and update graph structures • Data conversion, filtering, aggregation • De-structuring of input data • Transaction size control • Via Neo4j Browser or cypher-shell • https://neo4j.com/docs/cypher-refcard/current/
  • 40. Import data: LOAD CSV line ["yelping_since", "useful", "compliment_photos", "compliment_list", "compliment_funny", "funny", "review_count", "friends", "fans", "compliment_note", "compliment_plain", "compliment_writer", "compliment_cute", "average_stars", "user_id", "compliment_more", "elite", "compliment_hot", "cool", "name", "compliment_profile", "compliment_cool"] ["2014-11-03", "0", "0", "0", "0", "0", "8", "cvVMmlU1ouS3I5fhutaryQ;nj6UZ8tdGo8YJ9lUMTVWNw;RTtdEVhAmeWqCSp0IgJ99w;t3UKA1sl4e6LY_xsjuvI0A;s057_BvOfnKNvQquJf7VNg;VYrdepCgdzJ4WaxP7dBGpg;XXLSk6s QQDyr3dZ4zE-O0g;Py8ThfExQaXF2Woqr7kWUw;233YNvzVtZ1ObkaNkUzNIw;L6iE9NpmHHJQTk0JQlRlSA;Y7XTMgZ_q5Bj5f9KhK1R4Q", "[u'cvVMmlU1ouS3I5fhutaryQ', u'nj6UZ8tdGo8YJ9lUMTVWNw', u'RTtdEVhAmeWqCSp0IgJ99w', u't3UKA1sl4e6LY_xsjuvI0A', u's057_BvOfnKNvQquJf7VNg', u'VYrdepCgdzJ4WaxP7dBGpg', u'XXLSk6sQQDyr3dZ4zE-O0g', u'Py8ThfExQaXF2Woqr7kWUw', u'233YNvzVtZ1ObkaNkUzNIw', u'L6iE9NpmHHJQTk0JQlRlSA', u'Y7XTMgZ_q5Bj5f9KhK1R4Q']", "0", "0", "1", "0", "0", "4.67", "oMy_rEb0UBEmMlu-zcxnoQ", "0", "", "[]", "0", "0", "Johnny", "0", "0"] https://neo4j.com/docs/cypher-refcard/current/
  • 41. Import data: LOAD CSV https://neo4j.com/docs/cypher-refcard/current/
  • 42. Import data: LOAD CSV http://markhneedham.com/blog/2014/07/10/neo4j-load-csv-processing-hidden-arrays-in-your-csv-documents/
 https://neo4j.com/docs/cypher-refcard/current/
  • 43. Import data: LOAD CSV https://neo4j.com/docs/cypher-refcard/current/
  • 44. Import data: LOAD CSV https://neo4j.com/docs/cypher-refcard/current/
  • 45. Use JDBC with your sql database
  • 46. Use JDBC with your sql database apoc.load.jdbc  Access any database that provides a JDBC driver Execute queries whose results are turned into streams of rows Use the rows to update or create graph structures https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
  • 47. Use JDBC with your sql database CALL apoc.load.jdbc(“jdbc:mysql://localhost:3306/yelp_db? user=user&password=pwd", “business") 
 YIELD row 
 RETURN row https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
  • 48. Use JDBC with your sql database CALL apoc.load.jdbc("jdbc:mysql://localhost:3306/yelp_db? user=user&password=pwd", “business") YIELD row RETURN row.id, row.name, row.address, row.state https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
  • 49. Use JDBC with your sql database CALL apoc.load.jdbc("jdbc:mysql://localhost:3306/yelp_db? user=user&password=pwd", “business") YIELD row MERGE (:Business {id: row.id, name:row.name, address:row.address, state:row.state}) https://neo4j-contrib.github.io/neo4j-apoc-procedures/index30.html#_load_jdbc
  • 50. Import data: neo4j-admin import Command line bulk loader neo4j-admin import • For initial database population • Scale across CPUs and disk performance • Efficient RAM usage • Split- and compressed file support • For loads up to 10B+ records • Up to 1M records per second https://neo4j.com/docs/operations-manual/3.3/tutorial/import-tool/
  • 51. • Neo4j Desktop - Free for download • Neo4j Browser (included in Neo4j Desktop) • Sandbox: neo4j.com/sandbox • Drivers - Official Drivers and Community Supported Drivers • Webinars and Tutorials • Community and Meetups Get started with Neo4j