1. Mastering Neo4j A Graph Database Data Masters

2. Special Thanks To… Planet Linux Caffe http://planetlinuxcaffe.com

3. We now have a sponsor!! John Jadvani 954-527-0090

4.  Short bio about me…  Andrew Simkovsky  15 years working with database technology  Oracle, MySQL/MariaDB, SQL Server, Postgres  Redis, MongoDB, CouchDB, Cassandra, Neo4j  Worked across many industries  Consulting, Retail, Telecommunications, Energy  Data, Marketing, Gaming, Health care

5. DBTekPro www.dbtekpro.com andrew@dbtekpro.com @asimkovsky

6. Graph Databases

7.  What is a graph database?  Based on graph theory  Data is stored as “nodes”, and relationships as “edges”  Nodes have attributes.  Relationships have attributes

8. Relational vs Graph  Relational  Relationships are used to join entities together to get results  Data integrity is enforced through constraints  Graph  Relationships are considered data  Can easily “walk” from node to node using relationships  Can “walk” the graph in multiple directions in parallel

9. Relational Model actormovieactor_movie 1, Keanu Reeves 2, Carrie-Ann Moss 3, Lawrence Fishburne actor_id name movie_id title release_date actor_id movie_id role 1, The Matrix 2, The Matrix Reloaded 3, The Matrix Revolutions 1, 1, Neo 1, 2, Neo 1, 3, Neo 2, 1, Trinity 2, 2, Trinity 2, 3, Trinity 3, 1, Morpheus 3, 2, Morpheus 3, 3, Morpheus

10. Graph Model The Matrix The Matrix 2 The Matrix 3 Keanu Reeves Carrie- Ann Moss Lawrence Fishburne

11. Graph Model - Detailed type: Actor name: “Keanu Reeves” type: Movie title: “Matrix” :ACTS_IN type: Role, role: “Neo” Node Relationship PropertyValue Property Path

12. Example Graphs

15. Graph Databases – Examples Uses  Social relationships  Actor / movie relationships  Medicine interactions Just some of the many possibilities!

16. Cypher A Graph Query Language

17. Queries START [MATCH] [WITH] [WHERE] RETURN [ORDER BY] [SKIP] [LIMIT] Starting node(s) Matching pattern (except properties) Filter on properties Properties to return Further conditions / calculations

18. Query Example START user=node:nodeIndexName(name={“Bob”}) MATCH (user)-[:FRIEND]->(friend) WITH user, count(friend) as friends WHERE friends > 10 RETURN friend.name ORDER BY friend.name LIMIT 100

19. Query Parts START user=node:nodeIndexName(name={“Bob”}) made-up identifier object type node property identifier index namepropertyvalue

20. Query Parts MATCH (user)-[:FRIEND]->(friend) node relationship definition (including direction) Another made-up identifier

21. Query Parts WITH user, count(friend) as friends grouping node calculation alias

22. Query Parts WHERE friends > 10 property filter

23. Query Parts RETURN friend.name ORDER BY friend.name LIMIT 100

24. Query Example – All Together START user=node:nodeIndexName(name={“Bob”}) MATCH (user)-[:FRIEND]->(friend) WITH user, count(friend) as friends WHERE friends > 10 RETURN friend.name ORDER BY friend.name LIMIT 100 This will return all nodes where they are friends with Bob, and that Bob has more than 10 friends, but limit to the first 100 found.

25. Query Example – Matching START user=node:nodeIndexName(name={“Bob”}) MATCH (user)-[:FRIEND {since: “2001-01-01”} ]->(friend) RETURN friend.name Since relationships have properties, we can search on them too!!

26. Creating Data CREATE [UNIQUE]* [SET | DELETE | FOREACH]* [RETURN [ORDER BY][SKIP][LIMIT]]

27. Creating Data - Examples CREATE (n {name: “Bob”}) made-up identifier again propertyvalue

28. Creating Data - Examples CREATE (b {name: “Bob”}), (m {name: “Mary”}), (b)-[:KNOWS]->(m) Creates two nodes with a relationship between them. This is called creating a path.

29. Creating Data - Examples You can combine queries with create options! This allows you to create parts of the graph starting from a particular node (or nodes)! START b=node:nodeIndexName(name={“Bob”}), m=node:nodeIndexName(name={“Mary”}) MATCH (b)-[:KNOWS]->(m) CREATE (b)-[:LOVES]->(m)

30. Live Demo!

31. Where Do I Get It? www.neo4j.org

32. Thank You For Coming! Please rate this Meet Up: www.meetup.com/data-masters (or go there to join!) Check out my blog and forums: www.dbtekpro.com After Party!! Miller’s Ale House Miracle Mile