Introduction to Graph Databases wth neo4J
0 likes293 views
This document introduces graph databases and Neo4j. It discusses different database types and how graph databases are better suited than relational databases for certain types of connected data. It provides an overview of graph concepts, demonstrates graph queries in Cypher compared to relational queries, and shows how to model and query graph data in Neo4j. Examples include finding friends and degrees of separation between people.
![MATCH Clause
24
MATCH (a)-->(b)
MATCH (a)-[:FRIEND]->(b)
MATCH (a)<-[:FRIEND]-(b)
MATCH (a)-[:FRIEND]-(b)
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-24-320.jpg)
![MATCH Clause with Labels
25
MATCH (p:Person)-[:DIRECTED]->(m:Movie)
MATCH (a:Person)-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(d:Person)
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-25-320.jpg)
![WHERE
26
MATCH (p:Person)-[:DIRECTED]->(m:Movie)
WHERE p.name = 'Ron Howard'
AND p.born < 1955
MATCH (p:Person {name: 'Ron Howard'})-[:DIRECTED]->(m:Movie)
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-26-320.jpg)
![RETURN, ORDER BY, LIMIT
27
MATCH (p:Person {name: 'Ron Howard'})-[:DIRECTED]->(m:Movie)
RETURN m.title, m.released, m.tagline
ORDER BY m.title
LIMIT 3
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-27-320.jpg)
![Overall Read Query Structure
28
[MATCH WHERE]
[OPTIONAL MATCH WHERE]
[WITH [ORDER BY] [SKIP] [LIMIT]]
RETURN [ORDER BY] [SKIP] [LIMIT]
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-28-320.jpg)
![CREATE
29
CREATE (matrix:Movie {title:'The Matrix', released:1999})
CREATE (keanu:Person {name:'Keanu Reeves', born:1964})
CREATE (keanu)-[:ACTED_IN]->(matrix)
MATCH (matrix:Movie {title:'The Matrix'}),
(keanu:Person {name:'Keanu Reeves'})
CREATE (keanu)-[:ACTED_IN]->(matrix)
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-29-320.jpg)
![DELETE
31
MATCH (p:Person{name: 'Keanu Reeves'})
DELETE p
MATCH (p:Person{name: 'Keanu Reeves'})-[r]-()
DELETE r, p
MATCH (p:Person{name: 'Keanu Reeves'})
DETACH DELETE n
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-31-320.jpg)
![Who are Bob’s Friends
SELECT p2.id, p2.name
FROM person p1
JOIN person_relationship rel
ON p1.id = rel.start_person_id
AND p1.id = 1 --Bob
AND rel.relationship_type=1 --Friend
JOIN person p2
ON p2.id = rel.end_person_id
33
MATCH (b:Person {name:'Bob'})-[:FRIEND]->(f:Person)
RETURN f.name
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-33-320.jpg)
![Who are the Friends of Bob’s Friends?
SELECT p3.id, p3.name
FROM person p1
JOIN person_relationship rel1
ON p1.id = rel1.start_person_id
AND p1.id = 1 --Bob
AND rel1.relationship_type = 1 --Friend
JOIN person p2
ON p2.id = rel1.end_person_id
JOIN person_relationship rel2
ON p2.id = rel2.start_person_id
AND rel2.relationship_type = 1 --Friend
JOIN person p3
ON p3.id = rel2.end_person_id
34
MATCH (b:Person {name:'Bob'})-[:FRIEND]->(f:Person)-[:FRIEND]->(fof:Person)
RETURN DISTINCT fof.name
MATCH (b:Person {name:'Bob'})-[:FRIEND *2]->(fof:Person)
RETURN DISTINCT fof.name
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-34-320.jpg)
![Bob’s Friends’ Friends’ Friends to the N
35
MATCH (b:Person {name:'Bob'})-[:FRIEND *2]->(fof:Person)
RETURN DISTINCT fof.name
MATCH (b:Person {name:'Bob'})-[:FRIEND *]->(fof:Person)
RETURN DISTINCT fof.name
MATCH (b:Person {name:'Bob'})-[:FRIEND *..5]->(fof:Person)
RETURN DISTINCT fof.name
MATCH (b:Person {name:'Bob'})-[:FRIEND *2..5]->(fof:Person)
RETURN DISTINCT fof.name
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-35-320.jpg)
![What is Bob’s Bacon # ?
36
MATCH path=shortestPath(
(kb:Person {name:'Kevin Bacon'})-[*]-(b:Person {name:'Bob'})
)
RETURN length(path)
DEVSPACE 2017 | @tbrantb](https://image.slidesharecdn.com/graphdbintro2-171014141836/85/Introduction-to-Graph-Databases-wth-neo4J-36-320.jpg)
Introduction to Graph Databases wth neo4J
- 1. INTRODUCTION TO GRAPH DATABASES WITH NEO4J Brant Boehmann @tbrantb
- 2. 2DEVSPACE 2017 | @tbrantb
- 3. About Me - ~20 Years Dev Experience - Java/JVM Specialist - Lead Software Engineer @ScrippsNet 3DEVSPACE 2017 | @tbrantb
- 4. Outline - DB Types - What is a GraphDB - RDBMS vs GraphDB - Neo4J - Cypher - Neo4J Console 4DEVSPACE 2017 | @tbrantb
- 5. Multiple DB Types - Relational - Oracle, MS-SQL, PostgreSQL, MySQL, ... - Columnar - GreenPlum, RedShift, ... - Key-Value - Dynamo, Riak, ... - Document - MongoDB, CouchDB, ... - Graph - Neo4J, JanusDB, OrientDB, TigerGraph, ... 5DEVSPACE 2017 | @tbrantb
- 6. Which DB type is right? - Data Size - Data structure - Access Patterns - Write Patterns - Performance Requirements - Consistency Requirements - Degree of Data Connectedness 6DEVSPACE 2017 | @tbrantb
- 7. Remember Graph Basics - Node (Vertex) - Relationship (Edge) - Direction - Path A D B C E 7DEVSPACE 2017 | @tbrantb
- 8. Turn a Graph into a DB - Node Labels - Relationship Type - Properties 8DEVSPACE 2017 | @tbrantb
- 9. Shoehorn into RDBMS Attempt #1 - Convert a Graph to Table - Adjacency Matrix 9DEVSPACE 2017 | @tbrantb
- 10. Shoehorn into RDBMS Attempt #1 - Adjacency Matrix Doesn’t fit in RDBMS table :( - Why? - Schema / Static Columns - Column growth 10
- 11. Shoehorn into RDBMS Attempt #2 - Join Table - Many-To-Many 11DEVSPACE 2017 | @tbrantb
- 12. Who are Bob’s Friends Pretty Simple SELECT p2.id, p2.name FROM person p1 JOIN person_relationship rel ON p1.id = rel.start_person_id AND p1.id = 1 --Bob AND rel.relationship_type=1 --Friend JOIN person p2 ON p2.id = rel.end_person_id 12DEVSPACE 2017 | @tbrantb
- 13. Who are the Friends of Bob’s Friends? SELECT p3.id, p3.name FROM person p1 JOIN person_relationship rel1 ON p1.id = rel1.start_person_id AND p1.id = 1 --Bob AND rel1.relationship_type = 1 --Friend JOIN person p2 ON p2.id = rel1.end_person_id JOIN person_relationship rel2 ON p2.id = rel2.start_person_id AND rel2.relationship_type = 1 --Friend JOIN person p3 ON p3.id = rel2.end_person_id 13
- 14. Bob’s Friends’ Friends’ Friends to the N Do I have to? 14DEVSPACE 2017 | @tbrantb
- 15. What is Bob’s Bacon # ? ? 15DEVSPACE 2017 | @tbrantb
- 16. Not all problems are well suited for RDBMS 16DEVSPACE 2017 | @tbrantb
- 17. How do Graph DBs do this better? - RDBMS uses joins & table/index scans - Native vs Non-Native GraphDB - “Index Free Adjacency” 17DEVSPACE 2017 | @tbrantb
- 18. Popular GraphDB Use Cases - Social Networks - Fraud Detection - Recommendation Engines - IAM - Master Data Management (MDM) - Network Ops - Content/Asset Management - Journalism (see Panama Papers) 18DEVSPACE 2017 | @tbrantb
- 19. Algorithms/Concepts - Shortest Path - A* - Triadic Closures 19DEVSPACE 2017 | @tbrantb
- 20. Neo4J - Labeled Property Graph - Native Graph DB w/Index Free Adjacency - JVM Based - Fully ACID - All relationships are directed * - Schema-less, Schema-optional - Embedded, Single Instance Server, HA Cluster 20DEVSPACE 2017 | @tbrantb
- 21. Neo4J APIs - Embedded Java API - HTTP API - Drivers/Bolt Protocol 21DEVSPACE 2017 | @tbrantb
- 22. Cypher - Declarative Graph Query Language - Originated at Neo Technology - Standardizing at OpenCypher.org - Ascii Art-ish 22DEVSPACE 2017 | @tbrantb
- 23. Ascii Art-ish ? - () look like circles or nodes - --, -->, <-- look like relationships or edges 23 MATCH (a)-->(b) WHERE a.name = 'Bob' RETURN b DEVSPACE 2017 | @tbrantb
- 24. MATCH Clause 24 MATCH (a)-->(b) MATCH (a)-[:FRIEND]->(b) MATCH (a)<-[:FRIEND]-(b) MATCH (a)-[:FRIEND]-(b) DEVSPACE 2017 | @tbrantb
- 25. MATCH Clause with Labels 25 MATCH (p:Person)-[:DIRECTED]->(m:Movie) MATCH (a:Person)-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(d:Person) DEVSPACE 2017 | @tbrantb
- 26. WHERE 26 MATCH (p:Person)-[:DIRECTED]->(m:Movie) WHERE p.name = 'Ron Howard' AND p.born < 1955 MATCH (p:Person {name: 'Ron Howard'})-[:DIRECTED]->(m:Movie) DEVSPACE 2017 | @tbrantb
- 27. RETURN, ORDER BY, LIMIT 27 MATCH (p:Person {name: 'Ron Howard'})-[:DIRECTED]->(m:Movie) RETURN m.title, m.released, m.tagline ORDER BY m.title LIMIT 3 DEVSPACE 2017 | @tbrantb
- 28. Overall Read Query Structure 28 [MATCH WHERE] [OPTIONAL MATCH WHERE] [WITH [ORDER BY] [SKIP] [LIMIT]] RETURN [ORDER BY] [SKIP] [LIMIT] DEVSPACE 2017 | @tbrantb
- 29. CREATE 29 CREATE (matrix:Movie {title:'The Matrix', released:1999}) CREATE (keanu:Person {name:'Keanu Reeves', born:1964}) CREATE (keanu)-[:ACTED_IN]->(matrix) MATCH (matrix:Movie {title:'The Matrix'}), (keanu:Person {name:'Keanu Reeves'}) CREATE (keanu)-[:ACTED_IN]->(matrix) DEVSPACE 2017 | @tbrantb
- 30. UPDATE 30 MATCH (matrix:Movie {title:'The Matrix'}), (keanu:Person {name:'Keanu Reeves'}) SET matrix.tagline = 'Follow the White Rabbit', keanu.born = 1900 RETURN matrix, keanu //optional DEVSPACE 2017 | @tbrantb
- 31. DELETE 31 MATCH (p:Person{name: 'Keanu Reeves'}) DELETE p MATCH (p:Person{name: 'Keanu Reeves'})-[r]-() DELETE r, p MATCH (p:Person{name: 'Keanu Reeves'}) DETACH DELETE n DEVSPACE 2017 | @tbrantb
- 32. Remember our friends? 32DEVSPACE 2017 | @tbrantb
- 33. Who are Bob’s Friends SELECT p2.id, p2.name FROM person p1 JOIN person_relationship rel ON p1.id = rel.start_person_id AND p1.id = 1 --Bob AND rel.relationship_type=1 --Friend JOIN person p2 ON p2.id = rel.end_person_id 33 MATCH (b:Person {name:'Bob'})-[:FRIEND]->(f:Person) RETURN f.name DEVSPACE 2017 | @tbrantb
- 34. Who are the Friends of Bob’s Friends? SELECT p3.id, p3.name FROM person p1 JOIN person_relationship rel1 ON p1.id = rel1.start_person_id AND p1.id = 1 --Bob AND rel1.relationship_type = 1 --Friend JOIN person p2 ON p2.id = rel1.end_person_id JOIN person_relationship rel2 ON p2.id = rel2.start_person_id AND rel2.relationship_type = 1 --Friend JOIN person p3 ON p3.id = rel2.end_person_id 34 MATCH (b:Person {name:'Bob'})-[:FRIEND]->(f:Person)-[:FRIEND]->(fof:Person) RETURN DISTINCT fof.name MATCH (b:Person {name:'Bob'})-[:FRIEND *2]->(fof:Person) RETURN DISTINCT fof.name DEVSPACE 2017 | @tbrantb
- 35. Bob’s Friends’ Friends’ Friends to the N 35 MATCH (b:Person {name:'Bob'})-[:FRIEND *2]->(fof:Person) RETURN DISTINCT fof.name MATCH (b:Person {name:'Bob'})-[:FRIEND *]->(fof:Person) RETURN DISTINCT fof.name MATCH (b:Person {name:'Bob'})-[:FRIEND *..5]->(fof:Person) RETURN DISTINCT fof.name MATCH (b:Person {name:'Bob'})-[:FRIEND *2..5]->(fof:Person) RETURN DISTINCT fof.name DEVSPACE 2017 | @tbrantb
- 36. What is Bob’s Bacon # ? 36 MATCH path=shortestPath( (kb:Person {name:'Kevin Bacon'})-[*]-(b:Person {name:'Bob'}) ) RETURN length(path) DEVSPACE 2017 | @tbrantb
- 37. Resources - Developer Website - https://neo4j.com/developer/ - Neo4J Docs - https://neo4j.com/docs/ - Cypher Refcard - https://neo4j.com/docs/cypher-refcard/ - Neo4J Book (free) - Me @tbrantb on twitter 37