Modelling Data as Graphs (Neo4j)
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Modelling Data in Neo4j for beginners, common mistakes, frequently asked questions, hardware sizing and a few extra tips
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Modelling Data as Graphs (Neo4j)
- 1. GraphAware TM by Michal Bachman a few best practices and lessons learned Modelling Data in Neo4j
- 3. GraphAware TM Ride-sharing website History of rides Friendships from Facebook Aim: build trust between users Example Domain
- 4. GraphAware TM There is no single correct way. Modelling Data as Graphs
- 5. GraphAware TM Graphs are very whiteboard friendly. Modelling Data as Graphs
- 6. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF name: “Peter” User DROVE name: “Alice” User DROVE
- 7. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF name: “Peter” User DROVE name: “Alice” User DROVE name: “Jenny” User DROVE
- 8. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF name: “Peter” User DROVE name: “Alice” User DROVE name: “Jenny” User DROVE date: 2014-01-29date: 2014-01-29date: 2014-01-27
- 9. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF name: “Peter” User DROVE name: “Alice” User DROVE name: “Jenny” User DROVE date: 2014-01-29date: 2014-01-29date: 2014-01-27 RODE_TOGETHER RODE_TOGETHER
- 10. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER
- 11. GraphAware TM Make important concepts in your domain nodes, you will gain flexibility. Nodes vs. Relationships
- 12. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER
- 13. ipsum FRIEND_OF name: “Michael” User name: “Laura” User FRIEND_OF date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: 5RATED rating: 3
- 14. ipsum FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: 5RATED rating: 3
- 15. ipsum FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: 5RATED rating: 3
- 20. DEFEATED Czech Republic Sweden DEFEATED_BY GraphAware TM Ice HockeyIce Hockey (Implied Relationship)
- 21. PARTNERNeo Technology GraphAware PARTNERNeo Technology GraphAware GraphAware TM Company Partnership (Naturally Bidirectional)
- 22. PARTNER Neo Technology GraphAware PARTNER GraphAware TM Company Partnership (Naturally Bidirectional)
- 23. PARTNER Neo Technology GraphAware PARTNER GraphAware TM Company Partnership (Naturally Bidirectional)
- 26. GraphAware TM In Neo4j, the speed of traversal does not depend on the direction of the relationships being traversed. Traversal Speed
- 28. GraphAware TM Node Record in the Node Store (9 bytes), first bit = inUse flag Relationship Record in the Relationship Store (33 bytes), first bit = inUse flag, second bit unused next relationship (35 bits) next property (36 bits) first node (35 bits) second node (35 bits) type (16 bits) first node's previous relationship (35 bits) first node's next relationship (35 bits) second node's first relationship (35 bits) second node's next relationship (35 bits) next property (36 bits) Neo4j Data Layout
- 29. GraphAware TM Neo4j APIs allow developers to completely ignore relationship direction when querying the graph. Traversal APIs
- 33. GraphAware TM Different quality in each direction => should have two relationships! Heads Up! LOVES Geeky Guy Girl DOESN’T CARE ABOUT
- 34. ipsum FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: 5RATED rating: 3
- 35. ipsum FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: ?RATED rating: 3 HATED DISLIKED NEUTRAL LIKED LOVED
- 36. FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER LOVED NEUTRAL
- 38. ipsum FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER RATED rating: 5RATED rating: 3 Qualifying by Properties
- 39. GraphAware TM START ride=node({id}) MATCH (ride)<-‐[r:RATED]-‐(passenger) WHERE r.rating > 3 RETURN passenger Who liked the ride? (Cypher)
- 40. GraphAware TM for (Relationship r : ride.getRelationships(INCOMING, RATED)) { if ((int) r.getProperty("rating") > 3) { Node passenger = r.getStartNode(); //do something with it } } Who liked the ride? (Java)
- 41. FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER LOVED NEUTRAL Qualifying by Relationship Type
- 42. GraphAware TM START ride=node({id}) MATCH (ride)<-‐[r:LIKED|LOVED]-‐(passenger) RETURN passenger Who liked the ride? (Cypher)
- 43. GraphAware TM for (Relationship r : ride.getRelationships(INCOMING, LIKED, LOVED)) { Node passenger = r.getStartNode(); //do something with it } Who liked the ride? (Java)
- 44. GraphAware TM
- 45. GraphAware TM
- 46. FRIEND_OF name: “Michael” User name: “Laura” User date: 2014-01-29 from: “London” to: “Nottingham” Ride DRIVER name: “Alice” User PASSENGER date: 2014-01-27 from: “Brighton” to: “Hastings” Ride PASSENGER name: “Peter” User PASSENGER name: “Jenny” User DRIVER LOVED NEUTRAL Winner!
- 49. GraphAware TM HDD Record Files Transaction Log Operating System JVM Neo4j Object Cache Core API Other APIs Transaction Management File System Cache Nodes Relationships Properties Relationship Types Neo4j Architecture
- 50. GraphAware TM > cd data > ls -‐ah Disk Space
- 51. GraphAware TM drwxr-‐xr-‐x 5 bachmanm wheel 170B 19 Oct 12:56 index -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 31K 19 Oct 12:56 messages.log -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 69B 19 Oct 12:56 neostore -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 8.8K 19 Oct 12:56 neostore.nodestore.db -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.nodestore.db.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 39M 19 Oct 12:56 neostore.propertystore.db -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 153B 19 Oct 12:56 neostore.propertystore.db.arrays -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.propertystore.db.arrays.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.propertystore.db.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 43B 19 Oct 12:56 neostore.propertystore.db.index -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.propertystore.db.index.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 140B 19 Oct 12:56 neostore.propertystore.db.index.keys -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.propertystore.db.index.keys.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 154B 19 Oct 12:56 neostore.propertystore.db.strings -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.propertystore.db.strings.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 31M 19 Oct 12:56 neostore.relationshipstore.db -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.relationshipstore.db.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 38B 19 Oct 12:56 neostore.relationshiptypestore.db -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.relationshiptypestore.db.id -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 140B 19 Oct 12:56 neostore.relationshiptypestore.db.names -‐rw-‐r-‐-‐r-‐-‐ 1 bachmanm wheel 9B 19 Oct 12:56 neostore.relationshiptypestore.db.names.id Disk Space
- 52. GraphAware TM Disk Space node 14B relationship 33B property 41B
- 53. GraphAware TM Disk Space (Example) 1,000 nodes x 14B = 13.7 kB 1,000,000 rels x 33B = 31.5 MB 2,010,000 props x 41B = 78.6 MB TOTAL 110.1 MB
- 54. GraphAware TM How about low level cache? Any guesses? Low Level Cache
- 55. GraphAware TM Same as disk space Low Level Cache
- 56. GraphAware TM High Level Cache node 344B relationship 208B property 116B ...
- 58. GraphAware TM Cypher is great! Cypher is improving But don’t be afraid of writing some Java Java API vs. Cypher
- 61. GraphAware TM Next meetup • The transport graph – Roads, Nodes and Automobiles (Jacqui Read) – Transport Network Route Finding Using A Graph (Ian Cartwright & Ben Earlham) • 26th February 2014 • Here!
- 62. GraphAware TM
- 63. GraphAware TM Ian Robinson, Jim Webber & Emil Eifrem Graph Databases h Com plim ents ofNeo Technology
- 64. GraphAware TM Take me to the pub…