An intro to Neo4j and some use cases (JFokus 2011)
15 likes6,519 views
An introduction to Neo4j and graph databases, including some use cases. Presentation from JFokus 2011.
Ad
More Related Content
Viewers also liked (19)
More from Emil Eifrem (12)
Ad
An intro to Neo4j and some use cases (JFokus 2011)
- 1. Neo4j - or, why graph dbs are teh AWESOME!!!11 oh, and also... USE CASES!!! #neo4j Emil Eifrem @emileifrem Neo Technology [email protected]
- 2. What's the plan? An intro to graph databases and Neo4j Brief review of some use cases Conclusion and Q&A
- 3. Graph DBs & Neo4j intro
- 4. The Graph DB model: representation Core abstractions: name = “Emil” Nodes age = 29 sex = “yes” Relationships between nodes Properties on both 1 2 type = KNOWS time = 4 years 3 type = car vendor = “SAAB” model = “95 Aero”
- 5. Example: The Matrix name = “The Architect” name = “Morpheus” rank = “Captain” name = “Thomas Anderson” occupation = “Total badass” 42 age = 29 disclosure = public KNOWS KNOWS CODED_BY KNO 1 7 3 W S KN 13 S OW name = “Cypher” KNOW S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ 2 name = “Trinity”
- 6. Code (1): Building a node space GraphDatabaseService graphDb = ... // Get factory // Create Thomas 'Neo' Anderson Node mrAnderson = graphDb.createNode(); mrAnderson.setProperty( "name", "Thomas Anderson" ); mrAnderson.setProperty( "age", 29 ); // Create Morpheus Node morpheus = graphDb.createNode(); morpheus.setProperty( "name", "Morpheus" ); morpheus.setProperty( "rank", "Captain" ); morpheus.setProperty( "occupation", "Total bad ass" ); // Create a relationship representing that they know each other mrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS ); // ...create Trinity, Cypher, Agent Smith, Architect similarly
- 7. Code (1): Building a node space GraphDatabaseService graphDb = ... // Get factory Transaction tx = graphDb.beginTx(); // Create Thomas 'Neo' Anderson Node mrAnderson = graphDb.createNode(); mrAnderson.setProperty( "name", "Thomas Anderson" ); mrAnderson.setProperty( "age", 29 ); // Create Morpheus Node morpheus = graphDb.createNode(); morpheus.setProperty( "name", "Morpheus" ); morpheus.setProperty( "rank", "Captain" ); morpheus.setProperty( "occupation", "Total bad ass" ); // Create a relationship representing that they know each other mrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS ); // ...create Trinity, Cypher, Agent Smith, Architect similarly tx.commit();
- 8. Code (1b): Def ning RelationshipTypes i // In package org.neo4j.graphdb public interface RelationshipType { String name(); } // In package org.yourdomain.yourapp // Example on how to roll dynamic RelationshipTypes class MyDynamicRelType implements RelationshipType { private final String name; MyDynamicRelType( String name ){ this.name = name; } public String name() { return this.name; } } // Example on how to kick it, static-RelationshipType-like enum MyStaticRelTypes implements RelationshipType { KNOWS, WORKS_FOR, }
- 9. Whiteboard friendly owns Björn Big Car build drives DayCare
- 10. The Graph DB model: traversal Traverser framework for high-performance traversing name = “Emil” age = 31 across the node space sex = “yes” 1 2 type = KNOWS time = 4 years 3 type = car vendor = “SAAB” model = “95 Aero”
- 11. Example: Mr Anderson’s friends name = “The Architect” name = “Morpheus” rank = “Captain” name = “Thomas Anderson” occupation = “Total badass” 42 age = 29 disclosure = public KNOWS KNOWS CODED_BY KNO 1 7 3 W S KN 13 S OW name = “Cypher” KNOW S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ 2 name = “Trinity”
- 12. Code (2): Traversing a node space // Instantiate a traverser that returns Mr Anderson's friends Traverser friendsTraverser = mrAnderson.traverse( Traverser.Order.BREADTH_FIRST, StopEvaluator.END_OF_GRAPH, ReturnableEvaluator.ALL_BUT_START_NODE, RelTypes.KNOWS, Direction.OUTGOING ); // Traverse the node space and print out the result System.out.println( "Mr Anderson's friends:" ); for ( Node friend : friendsTraverser ) { System.out.printf( "At depth %d => %s%n", friendsTraverser.currentPosition().getDepth(), friend.getProperty( "name" ) ); }
- 13. name = “The Architect” name = “Morpheus” rank = “Captain” name = “Thomas Anderson” occupation = “Total badass” 42 age = 29 disclosure = public KNOWS KNOWS CODED_BY KNO 1 7 3 W S KN 13 S OW name = “Cypher” KNOW S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ 2 name = “Trinity” $ bin/start-neo-example Mr Anderson's friends: At depth 1 => Morpheus friendsTraverser = mrAnderson.traverse( Traverser.Order.BREADTH_FIRST, At depth 1 => Trinity StopEvaluator.END_OF_GRAPH, At depth 2 => Cypher ReturnableEvaluator.ALL_BUT_START_NODE, RelTypes.KNOWS, At depth 3 => Agent Smith Direction.OUTGOING ); $
- 14. Example: Friends in love? name = “The Architect” name = “Morpheus” rank = “Captain” name = “Thomas Anderson” occupation = “Total badass” 42 age = 29 disclosure = public KNOWS KNOWS CODED_BY KNO 1 7 3 W S KN 13 S KNOW OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” LO disclosure = secret version = 1.0b VE age = 6 months language = C++ S 2 name = “Trinity”
- 15. Code (3a): Custom traverser // Create a traverser that returns all “friends in love” Traverser loveTraverser = mrAnderson.traverse( Traverser.Order.BREADTH_FIRST, StopEvaluator.END_OF_GRAPH, new ReturnableEvaluator() { public boolean isReturnableNode( TraversalPosition pos ) { return pos.currentNode().hasRelationship( RelTypes.LOVES, Direction.OUTGOING ); } }, RelTypes.KNOWS, Direction.OUTGOING );
- 16. Code (3a): Custom traverser // Traverse the node space and print out the result System.out.println( "Who’s a lover?" ); for ( Node person : loveTraverser ) { System.out.printf( "At depth %d => %s%n", loveTraverser.currentPosition().getDepth(), person.getProperty( "name" ) ); }
- 17. name = “The Architect” name = “Morpheus” rank = “Captain” name = “Thomas Anderson” occupation = “Total badass” 42 age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY 1 7 3 W S KN 13 S name = “Cypher” KNOW OW S last name = “Reagan” name = “Agent Smith” LO disclosure = secret version = 1.0b VE age = 6 months language = C++ S 2 name = “Trinity” $ bin/start-neo-example new ReturnableEvaluator() Who’s a lover? { public boolean isReturnableNode( TraversalPosition pos) At depth 1 => Trinity { $ return pos.currentNode(). hasRelationship( RelTypes.LOVES, Direction.OUTGOING ); } },
- 18. Bonus code: domain model How do you implement your domain model? Use the delegator pattern, i.e. every domain entity wraps a Neo4j primitive: // In package org.yourdomain.yourapp class PersonImpl implements Person { private final Node underlyingNode; PersonImpl( Node node ){ this.underlyingNode = node; } public String getName() { return (String) this.underlyingNode.getProperty( "name" ); } public void setName( String name ) { this.underlyingNode.setProperty( "name", name ); } }
- 19. Domain layer frameworks Qi4j (www.qi4j.org) Framework for doing DDD in pure Java5 Def nes Entities / Associations / Properties i Sound familiar? Nodes / Rel’s / Properties! Neo4j is an “EntityStore” backend Jo4neo (http://code.google.com/p/jo4neo) Annotation driven Weaves Neo4j-backed persistence into domain objects at runtime S pring D a ta G ra ph (http://www.springsource.org/spring-data) Collaboration with SpringSource Annotation driven, AspectJ based
- 20. Neo4j system characteristics Disk-based Native graph storage engine with custom binary on-disk format Transactional JTA/JTS, XA, 2PC, Tx recovery, deadlock detection, MVCC, etc Scales up Many billions of nodes/rels/props on single JVM Robust 7+ years in 24/7 production
- 21. M'kay... but what are some use cases?
- 22. Social data (customer: e.g. EU largest social network) name = “Marcy Runkle” name = “Hank” last_name = “Moody” name = “Mike” age = 42 42 age = 29 S W NO disclosure = public K KNOWS KNOWS KNO 1 7 3 W S KN 13 S OW name = “Charlie” KNOW S last_name = “Runkle” name = “Dani” last_name = “California” age = 3 days age = 27 2 name = “Karen”
- 23. Just a social graph?
- 24. Spatial data (customer: large telecom company) name = ... name = “The Tavern” lat = 1295238237 name = “Omni Hotel” long = 234823492 42 lat = 3492848 long = 283823423 length = 7 miles AD RO ROAD ROAD ROO 1 7 3 OAD RO 13 AD name = ... ROAD lat, long = ... name = “Swedland” lat = 23410349 length = 3 miles long = 2342348852 2 name = ...
- 25. Social? Spatial? … Social AND spatial!
- 26. Social AND spatial data (customer: LBS) name = “Peter” name = “The Tavern” lat = 1295238237 name = “Omni Hotel” long = 234823492 42 lat = 3492848 S W NO long = 283823423 weight = 10 K ROAD LIKES SIBL 1 7 3 IN G RO 13 AD name = “Emil” ROAD beer_qual = expert name = “Maria” age = 30 length = 3 miles beer_qual = non-existant 2 name = ...
- 27. Financial data (customer: international bank) name = ... name = “The Tavern” lat = 1295238237 long = 234823492 42 name = “Mr Godfather” AW karma = veeeery-low HDR cash = more-than-you amount = $1000 IT W OWNS TRANSFER WIT 1 7 3 HDR AW 13 S FE R DE name = “Emil” P OS cash = always-too-li'l IT TRAN title = “ATM @ Wall St” id = 230918484233 amount = $1000 cash_left = 384204 2 name = ...
- 28. Cute. But what about performance? name = ... name = “The Tavern” lat = 1295238237 long = 234823492 42 name = “Mr Godfather” AW karma = veeeery-low HDR cash = more-than-you amount = $1000 IT W WITHDRAW TRANSFER WIT 1 7 3 HDR AW 13 S FE R DE name = “Emil” P OS cash = always-too-li'l IT TRAN title = “ATM @ Wall St” id = 230918484233 amount = $1000 cash_left = 384204 2 name = ... pathExists(a, b, 5) # nodes query time Relational database (MySQL) 1 000 2 000 ms Graph database (Neo4j) 1 000 2 ms Graph database (Neo4j) 1 000 000 2 ms
- 29. How ego are you? (aka other impls?) Franz’ A lle g roG ra ph (http://agraph.franz.com) Proprietary, Lisp, RDF-oriented but real graphdb Sones g ra phD B (http://sones.com) .NET, open source version available Twitter's Flo c k D B (http://github.com/twitter/flockdb) Twitter's graph database for large and shallow graphs Sparsity Technologies D ex (http://sparsitytechnologies.com) New on the scene, spun out of Spanish university Objectivity I nfiniteG ra ph (http://infinitegraph.com) Graph db on-top-of OODB
- 30. Conclusion Graphs && Neo4j => teh awesome! Available NOW under AGPLv3 / commercial license AGPLv3: “if you’re open source, we’re open source” If you have proprietary software? Must buy a commercial license But the first one is free! Download http://neo4j.org Feedback http://lists.neo4j.org
- 32. T he N eo 4j tea m is hiring ! Do you see the Matrix? Apply now.
- 33. Questions? Image credit: lost again! Sorry :(