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Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
Eifrem neo4j
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Eifrem neo4j

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presentation on Nodes and relationships

presentation on Nodes and relationships

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  • 1. Neo4j the benefits ofgraph databases
  • 2. Whats the plan? Why now? – Four trends NoSQL overview Graph databases && Neo4j Conclusions Food
  • 3. 988Trend 1:data set size402007 2010
  • 4. Trend 2: connectedness Giant Global Graph (GGG) Information connectivity Ontologies RDF Folksonomies Tagging Wikis User- generated content Blogs RSS Hypertext Text documents web 1.0 web 2.0 “web 3.0” 1990 2000 2010 2020
  • 5. Trend 3: semi-structure Individualization of content! In the salary lists of the 1970s, all elements had exactly one job In the salary lists of the 2000s, we need 5 job columns! Or 8? Or 15? Trend accelerated by the decentralization of content generation that is the hallmark of the age of participation (“web 2.0”)
  • 6. Aside: RDBMS performance Relational database Performance Salary List Majority of Webapps Social network } Semantic Trading custom Data complexity
  • 7. Trend 4: architecture 1990s: Database as integration hub
  • 8. Trend 4: architecture 2000s: (Slowly towards...) Decoupled services with own backend
  • 9. Why NoSQL 2009? Trend 1: Size. Trend 2: Connectivity. Trend 3: Semi-structure. Trend 4: Architecture.
  • 10. NoSQLoverview
  • 11. First off: the damn name NoSQL is NOT “Never SQL” NoSQL is NOT “No To SQL” NoSQL is NOT “WE HATE CHRIS DOG”
  • 12. NoSQL is simplyot nly !
  • 13. Four (emerging) NoSQL categories Key-value stores Based on Amazons Dynamo paper Data model: (global) collection of K-V pairs Example: Dynomite, Voldemort, Tokyo BigTable clones Based on Googles BigTable paper Data model: big table, column families Example: Hbase, Hypertable
  • 14. Four (emerging) NoSQL categories Document databases Inspired by Lotus Notes Data model: collections of K-V collections Example: CouchDB, MongoDB Graph databases Inspired by Euler & graph theory Data model: nodes, rels, K-V on both Example: AllegroGraph, VertexDB, Neo4j
  • 15. NoSQL data models Size Key-value stores Bigtable clones Document databases Graph databases Complexity
  • 16. NoSQL data models Size Key-value stores Bigtable clones Document databases Graph databases (This is still of 90% nodes & relationships) of usecases Complexity
  • 17. Graph DBs& Neo4j intro
  • 18. The Graph DB model: representation Core abstractions: name = “Emil” age = 29 Nodes sex = “yes” Relationships between nodes Properties on both type = KNOWS time = 4 years type = car vendor = “SAAB” model = “95 Aero”
  • 19. Example: The Matrix name = “The Architect” name = “Morpheus” rank = “Captain” occupation = “Total badass”name = “Thomas Anderson”age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY WS KN S KNO W OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ name = “Trinity”
  • 20. Code (1): Building a node spaceNeoService neo = ... // Get factory// Create Thomas Neo AndersonNode mrAnderson = neo.createNode();mrAnderson.setProperty( "name", "Thomas Anderson" );mrAnderson.setProperty( "age", 29 );// Create MorpheusNode morpheus = neo.createNode();morpheus.setProperty( "name", "Morpheus" );morpheus.setProperty( "rank", "Captain" );morpheus.setProperty( "occupation", "Total bad ass" );// Create a relationship representing that they know each othermrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS );// ...create Trinity, Cypher, Agent Smith, Architect similarly
  • 21. Code (1): Building a node spaceNeoService neo = ... // Get factoryTransaction tx = neo.beginTx();// Create Thomas Neo AndersonNode mrAnderson = neo.createNode();mrAnderson.setProperty( "name", "Thomas Anderson" );mrAnderson.setProperty( "age", 29 );// Create MorpheusNode morpheus = neo.createNode();morpheus.setProperty( "name", "Morpheus" );morpheus.setProperty( "rank", "Captain" );morpheus.setProperty( "occupation", "Total bad ass" );// Create a relationship representing that they know each othermrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS );// ...create Trinity, Cypher, Agent Smith, Architect similarlytx.commit();
  • 22. Code (1b): Defining RelationshipTypes// In package org.neo4j.api.corepublic interface RelationshipType{ String name();}// In package org.yourdomain.yourapp// Example on how to roll dynamic RelationshipTypesclass 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-likeenum MyStaticRelTypes implements RelationshipType{ KNOWS, WORKS_FOR,}
  • 23. Whiteboard friendly owns Björn Big Car build drives DayCare
  • 24. The Graph DB model: traversal Traverser framework for name = “Emil” high-performance traversing age = 29 sex = “yes” across the node space type = KNOWS time = 4 years type = car vendor = “SAAB” model = “95 Aero”
  • 25. Example: Mr Andersonʼs friends name = “The Architect” name = “Morpheus” rank = “Captain” occupation = “Total badass”name = “Thomas Anderson”age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY WS KN S KNO W OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ name = “Trinity”
  • 26. Code (2): Traversing a node space// Instantiate a traverser that returns Mr Andersons friendsTraverser 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 resultSystem.out.println( "Mr Andersons friends:" );for ( Node friend : friendsTraverser ){ System.out.printf( "At depth %d => %s%n", friendsTraverser.currentPosition().getDepth(), friend.getProperty( "name" ) );}
  • 27. name = “The Architect” name = “Morpheus” rank = “Captain” occupation = “Total badass” name = “Thomas Anderson” age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY WS KN S KNO W OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” disclosure = secret version = 1.0b age = 3 days age = 6 months language = C++ name = “Trinity” $ bin/start-neo-example Mr Andersons friends: At depth 1 => MorpheusfriendsTraverser = 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 ); $
  • 28. Example: Friends in love? name = “The Architect” name = “Morpheus” rank = “Captain” occupation = “Total badass”name = “Thomas Anderson”age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY WS KN S K NO W OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” LO disclosure = secret version = 1.0b VE language = C++ S age = 6 months name = “Trinity”
  • 29. 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 );
  • 30. Code (3a): Custom traverser// Traverse the node space and print out the resultSystem.out.println( "Who’s a lover?" );for ( Node person : loveTraverser ){ System.out.printf( "At depth %d => %s%n", loveTraverser.currentPosition().getDepth(), person.getProperty( "name" ) );}
  • 31. name = “The Architect” name = “Morpheus” rank = “Captain” occupation = “Total badass” name = “Thomas Anderson” age = 29 disclosure = public KNOWS KNOWS KNO CODED_BY WS KN S K NO W OW name = “Cypher” S last name = “Reagan” name = “Agent Smith” LO disclosure = secret version = 1.0b VE language = C++ S age = 6 months name = “Trinity” $ bin/start-neo-example Who’s a lover?new ReturnableEvaluator(){ public boolean isReturnableNode( At depth 1 => Trinity TraversalPosition pos) { $ return pos.currentNode(). hasRelationship( RelTypes. LOVES, Direction .OUTGOING ); }},
  • 32. 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.yourappclass PersonImpl implements Person{ private final Node underlyingNode; PersonImpl( Node node ){ this.underlyingNode = node; } public String getName() { return this.underlyingNode.getProperty( "name" ); } public void setName( String name ) { this.underlyingNode.setProperty( "name", name ); }}
  • 33. Domain layer frameworks Qi4j (www.qi4j.org) Framework for doing DDD in pure Java5 Defines Entities / Associations / Properties Sound familiar? Nodes / Relʼs / Properties! Neo4j is an “EntityStore” backend NeoWeaver (http://components.neo4j.org/neo-weaver) Weaves Neo4j-backed persistence into domain objects in runtime (dynamic proxy / cglib based) Veeeery alpha
  • 34. 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 (whats the x and the y?) Several billions of nodes/rels/props on single JVM Robust 6+ years in 24/7 production
  • 35. Social network pathExists() ~1k persons Avg 50 friends per person pathExists(a, b) limit depth 4 Two backends Eliminate disk IO so warm up caches
  • 36. Social network pathExists() Emil Mike Kevin John Marcus Bruce Leigh # persons query timeRelational database 1 000 2 000 msGraph database (Neo4j) 1 000 2 msGraph database (Neo4j) 1 000 000 2 ms
  • 37. Pros & Cons compared to RDBMS+ No O/R impedance mismatch (whiteboard friendly)+ Can easily evolve schemas+ Can represent semi-structured info+ Can represent graphs/networks (with performance)- Lacks in tool and framework support- Few other implementations => potential lock in- No support for ad-hoc queries
  • 38. Language bindings Neo4j.py – bindings for Jython and CPython http://components.neo4j.org/neo4j.py Neo4jrb – bindings for JRuby (incl RESTful API) http://wiki.neo4j.org/content/Ruby Clojure http://wiki.neo4j.org/content/Clojure Scala (incl RESTful API) http://wiki.neo4j.org/content/Scala … .NET? Erlang?
  • 39. Grails Neoclipse screendump
  • 40. Conclusion Graphs && Neo4j => teh awesome! Available NOW under AGPLv3 / commercial license AGPLv3: “if youʼre open source, weʼre open source” If you have proprietary software? Must buy a commercial license But up to 1M primitives itʼs free for all uses! Download http://neo4j.org Feedback http://lists.neo4j.org
  • 41. Poop 1 Key-value stores? => the awesome … if you have 1000s of BILLIONS records OR you dont care about programmer productivity What if you had no variables at all in your programs except a single globally accessible hashtable? Would your software be maintainable?
  • 42. Poop 2 In a not-suck architecture... … the only thing that makes sense is to have an embedded database.
  • 43. Looking ahead: polyglot persistence
  • 44. Questions? Image credit: lost again! Sorry :(
  • 45. http://neotechnology.com

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