Downloaded 31 times
![Neo4j
–
[IS_A]
-‐>
Property
Graph](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-37-2048.jpg)
![(node)
–
[relaHonship]
-‐>
(node)](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-40-2048.jpg)
![(Aleks)
–
[FRIENDS_WITH]
-‐>
(Tarjei)](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-41-2048.jpg)
![Describe
what
you
want
to
retrieve
with
PATTERNS
(a)-‐[r]-‐>(b)](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-45-2048.jpg)
![(Aleks)
–
[FRIENDS_WITH]
-‐>
(Tarjei)](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-46-2048.jpg)
![Path
depth
(a)-‐[*]-‐>(b)](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-47-2048.jpg)
![Friend
of
friend...
MATCH
(aleks)-‐[r:KNOWS]-‐()-‐[r2:KNOWS]
-‐>(friend_of_friend)
WHERE
aleks.firstName=
'Aleks'
RETURN
friend_of_friend.firstName](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-54-2048.jpg)
![Friend
of
friend...
MATCH
(aleks)-‐[:KNOWS*2..2]-‐>(friend_of_friend)
WHERE
aleks.firstName=
'Aleks'
AND
NOT
(aleks)-‐[:KNOWS]-‐>(friend_of_friend)
RETURN
friend_of_friend.firstName](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-55-2048.jpg)
![SpringData
Neo4j
-‐
Repositories
public
interface
PersonRepository
extends
GraphRepository<Person>{
List<Person>
findByFirstName(String
firstName);
@Query("MATCH
(p:Person{firstName:{0}})
RETURN
p")
List<Person>
getPersonWithFirstName
(String
firstName);
@Query(
"MATCH
(p:Person{firstName:{0}})-‐[:knows]-‐>friends
"
+
"
RETURN
friends")
Iterable<Person>
findFriendsOfPerson(String
firstName);
}](https://image.slidesharecdn.com/neo4jandspringdatafeb2015-150220025146-conversion-gate02/75/Introduction-to-graph-databases-Neo4j-and-Spring-Data-English-2015-Edition-75-2048.jpg)
Uploaded byAleksander Stensby
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
The document provides an introduction to graph databases, focusing on Neo4j and Spring Data, highlighting their advantages over relational databases for handling complex relationships. It discusses key concepts such as graph structure, Cypher query language, and various applications including social media and recommendation systems. Additionally, it offers configuration examples for setting up Spring Data with Neo4j and emphasizes lessons learned from utilizing these technologies.
More Related Content
![Neo4j -[:LOVES]-> Cypher](https://cdn.slidesharecdn.com/ss_thumbnails/geekoutpublish-120615074720-phpapp02-thumbnail.jpg?width=640&height=640&fit=bounds)
Similar to Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
- 1. Introduc)on to graph databases, Neo4j and Spring Data Aleksander M. Stensby Monokkel A/S
- 2. • Aleksander M. Stensby • CEO in Monokkel AS • Previously COO in Integrasco AS • Working with search and data analysis since 2004 www.monokkel.io
- 3. • Daglig leder i Monokkel AS • Tidligere COO i Integrasco AS • Persistering, Prosessering og Presentasjon av data Persistence – Processing – PresentaHon
- 4. Agenda • Intro to graph databases and modelling • Neo4j and Cypher • SpringData Neo4j
- 5.
- 6. …when it comes to relaHons
- 7. RelaHonal databases are awesome when it comes to aggregaHon of data, schema mapping and tabular data!
- 8.
- 9. We have a tendency to force _all_ our problems into our relaHonal databases!
- 10.
- 11.
- 12.
- 13.
- 14. NoSQL • Key-‐value stores – Amazon Dynamo – Ex: Voldemort,... • BigTable clones – Google’s BigTable – Ex: Hbase, ... • Document databases – Lotus Notes – Ex: MongoDB, CouchDB
- 15. NoSQL • Graph databases – Euler and graph theory – Ex: Neo4j, VertexDB, AllegroGraph, Giraphe, OrientDB, etc...
- 16. NoSQL Size Complexity Graphs Document BigTable KV
- 17. NoSQL Size Complexity Graphs Document BigTable KV 90% Billions of nodes and rela)onships
- 18.
- 19.
- 20. Person ID Name Friends PersonID FriendID
- 21. Person ID Name Friends PersonID FriendID «Aleks»’s friends SELECT p1.Person FROM Person p1 JOIN Friends ON Friends.FriendID = p1.ID JOIN Person p2 ON Friends.PersonID = p2.ID WHERE p2.Name= 'Aleks'
- 22. Person ID Name Friends PersonID FriendID Friends with «Aleks» SELECT p1.Person FROM Person p1 JOIN Friends ON Friends.PersonID = p1.ID JOIN Person p2 ON Friends.FriendID = p2.ID WHERE p2.Name = 'Aleks'
- 23. Person ID Name Friends PersonID FriendID «Aleks»’s friends’ friends? SELECT p1.Person AS PERSON, p2.Person AS FRIEND_OF_FRIEND FROM Friends v1 JOIN Person p1 ON v1.PersonID = p1.ID JOIN Friends v2 ON v2.FriendID = v1.FriendID JOIN Person p2 ON v2.FriendID = p2. ID WHERE p1.Name = 'Aleks‘ AND v2.FriendID <> p1.ID
- 24. Source: Neo4j in AcHon 1,000,000 persons Depth RDBMS Neo4j Records 2 0.016 0.01 ~ 2500 3 30.267 0.168 ~ 110,000 4 1543.505 1.359 ~ 600,000 5 DNF 2.132 ~ 800,000
- 26. A graph database... • uses graph structures with – Nodes – RelaHonships – Apributes • to store informaHon! • Exellent for relaHonships – but not necessarily best at aggregaHng data
- 27. Graph databases and neo4j • Visual – Schema less! • Doubly-‐linked-‐lists – each node has a list of incoming and outgoing relaWonships • Direct lookup = O(1)
- 28. A graph stores data in nodes ALEKS TARJEI
- 29. Nodes are connected by relaWonships FRIENDS_WITH ALEKS TARJEI
- 30. Nodes have aributes ALEKS TARJEI Age: 29 First Name: Aleksander Last Name: Stensby Age: 30 First Name: Tarjei Last Name: Romtveit FRIENDS_WITH
- 31. RelaWonships can also have aributes ALEKS TARJEI Age: 29 First Name: Aleksander Last Name: Stensby Age: 30 First Name: Tarjei Last Name: Romtveit FRIENDS_WITH Since: 01.01.2004
- 32. RelaWonships can be bi-‐direcHonal ALEKS TARJEI Age: 29 First Name: Aleksander Last Name: Stensby Age: 30 First Name: Tarjei Last Name: Romtveit FRIENDS_WITH Since: 01.01.2004 FRIENDS_WITH Since: 01.01.2004
- 33. ALEKS TARJEI Age: 29 First Name: Aleksander Last Name: Stensby Age: 30 First Name: Tarjei Last Name: Romtveit FRIENDS_WITH Since: 01.01.2004
- 34. ALEKS TARJEI Age: 29 First Name: Aleksander Last Name: Stensby Type: Person Age: 30 First Name: Tarjei Last Name: Romtveit Type: Person FRIENDS_WITH Since: 01.01.2004 different types of nodes
- 35. Person Person Sport Programming language Drink Person
- 36. Some use cases • Social Media • RecommendaHons • Geo rouHng and logisHcs • Access management • Network management • Finance / Fraud
- 37. Neo4j – [IS_A] -‐> Property Graph
- 38. Neo4j 2.2.x • Currently early access milestone 4 • New page cache -‐> high concurrency • TransacHonal and batch write performance • Cost-‐Based OpHmizer for Cypher
- 40. (node) – [relaHonship] -‐> (node)
- 41. (Aleks) – [FRIENDS_WITH] -‐> (Tarjei)
- 42. Cypher "Make the simple things simple, and the complex things possible"
- 43. Intro to Cypher • START • MATCH • WHERE • RETURN • CREATE • DELETE • SET • FOREACH • WITH
- 44. MATCH <papern> WHERE RETURN
- 45. Describe what you want to retrieve with PATTERNS (a)-‐[r]-‐>(b)
- 46. (Aleks) – [FRIENDS_WITH] -‐> (Tarjei)
- 47.
- 48. START START n=node(1) RETURN n
- 49. MATCH MATCH (movie:Movie) RETURN movie
- 50. WHERE MATCH movie WHERE move.Htle = ‘Blade Runner' RETURN movie
- 51. START a=node(*) MATCH (a:Person) WHERE a.name='Danny DeVito' RETURN a
- 52. START a=node(*) MATCH (a:Person) WHERE a.name='Danny DeVito' RETURN a
- 53. START a=node(*) MATCH (a:Person {name: 'Danny DeVito'} ) WHERE a.name='Danny DeVito' RETURN a Neo4j 2.0.1
- 54. Friend of friend... MATCH (aleks)-‐[r:KNOWS]-‐()-‐[r2:KNOWS] -‐>(friend_of_friend) WHERE aleks.firstName= 'Aleks' RETURN friend_of_friend.firstName
- 55. Friend of friend... MATCH (aleks)-‐[:KNOWS*2..2]-‐>(friend_of_friend) WHERE aleks.firstName= 'Aleks' AND NOT (aleks)-‐[:KNOWS]-‐>(friend_of_friend) RETURN friend_of_friend.firstName
- 56.
- 57.
- 58. And a whole lot more… • Traversals to navigate the graph • Traversals idenHfy paths • Paths order nodes • Cypher parameters • Indexes • Neo4j embedded, Neo4j REST • Neo4j 2.x – Labels and automaWc indexes • Gremlin (procedural) – Cypher (declaraHve) • Enterprise (mulH-‐instance cluster, online backup) • Neo4j SpaWal
- 59.
- 60.
- 62. Intro to SpringData Neo4j • SpringData • Repositories • Quick example <dependencies> <dependency> <groupId>org.springframework.data</groupId> <arHfactId>spring-‐data-‐neo4j</arHfactId> <version>3.2.2.RELEASE</version> </dependency> </dependencies> neo4j 2.1.7 spring-‐data-‐neo4j 3.2.2 spring 4.1.4
- 63. SpringData Neo4j Config @Configuration @EnableNeo4jRepositories("no.stensby.javabin.neo.repositories") public class Config extends Neo4jConfiguration { } @Autowired protected Neo4jTemplate template;
- 64. SpringData Neo4j Config @Configuration @EnableNeo4jRepositories("no.stensby.javabin.neo.repositories") public class Config extends Neo4jConfiguration { public Config (){ setBasePackage("no.stensby.javabin.neo.domain"); } } @Autowired protected Neo4jTemplate template;
- 65. SpringData Neo4j Config @Bean GraphDatabaseService graphDatabaseService() { return new GraphDatabaseFactory().newEmbeddedDatabase("tmp/neo4j"); } Embedded: REST: @Bean GraphDatabaseService graphDatabaseService() { return new SpringRestGraphDatabase("http://localhost:7474/db/data"); } @Bean(destroyMethod = "shutdown") @Scope(SCOPE_PROTOTYPE) public GraphDatabaseService graphDatabaseService() { return new TestGraphDatabaseFactory().newImpermanentDatabase(); } TEST:
- 66. SpringData Neo4j -‐ Domain @NodeEntity public class Person { @GraphId public Long nodeId; @Indexed(unique = true) public int id; public String firstName; public String lastName; }
- 67. 1-‐1 relaHonships @NodeEntity public class Address { private Country country; ... }
- 68. 1-‐1 relaHonships @NodeEntity public class Address { @Fetch private Country country; ... }
- 69. 1-‐m relaHonships -‐ @RelatedTo @RelatedTo(type = "ADDRESS") private Set<Address> addresses = new HashSet<Address>(); @RelatedTo private Set<Person> venner = new HashSet<Person> ();
- 70. m-‐m relaHonships -‐ @RelatedToVia @Fetch @RelatedToVia (type = "ACTS_IN") Set<Role> roles = new HashSet<Role>(); @Fetch @RelatedToVia(type = "ACTS_IN", direction = Direction.INCOMING) Set<Role> cast = new HashSet<Role>(); Actor Movie @RelationshipEntity(type = "ACTS_IN") public class Role { @GraphId Long nodeId; @StartNode Actor actor; @EndNode Movie movie; Role
- 71. SpringData Neo4j -‐ Repositories GraphRepository<Person> personRepository = template.repositoryFor(Person.class); @Autowired Neo4jTemplate template;
- 72. SpringData Neo4j -‐ Repositories public interface PersonRepository extends GraphRepository<Person>{} @Autowired PersonRepository repository;
- 73. SpringData Neo4j -‐ Repositories public interface PersonRepository extends GraphRepository<Person>{ List<Person> findByFirstName(String firstName); }
- 74. SpringData Neo4j -‐ Repositories public interface PersonRepository extends GraphRepository<Person>{ List<Person> findByFirstName(String firstName); @Query("MATCH (p:Person{firstName:{0}}) RETURN p") List<Person> getPersonWithFirstName (String firstName); }
- 75. SpringData Neo4j -‐ Repositories public interface PersonRepository extends GraphRepository<Person>{ List<Person> findByFirstName(String firstName); @Query("MATCH (p:Person{firstName:{0}}) RETURN p") List<Person> getPersonWithFirstName (String firstName); @Query( "MATCH (p:Person{firstName:{0}})-‐[:knows]-‐>friends " + " RETURN friends") Iterable<Person> findFriendsOfPerson(String firstName); }
- 76. Lessons Learned • Be careful with versions and upgrading … – Neo 1.9.x -‐> Neo 2.x = lots of problems… – Lots of breaking changes… – Spring Data Neo4j != Neo4j • Nodes are “first-‐class” ciHzens in the graph – Hyperedges are not supported -‐> use “event nodes” • AggregaHons are expensive – caching stats on nodes! • Unique and expressive relaHonship types
- 77. Pi•alls • Don’t use the graphid as your ID • IniHalize Set • Use @Fetch with care • Use standard gepers/sepers • Be careful with String escaping
- 78. InspiraHon • Single Malt Scotch Whisky hpp://gist.neo4j.org/?8139605 • Chess Games and PosiWons hpp://gist.neo4j.org/?6506717 • Movie RecommendaWons hpp://gist.neo4j.org/?8173017 • Food Recipes RecommendaWon hpp://gist.neo4j.org/?8731452