Going from relational databases to databases with relations with Neo4j and Spring Data

* Demo: https://
github.com/michael-simons/bootiful-music
* A series of blog posts: From relational databases to databases with relations
https://info.michael-simons.eu/2018/10/11/from-relational-databases-to-databases-with-relations/
* Curated set of SDN / OGM tips: 
https://github.com/michael-simons/neo4j-sdn-ogm-tips
* (German) Spring Boot Book: 
@SpringBootBuch // http://springbootbuch.de

Relational databases still have many use cases. Either being able to handle complex aggregations of time series, dealing with sums, products, either over all tuples or with moving windows. RDBMs are unbeaten handling huge sets with a relatively small number of joins. There has been quite the renaissance of SQL and RDBMs in the past years (and the presenter of this talk might not be innocent here), but there's one type of store whose qualities are not beaten by RDBMs: Graph Databases.

Graph databases like Neo4j have several features that no other store has. They are the first choice if your application deals with a lot of real relations, stores object trees that should be queryable and much more. Objects corresponds to nodes and relations are just that. Neo4j facilitates the use of both through its query language Cypher: An easy to learn, pattern matching query language.

In this talk I'll present my approach to Neo4j, Object Graph Mapper (OGM) and Spring Data Neo4j (SDN), coming from a relational background. I'll explain the building blocks of SDN, present different ways to to turn some or all of your relational data into a graph and access it from a Spring Boot based application.

Transcript

1. Going from relational databases to databases with relations
 Michael Simons, @rotnroll666 Neo4j and Spring Data
2. • About Neo4j • My „business“ domain • Getting data into Neo4j • Some options to access Neo4j on the JVM • Spring Data Neo4j • Some advanced queries Agenda 2
3. About Neo4j
4. • Neo4j is the #1 platform for connected data. • Neo4j powers the next generation of applications and analytics • Prominent use cases are found in areas like machine learning, personalized recommendations, fraud detection, data governance and more. Neo4j 4
5. Ecosystem Neo4j Professional Services 300+ partners 47,000 group members 61,000 trained engineers 3.5M downloads Mindset “Graph Thinking” is all about considering connections in data as important as the data itself. Native Graph Platform Neo4j is an internet-scale, native graph database which executes connected workloads faster than any other database management system. Neo4j 7
6. Spring Data and Neo4j 8
7. About me • Neo4j since July 2018 • Java Champion • Co-Founder and current lead of Java User Group EuregJUG • Author (Spring Boot 2 und Arc42 by example) 9 First contact to Neo4j through
8. Known for 10
9. My „business“ domain
10. Tracking musical data 12
11. Tracking musical data 12
12. Logical vs physical model • Logical model designed as ER diagram • Then normalized • All about being free of redundancies • UNF (Unnormalized) • 1NF: Atomic • 2NF: + No partial dependencies • 3NF: + No transitive dependencies Foreign keys between tables aren’t relations! 
 The tables itself and every query result are. 13
13. The whiteboard model 
 IS the physical model • Bands are founded in and 
 solo artists are born in countries • Sometimes Artists are
 associated with other Artists
 and bands have member • Artists used to release
 Albums :Artist
 :Band
 :SoloArtist :Country :FOUNDED_IN
 :BORN_IN :ASSOCIATED_WITH
 :HAS_MEMBER :Album :RELEASED_BY 15
14. The whiteboard model 
 IS the physical model Queen United Kingdom :FOUNDED_IN Innuendo :RELEASED_BY Freddie Brian John Roger :HAS_MEMBER 16
15. A Property Graph :Band :Country :SoloArtist Nodes represents objects (Nouns) :FOUNDED_IN :HAS_MEMBER
 joinedIn: 1970
 leftIn: 1991 name: Freddie
 role: Lead Singer Relationships connect nodes
 and represent actions (verbs) Both nodes and relationships
 can have properties 17
16. Querying • Cypher is to Neo4j what SQL is to RDBMS: 
 A declarative, powerful query language • https://www.opencypher.org / The GQL Manifesto MATCH (a:Album) -[:RELEASED_BY]"# (b:Band), (c) "$[:FOUNDED_IN]- (b) -[:HAS_MEMBER]"# (m) -[:BORN_IN]"# (c2) WHERE a.name = 'Innuendo' RETURN a, b, m, c , c2 18
17. Demo
18. Getting data into Neo4j
19. The Neo4j-ETL Tool 21
20. LOAD CSV Name;Founded in Slayer;US Die Ärzte;DE Die Toten Hosen;DE Pink Floyd;GB LOAD CSV WITH HEADERS FROM 'http:!"localhost:8001/data/artists.csv'
 AS line FIELDTERMINATOR ';' MERGE (a:Artist {name: line.Name}) MERGE (c:Country {code: line.`Founded in`}) MERGE (a) -[:FOUNDED_IN]"# (c) RETURN * 22
21. Building your own importer public class StatsIntegration { @Context public GraphDatabaseService db; @Procedure(name = "stats.loadArtistData", mode = Mode.WRITE) public void loadArtistData( @Name("userName") final String userName, @Name("password") final String password, @Name("url") final String url) { try (var connection = DriverManager.getConnection(url, userName, password); var neoTransaction = db.beginTx()) { DSL.using(connection) .selectFrom(ARTISTS) .forEach(a "# db.execute("MERGE (artist:Artist {name: $artistName}) ", Map.of("artistName", a.getName())) ); neoTransaction.success(); } catch (Exception e) {} } } 23
22. APOC • Not only a guy from the movie „The Matrix“ 24
23. APOC • Not only a guy from the movie „The Matrix“ • Also not that guy 24
24. APOC • Not only a guy from the movie „The Matrix“ • Also not that guy • „A Package Of Components“ for Neo4j • „Awesome Procedures on Cypher“ A huge set of all kinds of extension for Neo4j
 https://neo4j-contrib.github.io/neo4j-apoc- procedures/ 24
25. APOC • Import / Export • Graph refactoring • Job management • Graph algorithms 25
26. apoc.load.jdbc • Use with single tables • Or custom SQL statements 26
27. apoc.load.jdbc WITH "jdbc:postgresql:!"localhost:5432/bootiful-music?user=statsdb-dev&password=dev" as url, "SELECT DISTINCT a.name as artist_name, t.album, g.name as genre_name, t.year FROM tracks t JOIN artists a ON a.id = t.artist_id JOIN genres g ON g.id = t.genre_id WHERE t.compilation = 'f'" as sql CALL apoc.load.jdbc(url,sql) YIELD row MERGE (decade:Decade {value: row.year-row.year%10}) MERGE (year:Year {value: row.year}) MERGE (year) -[:PART_OF]"# (decade) MERGE (artist:Artist {name: row.artist_name}) MERGE (album:Album {name: row.album}) -[:RELEASED_BY]"# (artist) MERGE (genre:Genre {name: row.genre_name}) MERGE (album) -[:HAS]"# (genre) MERGE (album) -[:RELEASED_IN]"# (year) 27
28. Demo
29. Using Neo4j from the JVM
30. Different endpoints • Neo4j can run embedded in the same VM • Has an HTTP endpoint • Offers the binary Bolt protocol • Drivers for Java, Go, C#, Seabolt (C), Python, JavaScipt 30
31. Working directly with the driver try ( Driver driver = GraphDatabase.driver(uri, AuthTokens.basic(user, password)); Session session = driver.session() ) { List<String> artistNames = session .readTransaction(tx "# tx.run("MATCH (a:Artist) RETURN a", emptyMap())) .list(record "# record.get("a").get("name").asString()); } 31
32. Using Neo4j-OGM Java Driver Neo4j Object Graph Mapper (OGM) TransactionManger SessionFactory 32
33. Using Neo4j-OGM • Unified configuration • Annotation based • Mapping between Classes and Graph Model • Data access • Domain based • Through custom queries 33
34. Unified configuration • Transport-Mode • Connection pool sizes • Encryption • Most important: Which packages to scan for entities 34
35. Annotations @NodeEntity("Band") public class BandEntity extends ArtistEntity { @Id @GeneratedValue private Long id; private String name; @Relationship("FOUNDED_IN") private CountryEntity foundedIn; @Relationship("ACTIVE_SINCE") private YearEntity activeSince; @Relationship("HAS_MEMBER") private List<Member> member = new ArrayList"&(); } 35
36. @RelationshipEntity("HAS_MEMBER") public static class Member { @Id @GeneratedValue private Long memberId; @StartNode private BandEntity band; @EndNode private SoloArtistEntity artist; @Convert(YearConverter.class) private Year joinedIn; @Convert(YearConverter.class) private Year leftIn; } Annotations :Band :Country :SoloArtist :FOUNDED_IN :HAS_MEMBER
 joinedIn: 1970
 leftIn: 1991 36
37. Domain based data access var artist = new BandEntity("Queen"); artist.addMember(new SoloArtistEntity("Freddie Mercury")); var session = sessionFactory.openSession(); session.save(artist); 37
38. Domain based data access var queen = session.load(BandEntity.class, 4711); var allBands = session.loadAll(BandEntity.class); 38
39. Domain based data access var queen = session.load(BandEntity.class, 4711); var allBands = session.loadAll(BandEntity.class); 38
40. Domain based data access session.delete(queen); "' OR session.delete(queen, 1); session.deleteAll(BandEntity.class); 39
41. Data access with custom queries var britishBands = session.query( ArtistEntity.class, "MATCH (b:Band) -[:FOUNDED_IN]!% (:Country {code: 'GB'})", emptyMap()); Result result = session.query( "MATCH (b:Artist) !&[r:RELEASED_BY]- (a:Album) -[:RELEASED_IN]!% () - [:PART_OF]!% (:Decade {value: $decade})" "WHERE b.name = $name" + "RETURN b, r, a", Map.of("decade", 1970, "name", "Queen") ); 40
42. Works with • „Plain“ Java • Micronaut • Spring • Spring Boot 41
43. Spring Data Neo4j
44. Spring Data Neo4j • Very early Spring Data Module • First Version ~2010 (Emil Eifrem, Rod Johnson) • Build on top of Neo4j-OGM • Part of the Spring Data release trains • Offers • Derived finder methods • Custom results and projections • Domain Events • Integrated in Spring Boot 43
45. Spring Data Neo4j • Can be used store agnostic • Without Cypher • Or „Graph aware“ • limiting the fetch size • Custom Cypher 44
46. Domain based data access revised interface BandRepository extends Repository<BandEntity, Long> { } 45
47. Domain based data access revised interface BandRepository extends Neo4jRepository<BandEntity, Long> { } • CRUD Methods • (save, findById, delete, count) • Supports @Depth annotation as well as depth argument 45
48. Domain based data access revised var artist = new BandEntity("Queen"); artist.addMember(new SoloArtistEntity("Freddie Mercury")); artist = bandRepository.save(artist); 46
49. Domain based data access revised var artist = bandRepository.findByName("Nickelback") artist.ifPresent(bandRepository"(delete); 46
50. Derived finder methods interface AlbumRepository extends Neo4jRepository<AlbumEntity, Long> { Optional<AlbumEntity> findOneByName(String x); List<AlbumEntity> findAllByNameMatchesRegex(String name); List<AlbumEntity> findAllByNameMatchesRegex( String name, Sort sort, @Depth int depth); Optional<AlbumEntity> findOneByArtistNameAndName( String artistName, String name); } 47
51. Custom queries interface AlbumRepository extends Neo4jRepository<AlbumEntity, Long> { @Query(value = " MATCH (album:Album) - [:CONTAINS] "# (track:Track)" + " MATCH p=(album) - [*1] - ()" + " WHERE id(track) = $trackId" + " AND ALL(relationship IN relationships(p) " + " WHERE type(relationship) "& 'CONTAINS')" + " RETURN p" ) List<AlbumEntity> findAllByTrack(Long trackId); } 48
52. Custom results @QueryResult public class AlbumTrack { private Long id; private String name; private Long discNumber; private Long trackNumber; } 49
53. Custom results interface AlbumRepository extends Neo4jRepository<AlbumEntity, Long> { @Query(value = " MATCH (album:Album) - [c:CONTAINS] "# (track:Track) " + " WHERE id(album) = $albumId" + " RETURN id(track) AS id, track.name AS name, " + " c.discNumber AS discNumber, c.trackNumber AS trackNumber" + " ORDER BY c.discNumber ASC, c.trackNumber ASC" ) List<AlbumTrack> findAllAlbumTracks(Long albumId); } 49
54. Spring Transactions public class ArtistService { @Transactional public void deleteArtist(Long id) { this.bandRepository.findById(id).ifPresent(a "# { session.delete(a); session.query("MATCH (a:Album) WHERE size((a)-[:RELEASED_BY]"#(:Artist))=0 DETACH DELETE a", emptyMap()); session.query("MATCH (t:Track) WHERE size((:Album)-[:CONTAINS]"#(t))=0 DETACH DELETE t", emptyMap()); }); } } 50
55. TransactionTemplate transactionTemplate; return transactionTemplate.execute(t "# { ArtistEntity artist = this.findArtistById(artistId).get(); var oldLinks = artist.updateWikipediaLinks(newLinks); session.save(artist); oldLinks.forEach(session"(delete); return artist; }); Spring Transactions 51
56. With Spring Boot: Configuration properties and auto config spring.data.neo4j.username=neo4j spring.data.neo4j.password=music spring.data.neo4j.uri=bolt:!"localhost:7687 spring.data.neo4j.embedded.enabled=false org.springframework.boot:spring-boot-starter-neo4j 52
57. With Spring Boot: Test-Slice @DataNeo4jTest @TestInstance(Lifecycle.PER_CLASS) class CountryRepositoryTest { private final Session session; private final CountryRepository countryRepository; @Autowired CountryRepositoryTest(Session session, CountryRepository countryRepository) { this.session = session; this.countryRepository = countryRepository; } @BeforeAll void createTestData() {} @Test void getStatisticsForCountryShouldWork() {} } 53
58. Spring Data Neo4j: Dont’s • Not for batch processing • Don’t abuse derived method names
 i.e. Optional<AlbumEntity> findOneByArtistNameAndNameAndLiveIsTrueAndReleasedInValue(String artistName, String name, long year) • Don’t follow your Graph model blindly while modeling the domain • Graph model usually tailored to answer specific question • Domain often follows a different use-case 54
59. Don’t follow your Graph model blindly while modeling the domain 55 @NodeEntity("Artist") public class ArtistEntity { private String name; @Relationship( value = "RELEASED_BY", direction = INCOMING) private List<AlbumEntity> albums; } @NodeEntity("Album") public class AlbumEntity { @Relationship("RELEASED_BY") private ArtistEntity artist; @Relationship("CONTAINS") private List<TrackEntity> tracks; } @NodeEntity("Track") public class TrackEntity { @Relationship( value = "CONTAINS", direction = INCOMING) private List<AlbumEntity> tracks; }
60. Better approach 56 @NodeEntity("Artist") public class ArtistEntity { private String name; } @NodeEntity("Album") public class AlbumEntity { @Relationship("RELEASED_BY") private ArtistEntity artist; } @QueryResult public class AlbumTrack { private String name; private Long trackNumber; } interface AlbumRepository extends Repository<AlbumEntity, Long> { List<AlbumEntity> findAllByArtistNameMatchesRegex( String artistName, Sort sort); @Query(value = " MATCH (album:Album) - [c:CONTAINS] !% (track:Track) " + " WHERE id(album) = $albumId" + " RETURN track.name AS name, c.trackNumber AS trackNumber" + " ORDER BY c.discNumber ASC, c.trackNumber ASC" ) List<AlbumTrack> findAllAlbumTracks(long albumId); }
61. Some advanced queries
62. More Cypher
63. Putting it all together
64. My personal music database
65. Real use-cases
66. Neo4j https://neo4j.com/blog/icij-neo4j-unravel-panama-papers/ https://neo4j.com/blog/analyzing-panama-papers-neo4j/ ICIJ - International Consortium of Investigative Journalists https://neo4j.com/blog/analyzing-paradise-papers-neo4j/ 61
67. Neo4j https://www.zdnet.com/article/using-graph-database-technology-to-tackle-diabetes/ „In biology or medicine, data is connected. You know that entities are connected -- they are dependent on each other. The reason why we chose graph technology and Neo4j is because all the entities are connected.“ Dr Alexander Jarasch, DZD German centre of diabetic research 62
68. Try yourself
69. Neo4j • https://neo4j.com/download/ • Neo4j Desktop (Analyst centric) • Neo4j Server (Community and Enterprise Edition)
 Community Edition: GPLv3
 Enterprise Edition: Proprietary 62
70. Neo4j Datasets • https://neo4j.com/sandbox-v2/ • Preconfigured instance with several different datasets • https://neo4j.com/graphgists/ • Neo4j Graph Gists, Example Models and Cypher Queries • https://offshoreleaks.icij.org/ • Data convolutes mentioned early 63
71. My „Bootiful Music“ project • https://github.com/michael-simons/bootiful-music • Contains docker-compose-scripts for both relational database and Neo4j Instances • Two Spring Boot applications • charts: the relational part of the application • knowledge: the graph application • etl: the custom Neo4j plugin • A Micronaut demo as well 64
72. • Demo: 
 github.com/michael-simons/bootiful-music • A series of blog posts: From relational databases to databases with relations
 https://info.michael-simons.eu/2018/10/11/from-relational-databases-to-databases-with- relations/ • Slides: speakerdeck.com/michaelsimons • Curated set of SDN / OGM tips
 https://github.com/michael-simons/neo4j-sdn-ogm-tips • (German) Spring Boot Book
 @SpringBootBuch // springbootbuch.de Resources 66
73. Thank you!
74. • Medical graph: DZD German centre of diabetic research • Codd: Wikipedia • Apoc and Cypher: Stills from the motion picture „The Matrix“ • Demo: 
 https://unsplash.com/photos/Uduc5hJX2Ew
 https://unsplash.com/photos/FlPc9_VocJ4
 https://unsplash.com/photos/gp8BLyaTaA0 Images 68