Pouring Coffee into the Matrix: Building Java Applications on Neo4j

Many of us have built applications for traditional data structures (like relational database tables), but is it different for graph data stores? Do developers need to retool and relearn? In this session, we will cover a brief intro to graphs and walk through writing a typical Java application with Spring and connect it to a graph database. We will walk through interacting with the graph data from the application, and show it in the cloud, as well. Come to this session to apply your business applications to graph data!

Transcript

1. Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif LinkedIn: linkedin.com/in/jmhreif Github: GitHub.com/JMHReif Website: jmhreif.com Pouring Coffee into the Matrix Building Java applications on Neo4j
2. Who Am I? • Developer + Advocate • Continuous learner • Technical content writer • Conference speaker • Other: geek Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif LinkedIn: linkedin.com/in/jmhreif Github: GitHub.com/JMHReif Website: jmhreif.com
3. What is graph?
4. What is graph? • Database - data storage • Way to store relationships with entities • Powerful when… • Queried - results based on the network structure • Visualized - depth comprehension of network • Utilized in algorithms/pipelines - factoring network into calculations
5. Graph History • Graph much older than technology of the last decade… • Arose from solution need (then and now) Seven Bridges of Konigsberg problem. Leonhard Euler, 1735
6. Graph Data Model
7. Property Graph • Node (vertex) • Relationship (edge)
8. Nodes • Represent objects or entities • Can be labeled JavaVersion VersionDiff JavaVersion
9. Nodes • Represent objects or entities • Can be labeled • May have properties JavaVersion VersionDiff JavaVersion version: “17” gaDate: 2021-09-14 fromVersion: “17.0.3+7-tem” toVersion: “1.6.0_45-oracle” version: “6” gaDate: 2006-12-12 codeName: “Mustang”
10. Relationships • Must have a type • Must have a direction JavaVersion VersionDiff JavaVersion version: “17”
11. Relationships • Must have a type • Must have a direction • May have properties JavaVersion VersionDiff JavaVersion version: “17”
12. Relationships • Must have a type • Must have a direction • May have properties • Nodes can share multiple relationships JavaVersion VersionDiff JavaVersion version: “17”
13. Label • A group of nodes • Like a category • Domain class :) Person
14. Label • A group of nodes • Like a category • Domain class :) • Inheritance :) Person Employee Customer
15. Properties • Key-value pair • Associated with node or relationship • Like a variable name and value JavaVersion JavaVersion version: “17” version: “6” versionSteps: 3 M IG RATES gaDate: 2021-09-14 gaDate: 2006-12-12 codeName: “Mustang”
16. Modeling
17. Whiteboard friendliness
18. Graph data
19. Developing applications
20. Java App Data Store Options • Relational • Straight JDBC • JDBC Template • JOOQ • JPA or Hibernate • NoSQL - Document • MongoDB • Graph • Neo4j
21. Java Dev: Why Graph?
22. Answering data questions • Java Versions (i.e. 8, 11, 17) • Changes between versions over time • Di ff s • History for one speci fi c feature
23. Domain/Application alignment • Class • Entity/Object • Represents domain type • General outline for objects of that type • Variables/Properties • Details for that entity • Values may not always exist • Constructor - instance of object • Each instance is unique object with varying info @Node @Data @RequiredArgsConstructor public class JavaVersion { @Id @Property("version") private fi nal String javaVersion; private String name, codeName, status, apiSpec; private LocalDate gaDate, eolDate; }
24. Retaining Relationships • Adding relationships • Add variable as pointer to another object • Links entities together • Might have some annotations for mapping @Node @Data @RequiredArgsConstructor public class JavaVersion { @Relationship(“FROM_NEWER”) private List<VersionDiff> olderVersionDiffs; }
25. • Set theory - rows and columns • Schema - rigid, enforced • Entities - table row • Metadata - columns • Relationships - crafted JOINs • Queries - JOINs at runtime • Indexes - Lookups scans Graphs for Java devs • Graph theory - entity network • Schema - fl exible, optional • Entities - node (object) • Metadata - properties • Relationships - stored joins • Queries - joins at write • Indexes - place to start Relational database Graph database
26. • Links stored as primary/foreign keys • Traversal expressed as nested subqueries • Every subquery needs separate query plan Relational vs Graph • Links stored as pointers (IFA) • Traversal expressed as single pattern • One query plan for entire path
27. Demo Background
28. Neo4j AuraDB • Free tier instance • Java language version data loaded
29. Language drivers • Neo4j Java driver (o ffi cial) • Spring Data Neo4j • Uses Neo4j Java driver at base • Other options: • O ffi cial drivers-> Python, JavaScript, Go, .NET • Java frameworks-> Quarkus, Helidon, Micronaut, etc
30. Spring provisions • Spring Initializr • Spring Boot’s reduction of boilerplate • Annotation-based OGM for POJOs • Query derivation + DSL for custom (Cypher) • Spring Data’s easy connection to Neo4j • BOLT or HTTP
31. Let’s see some code! Demo time!
32. Resources • Source code: github.com/JMHReif/pouring-co ff ee-into-matrix-lombok • Spring Data Neo4j documentation: dev.neo4j.com/sdn-docs • Neo4j AuraDB: dev.neo4j.com/aura-java • Blog: bit.ly/jmhreif-blog • NODES: dev.neo4j.com/nodes Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif LinkedIn: linkedin.com/in/jmhreif Github: GitHub.com/JMHReif Website: jmhreif.com DON’T MISS!