Querying Graphs with GraphQL
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The document discusses Neo4j's property graph model, focusing on its use of the Cypher query language and integration with GraphQL. It introduces the neo4j-graphql tool, which allows users to convert GraphQL queries into Cypher, execute them, and manage data dynamically with features like auto-generated mutations and custom queries. The document provides a basic overview of setting up the Neo4j-GraphQL environment and highlights some of its functionalities and potential use cases.
![Cypher: Powerful & Expressive Graph Query Language
MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} )
LOVES
Dan Ann
LABEL PROPERTY
NODE NODE
LABEL PROPERTY](https://image.slidesharecdn.com/neo4j-graphql-lt-170825075344/85/Querying-Graphs-with-GraphQL-5-320.jpg)
![Neo4j is schema-free, so:
[x] Use GraphQL Schema](https://image.slidesharecdn.com/neo4j-graphql-lt-170825075344/85/Querying-Graphs-with-GraphQL-11-320.jpg)
![npm install -g neo4j-graphql-cli
neo4j-graphql [my.schema]](https://image.slidesharecdn.com/neo4j-graphql-lt-170825075344/85/Querying-Graphs-with-GraphQL-20-320.jpg)
![add superpower
type Actor {
totalMovies:Int @cypher(statement:
"RETURN size( (this)-[:ACTED_IN]->(:Movie) ) as total")
...
type Movie {
similar:[Movie] @cypher(statement:
"MATCH (this)-->(:Genre)<--(o:Movie) RETURN o LIMIT 10")
...
type QueryType {
topRatedMovies(score:Int) [Movie] @cypher(statement:
"MATCH (m:Movie)<-[r:RATED]-(:User) WHERE r.score > $score
RETURN m, avg(r.score) as score
ORDER BY score DESC LIMIT 10")](https://image.slidesharecdn.com/neo4j-graphql-lt-170825075344/85/Querying-Graphs-with-GraphQL-27-320.jpg)
Querying Graphs with GraphQL
- 3. Property Graph Model CAR name: “Dan” born: May 29, 1970 twitter: “@dan” name: “Ann” born: Dec 5, 1975 since: Jan 10, 2011 brand: “Volvo” model: “V70” LOVES LOVES LIVES WITH PERSON PERSON
- 4. Whiteboard Model Is the Physical Model
- 5. Cypher: Powerful & Expressive Graph Query Language MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} ) LOVES Dan Ann LABEL PROPERTY NODE NODE LABEL PROPERTY
- 7. Use Neo4j like a regular backing database https://launchpad.graphql.com/3wzp7qnjv
- 8. Or ... turn Neo4j into a native GraphQL backend
- 9. 1. take GraphQL query 2. transform to Cypher 3. execute against graph 4. return results
- 10. Based on ... what? Schema! Which schema?
- 11. Neo4j is schema-free, so: [x] Use GraphQL Schema
- 12. Neo4j is open source & extensible Let‘s build an extension
- 13. How hard can it be?
- 14. Transform + project Query / Results Thank you!
- 16. Basics Endpoint with basic auth host:port/graphql POST schema file run queries with params project results
- 17. Cool Features generate & run single graph query auto generated mutations for types first, offset, orderBy, @relation lookup by any field fragments, unlimited nesting
- 18. Power Up: @cypher computed fields custom mutations & queries parameter support
- 19. Cool! How can I use it?
- 20. npm install -g neo4j-graphql-cli neo4j-graphql [my.schema]
- 24. movies.schema
- 27. add superpower type Actor { totalMovies:Int @cypher(statement: "RETURN size( (this)-[:ACTED_IN]->(:Movie) ) as total") ... type Movie { similar:[Movie] @cypher(statement: "MATCH (this)-->(:Genre)<--(o:Movie) RETURN o LIMIT 10") ... type QueryType { topRatedMovies(score:Int) [Movie] @cypher(statement: "MATCH (m:Movie)<-[r:RATED]-(:User) WHERE r.score > $score RETURN m, avg(r.score) as score ORDER BY score DESC LIMIT 10")
Editor's Notes
- #2: When we combine GraphQL
- #3: Neo4j, an open source graph database.
- #4: which has a graph as its core data model Nodes The objects in the graph Can have name-value properties Can be labeled Relationships Relate nodes by type and direction Can have name-value properties
- #5: Where the database model is what is in your application and on your whiteboards
- #6: With its own powerful graph query language: Cypher
- #7: Neo4j and GraphQL, how would that work?
- #14: Actually it was not that hard, b/c the underlying data model was a great fit, as is the graph schema. And we had a bit of a head start due to Rod Johnson asking me to look into GraphQL + Neo4j some time last year.
- #15: Query transformation, language handling is easy. It runs on the JVM like Neo4j does.
- #16: computed fields e.g. for related, content,recommendations etc.
- #17: computed fields e.g. for related, content,recommendations etc.
- #18: computed fields e.g. for related, content,recommendations etc.
- #19: computed fields e.g. for related, content,recommendations etc.
- #20: computed fields e.g. for related, content,recommendations etc.
- #21: Easy
- #22: Easy
- #25: computed fields e.g. for related, content,recommendations etc.
- #29: computed fields e.g. for related, content,recommendations etc.