GraphAcademy

Graph Data Modeling Fundamentals

Getting Started

Modeling Nodes

Modeling Relationships

Testing the Model

Refactoring the Graph

Eliminating Duplicate Data

Using Specific Relationships

Adding Intermediate Nodes

Adding Language nodes

This is what the instance model will be refactored to:

Instance model with language node

Creating Language Nodes

Execute this code to refactor the graph to turn the languages property values into Language nodes:

cypher
Creating Language Nodes
MATCH (m:Movie)
UNWIND m.languages AS language
WITH  language, collect(m) AS movies
MERGE (l:Language {name:language})
WITH l, movies
UNWIND movies AS m
WITH l,m
MERGE (m)-[:IN_LANGUAGE]->(l);
MATCH (m:Movie)
SET m.languages = null

Modifying the Cypher statement

This is the Cypher code for what our use case used to be before the refactoring.

cypher
Previous Query
MATCH (m:Movie)
WHERE 'Italian' IN m.languages
RETURN m.title

This query can now be modified to instead use the newly-created Language node.

cypher
Using the Language Node
MATCH (m:Movie)-[:IN_LANGUAGE]-(l:Language)
WHERE  l.name = 'Italian'
RETURN m.title

This is the only use case that deals with languages so we need not retest all of our queries after the refactor.

Validate Results

Once you have run the query, click the Check Database button and we will check the database for you.

Hint

You will need to run the Cypher statement in Creating Language Nodes to perform this refactoring.

Then click Try Again.

Solution

To pass the challenge, run the following queries in sequence by clicking the Run in Sandbox.

cypher
1. Reset the graph
MATCH (n) DETACH DELETE n;
MERGE (apollo:Movie {title: 'Apollo 13', tmdbId: 568, released: '1995-06-30', imdbRating: 7.6, genres: ['Drama', 'Adventure', 'IMAX']})
MERGE (tom:Person {name: 'Tom Hanks', tmdbId: 31, born: '1956-07-09'})
MERGE (meg:Person {name: 'Meg Ryan', tmdbId: 5344, born: '1961-11-19'})
MERGE (danny:Person {name: 'Danny DeVito', tmdbId: 518, born: '1944-11-17'})
MERGE (sleep:Movie {title: 'Sleepless in Seattle', tmdbId: 858, released: '1993-06-25', imdbRating: 6.8, genres: ['Comedy', 'Drama', 'Romance']})
MERGE (hoffa:Movie {title: 'Hoffa', tmdbId: 10410, released: '1992-12-25', imdbRating: 6.6, genres: ['Crime', 'Drama']})
MERGE (jack:Person {name: 'Jack Nicholson', tmdbId: 514, born: '1937-04-22'})
MERGE (sandy:User {name: 'Sandy Jones', userId: 534})
MERGE (clinton:User {name: 'Clinton Spencer', userId: 105})
MERGE (tom)-[:ACTED_IN {role: 'Jim Lovell'}]->(apollo)
MERGE (tom)-[:ACTED_IN {role: 'Sam Baldwin'}]->(sleep)
MERGE (meg)-[:ACTED_IN {role: 'Annie Reed'}]->(sleep)
MERGE (danny)-[:ACTED_IN {role: 'Bobby Ciaro'}]->(hoffa)
MERGE (danny)-[:DIRECTED]->(hoffa)
MERGE (jack)-[:ACTED_IN {role: 'Jimmy Hoffa'}]->(hoffa)
MERGE (sandy)-[:RATED {rating:5}]->(apollo)
MERGE (sandy)-[:RATED {rating:4}]->(sleep)
MERGE (clinton)-[:RATED {rating:3}]->(apollo)
MERGE (clinton)-[:RATED {rating:3}]->(sleep)
MERGE (clinton )-[:RATED {rating:3}]->(hoffa)
MERGE (casino:Movie {title: 'Casino', tmdbId: 524, released: '1995-11-22', imdbRating: 8.2, genres: ['Drama','Crime']})
MERGE (martin:Person {name: 'Martin Scorsese', tmdbId: 1032})
MERGE (martin)-[:DIRECTED]->(casino)
SET tom:Actor
SET meg:Actor
SET danny:Actor
SET jack:Actor
SET danny:Director
SET martin:Director
SET apollo.languages = ['English']
SET sleep.languages =  ['English']
SET hoffa.languages =  ['English', 'Italian', 'Latin']
SET casino.languages =  ['English'];
cypher
2. Create the Language nodes
MATCH (m:Movie)
UNWIND m.languages AS language
WITH  language, collect(m) AS movies
MERGE (l:Language {name:language})
WITH l, movies
UNWIND movies AS m
WITH l,m
MERGE (m)-[:IN_LANGUAGE]->(l);
MATCH (m:Movie)
SET m.languages = null

Then click Try Again.

Summary

In this challenge, you demonstrated that you can refactor the graph to add nodes to replace duplication in properties.

In the next challenge, you will perform some additional factoring to eliminate duplication.