README

Model

Nodes

• Piece
• Composer
• Type
• Key
• User

Relationships

• (:Composer)-[:COMPOSED {role:"some role"}]->(:Movie)
• (:Piece)-[:HAS_TYPE]->(:TYPE)
• (:Piece)-[:HAS_KEY]->(:Key)
• (:User)-[:RATED {rating:"1-5"}]->(:Piece)

Database Setup

Docker Setup

This is the recommended way and should work similarly on Windows.

• Run the Neo4j Docker Container

docker run \
    --publish=7474:7474 --publish=7687:7687 \
    --volume=$HOME/neo4j/data:/data \
    --volume=$HOME/neo4j/import:/var/lib/neo4j/import \
    --name neo4j \
    neo4j

• Copy the csv files into the import directory:

cp csv/*.csv $HOME/neo4j/import

• Initialize the database:

docker exec -i neo4j bin/cypher-shell -u neo4j -p neo < ./setup.cql

Local Install

As an alternative to Docker you can also install Neo4j locally

• Download Neo4j Community Edition: .tar Version
• Set your NEO4J_HOME variable: export NEO4J_HOME=/path/to/neo4j-community
• From this project's root directory, run the import script:

docker exec -i my-neo4j bin/neo4j-admin import \
--nodes:Piece /var/lib/neo4j/import/piece_node.csv \
--nodes:User /var/lib/neo4j/import/users_node.csv \
--nodes:Type /var/lib/neo4j/import/type_node.csv \
--relationships:TYPE "/var/lib/neo4j/import/type_rels.csv" \
--delimiter ";" --array-delimiter "|" --id-type INTEGER
$NEO4J_HOME/bin/neo4j-import --into $NEO4J_HOME/data/databases/graph.db --nodes:Person csv/person_node.csv --nodes:Movie csv/movie_node.csv --nodes:Genre csv/genre_node.csv --nodes:Keyword csv/keyword_node.csv --relationships:ACTED_IN csv/acted_in_rels.csv --relationships:DIRECTED csv/directed_rels.csv --relationships:HAS_GENRE csv/has_genre_rels.csv --relationships:HAS_KEYWORD csv/has_keyword_rels.csv --relationships:PRODUCED csv/produced_rels.csv --relationships:WRITER_OF csv/writer_of_rels.csv --delimiter ";" --array-delimiter "|" --id-type INTEGER

If you see Input error: Directory 'neo4j-community-3.0.3/data/databases/graph.db' already contains a database, delete the graph.db directory and try again.

• Add constraints to your database: $NEO4J_HOME/bin/neo4j-shell < setup.cql -path $NEO4J_HOME/databases/graph.db
• Start the database: $NEO4J_HOME/bin/neo4j start

Workshop

Let's start with taking a look at the current state of the database. Therefore open the Neo4j browser.

Take a look at all currently existing Pieces in the database, by entering this command:

MATCH (n:Piece) RETURN n;

We can also find out which Pieces are Quartets:

MATCH (n:Piece)-[:HAS_TYPE]->(:Type {name: 'Quartet'}) RETURN n;

Moving on we can also create a new node ourselves. Let's add Mozart as a Composer to our database:

CREATE (n:Composer {name:'Mozart'}) RETURN n;

As all the Pieces in the database where composed by Mozart, connect them with a COMPOSED relationship:

MATCH (m:Composer {name:"Mozart"}), (p:Piece)
CREATE (m)-[:COMPOSED]->(p)

As described one of the strength of Graph Databases is the traversal over its paths. This can be used for recommendation systems, for example.

To set this up let's create a few users:

LOAD CSV WITH HEADERS FROM "file:///users_node.csv" AS r FIELDTERMINATOR ';'
CREATE (p:User {
  id: toInteger(r.`id:ID(User)`),
  name: r.name
});

Also create a few ratings:

MATCH (u:User), (p:Piece)
WITH u, p
WHERE rand() < 0.1
CREATE (u)-[:RATED]->(p)

and assign rating scores:

MATCH (:User)-[r:RATED]->(:Piece)
SET r.rating = floor(rand()*6)

Your task is now to develop an approach to recommend Pieces to a user, based on all information currently stored in the database.