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HenniHenni
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group3 initial setup
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‎RelationshipsG3/README.md

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# README
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## Model
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### Nodes
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* `Piece`
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* `Composer`
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* `Type`
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* `Key`
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* `User`
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### Relationships
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* `(:Composer)-[:COMPOSED {role:"some role"}]->(:Movie)`
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* `(:Piece)-[:HAS_TYPE]->(:TYPE)`
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* `(:Piece)-[:HAS_KEY]->(:Key)`
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* `(:User)-[:RATED {rating:"1-5"}]->(:Piece)`
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## Database Setup
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### Docker Setup
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This is the recommended way and should work similarly on Windows.
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* Run the Neo4j Docker Container
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```
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docker run \
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--publish=7474:7474 --publish=7687:7687 \
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--volume=$HOME/neo4j/data:/data \
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--volume=$HOME/neo4j/import:/var/lib/neo4j/import \
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--name neo4j \
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neo4j
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```
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* Copy the csv files into the import directory:
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```
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cp csv/*.csv $HOME/neo4j/import
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```
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* Initialize the database:
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```
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docker exec -i neo4j bin/cypher-shell -u neo4j -p neo < ./setup.cql
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```
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### Local Install
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As an alternative to Docker you can also install Neo4j locally
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* [Download Neo4j Community Edition: .tar Version](https://neo4j.com/download/other-releases/)
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* Set your `NEO4J_HOME` variable: `export NEO4J_HOME=/path/to/neo4j-community`
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* From this project's root directory, run the import script:
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```
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docker exec -i my-neo4j bin/neo4j-admin import \
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--nodes:Piece /var/lib/neo4j/import/piece_node.csv \
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--nodes:User /var/lib/neo4j/import/users_node.csv \
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--nodes:Type /var/lib/neo4j/import/type_node.csv \
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--relationships:TYPE "/var/lib/neo4j/import/type_rels.csv" \
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--delimiter ";" --array-delimiter "|" --id-type INTEGER
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$NEO4J_HOME/bin/neo4j-import --into $NEO4J_HOME/data/databases/graph.db --nodes:Person csv/person_node.csv --nodes:Movie csv/movie_node.csv --nodes:Genre csv/genre_node.csv --nodes:Keyword csv/keyword_node.csv --relationships:ACTED_IN csv/acted_in_rels.csv --relationships:DIRECTED csv/directed_rels.csv --relationships:HAS_GENRE csv/has_genre_rels.csv --relationships:HAS_KEYWORD csv/has_keyword_rels.csv --relationships:PRODUCED csv/produced_rels.csv --relationships:WRITER_OF csv/writer_of_rels.csv --delimiter ";" --array-delimiter "|" --id-type INTEGER
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```
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If you see `Input error: Directory 'neo4j-community-3.0.3/data/databases/graph.db' already contains a database`, delete the `graph.db` directory and try again.
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* Add [constraints](https://neo4j.com/docs/developer-manual/current/cypher/#query-constraints) to your database: `$NEO4J_HOME/bin/neo4j-shell < setup.cql -path $NEO4J_HOME/databases/graph.db`
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* Start the database: `$NEO4J_HOME/bin/neo4j start`
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## Workshop
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Let's start with taking a look at the current state of the database.
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Therefore open the Neo4j [browser](http://localhost:7474/browser/).
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Take a look at all currently existing Pieces in the database, by entering this command:
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```
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MATCH (n:Piece) RETURN n;
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```
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We can also find out which Pieces are Quartets:
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```
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MATCH (n:Piece)-[:HAS_TYPE]->(:Type {name: 'Quartet'}) RETURN n;
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```
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Moving on we can also create a new node ourselves. Let's add `Mozart` as a `Composer` to our database:
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```
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CREATE (n:Composer {name:'Mozart'}) RETURN n;
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```
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As all the Pieces in the database where composed by Mozart, connect them with a `COMPOSED` relationship:
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```
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MATCH (m:Composer {name:"Mozart"}), (p:Piece)
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CREATE (m)-[:COMPOSED]->(p)
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```
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As described one of the strength of Graph Databases is the traversal over its paths. This can be used for recommendation systems, for example.
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To set this up let's create a few users:
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```
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LOAD CSV WITH HEADERS FROM "file:///users_node.csv" AS r FIELDTERMINATOR ';'
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CREATE (p:User {
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id: toInteger(r.`id:ID(User)`),
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name: r.name
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});
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```
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Also create a few ratings:
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```
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MATCH (u:User), (p:Piece)
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WITH u, p
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WHERE rand() < 0.1
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CREATE (u)-[:RATED]->(p)
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```
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and assign rating scores:
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```
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MATCH (:User)-[r:RATED]->(:Piece)
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SET r.rating = floor(rand()*6)
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```
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Your task is now to develop an approach to recommend Pieces to a user, based on all information currently stored in the database.

‎RelationshipsG3/csv/piece_node.csv

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id:ID(Piece);date;location;work;key
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1;1761;Salzburg;Minuet for Harpsichord (See K. 1e);G Major
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2;1762;Salzburg;Minuet for Harpsichord;F Major
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3;1762;Salzburg;Allegro for Harpsichord;B Flat Major
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4;1762;Salzburg;Minuet for Harpsichord;F Major
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5;1762;Salzburg;Minuet for Harpsichord;F Major
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16;1764;London;Symphony No. 1;E Flat Major
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17;1764;London;Symphony No. 2 (Doubtful);B Flat Major
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18;1764;London;Symphony No. 3 (copy from K. F. Abel);E Flat Major
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26;1766;The Hague;Sonata for Harpsichord & Violin;
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27;1766;The Hague;Sonata for Harpsichord & Violin;
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41;1767;Salzburg;Concerto for Piano No. 4;
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51;1768;Vienna;Opera buffa `La finta semplice';
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55;1788;Vienna;Sonata for Piano & Violin (Doubtful);
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56;1788;Vienna;Sonata for Piano & Violin (Doubtful);
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57;1788;Vienna;Sonata for Piano & Violin (Doubtful);
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58;1788;Vienna;Sonata for Piano & Violin (Doubtful);
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112;1771;Milan;Symphony No. 13;F Major
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113;1771;Milan;Divertimento No. 1;E Flat Major
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114;1771;Salzburg;Symphony No. 14;A Major
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115;1773;Salzburg;Mass `Missa brevis';C Major
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183;1773;Salzburg;Symphony No. 25;G minor
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184;1773;Salzburg;Symphony No. 26 (Overture);E Flat Major
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185;1773;Vienna;Serenade No. 3 `Finalmusik';D Major
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186;1773;Milan;Divertimento No. 4;B Flat Major
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187;1773;Salzburg?;Divertimento No. 5;C Major
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188;1776;Salzburg;Divertimento No. 6;C Major
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189;1773;Vienna;March for Orchestra;D Major
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190;1773;Salzburg;Concertone for 2 Violins & Orchestra;C Major
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191;1774;Salzburg;Bassoon Concerto;B Flat Major
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192;1774;Salzburg;Mass `Missa brevis';F Major
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193;1774;Salzburg;Dixit & Magnificat;C Major
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194;1774;Salzburg;Mass `Missa brevis';D Major
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195;1774;Salzburg;Litaniae Lauretanae;D Major
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196;1774;Salzburg;Opera buffa `La finta giardiniera';
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367;1781;Munich;Ballet Music to Idomeneo;
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569;1789;Vienna;Aria `Ohne Zwang' (lost);
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570;1789;Vienna;Sonata for Piano;B Flat Major
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573;1789;Potsdam;9 Variations for Piano (Duport);D Major
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574;1789;Leipzig;Gigue for Piano;G minor
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575;1789;Vienna;Quartet for Strings No. 21;D Major
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576;1789;Vienna;Sonata for Piano;D Major
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581;1789;Vienna;Quintet for Clarinet & Strings;A Major
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587;1789;Vienna;Contredanse for Orchestra;
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588;1790;Vienna;Opera buffa `Cosi fan tutte';
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589;1790;Vienna;Quartet for Strings No. 22;B Flat Major
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590;1790;Vienna;Quartet for Strings No. 23;F Major
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598;1791;Vienna;Song with Piano `Wir Kinder';
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622;1791;Vienna;Concerto for Clarinet;A Major

‎RelationshipsG3/csv/type_node.csv

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id:ID(Type);name
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1;Minuet
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2;Symphony
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3;Sonata
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4;Concerto
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5;Opera
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6;Mass
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7;Quartet
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8;Quintet
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9;Aria

‎RelationshipsG3/csv/type_rels.csv

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:START_ID(Piece);:END_ID(Type)
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1;1
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2;1
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4;1
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5;1
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16;2
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17;2
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18;2
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112;2
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114;2
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183;2
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184;2
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26;3
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27;3
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55;3
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56;3
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57;3
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58;3
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570;3
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576;3
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41;4
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190;4
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622;4
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51;5
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196;5
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588;5
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115;6
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192;6
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194;6
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575;7
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589;7
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590;7
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581;8
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569;9

‎RelationshipsG3/csv/users_node.csv

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id:ID(User);name
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1;Alex
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2;Alicia
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3;Amber
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4;Amelie
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5;Andrew
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6;Benjamin
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7;Brandon
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8;Caitlin
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9;Cameron
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10;Charles
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11;Christopher
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12;Connor
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13;David
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14;Dylan
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15;Ethan
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16;Freddie
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17;Gabriel
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18;Georgia
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19;Isabel
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20;Isabella
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21;Jack
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22;Jake
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23;Jasmine
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24;Jay
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25;Jayden
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26;Jessica
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27;John
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28;Joshua
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29;Keira
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30;Laura
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31;Leon
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32;Liam
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33;Lilly
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34;Lola
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35;Lucas
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36;Madison
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37;Max
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38;Michael
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39;Mohammed
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40;Niamh
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41;Nicole
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42;Noah
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43;Rosie
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44;Samuel
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45;Sarah
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46;Sean
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47;Shannon
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48;Sienna
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49;Sophie
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50;Summer
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51;Thomas
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52;Tyler
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53;Zachary

‎RelationshipsG3/docker-compose.yml

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version: '2'
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services:
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neo4j:
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image: "neo4j"
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ports:
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- "7474:7474"
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- "7687:7687"
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volumes:
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- $HOME/neo4j/data:/data
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- $HOME/neo4j/import:/var/lib/neo4j/import

‎RelationshipsG3/setup.cql

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CREATE CONSTRAINT ON (n:User) ASSERT n.id IS UNIQUE;
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CREATE CONSTRAINT ON (n:Composer) ASSERT n.id IS UNIQUE;
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CREATE CONSTRAINT ON (n:Piece) ASSERT n.id IS UNIQUE;
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CREATE CONSTRAINT ON (n:Type) ASSERT n.id IS UNIQUE;
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LOAD CSV WITH HEADERS FROM "file:///piece_node.csv" AS r FIELDTERMINATOR ';'
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CREATE (p:Piece {
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id: toInteger(r.`id:ID(Piece)`),
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work: r.work,
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location: r.location,
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year: toInteger(r.date),
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key: r.key
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});
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LOAD CSV WITH HEADERS FROM "file:///type_node.csv" AS r FIELDTERMINATOR ';'
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CREATE (p:Type {
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id: toInteger(r.`id:ID(Type)`),
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name: r.name
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});
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LOAD CSV WITH HEADERS FROM "file:///type_rels.csv" AS r FIELDTERMINATOR ';'
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MATCH (p:Piece {id: toInteger(r.`:START_ID(Piece)`)}), (t:Type {id: toInteger(r.`:END_ID(Type)`)})
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CREATE (p)-[:HAS_TYPE]->(t);

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