import movielens data into neo4j container

steps

1. sample dataset

   1. ml-latest-small.zip about 900KB

2. unzip and serve these csv files

        $ cd /ml-latest-small
   

   1. line of data

       $ wc -l *
       9126 links.csv
       48 load.cql.sq
       9126 movies.csv
       100005 ratings.csv
       1297 tags.csv
       119749 total
      

   2. serve these data

       $ python -m SimpleHTTPServer
      

3. start neo4j container

        $ docker run --rm \
        --publish=7474:7474 \
        --publish=7687:7687 \
        --volume=$HOME/neo4j/data:/data \
        --volume=$HOME/neo4j/logs:/logs \
        --name gneo4j neo4j
   

4. import csv data

   1. create index

       CREATE CONSTRAINT ON (m:Movie) ASSERT m.id IS UNIQUE;
       CREATE CONSTRAINT ON (u:User) ASSERT u.id IS UNIQUE;
       CREATE CONSTRAINT ON (g:Genre) ASSERT g.name IS UNIQUE;
      

   2. import movies.csv

       //////////////////
       // movies.csv 9126
       // movieId,title,genres
       USING PERIODIC COMMIT LOAD CSV WITH HEADERS
       FROM "http://localhost:8000/movies.csv" AS line
       WITH line, SPLIT(line.genres, "|") AS Genres
       CREATE (m:Movie { id: TOINTEGER(line.`movieId`), title: line.`title` })
       WITH Genres
       UNWIND RANGE(0, SIZE(Genres)-1) as i
       MERGE (g:Genre {name: UPPER(Genres[i])})
       CREATE (m)-[r:GENRE {position:i+1}]->(g);
      
       // if you import from neo4j browser
       // Added 9145 labels, created 9251 nodes, set 18376 properties, created 106 relationships, statement completed in 8739 ms.
      

   3. import tags.csv

       ////////////////
       // tags.csv 1297
       // userId,movieId,tag,timestamp
       USING PERIODIC COMMIT LOAD CSV WITH HEADERS
       FROM "http://localhost:8000/tags.csv" AS line
       WITH line
       MATCH (m:Movie { id: TOINTEGER(line.`movieId`) })
       MERGE (u:User { id: TOINTEGER(line.`userId`) })
       CREATE (u)-[r:TAG {tag: line.`tag`}]->(m);
      
       // if you import from neo4j browser
       // Added 61 labels, created 61 nodes, set 1357 properties, created 1296 relationships, statement completed in 1789 ms.
      

   4. import ratings.csv

       /////////////////////
       // ratings.csv 100005
       // userId,movieId,rating,timestamp
       USING PERIODIC COMMIT LOAD CSV WITH HEADERS
       FROM "http://localhost:8000/ratings.csv" AS line
       WITH line
       MATCH (m:Movie { id: TOINTEGER(line.`movieId`) })
       MATCH (u:User { id: TOINTEGER(line.`userId`) })
       CREATE (u)-[r:RATING {rating: TOFLOAT(line.`rating`)}]->(m);
      
       // if you import from neo4j browser
       // Set 19072 properties, created 19072 relationships, statement completed in 11461 ms.
      

5. run cypher query against this dataset

   1. find user 23

       // find user 23
       MATCH (u:User {id: 23})
       RETURN u
      

   2. find user 23’s rating movies

       // find user 23's rating movies
       MATCH (u:User {id: 23})
       MATCH (u)-[:RATING]->(m:Movie)
       RETURN u, m
       LIMIT 10
      

   3. find user 23’s rating movies and movies’s genre

       // find user 23's rating movies and movies' genre
       MATCH (u:User {id: 23})
       MATCH (u)-[:RATING]->(m:Movie)
       MATCH (m)-[r:CATEGORY]->(g)
       RETURN u, m, g
       LIMIT 10