In this section of the tutorial, we will import metadata about songs into the Kiji table songs and import data about when users have listened to songs into the Kiji table users.

KijiExpress Custom Importers

Kiji provides stock bulk importers that work for a number of standard use cases. Because these importers can quickly become complicated once you have to customize them, we've provided custom importers written in KijiExpress for importing the user data and song metadata from JSON files on HDFS.

The source code for one of the importers is included at the bottom of this page.

Importing Tutorial Data

For this example, we use command-line options specific to this job to specify the input JSON file and the target Kiji table. * Run the the song metadata importer as a precompiled job contained in a JAR file:

express.py job -libjars=${MUSIC_EXPRESS_HOME}/lib/* \
    --user_jar=${MUSIC_EXPRESS_HOME}/lib/kiji-express-music-2.0.1.jar \
    --job-name=org.kiji.express.music.SongMetadataImporter --mode=hdfs \
    --input express-tutorial/song-metadata.json \
    --table-uri ${KIJI}/songs
  • Use a similar command to import the user data:
express.py job -libjars=${MUSIC_EXPRESS_HOME}/lib/* \
    --user-jar=${MUSIC_EXPRESS_HOME}/lib/kiji-express-music-2.0.1.jar \
    --job-name=org.kiji.express.music.SongPlaysImporter --mode=hdfs \
    --input express-tutorial/song-plays.json \
    --table-uri ${KIJI}/users

Verify Output

  • After running the importers, verify that the Kiji table songs contains the imported data using the kiji scan command:
kiji scan ${KIJI}/songs --max-rows=5

You should see something like:

Scanning kiji table: kiji://localhost:2181/kiji_express_music/songs/
entity-id=['song-32'] [1365548283995] info:metadata
    {"song_name": "song name-32", "artist_name": "artist-2", "album_name": "album-0", "genre": "genre1.0", "tempo": 120, "duration": 180}

entity-id=['song-49'] [1365548285203] info:metadata
    {"song_name": "song name-49", "artist_name": "artist-3", "album_name": "album-1", "genre": "genre4.0", "tempo": 150, "duration": 180}

entity-id=['song-36'] [1365548284255] info:metadata
    {"song_name": "song name-36", "artist_name": "artist-2", "album_name": "album-0", "genre": "genre1.0", "tempo": 90, "duration": 0}

entity-id=['song-10'] [1365548282517] info:metadata
    {"song_name": "song name-10", "artist_name": "artist-1", "album_name": "album-0", "genre": "genre5.0", "tempo": 160, "duration": 240}

entity-id=['song-8'] [1365548282382] info:metadata
    {"song_name": "song name-8", "artist_name": "artist-1", "album_name": "album-1", "genre": "genre5.0", "tempo": 140, "duration": 180}
  • Use the kiji scan command to verify that the import of the users table was successful:
kiji scan ${KIJI}/users --max-rows=2 --max-versions=5

You should see something like:

entity-id=['user-28'] [1325739120000] info:track_plays
                                 song-25
entity-id=['user-28'] [1325739060000] info:track_plays
                                 song-23
entity-id=['user-28'] [1325738940000] info:track_plays
                                 song-25
entity-id=['user-28'] [1325738760000] info:track_plays
                                 song-28

entity-id=['user-2'] [1325736420000] info:track_plays
                                 song-4
entity-id=['user-2'] [1325736180000] info:track_plays
                                 song-3
entity-id=['user-2'] [1325735940000] info:track_plays
                                 song-4
entity-id=['user-2'] [1325735760000] info:track_plays
                                 song-28
entity-id=['user-2'] [1325735520000] info:track_plays
                                 song-0

Now that you've imported your data, we are ready to start analyzing it! The source code for the song metadata importer is included below in case you are curious. We will go over the syntax of writing your own jobs in more detail in following sections.

(Optional) Source Code for Scalding Importer

The data is formatted with a JSON record on each line. Each record corresponds to a song, and provides the following metadata for the song:

  • song id
  • song name
  • artist name
  • album name
  • genre
  • tempo
  • duration

The info:metadata column of the table contains an Avro record containing this relevant song metadata.

The importer looks like this:

SongMetadataImporter.scala