Album split in multiple albums during import

[hacketiwack]

For some albums I have, I've discovered that when imported into the OwnTone database, they are split into multiple albums.
I can't figure out why they are split.

An example below of what is returned by the API call /api/library/albums?media_kind=music

{
  "items": [
    {
      "id": "2667289888762390960",
      "name": "A.I. Artificial Intelligence",
      "name_sort": "A.I. Artificial Intelligence",
      "artist": "John Williams",
      "artist_id": "628737532861436891",
      "track_count": 46,
      "length_ms": 10544224,
      "time_added": "2023-12-15T17:14:09Z",
      "in_progress": false,
      "media_kind": "music",
      "data_kind": "file",
      "year": 2015,
      "uri": "library:album:2667289888762390960",
      "artwork_url": "./artwork/group/30941"
    },
    {
      "id": "1335596877965614741",
      "name": "A.I. Artificial Intelligence",
      "name_sort": "A.I. Artificial Intelligence",
      "artist": "John Williams",
      "artist_id": "628737532861436891",
      "track_count": 1,
      "length_ms": 280816,
      "time_added": "2023-12-15T17:14:08Z",
      "in_progress": false,
      "media_kind": "music",
      "data_kind": "file",
      "year": 2015,
      "uri": "library:album:1335596877965614741",
      "artwork_url": "./artwork/group/30942"
    }]
}

There should be only one album. I don't know what triggers the creation of another album for some tracks.
Do I miss something? Is there a specific configuration that I miss? I can provide an example album that provokes this behaviour.

I'm using the latest master branch of OwnTone (Docker image created by this Dockerfile. I doubt that this is due to the build done under Alpine Linux.
I will test with another Docker image in the meantime to check if I obtain any different result.

Thanks in advance for any help.

[hacketiwack]

In the database, I have the following data:

sqlite> select id, songalbumid,fname,album from files where album like '%Intelligence';
381235|1335596877965614741|a5d5b552-e02b-4b6e-863a-379b75cca96e.mp3|A.I. Artificial Intelligence
381236|2667289888762390960|9b1eb417-725c-4fcc-b2d2-b5ca2d07bde8.mp3|A.I. Artificial Intelligence
381237|2667289888762390960|a6546177-4543-417c-abb3-48c0bee2250d.mp3|A.I. Artificial Intelligence
381238|2667289888762390960|1bd17d33-17ab-464c-817b-b4905b3d5b99.mp3|A.I. Artificial Intelligence
381239|2667289888762390960|5d046be9-acb8-47a7-927c-67d7276acd6f.mp3|A.I. Artificial Intelligence
381240|2667289888762390960|802ff2c8-b757-4c36-8a4e-5985b1fbf34c.mp3|A.I. Artificial Intelligence
381241|2667289888762390960|85a20596-6e0b-4cd2-b427-2127fb7d9bef.mp3|A.I. Artificial Intelligence
381242|2667289888762390960|52837661-2a76-4e3e-bf78-b7ed30a68e70.mp3|A.I. Artificial Intelligence
381243|2667289888762390960|1672d332-ece8-4bb2-bdee-352daad523c4.mp3|A.I. Artificial Intelligence
381244|2667289888762390960|3c537ba1-1e05-409d-bf84-fdae4e987f7d.mp3|A.I. Artificial Intelligence
381245|2667289888762390960|4a34ab96-ad93-4ce2-8984-fdbe55dfd99f.mp3|A.I. Artificial Intelligence
381246|2667289888762390960|95769787-7130-4c63-ba29-b1e00c8d7c6e.mp3|A.I. Artificial Intelligence
381247|2667289888762390960|7d733ace-8f83-4cbc-8bb1-8cc32e2790ad.mp3|A.I. Artificial Intelligence
381248|2667289888762390960|03d683de-1e7d-4b88-b304-4cb90a5f9982.mp3|A.I. Artificial Intelligence
381249|2667289888762390960|03bc286a-c7e4-47c4-8254-c22a9ce6d33b.mp3|A.I. Artificial Intelligence
381250|2667289888762390960|10beffd9-a283-41c8-a78d-05772559b3a5.mp3|A.I. Artificial Intelligence
381251|2667289888762390960|510b4fb4-f51a-4823-89dd-4e087685b43c.mp3|A.I. Artificial Intelligence
381252|2667289888762390960|fcfec769-b3d2-4e68-88f0-f70f572dbfe5.mp3|A.I. Artificial Intelligence
381253|2667289888762390960|aa9fcc2c-4d18-4ce2-af1b-848fbd2f505a.mp3|A.I. Artificial Intelligence
381254|2667289888762390960|1013da01-f208-4f79-9d56-ab4b5c06bdde.mp3|A.I. Artificial Intelligence
381255|2667289888762390960|cd4c3c0e-2c70-4262-8369-256795afc89a.mp3|A.I. Artificial Intelligence
381256|2667289888762390960|c3e217b0-74cd-45c1-aa7a-b847d9710c08.mp3|A.I. Artificial Intelligence
381257|2667289888762390960|7798fe74-27e4-40e0-8394-669d1b8f90cf.mp3|A.I. Artificial Intelligence
381258|2667289888762390960|f1f9c121-35c4-40a9-95f2-f851fbde2f43.mp3|A.I. Artificial Intelligence
381259|2667289888762390960|b26b9325-7126-4a0d-b8bd-4f96200e9aff.mp3|A.I. Artificial Intelligence
381260|2667289888762390960|07c65b20-e6a9-473c-8cd8-15f00fa665a7.mp3|A.I. Artificial Intelligence
381261|2667289888762390960|f757b418-80da-4fd7-b608-df7382489940.mp3|A.I. Artificial Intelligence
381262|2667289888762390960|38b436bd-1c8a-489b-bf34-a4493ff79c5a.mp3|A.I. Artificial Intelligence
381263|2667289888762390960|05564df6-c4bd-42fd-acae-689b8db3ee86.mp3|A.I. Artificial Intelligence
381264|2667289888762390960|818991cf-4683-499d-867c-f38509de0fc2.mp3|A.I. Artificial Intelligence
381265|2667289888762390960|1030e790-34f3-4613-a25e-6a2ea25c1356.mp3|A.I. Artificial Intelligence
381266|2667289888762390960|c7df9ab9-aab3-476a-a967-41ca6ea558d1.mp3|A.I. Artificial Intelligence
381267|2667289888762390960|703de320-cc25-4773-ba8d-062ce50b6905.mp3|A.I. Artificial Intelligence
381268|2667289888762390960|e5027dbe-9059-4092-82b4-4328661f8f5f.mp3|A.I. Artificial Intelligence
381269|2667289888762390960|259588d4-0297-491f-9d27-4ebd71bc9358.mp3|A.I. Artificial Intelligence
381270|2667289888762390960|0b203615-5920-45a3-843f-c87005113899.mp3|A.I. Artificial Intelligence
381271|2667289888762390960|e456c62a-4964-45e2-b227-2e1dc10bfccd.mp3|A.I. Artificial Intelligence
381272|2667289888762390960|a21b9bb8-2cfb-47cf-8369-257d40a25283.mp3|A.I. Artificial Intelligence
381273|2667289888762390960|faefdb7d-44ba-47ec-a944-48a26eab84dd.mp3|A.I. Artificial Intelligence
381274|2667289888762390960|ff3061fd-6620-4bfc-ad17-e5f29eb57e84.mp3|A.I. Artificial Intelligence
381275|2667289888762390960|095f221a-6567-44bf-b612-2b77b81b518a.mp3|A.I. Artificial Intelligence
381276|2667289888762390960|bcfd18a0-3cf3-4c54-bbe1-cb675d1d7d09.mp3|A.I. Artificial Intelligence
381277|2667289888762390960|f89e34b9-3061-444b-a0ff-e3b54f47fb56.mp3|A.I. Artificial Intelligence
381278|2667289888762390960|0b46a800-2f3d-4875-8cdd-6ff0d6c29527.mp3|A.I. Artificial Intelligence
381279|2667289888762390960|a039efaf-7f46-4c0a-a0d4-cfd53c2f91de.mp3|A.I. Artificial Intelligence
381280|2667289888762390960|d4576fdd-6380-42ea-8701-968c2d97cf9c.mp3|A.I. Artificial Intelligence
381281|2667289888762390960|3d60b4cf-4c1a-40d7-ab78-7baf07e5f8c1.mp3|A.I. Artificial Intelligence

[ejurgensen]

Try running with ffprobe on some of the tracks to check the metadata. It is probably one of these that is the cause of it.

[hacketiwack]

Thanks for the speedy reply. I checked with ffprobe (command below).

for i in *.mp3; do ffprobe -loglevel quiet -show_entries stream_tags:format_tags -of json -i "$i" |jq '.format.tags.["MusicBrainz Album Id"]' ; done;

All tracks have the following metadata:

{
  "title": "Wearing Perfume",
  "artist": "John Williams",
  "track": "8/22",
  "album": "A.I. Artificial Intelligence",
  "disc": "1/3",
  "genre": "Classical/Pop",
  "TMED": "CD",
  "MusicBrainz Release Group Id": "eede62fc-9356-3818-a8aa-b4c31a654a26",
  "TORY": "2001",
  "MusicBrainz Release Track Id": "ff3061fd-6620-4bfc-ad17-e5f29eb57e84",
  "TSRC": "USWB11504429",
  "SCRIPT": "Latn",
  "album_artist": "John Williams",
  "TSO2": "Williams, John",
  "artist-sort": "Williams, John",
  "publisher": "La‐La Land Records",
  "originalyear": "2001",
  "BARCODE": "826924135327",
  "ARTISTS": "John Williams",
  "CATALOGNUMBER": "LLLCD 1353",
  "MusicBrainz Album Status": "official",
  "MusicBrainz Album Release Country": "US",
  "MusicBrainz Album Type": "album/soundtrack",
  "Acoustid Id": "fe7def0e-948a-4853-979d-88fe36d994df",
  "MusicBrainz Album Id": "7985f15c-350a-4198-bc51-8b58490ec35f",
  "MusicBrainz Artist Id": "53b106e7-0cc6-42cc-ac95-ed8d30a3a98e",
  "MusicBrainz Album Artist Id": "53b106e7-0cc6-42cc-ac95-ed8d30a3a98e",
  "date": "2015-06-16"
}

All the files have the same:

• MusicBrainz Album Id
• CATALOGNUMBER
• MusicBrainz Release Group Id
• BARCODE

Command used:

for i in *.mp3; do ffprobe -loglevel quiet -show_entries stream_
tags:format_tags -of json -i $i | grep '"MusicBrainz Album Id"' | sed 's/.*: "\(.*\)".*/\1/' ; done | uniq

They were tagged with MusicBrainz Picard.

[ejurgensen]

Weird. Then I would suggest you run OwnTone in a debugger and set a breakpoint at the end of parse_albumid in filescanner_ffmpeg.c. Or add a log statement. Then use "touch" to trigger a rescan of two files that are in different albums. You should then be seeing two different songalbumids, and you can check the id_string that is used as input. That should give a clue.

[ejurgensen]

I think I know what the cause is. It's a regression from the lyrics change, PR #1655, where the way the metadata tags are read was changed to no longer be in the order of the struct. I will try to make a fix for it.

[hacketiwack]

Wow! You're great! Thanks a lot!

[ejurgensen]

I think it should be fixed with the latest commit. Unfortunately you will need to rescan the entire library to get the ID's set to the correct values.

[hacketiwack]

It works! Thanks a lot!