-- Keep ListenBrainz's whole similar-recordings answer, and record every
-- fetch, so the library match is made locally and can be made again.
--
-- Before: the worker kept only the recordings already in the library (at most
-- 20 of LB's 50) and threw the rest away. Two things followed:
--
--   * A recording that reached the library later — a Lidarr import, or an MBID
--     filled in by the AcoustID lookup — was not linked until its seed was
--     fetched again.
--   * A seed with no in-library match wrote nothing at all, and freshness was
--     read from track_similarity, so that seed was never fresh. With the queue
--     ordered by id, such seeds held its head and were re-asked every hour
--     while the rest waited.
--
-- The listenbrainz rows in track_similarity are now derived from this cache by
-- ResolveListenBrainzTrackEdges.

CREATE TABLE listenbrainz_similar_recordings (
    seed_track_id   uuid             NOT NULL REFERENCES tracks(id) ON DELETE CASCADE,
    recording_mbid  text             NOT NULL,
    score           DOUBLE PRECISION NOT NULL,
    PRIMARY KEY (seed_track_id, recording_mbid)
);

-- The resolve joins the cache to tracks by recording MBID.
CREATE INDEX listenbrainz_similar_recordings_mbid_idx
    ON listenbrainz_similar_recordings (recording_mbid);

-- One row per seed that ListenBrainz has answered for, an empty answer
-- included. The worker's queue reads this, not the edges.
CREATE TABLE track_similarity_fetches (
    track_id    uuid        PRIMARY KEY REFERENCES tracks(id) ON DELETE CASCADE,
    fetched_at  timestamptz NOT NULL DEFAULT now(),
    returned    integer     NOT NULL
);

-- The same for artists. Their answer is already kept, in artist_similarity and
-- artist_similarity_unmatched; this only stops an empty answer being re-asked.
CREATE TABLE artist_similarity_fetches (
    artist_id   uuid        PRIMARY KEY REFERENCES artists(id) ON DELETE CASCADE,
    fetched_at  timestamptz NOT NULL DEFAULT now(),
    returned    integer     NOT NULL
);