Koito/thoughts/plans/20260325_bulk_import_optimization.md
safierinx-a 8ce6ec494d Add bulk import optimization: track_lookup cache, batch inserts, BulkSubmitter
Adopts ListenBrainz-inspired patterns to speed up imports from ~24h to
under 30 minutes for 49k scrobbles.

Phase 1 - track_lookup cache table:
- New migration (000006) adds persistent entity lookup cache
- Maps normalized (artist, track, album) → (artist_id, album_id, track_id)
- SubmitListen fast path: cache hit skips 18 DB queries → 2 queries
- Cache populated after entity resolution, invalidated on merge/delete
- Benefits both live scrobbles and imports

Phase 2 - SaveListensBatch:
- New batch listen insert using pgx CopyFrom → temp table → INSERT ON CONFLICT
- Thousands of inserts per second vs one-at-a-time

Phase 3 - BulkSubmitter:
- Reusable import accelerator for all importers
- Pre-deduplicates scrobbles by (artist, track, album) in memory
- Worker pool (4 goroutines) for parallel entity creation on cache miss
- Batch listen insertion via SaveListensBatch

Phase 4 - Migrate importers:
- Maloja, Spotify, LastFM, ListenBrainz importers use BulkSubmitter
- Koito importer left as-is (already fast with pre-resolved IDs)

Phase 5 - Skip image lookups during import:
- GetArtistImage/GetAlbumImage calls fully skipped when SkipCacheImage=true
- Background tasks (FetchMissingArtistImages/FetchMissingAlbumImages) backfill

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 04:17:50 +05:30

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26 KiB
Markdown

# Bulk Import Optimization — Implementation Plan
## Overview
Optimize Koito's import pipeline from ~20 listens/min to thousands/min by adopting ListenBrainz-inspired patterns: a persistent entity lookup cache, batch DB writes, pre-deduplication, and deferred enrichment. The core insight from the ecosystem research is **write raw first, enrich async** — and the persistent lookup table benefits all scrobbles (live + import), not just bulk imports.
## Current State Analysis
### The Problem
Importing 49,050 Maloja scrobbles takes ~24 hours. The import is stable (our PR 1 fixes eliminated panics) but each scrobble runs through the full `SubmitListen` path:
- **`GetArtist`** issues 6 DB queries per lookup (including rank computation via window functions)
- **`GetAlbum`** issues 6 DB queries per lookup
- **`GetTrack`** issues 5-6 DB queries per lookup
- **`GetArtistImage` / `GetAlbumImage`** makes HTTP calls even when all image providers are disabled
- **`SaveListen`** is a single INSERT — the only fast part
Per unique scrobble: ~18 DB round-trips + 2 image lookups. Per repeated scrobble: ~18 DB round-trips (no caching). With 5,589 unique artists, 2,628 unique albums, and 49,050 total scrobbles, this is massively redundant.
### Key Discoveries
- `SubmitListenOpts.SkipSaveListen` (`catalog.go:43`) can be used to create entities without recording a listen — useful for entity pre-creation
- `SubmitListenOpts.SkipCacheImage` (`catalog.go:46`) controls image download but NOT image URL resolution — the HTTP calls still happen
- The Koito native importer (`importer/koito.go`) already bypasses `SubmitListen` and does direct DB calls — a precedent for a faster import path
- `pgxpool.Pool` is goroutine-safe — concurrent DB operations are safe at the pool level
- `SaveListen` SQL uses `ON CONFLICT DO NOTHING` — re-importing is idempotent
- No batch insert methods exist anywhere in the codebase
- `GetArtist`/`GetAlbum`/`GetTrack` compute full stats (listen count, time listened, rank) on every call — unnecessary during import
### Ecosystem Patterns (from research)
- **ListenBrainz**: Stores raw scrobbles immediately, resolves MBIDs asynchronously via background worker + Typesense index. Uses MessyBrainz as a stable `(artist, track, release) → ID` mapping.
- **Maloja**: Runs every import through the full normalize → dedup → cache-invalidate cycle. Works for live scrobbles, kills bulk import. **This is exactly Koito's current problem.**
- **Last.fm**: Resolves metadata at write time (corrections), batches up to 50 scrobbles per request.
- **General**: DB-level dedup via unique constraint + `ON CONFLICT` is the industry standard.
## Desired End State
1. A `track_lookup` table provides O(1) entity resolution for any `(artist, track, album)` tuple — both live and import scrobbles benefit
2. All 5 importers use a shared `BulkSubmitter` that pre-deduplicates, creates entities in parallel, and batch-inserts listens
3. Image/MBZ enrichment is fully deferred to existing background tasks during import
4. 49k Maloja import completes in **under 30 minutes** (vs 24 hours currently)
5. Live scrobbles are faster too — cache hit skips 18 DB queries, goes straight to 1 SELECT + 1 INSERT
### Verification
- `go build ./...` compiles
- `go test ./...` passes (existing + new tests)
- Manual: import 49k Maloja scrobbles in under 30 minutes on vo-pc
- Manual: verify live scrobbles from multi-scrobbler still work correctly
- Manual: verify album art appears after background image backfill runs
## What We're NOT Doing
- **Replacing the DB engine** (no TimescaleDB, no Redis) — Postgres is fine for self-hosted scale
- **Local MusicBrainz mirror or Typesense index** — overkill for single-user; the live API + background enrichment is sufficient
- **Changing the live `SubmitListen` API path** — the lookup cache makes it faster, but the logic stays the same
- **Parallelizing live scrobbles** — only imports use the worker pool; live scrobbles remain single-threaded through `SubmitListen`
- **Changing the ListenBrainz/Last.fm relay** — multi-scrobbler handles that independently
## Implementation Approach
Adopt ListenBrainz's "MessyBrainz" pattern as a persistent Postgres table: a normalized `(artist, track, album)` tuple maps to resolved `(artist_id, album_id, track_id)`. This is the foundational optimization — everything else builds on it.
```
Before (per scrobble):
GetArtist (6 queries) → GetAlbum (6 queries) → GetTrack (6 queries) → SaveListen (1 query)
= 19 queries minimum
After (cache hit):
SELECT FROM track_lookup (1 query) → SaveListen (1 query)
= 2 queries
After (bulk import, cache hit):
In-memory map lookup (0 queries) → batched SaveListen
= amortized ~0.01 queries per scrobble
```
---
## Phase 1: `track_lookup` Cache Table
### Overview
Add a persistent lookup table that maps normalized `(artist_name, track_title, release_title)` to resolved entity IDs. Integrate into `SubmitListen` so both live and import scrobbles benefit.
### Changes Required
#### 1. New Migration
**File**: `db/migrations/000006_track_lookup.sql`
```sql
-- +goose Up
CREATE TABLE track_lookup (
lookup_key TEXT NOT NULL PRIMARY KEY,
artist_id INT NOT NULL REFERENCES artists(id) ON DELETE CASCADE,
album_id INT NOT NULL REFERENCES releases(id) ON DELETE CASCADE,
track_id INT NOT NULL REFERENCES tracks(id) ON DELETE CASCADE,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE INDEX idx_track_lookup_track_id ON track_lookup(track_id);
CREATE INDEX idx_track_lookup_artist_id ON track_lookup(artist_id);
CREATE INDEX idx_track_lookup_album_id ON track_lookup(album_id);
-- +goose Down
DROP TABLE IF EXISTS track_lookup;
```
The `lookup_key` is a normalized string: `lower(artist) || '\x00' || lower(track) || '\x00' || lower(album)`. Using a single TEXT key with a null-byte separator is simpler and faster than a multi-column composite key with `citext`.
#### 2. New SQL Queries
**File**: `db/queries/track_lookup.sql`
```sql
-- name: GetTrackLookup :one
SELECT artist_id, album_id, track_id
FROM track_lookup
WHERE lookup_key = $1;
-- name: InsertTrackLookup :exec
INSERT INTO track_lookup (lookup_key, artist_id, album_id, track_id)
VALUES ($1, $2, $3, $4)
ON CONFLICT (lookup_key) DO UPDATE SET
artist_id = EXCLUDED.artist_id,
album_id = EXCLUDED.album_id,
track_id = EXCLUDED.track_id;
-- name: DeleteTrackLookupByArtist :exec
DELETE FROM track_lookup WHERE artist_id = $1;
-- name: DeleteTrackLookupByAlbum :exec
DELETE FROM track_lookup WHERE album_id = $1;
-- name: DeleteTrackLookupByTrack :exec
DELETE FROM track_lookup WHERE track_id = $1;
```
#### 3. Regenerate sqlc
Run `sqlc generate` to create the Go bindings in `internal/repository/`.
#### 4. DB Interface + Psql Implementation
**File**: `internal/db/db.go` — Add to interface:
```go
// Track Lookup Cache
GetTrackLookup(ctx context.Context, key string) (*TrackLookupResult, error)
SaveTrackLookup(ctx context.Context, opts SaveTrackLookupOpts) error
InvalidateTrackLookup(ctx context.Context, opts InvalidateTrackLookupOpts) error
```
**File**: `internal/db/opts.go` — Add types:
```go
type TrackLookupResult struct {
ArtistID int32
AlbumID int32
TrackID int32
}
type SaveTrackLookupOpts struct {
Key string
ArtistID int32
AlbumID int32
TrackID int32
}
type InvalidateTrackLookupOpts struct {
ArtistID int32
AlbumID int32
TrackID int32
}
```
**File**: `internal/db/psql/track_lookup.go` — New file implementing the three methods.
#### 5. Lookup Key Helper
**File**: `internal/catalog/lookup_key.go` — New file:
```go
package catalog
import "strings"
// TrackLookupKey builds a normalized cache key for entity resolution.
func TrackLookupKey(artist, track, album string) string {
return strings.ToLower(artist) + "\x00" + strings.ToLower(track) + "\x00" + strings.ToLower(album)
}
```
#### 6. Integrate into SubmitListen
**File**: `internal/catalog/catalog.go` — Add fast path at the top of `SubmitListen`:
```go
func SubmitListen(ctx context.Context, store db.DB, opts SubmitListenOpts) error {
l := logger.FromContext(ctx)
if opts.Artist == "" || opts.TrackTitle == "" {
return errors.New("track name and artist are required")
}
opts.Time = opts.Time.Truncate(time.Second)
// Fast path: check lookup cache for known entity combo
if !opts.SkipSaveListen {
key := TrackLookupKey(opts.Artist, opts.TrackTitle, opts.ReleaseTitle)
cached, err := store.GetTrackLookup(ctx, key)
if err == nil && cached != nil {
l.Debug().Msg("Track lookup cache hit — skipping entity resolution")
return store.SaveListen(ctx, db.SaveListenOpts{
TrackID: cached.TrackID,
Time: opts.Time,
UserID: opts.UserID,
Client: opts.Client,
})
}
}
// ... existing SubmitListen logic (unchanged) ...
// After successful entity resolution, populate the cache
store.SaveTrackLookup(ctx, db.SaveTrackLookupOpts{
Key: TrackLookupKey(opts.Artist, opts.TrackTitle, opts.ReleaseTitle),
ArtistID: artists[0].ID,
AlbumID: rg.ID,
TrackID: track.ID,
})
// ... rest of existing logic ...
}
```
Note: The cache only applies when we have a direct artist+track+album text match. Scrobbles with MBZ IDs that resolve to different text representations will still go through the full path on first encounter, then be cached.
#### 7. Invalidation on Merge/Delete
**File**: `internal/db/psql/artist.go` — In `DeleteArtist` and `MergeArtists`, add:
```go
d.q.DeleteTrackLookupByArtist(ctx, id)
```
**File**: `internal/db/psql/album.go` — In `DeleteAlbum` and `MergeAlbums`, add:
```go
d.q.DeleteTrackLookupByAlbum(ctx, id)
```
**File**: `internal/db/psql/track.go` — In `DeleteTrack` and `MergeTracks`, add:
```go
d.q.DeleteTrackLookupByTrack(ctx, id)
```
### Success Criteria
- [ ] `go build ./...` compiles
- [ ] `go test ./...` passes
- [ ] New test: `TestSubmitListen_LookupCacheHit` — second identical scrobble uses cache
- [ ] New test: `TestSubmitListen_LookupCacheInvalidateOnDelete` — deleting entity clears cache
- [ ] Migration applies cleanly on fresh and existing databases
- [ ] Live scrobbles from multi-scrobbler populate the cache on first hit, use it on second
---
## Phase 2: `SaveListensBatch` DB Method
### Overview
Add a batch listen insert method using pgx's `CopyFrom` for high-throughput listen insertion. This is the DB foundation for the BulkSubmitter.
### Changes Required
#### 1. New SQL + DB Interface
**File**: `internal/db/db.go` — Add to interface:
```go
SaveListensBatch(ctx context.Context, opts []SaveListenOpts) (int64, error)
```
Returns the number of rows actually inserted (excluding `ON CONFLICT` duplicates).
#### 2. Psql Implementation
**File**: `internal/db/psql/listen.go` — New method:
```go
func (d *Psql) SaveListensBatch(ctx context.Context, opts []db.SaveListenOpts) (int64, error) {
if len(opts) == 0 {
return 0, nil
}
// Use a transaction with a temp table + INSERT ... ON CONFLICT pattern
// since CopyFrom doesn't support ON CONFLICT directly
tx, err := d.conn.BeginTx(ctx, pgx.TxOptions{})
if err != nil {
return 0, fmt.Errorf("SaveListensBatch: BeginTx: %w", err)
}
defer tx.Rollback(ctx)
// Create temp table
_, err = tx.Exec(ctx, `
CREATE TEMP TABLE tmp_listens (
track_id INT,
listened_at TIMESTAMPTZ,
user_id INT,
client TEXT
) ON COMMIT DROP
`)
if err != nil {
return 0, fmt.Errorf("SaveListensBatch: create temp table: %w", err)
}
// CopyFrom into temp table
rows := make([][]interface{}, len(opts))
for i, o := range opts {
var client interface{}
if o.Client != "" {
client = o.Client
}
rows[i] = []interface{}{o.TrackID, o.Time, o.UserID, client}
}
_, err = tx.CopyFrom(ctx,
pgx.Identifier{"tmp_listens"},
[]string{"track_id", "listened_at", "user_id", "client"},
pgx.CopyFromRows(rows),
)
if err != nil {
return 0, fmt.Errorf("SaveListensBatch: CopyFrom: %w", err)
}
// Insert from temp table with dedup
tag, err := tx.Exec(ctx, `
INSERT INTO listens (track_id, listened_at, user_id, client)
SELECT track_id, listened_at, user_id, client FROM tmp_listens
ON CONFLICT DO NOTHING
`)
if err != nil {
return 0, fmt.Errorf("SaveListensBatch: insert: %w", err)
}
if err := tx.Commit(ctx); err != nil {
return 0, fmt.Errorf("SaveListensBatch: Commit: %w", err)
}
return tag.RowsAffected(), nil
}
```
This uses the standard `CopyFrom → temp table → INSERT ON CONFLICT` pattern, which is the fastest bulk insert approach with pgx while still supporting deduplication.
### Success Criteria
- [ ] `go build ./...` compiles
- [ ] `go test ./...` passes
- [ ] New test: `TestSaveListensBatch` — insert 1000 listens, verify count
- [ ] New test: `TestSaveListensBatch_Dedup` — insert duplicates, verify no double-counting
- [ ] New test: `TestSaveListensBatch_Empty` — empty input returns 0, no error
---
## Phase 3: `BulkSubmitter` Helper
### Overview
A reusable import accelerator that all importers can use. Pre-deduplicates scrobbles in memory, resolves entities via the `track_lookup` cache (falling back to `SubmitListen` on cache miss), and batch-inserts listens.
### Design
```
BulkSubmitter
├── Accept(SubmitListenOpts) — buffer a scrobble
├── Flush() (int, error) — process all buffered scrobbles
│ ├── Phase A: Deduplicate by (artist, track, album) key
│ ├── Phase B: Resolve entities
│ │ ├── Check track_lookup cache (single SELECT)
│ │ ├── On miss: call SubmitListen(SkipSaveListen=true) to create entities
│ │ ├── Worker pool: N goroutines for parallel entity creation
│ │ └── Populate track_lookup cache after creation
│ ├── Phase C: Map all scrobbles to track_ids via resolved cache
│ └── Phase D: SaveListensBatch
└── Progress callback for logging
```
### Changes Required
#### 1. New Package
**File**: `internal/importer/bulk.go`
```go
package importer
import (
"context"
"sync"
"github.com/gabehf/koito/internal/catalog"
"github.com/gabehf/koito/internal/db"
"github.com/gabehf/koito/internal/logger"
"github.com/gabehf/koito/internal/mbz"
)
type BulkSubmitter struct {
store db.DB
mbzc mbz.MusicBrainzCaller
ctx context.Context
buffer []catalog.SubmitListenOpts
workers int
onProgress func(imported, total int)
}
type BulkSubmitterOpts struct {
Store db.DB
Mbzc mbz.MusicBrainzCaller
Workers int // default 4
OnProgress func(imported, total int) // called every 500 items
}
func NewBulkSubmitter(ctx context.Context, opts BulkSubmitterOpts) *BulkSubmitter {
workers := opts.Workers
if workers <= 0 {
workers = 4
}
return &BulkSubmitter{
store: opts.Store,
mbzc: opts.Mbzc,
ctx: ctx,
workers: workers,
onProgress: opts.OnProgress,
}
}
func (bs *BulkSubmitter) Accept(opts catalog.SubmitListenOpts) {
bs.buffer = append(bs.buffer, opts)
}
func (bs *BulkSubmitter) Flush() (int, error) {
l := logger.FromContext(bs.ctx)
if len(bs.buffer) == 0 {
return 0, nil
}
l.Info().Msgf("BulkSubmitter: Processing %d scrobbles", len(bs.buffer))
// Phase A: Deduplicate — find unique (artist, track, album) tuples
type entityKey = string
unique := make(map[entityKey]catalog.SubmitListenOpts)
for _, opts := range bs.buffer {
key := catalog.TrackLookupKey(opts.Artist, opts.TrackTitle, opts.ReleaseTitle)
if _, exists := unique[key]; !exists {
unique[key] = opts
}
}
l.Info().Msgf("BulkSubmitter: %d unique entity combos from %d scrobbles", len(unique), len(bs.buffer))
// Phase B: Resolve entities — check cache, create on miss
resolved := make(map[entityKey]int32) // key → trackID
var mu sync.Mutex
var wg sync.WaitGroup
sem := make(chan struct{}, bs.workers)
resolveCount := 0
for key, opts := range unique {
// Check track_lookup cache first
cached, err := bs.store.GetTrackLookup(bs.ctx, key)
if err == nil && cached != nil {
mu.Lock()
resolved[key] = cached.TrackID
resolveCount++
mu.Unlock()
continue
}
// Cache miss — create entities via SubmitListen (with worker pool)
wg.Add(1)
sem <- struct{}{} // acquire worker slot
go func(k entityKey, o catalog.SubmitListenOpts) {
defer wg.Done()
defer func() { <-sem }() // release worker slot
o.SkipSaveListen = true
o.SkipCacheImage = true
err := catalog.SubmitListen(bs.ctx, bs.store, o)
if err != nil {
l.Err(err).Msgf("BulkSubmitter: Failed to create entities for '%s' by '%s'", o.TrackTitle, o.Artist)
return
}
// Re-check cache (SubmitListen populates it in Phase 1's integration)
cached, err := bs.store.GetTrackLookup(bs.ctx, k)
if err == nil && cached != nil {
mu.Lock()
resolved[k] = cached.TrackID
mu.Unlock()
}
}(key, opts)
}
wg.Wait()
l.Info().Msgf("BulkSubmitter: Resolved %d/%d entity combos", len(resolved), len(unique))
// Phase C: Build listen batch
batch := make([]db.SaveListenOpts, 0, len(bs.buffer))
skipped := 0
for _, opts := range bs.buffer {
key := catalog.TrackLookupKey(opts.Artist, opts.TrackTitle, opts.ReleaseTitle)
trackID, ok := resolved[key]
if !ok {
skipped++
continue
}
batch = append(batch, db.SaveListenOpts{
TrackID: trackID,
Time: opts.Time.Truncate(time.Second),
UserID: opts.UserID,
Client: opts.Client,
})
}
if skipped > 0 {
l.Warn().Msgf("BulkSubmitter: Skipped %d scrobbles with unresolved entities", skipped)
}
// Phase D: Batch insert listens
inserted, err := bs.store.SaveListensBatch(bs.ctx, batch)
if err != nil {
return 0, fmt.Errorf("BulkSubmitter: SaveListensBatch: %w", err)
}
l.Info().Msgf("BulkSubmitter: Inserted %d listens (%d duplicates skipped)", inserted, int64(len(batch))-inserted)
return int(inserted), nil
}
```
#### 2. TOCTOU Safety for Parallel Entity Creation
The worker pool creates entities via `SubmitListen(SkipSaveListen=true)`. Two workers could race on the same artist name. The existing code uses a get-then-save pattern. Mitigations:
- Pre-dedup in Phase A ensures each unique tuple is processed by exactly one goroutine — **no TOCTOU within the worker pool**
- The only remaining race is between the import workers and live scrobbles from multi-scrobbler hitting the same `SubmitListen` path. This is already handled by the DB's unique constraints + `ON CONFLICT` clauses on join tables.
### Success Criteria
- [ ] `go build ./...` compiles
- [ ] `go test ./...` passes
- [ ] New test: `TestBulkSubmitter_BasicImport` — buffer 100 scrobbles, flush, verify all imported
- [ ] New test: `TestBulkSubmitter_Dedup` — buffer 100 scrobbles with 10 unique combos, verify 10 entity creations
- [ ] New test: `TestBulkSubmitter_CacheHit` — pre-populate track_lookup, verify no SubmitListen calls
- [ ] New test: `TestBulkSubmitter_PartialFailure` — one entity creation fails, rest still imported
---
## Phase 4: Migrate All Importers
### Overview
Wire all 5 importers to use BulkSubmitter instead of calling `SubmitListen` directly in a loop.
### Changes Required
#### 1. Maloja Importer
**File**: `internal/importer/maloja.go`
Replace the per-item `catalog.SubmitListen` loop with:
```go
func ImportMalojaFile(ctx context.Context, store db.DB, mbzc mbz.MusicBrainzCaller, filename string) error {
l := logger.FromContext(ctx)
// ... file reading and JSON parsing (unchanged) ...
bs := NewBulkSubmitter(ctx, BulkSubmitterOpts{
Store: store,
Mbzc: mbzc,
OnProgress: func(imported, total int) {
l.Info().Msgf("Maloja import progress: %d/%d", imported, total)
},
})
for _, item := range items {
// ... existing artist parsing, time window check (unchanged) ...
bs.Accept(catalog.SubmitListenOpts{
MbzCaller: mbzc,
Artist: item.Track.Artists[0],
ArtistNames: artists,
TrackTitle: item.Track.Title,
ReleaseTitle: releaseTitle,
Time: ts.Local(),
Client: "maloja",
UserID: 1,
SkipCacheImage: true,
})
}
count, err := bs.Flush()
if err != nil {
return fmt.Errorf("ImportMalojaFile: %w", err)
}
return finishImport(ctx, filename, count)
}
```
#### 2. Spotify Importer
**File**: `internal/importer/spotify.go` — Same pattern: Accept into BulkSubmitter, Flush at end.
#### 3. LastFM Importer
**File**: `internal/importer/lastfm.go` — Same pattern. Note: LastFM scrobbles include MBZ IDs, which will pass through to `SubmitListen` on cache miss for proper entity resolution.
#### 4. ListenBrainz Importer
**File**: `internal/importer/listenbrainz.go` — Same pattern. ListenBrainz data is the richest (full MBZ IDs, MBID mappings) — cache hits will be common after first import.
#### 5. Koito Importer
**File**: `internal/importer/koito.go` — This one currently bypasses `SubmitListen` with direct DB calls. Two options:
- **Option A**: Migrate to BulkSubmitter (consistent, benefits from cache)
- **Option B**: Leave as-is (it's already fast, Koito exports have pre-resolved IDs)
Recommend **Option A** for consistency, with the Koito importer becoming the simplest BulkSubmitter user since its data is pre-resolved.
### Success Criteria
- [ ] `go build ./...` compiles
- [ ] `go test ./...` passes — all existing import tests still pass
- [ ] `TestImportMaloja` — 38 listens imported correctly
- [ ] `TestImportMaloja_NullAlbum` — null album handled
- [ ] `TestImportMaloja_ApiFormat` — list format works
- [ ] `TestImportSpotify` — duration data preserved
- [ ] `TestImportLastFM` — MBZ IDs resolved
- [ ] `TestImportListenBrainz` — MBID mappings applied
- [ ] `TestImportKoito` — aliases preserved
- [ ] Manual: 49k Maloja import on vo-pc completes in under 30 minutes
---
## Phase 5: Skip Image Lookups During Import
### Overview
Short-circuit `GetArtistImage` and `GetAlbumImage` calls when `SkipCacheImage` is true. Currently these functions still make HTTP calls (or call providers that return "no providers enabled") even when the result won't be used. The existing background tasks (`FetchMissingArtistImages`, `FetchMissingAlbumImages`) will backfill images after import.
### Changes Required
#### 1. Early Return in Associate Functions
**File**: `internal/catalog/associate_artists.go`
In `resolveAliasOrCreateArtist` (line ~248) and `matchArtistsByNames` (line ~304):
```go
// Before:
imgUrl, err := images.GetArtistImage(ctx, images.ArtistImageOpts{...})
if err == nil && imgUrl != "" {
imgid = uuid.New()
if !opts.SkipCacheImage {
// download image
}
}
// After:
var imgUrl string
if !opts.SkipCacheImage {
imgUrl, err = images.GetArtistImage(ctx, images.ArtistImageOpts{...})
if err == nil && imgUrl != "" {
imgid = uuid.New()
// download image
}
}
```
**File**: `internal/catalog/associate_album.go`
Same pattern in `createOrUpdateAlbumWithMbzReleaseID` (line ~125) and `matchAlbumByTitle` (line ~220).
### Success Criteria
- [ ] `go build ./...` compiles
- [ ] `go test ./...` passes
- [ ] No `GetArtistImage`/`GetAlbumImage` calls during import (verify via log: no "No image providers" warnings)
- [ ] Background tasks still fetch images after import completes
- [ ] Live scrobbles (SkipCacheImage=false) still fetch images normally
---
## Performance Estimates
| Scenario | Current | After Phase 1 | After All Phases |
|---|---|---|---|
| Repeated live scrobble | ~19 queries | 2 queries (cache hit) | 2 queries |
| New live scrobble | ~19 queries | ~19 queries + 1 cache write | ~19 queries + 1 cache write |
| 49k Maloja import | ~24 hours | ~12 hours (cache helps repeats) | ~15-30 minutes |
| 49k import (second run) | ~24 hours | ~20 minutes (all cache hits) | ~5 minutes |
## Implementation Order
1. **Phase 1** (track_lookup) — standalone, immediate benefit for all scrobbles
2. **Phase 5** (skip image lookups) — standalone, no dependencies, quick win
3. **Phase 2** (SaveListensBatch) — DB layer, needed by Phase 3
4. **Phase 3** (BulkSubmitter) — the core, depends on Phase 1 + 2
5. **Phase 4** (migrate importers) — depends on Phase 3
Phases 1 and 5 can be done first as independent PRs. Phases 2-4 are one PR.
## References
- ListenBrainz architecture: https://listenbrainz.readthedocs.io/en/latest/developers/architecture.html
- ListenBrainz MBID mapping: https://listenbrainz.readthedocs.io/en/latest/developers/mapping.html
- MusicBrainz rate limiting: https://musicbrainz.org/doc/MusicBrainz_API/Rate_Limiting
- PR 1 (importer fixes): https://github.com/gabehf/Koito/pull/228
- PR 2 (MBZ search): https://github.com/gabehf/Koito/pull/229
- Koito native importer (bypass pattern): `internal/importer/koito.go`
- Current SubmitListen: `internal/catalog/catalog.go:70`
- pgx CopyFrom docs: https://pkg.go.dev/github.com/jackc/pgx/v5#Conn.CopyFrom