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that the scanner was run, the ttlcache was also created each time. This caused (under testing with 166 genres in the database) the memory consumed by navidrome to 101.18MB over approx 3 days; 96% of which is in instances of this cache. Swapping to a singleton has reduced this to down to ~ 2.6MB Co-authored-by: Rob Emery <git@mintsoft.net>
47 lines
1.1 KiB
Go
47 lines
1.1 KiB
Go
package scanner
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import (
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"context"
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"strings"
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"time"
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"github.com/jellydator/ttlcache/v2"
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"github.com/navidrome/navidrome/log"
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"github.com/navidrome/navidrome/model"
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"github.com/navidrome/navidrome/utils/singleton"
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)
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func newCachedGenreRepository(ctx context.Context, repo model.GenreRepository) model.GenreRepository {
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return singleton.GetInstance(func() *cachedGenreRepo {
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r := &cachedGenreRepo{
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GenreRepository: repo,
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ctx: ctx,
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}
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genres, err := repo.GetAll()
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if err != nil {
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log.Error(ctx, "Could not load genres from DB", err)
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panic(err)
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}
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r.cache = ttlcache.NewCache()
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for _, g := range genres {
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_ = r.cache.Set(strings.ToLower(g.Name), g.ID)
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}
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return r
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})
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}
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type cachedGenreRepo struct {
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model.GenreRepository
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cache *ttlcache.Cache
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ctx context.Context
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}
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func (r *cachedGenreRepo) Put(g *model.Genre) error {
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id, err := r.cache.GetByLoader(strings.ToLower(g.Name), func(key string) (interface{}, time.Duration, error) {
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err := r.GenreRepository.Put(g)
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return g.ID, 24 * time.Hour, err
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})
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g.ID = id.(string)
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return err
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}
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