╭─────────────────────────────────────────────────────────╮
│ ✻ Welcome to Claude Code!                               │
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│   /help for help, /status for your current setup        │
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│   cwd: /Users/cloud/github.com/cloud8421/music_library  │
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> Can you optimize this query?

SELECT s0."scrobbled_at_uts", s0."musicbrainz_id", s0."title", s0."cover_url", s0."scrobbled_at_label", s0."artist", s0."album", 
s0."last_fm_data", s1."record_id", s2."record_id", s3."musicbrainz_id", coalesce(s1."cover_hash", s2."cover_hash") FROM 
"scrobbled_tracks" AS s0 LEFT OUTER JOIN (SELECT records.id AS "record_id", records.cover_hash AS "cover_hash", sf0."value" AS 
"release_id" FROM records, json_each(records.release_ids) AS sf0 WHERE (records.purchased_at IS NOT NULL)) AS s1 ON 
s1."release_id" = s0."album" ->> '$.musicbrainz_id' LEFT OUTER JOIN (SELECT records.id AS "record_id", records.cover_hash AS 
"cover_hash", sf0."value" AS "release_id" FROM records, json_each(records.release_ids) AS sf0 WHERE (records.purchased_at IS 
NULL)) AS s2 ON s2."release_id" = s0."album" ->> '$.musicbrainz_id' LEFT OUTER JOIN (SELECT DISTINCT sa0."musicbrainz_id" AS 
"musicbrainz_id", sa0."record_id" AS "record_id", sa0."artist" AS "artist" FROM "artist_records" AS sa0) AS s3 ON (s2."record_id" 
= s3."record_id") OR (s1."record_id" = s3."record_id") ORDER BY s0."scrobbled_at_uts" DESC LIMIT 100

⏺ I'll analyze this query to identify optimization opportunities. Let me first examine the current database schema and understand
  the query structure.
  ⎿  * LastFm.Album at lib/last_fm/album.ex:1                                                                                    
     * LastFm.Artist at lib/last_fm/artist.ex:1
     * LastFm.Track at lib/last_fm/track.ex:1
     … +11 lines (ctrl+o to expand)

⏺ Search(pattern: "scrobbled_tracks")
  ⎿  Found 11 files (ctrl+o to expand)

⏺ Read(lib/last_fm/track.ex)
  ⎿  Read 95 lines (ctrl+o to expand)

⏺ Read(priv/repo/migrations/20250530203701_create_scrobbled_tracks.exs)
  ⎿  Read 19 lines (ctrl+o to expand)

⏺ Read(lib/music_library/records/record.ex)
  ⎿  Read 276 lines (ctrl+o to expand)

⏺ Now let me find where this query is being generated to understand the context:

⏺ Search(pattern: "FROM.*scrobbled_tracks.*AS s0")
  ⎿  Found 0 files 

⏺ Search(pattern: "scrobbled_tracks.*LEFT OUTER JOIN", output_mode: "content")
  ⎿  Found 0 lines 

⏺ Search(pattern: "json_each.*release_ids")
  ⎿  Found 3 files (ctrl+o to expand)

⏺ Search(pattern: "scrobbled_tracks.*s0", output_mode: "content")
  ⎿  Found 0 lines 

⏺ Let me search in the last_fm.ex file where this query might be generated:

⏺ Read(lib/last_fm.ex)
  ⎿  Read 87 lines (ctrl+o to expand)

⏺ Let me search for more specific patterns to find where this query is generated:

⏺ Search(pattern: "purchased_at IS NOT NULL")
  ⎿  Found 2 files (ctrl+o to expand)

⏺ Read(lib/music_library/collection.ex)
  ⎿  Read 127 lines (ctrl+o to expand)

⏺ Search(pattern: "coalesce.*cover_hash")
  ⎿  Found 1 file (ctrl+o to expand)

⏺ Read(lib/music_library/scrobble_activity.ex)
  ⎿  Read 472 lines (ctrl+o to expand)

⏺ Found it! The query comes from the recent_activity/2 function in MusicLibrary.ScrobbleActivity. Let me examine the database
  indexes to understand the current optimization opportunities:

⏺ tidewave - execute_sql_query (MCP)(query: "SELECT name, sql FROM sqlite_master WHERE type='index' AND tbl_name IN
                                    ('scrobbled_tracks', 'records') ORDER BY tbl_name, name")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["name", "sql"],
     … +3 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "SELECT name, sql FROM sqlite_master WHERE type='index' ORDER BY name")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["name", "sql"],
     … +7 lines (ctrl+o to expand)

⏺ Let me check what indexes exist specifically for the tables we're working with:

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_list('scrobbled_tracks')")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seq", "name", "unique", "origin", "partial"],
     … +3 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_list('records')")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seq", "name", "unique", "origin", "partial"],
     … +3 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "SELECT name FROM sqlite_master WHERE type='table' ORDER BY name")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["name"],
     … +3 lines (ctrl+o to expand)

⏺ Let me check if the scrobbled_tracks table actually exists and examine its structure:

⏺ tidewave - execute_sql_query (MCP)(query: ".tables")
  ⎿  Error: Failed to execute query: %Exqlite.Error{message: "near \".\": syntax error", statement: ".tables"}

⏺ Bash(mix ecto.migrate)
  ⎿ 21:39:52.643 [info] Migrations already up                                                                                    

    21:39:52.646 [debug] Exqlite: loading extension `/Users/cloud/github.com/cloud8421/music_library/_build/dev/lib/music_library
    … +5 lines (ctrl+o to expand)


⏺ tidewave - execute_sql_query (MCP)(query: "SELECT name FROM sqlite_master WHERE type='table' AND name LIKE '%scrobbled%' OR name
                                    LIKE '%records%'")
  ⎿  %Exqlite.Result{command: :execute, columns: ["name"], rows: [], num_rows: 0}                                                

⏺ tidewave - execute_sql_query (MCP)(query: "SELECT name FROM sqlite_master WHERE type='table'", repo: "MusicLibrary.Repo")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["name"],
     … +28 lines (ctrl+o to expand)

⏺ Now let me check the existing indexes:

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_list('scrobbled_tracks')", repo: "MusicLibrary.Repo")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seq", "name", "unique", "origin", "partial"],
     … +3 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_list('records')", repo: "MusicLibrary.Repo")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seq", "name", "unique", "origin", "partial"],
     … +18 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_info('scrobbled_tracks_scrobbled_at_uts_title_index')", repo:
                                    "MusicLibrary.Repo")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seqno", "cid", "name"],
     … +3 lines (ctrl+o to expand)

⏺ tidewave - execute_sql_query (MCP)(query: "PRAGMA index_info('records_release_ids_index')", repo: "MusicLibrary.Repo")
  ⎿  %Exqlite.Result{                                                                                                            
       command: :execute,
       columns: ["seqno", "cid", "name"],
     … +3 lines (ctrl+o to expand)

⏺ Query Optimization Analysis

  The query from MusicLibrary.ScrobbleActivity.recent_activity/2 has several optimization opportunities:

  Current Issues:

  1. Complex subqueries with json_each(): The query uses json_each() on release_ids arrays for both collection and wishlist joins,
   which is expensive for each row.
  2. Multiple LEFT JOINs with subqueries: Three separate subqueries are executed and joined, creating a cartesian product that's
  then filtered.
  3. JSON extraction in WHERE clauses: Using fragment("? ->> '$.musicbrainz_id'", t.album) requires JSON parsing for every row.
  4. Missing indexes: No composite indexes for the JSON-based join conditions.

  Recommended Optimizations:

  1. Add Strategic Indexes

  -- Index for album musicbrainz_id JSON extraction (most critical)
  CREATE INDEX idx_scrobbled_tracks_album_mbid
  ON scrobbled_tracks((album ->> '$.musicbrainz_id'));

  -- Composite index for the main query
  CREATE INDEX idx_scrobbled_tracks_scrobbled_at_album_mbid
  ON scrobbled_tracks(scrobbled_at_uts DESC, (album ->> '$.musicbrainz_id'));

  2. Rewrite the Query Structure

  Instead of multiple subqueries, use CTEs and reduce the number of joins:

  def recent_activity_optimized(timezone, limit \\ 100) do
    # Single CTE for all releases with their collection/wishlist status
    releases_cte = """
    WITH releases AS (
      SELECT 
        r.id as record_id,
        r.cover_hash,
        r.purchased_at IS NOT NULL as is_collected,
        sf.value as release_id
      FROM records r, json_each(r.release_ids) sf
    )
    """

    query = from t in Track,
      left_join: r in fragment("""
        (SELECT record_id, cover_hash, release_id,
                CASE WHEN is_collected THEN record_id END as collected_record_id,
                CASE WHEN NOT is_collected THEN record_id END as wishlisted_record_id
         FROM releases)
      """),
      on: r.release_id == fragment("? ->> '$.musicbrainz_id'", t.album),
      left_join: ar in ArtistRecord,
      on: ar.record_id == r.record_id,
      order_by: [desc: t.scrobbled_at_uts],
      limit: ^limit,
      select: %{
        track: t,
        collected_record_id: r.collected_record_id,
        wishlisted_record_id: r.wishlisted_record_id,
        artist_id: ar.musicbrainz_id,
        cover_hash: r.cover_hash
      }
  end

  3. Alternative: Materialized View Approach

  Create a materialized view that pre-joins release data:

  CREATE VIEW release_lookup AS
  SELECT
    r.id as record_id,
    r.cover_hash,
    r.purchased_at IS NOT NULL as is_collected,
    sf.value as release_id
  FROM records r, json_each(r.release_ids) sf;

  CREATE INDEX idx_release_lookup_release_id ON release_lookup(release_id);

  4. Denormalization Option

  Consider adding a release_musicbrainz_id field directly to scrobbled_tracks to avoid JSON extraction:

  # In migration
  add :album_musicbrainz_id, :string
  create index(:scrobbled_tracks, [:album_musicbrainz_id])
  create index(:scrobbled_tracks, [:scrobbled_at_uts, :album_musicbrainz_id])

⏺ Immediate Impact Recommendations:

  High Impact, Low Risk:
  1. Add the JSON extraction index: CREATE INDEX idx_scrobbled_tracks_album_mbid ON scrobbled_tracks((album ->> 
  '$.musicbrainz_id'))
  2. Add composite index: CREATE INDEX idx_scrobbled_tracks_scrobbled_at_album_mbid ON scrobbled_tracks(scrobbled_at_uts DESC, 
  (album ->> '$.musicbrainz_id'))

  Medium Impact, Medium Risk:
  3. Rewrite query to use a single CTE instead of multiple subqueries
  4. Create the release_lookup view for better join performance

  High Impact, Higher Risk:
  5. Denormalize by adding album_musicbrainz_id column to eliminate JSON extraction entirely

  The most critical optimization is adding indexes for the JSON extraction operations, which should provide immediate performance
  improvements with no code changes required.