perf(db): the channel manager and the feed sidebar read an index, not the video heap
GET /api/channels summed every subscribed channel's videos by reading each video's heap page (681 MB on prod): 51-61 ms warm, but 2.25 s on a first open and 6.4 s under EXPLAIN once the table had left memory. /feed/summary and /feed/years did the same (~140 ms warm, ~800 ms cold). Migration 0095 replaces ix_videos_channel_pub_desc with the same key INCLUDING the columns those queries read, so they are Index Only Scans over a 25 MB index. A test holds the queries and the index's column list together. The admin Configuration page did a db.get per setting (two for an unset one): it now reads every override in one query (~40 ms of ~55 on prod).
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@@ -6,7 +6,7 @@ from datetime import datetime, timezone
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from fastapi import APIRouter, BackgroundTasks, Depends
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from pydantic import BaseModel
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from sqlalchemy import func, select, update
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from sqlalchemy import Select, func, select, update
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from sqlalchemy.orm import Session
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from app.collation import collated, sorted_words
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@@ -40,6 +40,22 @@ router = APIRouter(prefix="/api/channels", tags=["channels"])
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log = logs.get_logger(__name__)
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def channel_aggregates(channel_ids: list[str]) -> Select:
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"""Per-channel stored count, last upload and total duration, in one grouped pass. Every column it
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reads is in `ix_videos_channel_pub_cover` (migration 0095), so Postgres answers it from the index
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alone; a test holds that (test_channel_list_index_only)."""
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return (
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select(
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Video.channel_id,
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func.count(Video.id),
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func.max(Video.published_at),
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func.coalesce(func.sum(Video.duration_seconds), 0),
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)
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.where(Video.channel_id.in_(channel_ids))
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.group_by(Video.channel_id)
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)
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@router.get("")
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def list_channels(user: User = Depends(current_user), db: Session = Depends(get_db)) -> list[dict]:
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rows = db.execute(
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@@ -49,24 +65,15 @@ def list_channels(user: User = Depends(current_user), db: Session = Depends(get_
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.order_by(Subscription.priority.desc(), collated(Channel.title, lang_for_user(user)))
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).all()
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# Per-channel aggregates over the shared catalog in ONE grouped pass: stored count, last
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# upload, total duration. Cheap — a single grouped scan, so computed on read rather than
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# denormalised (measure-first: reads aren't frequent/hot enough to warrant cached columns).
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# Per-channel aggregates over the shared catalog (channel_aggregates), computed on read rather than
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# denormalised: an Index Only Scan over a ~20 MB index, where it used to read every video's heap page
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# (681 MB on prod, a 2–6 s first open once something else had pushed it out of memory, E31 S4d).
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# (The Normal/Shorts/Live breakdown moved to the channel-detail page in R14, so it is no longer
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# computed here — the manager table dropped its N/S/L column.)
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channel_ids = [c.id for _, c in rows]
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agg: dict[str, dict] = {}
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if channel_ids:
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for cid, n, last_up, total_dur in db.execute(
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select(
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Video.channel_id,
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func.count(Video.id),
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func.max(Video.published_at),
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func.coalesce(func.sum(Video.duration_seconds), 0),
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)
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.where(Video.channel_id.in_(channel_ids))
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.group_by(Video.channel_id)
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).all():
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for cid, n, last_up, total_dur in db.execute(channel_aggregates(channel_ids)).all():
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agg[cid] = {
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"stored": n,
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"last_video_at": iso(last_up),
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