api: non-blocking /sync via background refresher (full-scan counts cached)
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+56
-10
@@ -7,6 +7,7 @@ whole data flow being pulsed and recognised downstream.
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from __future__ import annotations
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import asyncio
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import os
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import time
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from typing import Any
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@@ -43,6 +44,29 @@ SOURCE_COUNT_SQL = {
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}
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_token_cache: dict[str, Any] = {"token": None, "exp": 0.0}
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# count(*) over these connectors does a full scan (slow), so a background task
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# refreshes the counts periodically and the endpoint always returns instantly.
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_sync_cache: dict[str, Any] = {"counts": {k: None for k in SOURCE_COUNT_SQL}, "ts": 0.0}
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_refresher_started = False
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_SYNC_INTERVAL = 60.0
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async def _sync_refresh_loop() -> None:
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while True:
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try:
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keys = list(SOURCE_COUNT_SQL.keys())
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results = await asyncio.gather(
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*[_trino_scalar(SOURCE_COUNT_SQL[k], deadline_s=90.0) for k in keys]
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)
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merged = dict(_sync_cache["counts"])
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for k, v in zip(keys, results):
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if v is not None:
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merged[k] = v
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_sync_cache["counts"] = merged
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_sync_cache["ts"] = time.time()
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except Exception:
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pass
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await asyncio.sleep(_SYNC_INTERVAL)
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async def _airflow_token(client: httpx.AsyncClient) -> str:
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@@ -61,9 +85,16 @@ async def _airflow_token(client: httpx.AsyncClient) -> str:
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return tok
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async def _trino_scalar(sql: str, timeout: float = 12.0) -> int | None:
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async def _trino_scalar(sql: str, deadline_s: float = 8.0) -> int | None:
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"""Run a scalar Trino query with a hard wall-clock deadline.
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count(*) over a large Cassandra table can scan for a long time; without a
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total deadline the result-paging loop would hang the endpoint. On timeout
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we abort the query and return None so the UI degrades gracefully.
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"""
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end = time.time() + deadline_s
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try:
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async with httpx.AsyncClient(timeout=timeout) as client:
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async with httpx.AsyncClient(timeout=5.0) as client:
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r = await client.post(
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f"{TRINO_URL}/v1/statement",
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content=sql.encode(),
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@@ -71,10 +102,16 @@ async def _trino_scalar(sql: str, timeout: float = 12.0) -> int | None:
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)
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data = r.json()
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rows: list[Any] = []
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nxt = data.get("nextUri")
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if data.get("data"):
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rows += data["data"]
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nxt = data.get("nextUri")
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while nxt:
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if time.time() > end:
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try:
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await client.delete(nxt, timeout=3.0)
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except Exception:
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pass
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return None
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rr = await client.get(nxt)
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d = rr.json()
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if d.get("data"):
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@@ -156,10 +193,19 @@ async def runs(source: str, limit: int = Query(5)) -> JSONResponse:
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@router.get("/sync")
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async def sync(source: str | None = Query(None)) -> JSONResponse:
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"""Live row counts per source (via Trino) for the 'in sync' display."""
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targets = [source] if source and source in SOURCE_COUNT_SQL else list(SOURCE_COUNT_SQL.keys())
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counts: dict[str, Any] = {}
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for src in targets:
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counts[src] = await _trino_scalar(SOURCE_COUNT_SQL[src])
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return JSONResponse({"ok": True, "counts": counts})
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async def sync(source: str | None = Query(None), refresh: bool = Query(False)) -> JSONResponse:
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"""Live row counts per source (via Trino) for the 'in sync' display.
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Counts are cached (TTL) and refreshed concurrently because count(*) over
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these connectors does a full scan. Returns immediately from cache when
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fresh; otherwise refreshes once (other concurrent callers reuse the cache).
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"""
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global _refresher_started
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if not _refresher_started:
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_refresher_started = True
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asyncio.create_task(_sync_refresh_loop())
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counts = _sync_cache["counts"]
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age = round(time.time() - _sync_cache["ts"], 1) if _sync_cache["ts"] else None
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if source and source in counts:
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return JSONResponse({"ok": True, "counts": {source: counts[source]}, "age_s": age})
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return JSONResponse({"ok": True, "counts": counts, "age_s": age})
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