yuseok89 commented on code in PR #67242:
URL: https://github.com/apache/airflow/pull/67242#discussion_r3318841858
##########
airflow-core/src/airflow/api_fastapi/core_api/routes/ui/dags.py:
##########
@@ -308,3 +311,45 @@ def get_latest_run_info(dag_id: str, session: SessionDep)
-> DAGRunLightResponse
latest_run_info = session.execute(latest_run_info_select).one_or_none()
return DAGRunLightResponse(**latest_run_info._mapping) if latest_run_info
else None
+
+
+@dags_router.get(
+ "/run_state_counts",
+ dependencies=[
+ Depends(requires_access_dag(method="GET")),
+ Depends(requires_access_dag(method="GET",
access_entity=DagAccessEntity.RUN)),
+ ],
+ operation_id="get_dag_run_state_counts_ui",
+)
+def get_dag_run_state_counts(
+ session: SessionDep,
+ readable_dags_filter: ReadableDagsFilterDep,
+ dag_ids: Annotated[list[str], Query(min_length=1)],
+ run_after_gte: datetime | None = None,
+) -> DAGsRunStateCountsCollectionResponse:
+ """Return per-Dag DagRun state counts (zero-filled) for the Dag list
page."""
+ permitted_dag_ids = readable_dags_filter.value or set()
+ requested_dag_ids = [dag_id for dag_id in dict.fromkeys(dag_ids) if dag_id
in permitted_dag_ids]
+ counts_by_dag: dict[str, dict[DagRunState, int]] = {
+ dag_id: {state: 0 for state in DagRunState} for dag_id in
requested_dag_ids
+ }
+
+ if requested_dag_ids:
+ count_query = (
+ select(DagRun.dag_id, DagRun.state, func.count().label("cnt"))
+ .where(DagRun.dag_id.in_(requested_dag_ids))
+ .group_by(DagRun.dag_id, DagRun.state)
+ )
+ if run_after_gte is not None:
+ count_query = count_query.where(DagRun.run_after >= run_after_gte)
+ for row in session.execute(count_query):
+ if row.state is None:
+ continue
+ counts_by_dag[row.dag_id][DagRunState(row.state)] = row.cnt
+
Review Comment:
I'm fully on board with UI scalability being the priority.
One thing I noticed, though. Even at 5M, which is below the 10M figure that
has come up, the Home page (the scalable reference here) is already fairly
slow. See the attached capture of the load time with 5M DagRuns.
<img width="988" height="472" alt="image"
src="https://github.com/user-attachments/assets/b246504c-bf30-436e-a1b6-72a6b9c85c60";
/>
Are numbers like 5M to 10M runs realistic targets to design around?
> How do you generate that many runs?
On generating the data, I created the 5M by bulk-inserting DagRun rows
directly into the metadata DB from a breeze shell, with a one-off script (no
scheduler involved). If that isn't a representative way to stress-test this,
please let me know.
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