uranusjr commented on code in PR #66463:
URL: https://github.com/apache/airflow/pull/66463#discussion_r3219190096
##########
airflow-core/src/airflow/state/metastore.py:
##########
@@ -252,6 +272,51 @@ def _clear_asset_state(self, scope: AssetScope, *,
session: Session) -> None:
)
)
+ def cleanup(self) -> None:
+ """
+ Remove expired task state rows.
+
+ ``expires_at`` is set at write time on every ``set()`` call, so
cleanup is a single
+ ``WHERE expires_at < now()`` pass. Rows with ``expires_at=NULL``
(default_retention_days=0)
+ are never deleted. Batching is configurable via ``[state_store]
state_cleanup_batch_size``.
+ """
+ batch_size = conf.getint("state_store", "state_cleanup_batch_size")
+ now = timezone.utcnow()
+
+ def _delete_batched(where_clause) -> int:
+ total = 0
+ with create_session() as session:
+ while True:
+ id_query = select(TaskStateModel.id).where(where_clause)
+ if batch_size > 0:
+ id_query = id_query.limit(batch_size)
+ ids = session.scalars(id_query).all()
+ if not ids:
+ break
+
session.execute(delete(TaskStateModel).where(TaskStateModel.id.in_(ids)))
+ session.commit()
+ total += len(ids)
+ if batch_size <= 0 or len(ids) < batch_size:
+ break
+ return total
+
+ deleted = _delete_batched(TaskStateModel.expires_at < now)
Review Comment:
What do you mean by a second pass? Where would this happen? (In abstract it
sounds like a plan; it’s similar to how the next run needs to be recalculated
when you change the dag schedule definition.)
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