ashb commented on a change in pull request #16401:
URL: https://github.com/apache/airflow/pull/16401#discussion_r659897924
##########
File path: airflow/jobs/scheduler_job.py
##########
@@ -984,89 +956,86 @@ def _create_dag_runs(self, dag_models:
Iterable[DagModel], session: Session) ->
# are not updated.
# We opted to check DagRun existence instead
# of catching an Integrity error and rolling back the session i.e
- # we need to run self._update_dag_next_dagruns if the Dag Run
already exists or if we
+ # we need to set dag.next_dagrun_info if the Dag Run already
exists or if we
# create a new one. This is so that in the next Scheduling loop we
try to create new runs
# instead of falling in a loop of Integrity Error.
- if (dag.dag_id, dag_model.next_dagrun) not in active_dagruns:
- run = dag.create_dagrun(
+ if (dag.dag_id, dag_model.next_dagrun) not in existing_dagruns:
+ dag.create_dagrun(
run_type=DagRunType.SCHEDULED,
execution_date=dag_model.next_dagrun,
- start_date=timezone.utcnow(),
- state=State.RUNNING,
+ state=State.QUEUED,
external_trigger=False,
session=session,
dag_hash=dag_hash,
creating_job_id=self.id,
)
-
- expected_start_date =
dag.following_schedule(run.execution_date)
- if expected_start_date:
- schedule_delay = run.start_date - expected_start_date
- Stats.timing(
- f'dagrun.schedule_delay.{dag.dag_id}',
- schedule_delay,
- )
-
- self._update_dag_next_dagruns(dag_models, session)
+ dag_model.next_dagrun, dag_model.next_dagrun_create_after =
dag.next_dagrun_info(
+ dag_model.next_dagrun
+ )
# TODO[HA]: Should we do a session.flush() so we don't have to keep
lots of state/object in
# memory for larger dags? or expunge_all()
- def _update_dag_next_dagruns(self, dag_models: Iterable[DagModel],
session: Session) -> None:
+ def _start_queued_dagruns(
+ self,
+ session: Session,
+ ) -> int:
"""
- Bulk update the next_dagrun and next_dagrun_create_after for all the
dags.
+ Find DagRuns in queued state and decide moving them to running state
- We batch the select queries to get info about all the dags at once
+ :param dag_run: The DagRun to schedule
"""
- # Check max_active_runs, to see if we are _now_ at the limit for any of
- # these dag? (we've just created a DagRun for them after all)
- active_runs_of_dags = dict(
+ dag_runs = self._get_next_dagruns_to_examine(State.QUEUED, session)
+
+ active_runs_of_dags = defaultdict(
+ lambda: 0,
session.query(DagRun.dag_id, func.count('*'))
.filter(
- DagRun.dag_id.in_([o.dag_id for o in dag_models]),
+ DagRun.dag_id.in_([dr.dag_id for dr in dag_runs]),
Review comment:
This will potentially put a lot of the same dag_id in the query multiple
times which could produce an inefficient query.
```suggestion
DagRun.dag_id.in_(list(set(dr.dag_id for dr in dag_runs))),
```
And probably needs a comment saying why you need `list(set())` (which is
that _I think_ SQLA doesn't accept a set)
##########
File path:
airflow/migrations/versions/a84a5abfca95_update_dagrun_state_and_datetime.py
##########
@@ -0,0 +1,122 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""update-dagrun-state-and-datetime
+
+Revision ID: a84a5abfca95
+Revises: 30867afad44a
+Create Date: 2021-06-13 11:08:18.705168
+
+"""
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import mysql
+
+from airflow.utils.dates import timezone
+from airflow.utils.state import State
+
+# revision identifiers, used by Alembic.
+revision = 'a84a5abfca95'
+down_revision = '30867afad44a'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+ """Apply Set default start_time for dagrun to None and set default state
to QUEUED"""
+ conn = op.get_bind()
+ if conn.dialect.name == "mysql":
+ conn.execute("SET time_zone = '+00:00'")
+ cur = conn.execute("SELECT @@explicit_defaults_for_timestamp")
+ res = cur.fetchall()
+ if res[0][0] == 0:
+ raise Exception("Global variable explicit_defaults_for_timestamp
needs to be on (1) for mysql")
+ op.alter_column(
+ 'dag_run',
+ 'start_date',
+ type_=mysql.DATETIME(fsp=6),
+ existing_server_default=timezone.utcnow(),
+ server_default=None,
+ )
+
+ else:
+ # sqlite and mssql datetime are fine as is. Therefore, not converting
+ if conn.dialect.name in ("sqlite", "mssql"):
+ return
Review comment:
We're changing the default aren't we -- that should apply equally to all
database types
##########
File path: airflow/models/taskinstance.py
##########
@@ -237,7 +237,8 @@ def clear_task_instances(
)
for dr in drs:
dr.state = dag_run_state
- dr.start_date = timezone.utcnow()
+ dr.start_date = None
+ dr.last_scheduling_decision = None
Review comment:
Oh, _technically_ someone could set a state other than queued here -- so
maybe we need an `if dag_run_state == State.QUEUED: ... else: ...` here?
##########
File path: airflow/jobs/scheduler_job.py
##########
@@ -980,89 +952,86 @@ def _create_dag_runs(self, dag_models:
Iterable[DagModel], session: Session) ->
# are not updated.
# We opted to check DagRun existence instead
# of catching an Integrity error and rolling back the session i.e
- # we need to run self._update_dag_next_dagruns if the Dag Run
already exists or if we
+ # we need to set dag.next_dagrun_info if the Dag Run already
exists or if we
# create a new one. This is so that in the next Scheduling loop we
try to create new runs
# instead of falling in a loop of Integrity Error.
- if (dag.dag_id, dag_model.next_dagrun) not in active_dagruns:
- run = dag.create_dagrun(
+ if (dag.dag_id, dag_model.next_dagrun) not in existing_dagruns:
+ dag.create_dagrun(
run_type=DagRunType.SCHEDULED,
execution_date=dag_model.next_dagrun,
- start_date=timezone.utcnow(),
- state=State.RUNNING,
+ state=State.QUEUED,
Review comment:
Actually to avoid a _second_ migration, I think it makes sense to do in
this PR, sorry.
(Migrations are relatively slow, so if we are already altering a table it's
better to do all the changes at once.)
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