def expand_mapped_task(self, run_id: str, *,
session: Session) -> Sequence["TaskInstance"]:
"""Create the mapped task instances for mapped task.
:return: The mapped task instances, in ascending order by map index.
"""
from airflow.models.taskinstance import TaskInstance
from airflow.settings import task_instance_mutation_hook
total_length = functools.reduce(
operator.mul,
self._get_map_lengths(run_id, session=session).values())
state: Optional[TaskInstanceState] = None
unmapped_ti: Optional[TaskInstance] = (
session.query(TaskInstance).filter(
TaskInstance.dag_id == self.dag_id,
TaskInstance.task_id == self.task_id,
TaskInstance.run_id == run_id,
TaskInstance.map_index == -1,
or_(TaskInstance.state.in_(State.unfinished),
TaskInstance.state.is_(None)),
).one_or_none())
ret: List[TaskInstance] = []
if unmapped_ti:
# The unmapped task instance still exists and is unfinished, i.e. we
# haven't tried to run it before.
if total_length < 1:
# If the upstream maps this to a zero-length value, simply marked the
# unmapped task instance as SKIPPED (if needed).
self.log.info(
"Marking %s as SKIPPED since the map has %d values to expand",
unmapped_ti,
total_length,
)
unmapped_ti.state = TaskInstanceState.SKIPPED
session.flush()
return ret
# Otherwise convert this into the first mapped index, and create
# TaskInstance for other indexes.
unmapped_ti.map_index = 0
state = unmapped_ti.state
self.log.debug("Updated in place to become %s", unmapped_ti)
ret.append(unmapped_ti)
indexes_to_map = range(1, total_length)
else:
# Only create "missing" ones.
current_max_mapping = (session.query(
func.max(TaskInstance.map_index)).filter(
TaskInstance.dag_id == self.dag_id,
TaskInstance.task_id == self.task_id,
TaskInstance.run_id == run_id,
).scalar())
indexes_to_map = range(current_max_mapping + 1, total_length)
for index in indexes_to_map:
# TODO: Make more efficient with bulk_insert_mappings/bulk_save_mappings.
# TODO: Change `TaskInstance` ctor to take Operator, not BaseOperator
ti = TaskInstance(self,
run_id=run_id,
map_index=index,
state=state) # type: ignore
self.log.debug("Expanding TIs upserted %s", ti)
task_instance_mutation_hook(ti)
ti = session.merge(ti)
ti.task = self
ret.append(ti)
# Set to "REMOVED" any (old) TaskInstances with map indices greater
# than the current map value
session.query(TaskInstance).filter(
TaskInstance.dag_id == self.dag_id,
TaskInstance.task_id == self.task_id,
TaskInstance.run_id == run_id,
TaskInstance.map_index >= total_length,
).update({TaskInstance.state: TaskInstanceState.REMOVED})
session.flush()
return ret
def _per_task_process(key, ti: TaskInstance, session=None):
ti.refresh_from_db(lock_for_update=True, session=session)
task = self.dag.get_task(ti.task_id, include_subdags=True)
ti.task = task
self.log.debug("Task instance to run %s state %s", ti,
ti.state)
# The task was already marked successful or skipped by a
# different Job. Don't rerun it.
if ti.state == State.SUCCESS and not self.rerun_succeeded_tasks:
ti_status.succeeded.add(key)
self.log.debug("Task instance %s succeeded. Don't rerun.",
ti)
ti_status.to_run.pop(key)
if key in ti_status.running:
ti_status.running.pop(key)
return
elif ti.state == State.SKIPPED:
ti_status.skipped.add(key)
self.log.debug("Task instance %s skipped. Don't rerun.",
ti)
ti_status.to_run.pop(key)
if key in ti_status.running:
ti_status.running.pop(key)
return
# guard against externally modified tasks instances or
# in case max concurrency has been reached at task runtime
elif ti.state == State.NONE:
self.log.warning(
"FIXME: Task instance %s state was set to None externally. This should not happen",
ti)
ti.set_state(State.SCHEDULED, session=session)
if self.rerun_failed_tasks:
# Rerun failed tasks or upstreamed failed tasks
if ti.state in (State.FAILED, State.UPSTREAM_FAILED):
self.log.error("Task instance %s with state %s", ti,
ti.state)
if key in ti_status.running:
ti_status.running.pop(key)
# Reset the failed task in backfill to scheduled state
ti.set_state(State.SCHEDULED, session=session)
elif self.rerun_succeeded_tasks and ti.state == State.SUCCESS:
# Rerun succeeded tasks
self.log.info(
"Task instance %s with state %s, rerunning succeeded task ",
ti, ti.state)
if key in ti_status.running:
ti_status.running.pop(key)
# Reset the succeeded task in backfill to scheduled state
ti.set_state(State.SCHEDULED, session=session)
else:
# Default behaviour which works for subdag.
if ti.state in (State.FAILED, State.UPSTREAM_FAILED):
self.log.error("Task instance %s with state %s", ti,
ti.state)
ti_status.failed.add(key)
ti_status.to_run.pop(key)
if key in ti_status.running:
ti_status.running.pop(key)
return
if self.ignore_first_depends_on_past:
dagrun = ti.get_dagrun(session=session)
ignore_depends_on_past = dagrun.execution_date == (
start_date or ti.start_date)
else:
ignore_depends_on_past = False
backfill_context = DepContext(
deps=BACKFILL_QUEUED_DEPS,
ignore_depends_on_past=ignore_depends_on_past,
ignore_task_deps=self.ignore_task_deps,
flag_upstream_failed=True,
)
# Is the task runnable? -- then run it
# the dependency checker can change states of tis
if ti.are_dependencies_met(dep_context=backfill_context,
session=session,
verbose=self.verbose):
if executor.has_task(ti):
self.log.debug(
"Task Instance %s already in executor waiting for queue to clear",
ti)
else:
self.log.debug('Sending %s to executor', ti)
# Skip scheduled state, we are executing immediately
ti.state = State.QUEUED
ti.queued_by_job_id = self.id
ti.queued_dttm = timezone.utcnow()
session.merge(ti)
cfg_path = None
if self.executor_class in (
executor_constants.LOCAL_EXECUTOR,
executor_constants.SEQUENTIAL_EXECUTOR,
):
cfg_path = tmp_configuration_copy()
executor.queue_task_instance(
ti,
mark_success=self.mark_success,
pickle_id=pickle_id,
ignore_task_deps=self.ignore_task_deps,
ignore_depends_on_past=ignore_depends_on_past,
pool=self.pool,
cfg_path=cfg_path,
)
ti_status.running[key] = ti
ti_status.to_run.pop(key)
session.commit()
return
if ti.state == State.UPSTREAM_FAILED:
self.log.error("Task instance %s upstream failed", ti)
ti_status.failed.add(key)
ti_status.to_run.pop(key)
if key in ti_status.running:
ti_status.running.pop(key)
return
# special case
if ti.state == State.UP_FOR_RETRY:
self.log.debug(
"Task instance %s retry period not expired yet", ti)
if key in ti_status.running:
ti_status.running.pop(key)
ti_status.to_run[key] = ti
return
# special case
if ti.state == State.UP_FOR_RESCHEDULE:
self.log.debug(
"Task instance %s reschedule period not expired yet",
ti)
if key in ti_status.running:
ti_status.running.pop(key)
ti_status.to_run[key] = ti
return
# all remaining tasks
self.log.debug('Adding %s to not_ready', ti)
ti_status.not_ready.add(key)