class AstronomerAvailableVersion(Base):
__tablename__ = "astro_available_version"
version = Column(Text, nullable=False, primary_key=True)
level = Column(Text, nullable=False)
date_released = Column(UtcDateTime(timezone=True), nullable=False)
description = Column(Text)
url = Column(Text)
hidden_from_ui = Column(Boolean, default=False, nullable=False)
__table_args__ = (
Index('idx_astro_available_version_hidden', hidden_from_ui),
)
class BaseJob(Base, LoggingMixin):
"""
Abstract class to be derived for jobs. Jobs are processing items with state
and duration that aren't task instances. For instance a BackfillJob is
a collection of task instance runs, but should have its own state, start
and end time.
"""
__tablename__ = "job"
id = Column(Integer, primary_key=True)
dag_id = Column(
String(ID_LEN),
)
state = Column(String(20))
job_type = Column(String(30))
start_date = Column(UtcDateTime())
end_date = Column(UtcDateTime())
latest_heartbeat = Column(UtcDateTime())
executor_class = Column(String(500))
hostname = Column(String(500))
unixname = Column(String(1000))
__mapper_args__ = {'polymorphic_on': job_type, 'polymorphic_identity': 'BaseJob'}
__table_args__ = (
Index('job_type_heart', job_type, latest_heartbeat),
Index('idx_job_state_heartbeat', state, latest_heartbeat),
Index('idx_job_dag_id', dag_id),
)
task_instances_enqueued = relationship(
TaskInstance,
primaryjoin=id == foreign(TaskInstance.queued_by_job_id),
backref=backref('queued_by_job', uselist=False),
)
dag_runs = relationship(
DagRun,
primaryjoin=id == foreign(DagRun.creating_job_id),
backref=backref('creating_job'),
)
"""
TaskInstances which have been enqueued by this Job.
Only makes sense for SchedulerJob and BackfillJob instances.
"""
heartrate = conf.getfloat('scheduler', 'JOB_HEARTBEAT_SEC')
def __init__(self, executor=None, heartrate=None, *args, **kwargs):
self.hostname = get_hostname()
if executor:
self.executor = executor
self.executor_class = executor.__class__.__name__
else:
self.executor_class = conf.get('core', 'EXECUTOR')
self.start_date = timezone.utcnow()
self.latest_heartbeat = timezone.utcnow()
if heartrate is not None:
self.heartrate = heartrate
self.unixname = getuser()
self.max_tis_per_query: int = conf.getint('scheduler', 'max_tis_per_query')
super().__init__(*args, **kwargs)
@cached_property
def executor(self):
return ExecutorLoader.get_default_executor()
@classmethod
@provide_session
def most_recent_job(cls, session=None) -> Optional['BaseJob']:
"""
Return the most recent job of this type, if any, based on last
heartbeat received.
This method should be called on a subclass (i.e. on SchedulerJob) to
return jobs of that type.
:param session: Database session
:rtype: BaseJob or None
"""
return session.query(cls).order_by(cls.latest_heartbeat.desc()).limit(1).first()
def is_alive(self, grace_multiplier=2.1):
"""
Is this job currently alive.
We define alive as in a state of RUNNING, and having sent a heartbeat
within a multiple of the heartrate (default of 2.1)
:param grace_multiplier: multiplier of heartrate to require heart beat
within
:type grace_multiplier: number
:rtype: boolean
"""
return (
self.state == State.RUNNING
and (timezone.utcnow() - self.latest_heartbeat).total_seconds()
< self.heartrate * grace_multiplier
)
@provide_session
def kill(self, session=None):
"""Handles on_kill callback and updates state in database."""
job = session.query(BaseJob).filter(BaseJob.id == self.id).first()
job.end_date = timezone.utcnow()
try:
self.on_kill()
except Exception as e:
self.log.error('on_kill() method failed: %s', str(e))
session.merge(job)
session.commit()
raise AirflowException("Job shut down externally.")
def on_kill(self):
"""Will be called when an external kill command is received"""
def heartbeat_callback(self, session=None):
"""Callback that is called during heartbeat. This method should be overwritten."""
def heartbeat(self, only_if_necessary: bool = False):
"""
Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for SchedulerJob would mean something
is wrong.
This also allows for any job to be killed externally, regardless
of who is running it or on which machine it is running.
Note that if your heart rate is set to 60 seconds and you call this
method after 10 seconds of processing since the last heartbeat, it
will sleep 50 seconds to complete the 60 seconds and keep a steady
heart rate. If you go over 60 seconds before calling it, it won't
sleep at all.
:param only_if_necessary: If the heartbeat is not yet due then do
nothing (don't update column, don't call ``heartbeat_callback``)
:type only_if_necessary: boolean
"""
seconds_remaining = 0
if self.latest_heartbeat:
seconds_remaining = self.heartrate - (timezone.utcnow() - self.latest_heartbeat).total_seconds()
if seconds_remaining > 0 and only_if_necessary:
return
previous_heartbeat = self.latest_heartbeat
try:
with create_session() as session:
# This will cause it to load from the db
session.merge(self)
previous_heartbeat = self.latest_heartbeat
if self.state in State.terminating_states:
self.kill()
# Figure out how long to sleep for
sleep_for = 0
if self.latest_heartbeat:
seconds_remaining = (
self.heartrate - (timezone.utcnow() - self.latest_heartbeat).total_seconds()
)
sleep_for = max(0, seconds_remaining)
sleep(sleep_for)
# Update last heartbeat time
with create_session() as session:
# Make the session aware of this object
session.merge(self)
self.latest_heartbeat = timezone.utcnow()
session.commit()
# At this point, the DB has updated.
previous_heartbeat = self.latest_heartbeat
self.heartbeat_callback(session=session)
self.log.debug('[heartbeat]')
except OperationalError:
Stats.incr(convert_camel_to_snake(self.__class__.__name__) + '_heartbeat_failure', 1, 1)
self.log.exception("%s heartbeat got an exception", self.__class__.__name__)
# We didn't manage to heartbeat, so make sure that the timestamp isn't updated
self.latest_heartbeat = previous_heartbeat
def run(self):
"""Starts the job."""
Stats.incr(self.__class__.__name__.lower() + '_start', 1, 1)
# Adding an entry in the DB
with create_session() as session:
self.state = State.RUNNING
session.add(self)
session.commit()
make_transient(self)
try:
self._execute()
# In case of max runs or max duration
self.state = State.SUCCESS
except SystemExit:
# In case of ^C or SIGTERM
self.state = State.SUCCESS
except Exception:
self.state = State.FAILED
raise
finally:
self.end_date = timezone.utcnow()
session.merge(self)
session.commit()
Stats.incr(self.__class__.__name__.lower() + '_end', 1, 1)
def _execute(self):
raise NotImplementedError("This method needs to be overridden")
class BaseJob(Base, LoggingMixin):
"""
Abstract class to be derived for jobs. Jobs are processing items with state
and duration that aren't task instances. For instance a BackfillJob is
a collection of task instance runs, but should have its own state, start
and end time.
"""
__tablename__ = "job"
id = Column(Integer, primary_key=True)
dag_id = Column(String(ID_LEN), )
state = Column(String(20))
job_type = Column(String(30))
start_date = Column(UtcDateTime())
end_date = Column(UtcDateTime())
latest_heartbeat = Column(UtcDateTime())
executor_class = Column(String(500))
hostname = Column(String(500))
unixname = Column(String(1000))
__mapper_args__ = {
'polymorphic_on': job_type,
'polymorphic_identity': 'BaseJob'
}
__table_args__ = (
Index('job_type_heart', job_type, latest_heartbeat),
Index('idx_job_state_heartbeat', state, latest_heartbeat),
)
heartrate = conf.getfloat('scheduler', 'JOB_HEARTBEAT_SEC')
def __init__(self, executor=None, heartrate=None, *args, **kwargs):
self.hostname = get_hostname()
self.executor = executor or ExecutorLoader.get_default_executor()
self.executor_class = self.executor.__class__.__name__
self.start_date = timezone.utcnow()
self.latest_heartbeat = timezone.utcnow()
if heartrate is not None:
self.heartrate = heartrate
self.unixname = getpass.getuser()
self.max_tis_per_query = conf.getint('scheduler', 'max_tis_per_query')
super().__init__(*args, **kwargs)
@classmethod
@provide_session
def most_recent_job(cls, session=None) -> Optional['BaseJob']:
"""
Return the most recent job of this type, if any, based on last
heartbeat received.
This method should be called on a subclass (i.e. on SchedulerJob) to
return jobs of that type.
:param session: Database session
:rtype: BaseJob or None
"""
return session.query(cls).order_by(
cls.latest_heartbeat.desc()).limit(1).first()
def is_alive(self, grace_multiplier=2.1):
"""
Is this job currently alive.
We define alive as in a state of RUNNING, and having sent a heartbeat
within a multiple of the heartrate (default of 2.1)
:param grace_multiplier: multiplier of heartrate to require heart beat
within
:type grace_multiplier: number
:rtype: boolean
"""
return (self.state == State.RUNNING and
(timezone.utcnow() - self.latest_heartbeat).total_seconds() <
self.heartrate * grace_multiplier)
@provide_session
def kill(self, session=None):
"""
Handles on_kill callback and updates state in database.
"""
job = session.query(BaseJob).filter(BaseJob.id == self.id).first()
job.end_date = timezone.utcnow()
try:
self.on_kill()
except Exception as e: # pylint: disable=broad-except
self.log.error('on_kill() method failed: %s', str(e))
session.merge(job)
session.commit()
raise AirflowException("Job shut down externally.")
def on_kill(self):
"""
Will be called when an external kill command is received
"""
def heartbeat_callback(self, session=None):
"""
Callback that is called during heartbeat. This method should be overwritten.
"""
def heartbeat(self, only_if_necessary: bool = False):
"""
Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for SchedulerJob would mean something
is wrong.
This also allows for any job to be killed externally, regardless
of who is running it or on which machine it is running.
Note that if your heart rate is set to 60 seconds and you call this
method after 10 seconds of processing since the last heartbeat, it
will sleep 50 seconds to complete the 60 seconds and keep a steady
heart rate. If you go over 60 seconds before calling it, it won't
sleep at all.
:param only_if_necessary: If the heartbeat is not yet due then do
nothing (don't update column, don't call ``heartbeat_callback``)
:type only_if_necessary: boolean
"""
seconds_remaining = 0
if self.latest_heartbeat:
seconds_remaining = self.heartrate - (
timezone.utcnow() - self.latest_heartbeat).total_seconds()
if seconds_remaining > 0 and only_if_necessary:
return
previous_heartbeat = self.latest_heartbeat
try:
with create_session() as session:
# This will cause it to load from the db
session.merge(self)
previous_heartbeat = self.latest_heartbeat
if self.state == State.SHUTDOWN:
self.kill()
# Figure out how long to sleep for
sleep_for = 0
if self.latest_heartbeat:
seconds_remaining = self.heartrate - \
(timezone.utcnow() - self.latest_heartbeat)\
.total_seconds()
sleep_for = max(0, seconds_remaining)
sleep(sleep_for)
# Update last heartbeat time
with create_session() as session:
# Make the sesion aware of this object
session.merge(self)
self.latest_heartbeat = timezone.utcnow()
session.commit()
# At this point, the DB has updated.
previous_heartbeat = self.latest_heartbeat
self.heartbeat_callback(session=session)
self.log.debug('[heartbeat]')
except OperationalError:
Stats.incr(
convert_camel_to_snake(self.__class__.__name__) +
'_heartbeat_failure', 1, 1)
self.log.exception("%s heartbeat got an exception",
self.__class__.__name__)
# We didn't manage to heartbeat, so make sure that the timestamp isn't updated
self.latest_heartbeat = previous_heartbeat
def run(self):
"""
Starts the job.
"""
Stats.incr(self.__class__.__name__.lower() + '_start', 1, 1)
# Adding an entry in the DB
with create_session() as session:
self.state = State.RUNNING
session.add(self)
session.commit()
make_transient(self)
try:
self._execute()
# In case of max runs or max duration
self.state = State.SUCCESS
except SystemExit:
# In case of ^C or SIGTERM
self.state = State.SUCCESS
except Exception:
self.state = State.FAILED
raise
finally:
self.end_date = timezone.utcnow()
session.merge(self)
session.commit()
Stats.incr(self.__class__.__name__.lower() + '_end', 1, 1)
def _execute(self):
raise NotImplementedError("This method needs to be overridden")
@provide_session
def reset_state_for_orphaned_tasks(self,
filter_by_dag_run=None,
session=None):
"""
This function checks if there are any tasks in the dagrun (or all)
that have a scheduled state but are not known by the
executor. If it finds those it will reset the state to None
so they will get picked up again.
The batch option is for performance reasons as the queries are made in
sequence.
:param filter_by_dag_run: the dag_run we want to process, None if all
:type filter_by_dag_run: airflow.models.DagRun
:return: the TIs reset (in expired SQLAlchemy state)
:rtype: list[airflow.models.TaskInstance]
"""
queued_tis = self.executor.queued_tasks
# also consider running as the state might not have changed in the db yet
running_tis = self.executor.running
resettable_states = [State.SCHEDULED, State.QUEUED]
TI = models.TaskInstance
DR = models.DagRun
if filter_by_dag_run is None:
resettable_tis = (
session.query(TI).join(
DR,
and_(TI.dag_id == DR.dag_id,
TI.execution_date == DR.execution_date)).filter(
# pylint: disable=comparison-with-callable
DR.state == State.RUNNING,
DR.run_id.notlike(
f"{DagRunType.BACKFILL_JOB.value}__%"),
TI.state.in_(resettable_states))).all()
else:
resettable_tis = filter_by_dag_run.get_task_instances(
state=resettable_states, session=session)
tis_to_reset = []
# Can't use an update here since it doesn't support joins
for ti in resettable_tis:
if ti.key not in queued_tis and ti.key not in running_tis:
tis_to_reset.append(ti)
if len(tis_to_reset) == 0:
return []
def query(result, items):
if not items:
return result
filter_for_tis = TI.filter_for_tis(items)
reset_tis = session.query(TI).filter(
filter_for_tis,
TI.state.in_(resettable_states)).with_for_update().all()
for ti in reset_tis:
ti.state = State.NONE
session.merge(ti)
return result + reset_tis
reset_tis = helpers.reduce_in_chunks(query, tis_to_reset, [],
self.max_tis_per_query)
task_instance_str = '\n\t'.join([repr(x) for x in reset_tis])
session.commit()
self.log.info("Reset the following %s TaskInstances:\n\t%s",
len(reset_tis), task_instance_str)
return reset_tis
class BaseJob(Base, LoggingMixin):
"""
Abstract class to be derived for jobs. Jobs are processing items with state
and duration that aren't task instances. For instance a BackfillJob is
a collection of task instance runs, but should have its own state, start
and end time.
"""
__tablename__ = "job"
id = Column(Integer, primary_key=True)
dag_id = Column(String(ID_LEN), )
state = Column(String(20))
job_type = Column(String(30))
start_date = Column(UtcDateTime())
end_date = Column(UtcDateTime())
latest_heartbeat = Column(UtcDateTime())
executor_class = Column(String(500))
hostname = Column(String(500))
unixname = Column(String(1000))
__mapper_args__ = {
'polymorphic_on': job_type,
'polymorphic_identity': 'BaseJob'
}
__table_args__ = (
Index('job_type_heart', job_type, latest_heartbeat),
Index('idx_job_state_heartbeat', state, latest_heartbeat),
)
def __init__(self,
executor=executors.get_default_executor(),
heartrate=conf.getfloat('scheduler', 'JOB_HEARTBEAT_SEC'),
*args,
**kwargs):
self.hostname = get_hostname()
self.executor = executor
self.executor_class = executor.__class__.__name__
self.start_date = timezone.utcnow()
self.latest_heartbeat = timezone.utcnow()
self.heartrate = heartrate
self.unixname = getpass.getuser()
self.max_tis_per_query = conf.getint('scheduler', 'max_tis_per_query')
super().__init__(*args, **kwargs)
def is_alive(self):
return ((timezone.utcnow() - self.latest_heartbeat).seconds <
(conf.getint('scheduler', 'JOB_HEARTBEAT_SEC') * 2.1))
@provide_session
def kill(self, session=None):
job = session.query(BaseJob).filter(BaseJob.id == self.id).first()
job.end_date = timezone.utcnow()
try:
self.on_kill()
except Exception as e:
self.log.error('on_kill() method failed: %s', str(e))
session.merge(job)
session.commit()
raise AirflowException("Job shut down externally.")
def on_kill(self):
"""
Will be called when an external kill command is received
"""
pass
def heartbeat_callback(self, session=None):
pass
def heartbeat(self):
"""
Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for SchedulerJob would mean something
is wrong.
This also allows for any job to be killed externally, regardless
of who is running it or on which machine it is running.
Note that if your heartbeat is set to 60 seconds and you call this
method after 10 seconds of processing since the last heartbeat, it
will sleep 50 seconds to complete the 60 seconds and keep a steady
heart rate. If you go over 60 seconds before calling it, it won't
sleep at all.
"""
try:
with create_session() as session:
job = session.query(BaseJob).filter_by(id=self.id).one()
make_transient(job)
session.commit()
if job.state == State.SHUTDOWN:
self.kill()
is_unit_test = conf.getboolean('core', 'unit_test_mode')
if not is_unit_test:
# Figure out how long to sleep for
sleep_for = 0
if job.latest_heartbeat:
seconds_remaining = self.heartrate - \
(timezone.utcnow() - job.latest_heartbeat)\
.total_seconds()
sleep_for = max(0, seconds_remaining)
sleep(sleep_for)
# Update last heartbeat time
with create_session() as session:
job = session.query(BaseJob).filter(
BaseJob.id == self.id).first()
job.latest_heartbeat = timezone.utcnow()
session.merge(job)
session.commit()
self.heartbeat_callback(session=session)
self.log.debug('[heartbeat]')
except OperationalError as e:
self.log.error("Scheduler heartbeat got an exception: %s", str(e))
def run(self):
Stats.incr(self.__class__.__name__.lower() + '_start', 1, 1)
# Adding an entry in the DB
with create_session() as session:
self.state = State.RUNNING
session.add(self)
session.commit()
id_ = self.id
make_transient(self)
self.id = id_
try:
self._execute()
# In case of max runs or max duration
self.state = State.SUCCESS
except SystemExit:
# In case of ^C or SIGTERM
self.state = State.SUCCESS
except Exception:
self.state = State.FAILED
raise
finally:
self.end_date = timezone.utcnow()
session.merge(self)
session.commit()
Stats.incr(self.__class__.__name__.lower() + '_end', 1, 1)
def _execute(self):
raise NotImplementedError("This method needs to be overridden")
@provide_session
def reset_state_for_orphaned_tasks(self,
filter_by_dag_run=None,
session=None):
"""
This function checks if there are any tasks in the dagrun (or all)
that have a scheduled state but are not known by the
executor. If it finds those it will reset the state to None
so they will get picked up again.
The batch option is for performance reasons as the queries are made in
sequence.
:param filter_by_dag_run: the dag_run we want to process, None if all
:type filter_by_dag_run: airflow.models.DagRun
:return: the TIs reset (in expired SQLAlchemy state)
:rtype: list[airflow.models.TaskInstance]
"""
from airflow.jobs.backfill_job import BackfillJob
queued_tis = self.executor.queued_tasks
# also consider running as the state might not have changed in the db yet
running_tis = self.executor.running
resettable_states = [State.SCHEDULED, State.QUEUED]
TI = models.TaskInstance
DR = models.DagRun
if filter_by_dag_run is None:
resettable_tis = (session.query(TI).join(
DR,
and_(TI.dag_id == DR.dag_id,
TI.execution_date == DR.execution_date)).filter(
DR.state == State.RUNNING,
DR.run_id.notlike(BackfillJob.ID_PREFIX + '%'),
TI.state.in_(resettable_states))).all()
else:
resettable_tis = filter_by_dag_run.get_task_instances(
state=resettable_states, session=session)
tis_to_reset = []
# Can't use an update here since it doesn't support joins
for ti in resettable_tis:
if ti.key not in queued_tis and ti.key not in running_tis:
tis_to_reset.append(ti)
if len(tis_to_reset) == 0:
return []
def query(result, items):
filter_for_tis = ([
and_(TI.dag_id == ti.dag_id, TI.task_id == ti.task_id,
TI.execution_date == ti.execution_date) for ti in items
])
reset_tis = (session.query(TI).filter(
or_(*filter_for_tis),
TI.state.in_(resettable_states)).with_for_update().all())
for ti in reset_tis:
ti.state = State.NONE
session.merge(ti)
return result + reset_tis
reset_tis = helpers.reduce_in_chunks(query, tis_to_reset, [],
self.max_tis_per_query)
task_instance_str = '\n\t'.join([repr(x) for x in reset_tis])
session.commit()
self.log.info("Reset the following %s TaskInstances:\n\t%s",
len(reset_tis), task_instance_str)
return reset_tis
class AstronomerVersionCheck(Base):
__tablename__ = "astro_version_check"
singleton = Column(Boolean, default=True, nullable=False, primary_key=True)
# For infomration only
last_checked = Column(UtcDateTime(timezone=True))
last_checked_by = Column(Text)
@classmethod
def ensure_singleton(cls):
"""
Ensure that the singleton row exists in this table
"""
with create_session() as session:
# To keep PG logs quieter (it shows an ERROR for the PK violation),
# we try and select first
if session.query(cls).get({"singleton": True}) is not None:
return
try:
session.bulk_save_objects([cls(singleton=True)])
except sqlalchemy.exc.IntegrityError:
# Already exists, we're good
session.rollback()
@classmethod
def acquire_lock(cls, check_interval, session): # type: (datetime.timedelta, sqlalchemy.Session) -> Optional[AstronomerVersionCheck]
"""
Acquire an exclusive lock to perform an update check if the check is due
and if another check is not already in progress.
We use the database to hold the lock for as long as this transaction is open using `FOR UPDATE SKIP LOCKED`.
This method will either return a row meaning the check is due and we
have acquired the lock. The lock will be held for the duration of the
database transaction -- be careful to to close this before you are
done!
This will throw an error if the lock is held by another transaction.
"""
now = utcnow()
return session.query(cls).filter(
cls.singleton.is_(True),
or_(cls.last_checked.is_(None), cls.last_checked <= now - check_interval),
).with_for_update(nowait=True).one_or_none()
@classmethod
def get(cls, session):
"""
Return the update tracking row
"""
return session.query(cls).filter(cls.singleton.is_(True)).one()
@staticmethod
def host_identifier():
return "{hostname}-{pid}#{tid}".format(
hostname=get_hostname(),
pid=os.getpid(),
tid=threading.get_ident()
)
