airflow/models/taskinstance.py
def clear_task_instances(tis,
                         session,
                         activate_dag_runs=True,
                         dag=None,
                         ):
    """
    Clears a set of task instances, but makes sure the running ones
    get killed.

    :param tis: a list of task instances
    :param session: current session
    :param activate_dag_runs: flag to check for active dag run
    :param dag: DAG object
    """
    job_ids = []
    for ti in tis:
        if ti.state == State.RUNNING:
            if ti.job_id:
                ti.state = State.SHUTDOWN
                job_ids.append(ti.job_id)
        else:
            task_id = ti.task_id
            if dag and dag.has_task(task_id):
                task = dag.get_task(task_id)
                task_retries = task.retries
                ti.max_tries = ti.try_number + task_retries - 1
            else:
                # Ignore errors when updating max_tries if dag is None or
                # task not found in dag since database records could be
                # outdated. We make max_tries the maximum value of its
                # original max_tries or the current task try number.
                ti.max_tries = max(ti.max_tries, ti.try_number - 1)
            ti.state = State.NONE
            session.merge(ti)

    if job_ids:
        from airflow.jobs import BaseJob as BJ
        for job in session.query(BJ).filter(BJ.id.in_(job_ids)).all():
            job.state = State.SHUTDOWN

    if activate_dag_runs and tis:
        from airflow.models.dagrun import DagRun  # Avoid circular import
        drs = session.query(DagRun).filter(
            DagRun.dag_id.in_({ti.dag_id for ti in tis}),
            DagRun.execution_date.in_({ti.execution_date for ti in tis}),
        ).all()
        for dr in drs:
            dr.state = State.RUNNING
            dr.start_date = timezone.utcnow()
def clear_task_instances(tis,
                         session,
                         activate_dag_runs=True,
                         dag=None,
                         ):
    """
    Clears a set of task instances, but makes sure the running ones
    get killed.

    :param tis: a list of task instances
    :param session: current session
    :param activate_dag_runs: flag to check for active dag run
    :param dag: DAG object
    """
    job_ids = []
    for ti in tis:
        if ti.state == State.RUNNING:
            if ti.job_id:
                ti.state = State.SHUTDOWN
                job_ids.append(ti.job_id)
        else:
            task_id = ti.task_id
            if dag and dag.has_task(task_id):
                task = dag.get_task(task_id)
                task_retries = task.retries
                ti.max_tries = ti.try_number + task_retries - 1
            else:
                # Ignore errors when updating max_tries if dag is None or
                # task not found in dag since database records could be
                # outdated. We make max_tries the maximum value of its
                # original max_tries or the current task try number.
                ti.max_tries = max(ti.max_tries, ti.try_number - 1)
            ti.state = State.NONE
            session.merge(ti)

    if job_ids:
        from airflow.jobs import BaseJob as BJ
        for job in session.query(BJ).filter(BJ.id.in_(job_ids)).all():
            job.state = State.SHUTDOWN

    if activate_dag_runs and tis:
        from airflow.models.dagrun import DagRun  # Avoid circular import
        drs = session.query(DagRun).filter(
            DagRun.dag_id.in_({ti.dag_id for ti in tis}),
            DagRun.execution_date.in_({ti.execution_date for ti in tis}),
        ).all()
        for dr in drs:
            dr.state = State.RUNNING
            dr.start_date = timezone.utcnow()
Clears a set of task instances, but makes sure the running ones
    get killed.

    :param tis: a list of task instances
    :param session: current session
    :param activate_dag_runs: flag to check for active dag run
    :param dag: DAG object