559 lines
15 KiB
Python
559 lines
15 KiB
Python
# Copyright 2014 - Mirantis, Inc.
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# Copyright 2015 - StackStorm, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from mistral.db import utils as db_utils
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from mistral.db.v2 import api as db_api
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from mistral.engine import base
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from mistral.engine import post_tx_queue
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from mistral.engine import workflow_handler as wf_handler
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from mistral import expressions
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from mistral.services import scheduler
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from mistral.utils import wf_trace
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from mistral.workflow import data_flow
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from mistral.workflow import states
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import six
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_CONTINUE_TASK_PATH = 'mistral.engine.policies._continue_task'
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_COMPLETE_TASK_PATH = 'mistral.engine.policies._complete_task'
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_FAIL_IF_INCOMPLETE_TASK_PATH = (
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'mistral.engine.policies._fail_task_if_incomplete'
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)
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def _log_task_delay(task_ex, delay_sec):
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wf_trace.info(
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task_ex,
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"Task '%s' [%s -> %s, delay = %s sec]" %
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(task_ex.name, task_ex.state, states.RUNNING_DELAYED, delay_sec)
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)
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def build_policies(policies_spec, wf_spec):
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task_defaults = wf_spec.get_task_defaults()
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wf_policies = task_defaults.get_policies() if task_defaults else None
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if not (policies_spec or wf_policies):
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return []
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return construct_policies_list(policies_spec, wf_policies)
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def get_policy_factories():
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return [
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build_pause_before_policy,
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build_wait_before_policy,
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build_wait_after_policy,
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build_retry_policy,
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build_timeout_policy,
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build_concurrency_policy
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]
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def construct_policies_list(policies_spec, wf_policies):
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policies = []
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for factory in get_policy_factories():
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policy = factory(policies_spec)
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if wf_policies and not policy:
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policy = factory(wf_policies)
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if policy:
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policies.append(policy)
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return policies
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def build_wait_before_policy(policies_spec):
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if not policies_spec:
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return None
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wait_before = policies_spec.get_wait_before()
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if isinstance(wait_before, six.string_types) or wait_before > 0:
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return WaitBeforePolicy(wait_before)
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else:
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return None
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def build_wait_after_policy(policies_spec):
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if not policies_spec:
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return None
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wait_after = policies_spec.get_wait_after()
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if isinstance(wait_after, six.string_types) or wait_after > 0:
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return WaitAfterPolicy(wait_after)
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else:
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return None
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def build_retry_policy(policies_spec):
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if not policies_spec:
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return None
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retry = policies_spec.get_retry()
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if not retry:
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return None
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return RetryPolicy(
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retry.get_count(),
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retry.get_delay(),
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retry.get_break_on(),
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retry.get_continue_on()
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)
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def build_timeout_policy(policies_spec):
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if not policies_spec:
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return None
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timeout_policy = policies_spec.get_timeout()
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if isinstance(timeout_policy, six.string_types) or timeout_policy > 0:
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return TimeoutPolicy(timeout_policy)
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else:
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return None
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def build_pause_before_policy(policies_spec):
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if not policies_spec:
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return None
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pause_before_policy = policies_spec.get_pause_before()
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return (PauseBeforePolicy(pause_before_policy)
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if pause_before_policy else None)
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def build_concurrency_policy(policies_spec):
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if not policies_spec:
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return None
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concurrency_policy = policies_spec.get_concurrency()
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return (ConcurrencyPolicy(concurrency_policy)
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if concurrency_policy else None)
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def _ensure_context_has_key(runtime_context, key):
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if not runtime_context:
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runtime_context = {}
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if key not in runtime_context:
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runtime_context.update({key: {}})
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return runtime_context
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def _has_incomplete_inbound_tasks(task_ex):
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if "triggered_by" not in task_ex.runtime_context:
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return False
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for trigger in task_ex.runtime_context["triggered_by"]:
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if trigger["event"] == "not triggered":
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return True
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return False
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class WaitBeforePolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"delay": {
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"type": "integer",
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"minimum": 0
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}
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}
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}
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def __init__(self, delay):
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self.delay = delay
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def before_task_start(self, task_ex, task_spec):
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super(WaitBeforePolicy, self).before_task_start(task_ex, task_spec)
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# No need to wait for a task if delay is 0
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if self.delay == 0:
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return
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context_key = 'wait_before_policy'
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runtime_context = _ensure_context_has_key(
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task_ex.runtime_context,
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context_key
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)
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task_ex.runtime_context = runtime_context
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policy_context = runtime_context[context_key]
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if policy_context.get('skip'):
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# Unset state 'RUNNING_DELAYED'.
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wf_trace.info(
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task_ex,
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"Task '%s' [%s -> %s]"
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% (task_ex.name, states.RUNNING_DELAYED, states.RUNNING)
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)
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task_ex.state = states.RUNNING
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return
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if task_ex.state != states.IDLE:
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policy_context.update({'skip': True})
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_log_task_delay(task_ex, self.delay)
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task_ex.state = states.RUNNING_DELAYED
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scheduler.schedule_call(
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None,
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_CONTINUE_TASK_PATH,
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self.delay,
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task_ex_id=task_ex.id,
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)
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class WaitAfterPolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"delay": {
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"type": "integer",
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"minimum": 0
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}
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}
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}
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def __init__(self, delay):
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self.delay = delay
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def after_task_complete(self, task_ex, task_spec):
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super(WaitAfterPolicy, self).after_task_complete(task_ex, task_spec)
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# No need to postpone a task if delay is 0
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if self.delay == 0:
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return
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context_key = 'wait_after_policy'
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runtime_context = _ensure_context_has_key(
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task_ex.runtime_context,
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context_key
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)
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task_ex.runtime_context = runtime_context
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policy_context = runtime_context[context_key]
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if policy_context.get('skip'):
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# Skip, already processed.
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return
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policy_context.update({'skip': True})
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_log_task_delay(task_ex, self.delay)
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end_state = task_ex.state
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end_state_info = task_ex.state_info
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# TODO(rakhmerov): Policies probably need to have tasks.Task
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# interface in order to manage task state safely.
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# Set task state to 'RUNNING_DELAYED'.
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task_ex.state = states.RUNNING_DELAYED
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task_ex.state_info = (
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'Suspended by wait-after policy for %s seconds' % self.delay
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)
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# Schedule to change task state to RUNNING again.
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scheduler.schedule_call(
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None,
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_COMPLETE_TASK_PATH,
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self.delay,
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task_ex_id=task_ex.id,
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state=end_state,
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state_info=end_state_info
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)
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class RetryPolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"delay": {
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"type": "integer",
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"minimum": 0
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},
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"count": {
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"type": "integer",
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"minimum": 0
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},
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}
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}
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def __init__(self, count, delay, break_on, continue_on):
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self.count = count
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self.delay = delay
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self._break_on_clause = break_on
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self._continue_on_clause = continue_on
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def after_task_complete(self, task_ex, task_spec):
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"""Possible Cases:
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1. state = SUCCESS
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if continue_on is not specified,
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no need to move to next iteration;
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if current:count achieve retry:count then policy
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breaks the loop (regardless on continue-on condition);
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otherwise - check continue_on condition and if
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it is True - schedule the next iteration,
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otherwise policy breaks the loop.
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2. retry:count = 5, current:count = 2, state = ERROR,
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state = IDLE/DELAYED, current:count = 3
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3. retry:count = 5, current:count = 4, state = ERROR
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Iterations complete therefore state = #{state}, current:count = 4.
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"""
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super(RetryPolicy, self).after_task_complete(task_ex, task_spec)
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# There is nothing to repeat
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if self.count == 0:
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return
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# TODO(m4dcoder): If the task_ex.action_executions and
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# task_ex.workflow_executions collection are not called,
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# then the retry_no in the runtime_context of the task_ex will not
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# be updated accurately. To be exact, the retry_no will be one
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# iteration behind.
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ex = task_ex.executions # noqa
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context_key = 'retry_task_policy'
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runtime_context = _ensure_context_has_key(
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task_ex.runtime_context,
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context_key
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)
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wf_ex = task_ex.workflow_execution
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ctx_view = data_flow.ContextView(
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data_flow.get_current_task_dict(task_ex),
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data_flow.evaluate_task_outbound_context(task_ex),
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wf_ex.context,
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wf_ex.input
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)
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continue_on_evaluation = expressions.evaluate(
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self._continue_on_clause,
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ctx_view
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)
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break_on_evaluation = expressions.evaluate(
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self._break_on_clause,
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ctx_view
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)
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task_ex.runtime_context = runtime_context
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state = task_ex.state
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if not states.is_completed(state) or states.is_cancelled(state):
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return
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policy_context = runtime_context[context_key]
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retry_no = 0
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if 'retry_no' in policy_context:
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retry_no = policy_context['retry_no']
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del policy_context['retry_no']
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retries_remain = retry_no < self.count
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stop_continue_flag = (
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task_ex.state == states.SUCCESS and
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not self._continue_on_clause
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)
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stop_continue_flag = (
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stop_continue_flag or
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(self._continue_on_clause and not continue_on_evaluation)
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)
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stop_continue_flag = (
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stop_continue_flag or
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_has_incomplete_inbound_tasks(task_ex)
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)
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break_triggered = (
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task_ex.state == states.ERROR and
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break_on_evaluation
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)
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if not retries_remain or break_triggered or stop_continue_flag:
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return
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_log_task_delay(task_ex, self.delay)
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data_flow.invalidate_task_execution_result(task_ex)
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task_ex.state = states.RUNNING_DELAYED
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policy_context['retry_no'] = retry_no + 1
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runtime_context[context_key] = policy_context
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scheduler.schedule_call(
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None,
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_CONTINUE_TASK_PATH,
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self.delay,
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task_ex_id=task_ex.id,
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)
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@staticmethod
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def refresh_runtime_context(task_ex):
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runtime_context = task_ex.runtime_context or {}
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retry_task_policy = runtime_context.get('retry_task_policy')
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if retry_task_policy:
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retry_task_policy['retry_no'] = 0
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task_ex.runtime_context['retry_task_policy'] = retry_task_policy
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class TimeoutPolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"delay": {
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"type": "integer",
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"minimum": 0
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}
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}
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}
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def __init__(self, timeout_sec):
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self.delay = timeout_sec
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def before_task_start(self, task_ex, task_spec):
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super(TimeoutPolicy, self).before_task_start(task_ex, task_spec)
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# No timeout if delay is 0
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if self.delay == 0:
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return
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scheduler.schedule_call(
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None,
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_FAIL_IF_INCOMPLETE_TASK_PATH,
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self.delay,
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task_ex_id=task_ex.id,
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timeout=self.delay
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)
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wf_trace.info(
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task_ex,
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"Timeout check scheduled [task=%s, timeout(s)=%s]." %
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(task_ex.id, self.delay)
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)
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class PauseBeforePolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"expr": {"type": "boolean"}
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}
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}
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def __init__(self, expression):
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self.expr = expression
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def before_task_start(self, task_ex, task_spec):
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super(PauseBeforePolicy, self).before_task_start(task_ex, task_spec)
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if not self.expr:
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return
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wf_trace.info(
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task_ex,
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"Workflow paused before task '%s' [%s -> %s]" %
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(task_ex.name, task_ex.workflow_execution.state, states.PAUSED)
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)
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task_ex.state = states.IDLE
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wf_handler.pause_workflow(task_ex.workflow_execution)
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class ConcurrencyPolicy(base.TaskPolicy):
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_schema = {
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"properties": {
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"concurrency": {
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"type": "integer",
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"minimum": 0
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}
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}
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}
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def __init__(self, concurrency):
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self.concurrency = concurrency
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def before_task_start(self, task_ex, task_spec):
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super(ConcurrencyPolicy, self).before_task_start(task_ex, task_spec)
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if self.concurrency == 0:
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return
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# This policy doesn't do anything except validating "concurrency"
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# property value and setting a variable into task runtime context.
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# This variable is then used to define how many action executions
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# may be started in parallel.
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context_key = 'concurrency'
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runtime_context = _ensure_context_has_key(
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task_ex.runtime_context,
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context_key
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)
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runtime_context[context_key] = self.concurrency
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task_ex.runtime_context = runtime_context
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@db_utils.retry_on_db_error
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@post_tx_queue.run
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def _continue_task(task_ex_id):
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from mistral.engine import task_handler
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with db_api.transaction():
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task_handler.continue_task(db_api.get_task_execution(task_ex_id))
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@db_utils.retry_on_db_error
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@post_tx_queue.run
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def _complete_task(task_ex_id, state, state_info):
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from mistral.engine import task_handler
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with db_api.transaction():
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task_ex = db_api.get_task_execution(task_ex_id)
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task_handler.complete_task(task_ex, state, state_info)
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@db_utils.retry_on_db_error
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@post_tx_queue.run
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def _fail_task_if_incomplete(task_ex_id, timeout):
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from mistral.engine import task_handler
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with db_api.transaction():
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task_ex = db_api.get_task_execution(task_ex_id)
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if not states.is_completed(task_ex.state):
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msg = 'Task timed out [timeout(s)=%s].' % timeout
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task_handler.complete_task(task_ex, states.ERROR, msg)
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