295 lines
9.9 KiB
Python
295 lines
9.9 KiB
Python
# Copyright 2014 - Mirantis, 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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import abc
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from oslo.config import cfg
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from mistral.engine1 import commands
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from mistral import exceptions as exc
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from mistral.openstack.common import log as logging
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from mistral import utils
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from mistral.workbook import parser as spec_parser
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from mistral.workflow import data_flow
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from mistral.workflow import for_each
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from mistral.workflow import states
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from mistral.workflow import utils as wf_utils
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LOG = logging.getLogger(__name__)
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WF_TRACE = logging.getLogger(cfg.CONF.workflow_trace_log_name)
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class WorkflowHandler(object):
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"""Workflow Handler base class.
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Different workflow handler implement different workflow algorithms.
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In practice it may actually mean that there may be multiple ways of
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describing workflow models (and even languages) that will be supported
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by Mistral.
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"""
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def __init__(self, exec_db):
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"""Creates new workflow handler.
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:param exec_db: Execution.
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"""
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self.exec_db = exec_db
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self.wf_spec = spec_parser.get_workflow_spec(exec_db.wf_spec)
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@abc.abstractmethod
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def start_workflow(self, **params):
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"""Starts workflow.
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Given a workflow specification this method makes required analysis
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according to this workflow type rules and identifies a list of
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tasks that can be scheduled for execution.
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:param params: Additional parameters specific to workflow type.
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:return: List of engine commands that needs to be performed.
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"""
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raise NotImplementedError
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def on_task_result(self, task_db, raw_result):
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"""Handles event of arriving a task result.
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Given task result performs analysis of the workflow execution and
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identifies tasks that can be scheduled for execution.
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:param task_db: Task that the result corresponds to.
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:param raw_result: Raw task result that comes from action/workflow
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(before publisher). Instance of mistral.workflow.utils.TaskResult
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:return List of engine commands that needs to be performed.
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"""
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# Ignore if task already completed.
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if states.is_completed(task_db.state):
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return []
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wf_trace_msg = "Task '%s' [%s -> " % (task_db.name, task_db.state)
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task_spec = self.wf_spec.get_tasks()[task_db.name]
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task_db.output = self._determine_task_output(
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task_spec,
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task_db,
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raw_result
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)
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task_db.state = self._determine_task_state(
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task_db,
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task_spec,
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raw_result
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)
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wf_trace_msg += "%s" % task_db.state
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if task_db.state == states.ERROR:
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wf_trace_msg += ", error = %s]" % utils.cut(raw_result.error)
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WF_TRACE.info(wf_trace_msg)
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else:
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wf_trace_msg += ", result = %s]" % utils.cut(raw_result.data)
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WF_TRACE.info(wf_trace_msg)
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if self.is_paused_or_completed():
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return []
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cmds = self._find_next_commands(task_db)
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if (task_db.state == states.ERROR and
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not self._is_error_handled(task_db)):
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if not self.is_paused_or_completed():
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self._set_execution_state(states.ERROR)
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return []
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if len(cmds) == 0:
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# If there are no running tasks at this point we can conclude that
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# the workflow has finished.
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if not wf_utils.find_running_tasks(self.exec_db):
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if not self.is_paused_or_completed():
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self._set_execution_state(states.SUCCESS)
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task_out_ctx = data_flow.evaluate_outbound_context(task_db)
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self.exec_db.output = data_flow.evaluate_workflow_output(
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self.wf_spec,
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task_out_ctx
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)
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return cmds
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@staticmethod
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def _determine_task_output(task_spec, task_db, raw_result):
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for_each_spec = task_spec.get_for_each()
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if for_each_spec:
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return for_each.get_for_each_output(
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task_db, task_spec, raw_result
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)
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else:
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return data_flow.evaluate_task_output(task_spec, raw_result)
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@staticmethod
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def _determine_task_state(task_db, task_spec, raw_result):
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state = states.ERROR if raw_result.is_error() else states.SUCCESS
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for_each_spec = task_spec.get_for_each()
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if for_each_spec:
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# Check if all iterations are completed.
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if for_each.is_iteration_incomplete(task_db, task_spec):
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state = states.RUNNING
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return state
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@abc.abstractmethod
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def _find_next_commands(self, task_db):
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"""Finds commands that should run next.
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A concrete algorithm of finding such tasks depends on a concrete
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workflow handler.
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:param task_db: Task DB model causing the operation (completed).
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:return: List of engine commands.
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"""
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raise NotImplementedError
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def _is_error_handled(self, task_db):
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return False
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def _find_commands_to_resume(self, tasks):
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"""Finds commands that should run after pause.
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:param tasks: List of task_db instances.
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:return: List of engine commands.
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"""
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def filter_task_cmds(cmds):
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return [cmd for cmd in cmds if isinstance(cmd, commands.RunTask)]
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def get_tasks_to_schedule(task_db, schedule_tasks):
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"""Finds tasks that should run after given task and searches them
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in DB. If there are no tasks in the DB, it should be scheduled
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now. If there are tasks in the DB, continue search to next tasks
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in workflow if this task is finished. If this task is in IDLE
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state, schedule it for resume.
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:param task_db: Task DB.
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:param schedule_tasks: Task names from previous iteration.
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:return: List of task names that should be scheduled.
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"""
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next_cmds = filter_task_cmds(self._find_next_commands(task_db))
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next_t_names = [cmd.task_spec.get_name() for cmd in next_cmds]
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if states.is_completed(task_db.state):
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for task_name in next_t_names:
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task_spec = self.wf_spec.get_tasks()[task_name]
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t_db = wf_utils.find_db_task(self.exec_db, task_spec)
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if not t_db:
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schedule_tasks += [task_name]
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else:
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schedule_tasks += get_tasks_to_schedule(
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t_db,
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schedule_tasks
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)
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elif states.is_idle(task_db.state):
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schedule_tasks += [task_db.name]
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return schedule_tasks
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params = self.exec_db.start_params
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start_task_cmds = filter_task_cmds(
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self.start_workflow(**params if params else {})
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)
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task_names = []
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for cmd in start_task_cmds:
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task_db = [t for t in tasks
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if t.name == cmd.task_spec.get_name()][0]
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task_names += get_tasks_to_schedule(task_db, [])
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schedule_cmds = []
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for t_name in task_names:
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t_spec = self.wf_spec.get_tasks()[t_name]
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t_db = wf_utils.find_db_task(self.exec_db, t_spec)
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schedule_cmds += [commands.RunTask(t_spec, t_db)]
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return schedule_cmds
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def is_paused_or_completed(self):
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return states.is_paused_or_completed(self.exec_db.state)
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def pause_workflow(self):
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"""Stops workflow this handler is associated with.
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:return: Execution object.
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"""
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self._set_execution_state(states.PAUSED)
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return self.exec_db
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def resume_workflow(self):
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"""Resumes workflow this handler is associated with.
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:return: List of engine commands that needs to be performed..
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"""
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self._set_execution_state(states.RUNNING)
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tasks = self.exec_db.tasks
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if not all([t.state == states.RUNNING for t in tasks]):
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return self._find_commands_to_resume(tasks)
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return []
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@abc.abstractmethod
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def get_upstream_tasks(self, task_spec):
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"""Gets workflow upstream tasks for the given task.
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:param task_spec: Task specification.
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:return: List of upstream task specifications for the given task spec.
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"""
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raise NotImplementedError
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def _set_execution_state(self, state):
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cur_state = self.exec_db.state
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if states.is_valid_transition(cur_state, state):
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WF_TRACE.info("Execution of workflow '%s' [%s -> %s]"
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% (self.exec_db.wf_name, cur_state, state))
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self.exec_db.state = state
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else:
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msg = "Can't change workflow state [execution=%s," \
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" state=%s -> %s]" % (self.exec_db, cur_state, state)
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raise exc.WorkflowException(msg)
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class FlowControl(object):
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"""Flow control structure.
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Expresses a control structure that influences the way how workflow
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execution goes at a certain point.
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"""
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def decide(self, upstream_tasks, downstream_tasks):
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"""Makes a decision in a form of changed states of downstream tasks.
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:param upstream_tasks: Upstream workflow tasks.
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:param downstream_tasks: Downstream workflow tasks.
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:return: Dictionary {task: state} for those tasks whose states
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have changed. {task} is a subset of {downstream_tasks}.
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"""
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raise NotImplementedError
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