Files
deb-python-taskflow/taskflow/engines/action_engine/runner.py
Joshua Harlow 93d73b85c6 Show the failure discarded (and the future intention)
When DEBUG is enabled it is quite useful to show information
about why a failure of a atom is being discarded (typically
it is being retried) so when this happens and DEBUG is enabled
add appropriate logging messages that show this decision and
future intentions.

Change-Id: I9aeb928ce85d057f872392b593b3e97f694474d1
2015-01-22 16:25:04 -08:00

268 lines
11 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from taskflow import logging
from taskflow import states as st
from taskflow.types import failure
from taskflow.types import fsm
# Waiting state timeout (in seconds).
_WAITING_TIMEOUT = 60
# Meta states the state machine uses.
_UNDEFINED = 'UNDEFINED'
_GAME_OVER = 'GAME_OVER'
_META_STATES = (_GAME_OVER, _UNDEFINED)
# Event name constants the state machine uses.
_SCHEDULE = 'schedule_next'
_WAIT = 'wait_finished'
_ANALYZE = 'examine_finished'
_FINISH = 'completed'
_FAILED = 'failed'
_SUSPENDED = 'suspended'
_SUCCESS = 'success'
_REVERTED = 'reverted'
_START = 'start'
LOG = logging.getLogger(__name__)
class _MachineMemory(object):
"""State machine memory."""
def __init__(self):
self.next_nodes = set()
self.not_done = set()
self.failures = []
self.done = set()
class _MachineBuilder(object):
"""State machine *builder* that the runner uses.
NOTE(harlowja): the machine states that this build will for are::
+--------------+------------------+------------+----------+---------+
Start | Event | End | On Enter | On Exit
+--------------+------------------+------------+----------+---------+
ANALYZING | completed | GAME_OVER | |
ANALYZING | schedule_next | SCHEDULING | |
ANALYZING | wait_finished | WAITING | |
FAILURE[$] | | | |
GAME_OVER | failed | FAILURE | |
GAME_OVER | reverted | REVERTED | |
GAME_OVER | success | SUCCESS | |
GAME_OVER | suspended | SUSPENDED | |
RESUMING | schedule_next | SCHEDULING | |
REVERTED[$] | | | |
SCHEDULING | wait_finished | WAITING | |
SUCCESS[$] | | | |
SUSPENDED[$] | | | |
UNDEFINED[^] | start | RESUMING | |
WAITING | examine_finished | ANALYZING | |
+--------------+------------------+------------+----------+---------+
Between any of these yielded states (minus ``GAME_OVER`` and ``UNDEFINED``)
if the engine has been suspended or the engine has failed (due to a
non-resolveable task failure or scheduling failure) the machine will stop
executing new tasks (currently running tasks will be allowed to complete)
and this machines run loop will be broken.
"""
def __init__(self, runtime, waiter):
self._analyzer = runtime.analyzer
self._completer = runtime.completer
self._scheduler = runtime.scheduler
self._storage = runtime.storage
self._waiter = waiter
def runnable(self):
return self._storage.get_flow_state() == st.RUNNING
def build(self, timeout=None):
memory = _MachineMemory()
if timeout is None:
timeout = _WAITING_TIMEOUT
def resume(old_state, new_state, event):
memory.next_nodes.update(self._completer.resume())
memory.next_nodes.update(self._analyzer.get_next_nodes())
return _SCHEDULE
def game_over(old_state, new_state, event):
if memory.failures:
return _FAILED
if self._analyzer.get_next_nodes():
return _SUSPENDED
elif self._analyzer.is_success():
return _SUCCESS
else:
return _REVERTED
def schedule(old_state, new_state, event):
if self.runnable() and memory.next_nodes:
not_done, failures = self._scheduler.schedule(
memory.next_nodes)
if not_done:
memory.not_done.update(not_done)
if failures:
memory.failures.extend(failures)
memory.next_nodes.clear()
return _WAIT
def wait(old_state, new_state, event):
# TODO(harlowja): maybe we should start doing 'yield from' this
# call sometime in the future, or equivalent that will work in
# py2 and py3.
if memory.not_done:
done, not_done = self._waiter.wait_for_any(memory.not_done,
timeout)
memory.done.update(done)
memory.not_done = not_done
return _ANALYZE
def analyze(old_state, new_state, event):
next_nodes = set()
while memory.done:
fut = memory.done.pop()
node = fut.atom
try:
event, result = fut.result()
retain = self._completer.complete(node, event, result)
if isinstance(result, failure.Failure):
if retain:
memory.failures.append(result)
else:
# NOTE(harlowja): avoid making any
# intention request to storage unless we are
# sure we are in DEBUG enabled logging (otherwise
# we will call this all the time even when DEBUG
# is not enabled, which would suck...)
if LOG.isEnabledFor(logging.DEBUG):
intention = self._storage.get_atom_intention(
node.name)
LOG.debug("Discarding failure '%s' (in"
" response to event '%s') under"
" completion units request during"
" completion of node '%s' (intention"
" is to %s)", result, event,
node, intention)
except Exception:
memory.failures.append(failure.Failure())
else:
try:
more_nodes = self._analyzer.get_next_nodes(node)
except Exception:
memory.failures.append(failure.Failure())
else:
next_nodes.update(more_nodes)
if self.runnable() and next_nodes and not memory.failures:
memory.next_nodes.update(next_nodes)
return _SCHEDULE
elif memory.not_done:
return _WAIT
else:
return _FINISH
def on_exit(old_state, event):
LOG.debug("Exiting old state '%s' in response to event '%s'",
old_state, event)
def on_enter(new_state, event):
LOG.debug("Entering new state '%s' in response to event '%s'",
new_state, event)
# NOTE(harlowja): when ran in debugging mode it is quite useful
# to track the various state transitions as they happen...
watchers = {}
if LOG.isEnabledFor(logging.DEBUG):
watchers['on_exit'] = on_exit
watchers['on_enter'] = on_enter
m = fsm.FSM(_UNDEFINED)
m.add_state(_GAME_OVER, **watchers)
m.add_state(_UNDEFINED, **watchers)
m.add_state(st.ANALYZING, **watchers)
m.add_state(st.RESUMING, **watchers)
m.add_state(st.REVERTED, terminal=True, **watchers)
m.add_state(st.SCHEDULING, **watchers)
m.add_state(st.SUCCESS, terminal=True, **watchers)
m.add_state(st.SUSPENDED, terminal=True, **watchers)
m.add_state(st.WAITING, **watchers)
m.add_state(st.FAILURE, terminal=True, **watchers)
m.add_transition(_GAME_OVER, st.REVERTED, _REVERTED)
m.add_transition(_GAME_OVER, st.SUCCESS, _SUCCESS)
m.add_transition(_GAME_OVER, st.SUSPENDED, _SUSPENDED)
m.add_transition(_GAME_OVER, st.FAILURE, _FAILED)
m.add_transition(_UNDEFINED, st.RESUMING, _START)
m.add_transition(st.ANALYZING, _GAME_OVER, _FINISH)
m.add_transition(st.ANALYZING, st.SCHEDULING, _SCHEDULE)
m.add_transition(st.ANALYZING, st.WAITING, _WAIT)
m.add_transition(st.RESUMING, st.SCHEDULING, _SCHEDULE)
m.add_transition(st.SCHEDULING, st.WAITING, _WAIT)
m.add_transition(st.WAITING, st.ANALYZING, _ANALYZE)
m.add_reaction(_GAME_OVER, _FINISH, game_over)
m.add_reaction(st.ANALYZING, _ANALYZE, analyze)
m.add_reaction(st.RESUMING, _START, resume)
m.add_reaction(st.SCHEDULING, _SCHEDULE, schedule)
m.add_reaction(st.WAITING, _WAIT, wait)
m.freeze()
return (m, memory)
class Runner(object):
"""Runner that iterates while executing nodes using the given runtime.
This runner acts as the action engine run loop/state-machine, it resumes
the workflow, schedules all task it can for execution using the runtimes
scheduler and analyzer components, and than waits on returned futures and
then activates the runtimes completion component to finish up those tasks
and so on...
NOTE(harlowja): If the runtimes scheduler component is able to schedule
tasks in parallel, this enables parallel running and/or reversion.
"""
# Informational states this action yields while running, not useful to
# have the engine record but useful to provide to end-users when doing
# execution iterations.
ignorable_states = (st.SCHEDULING, st.WAITING, st.RESUMING, st.ANALYZING)
def __init__(self, runtime, waiter):
self._builder = _MachineBuilder(runtime, waiter)
@property
def builder(self):
return self._builder
def runnable(self):
return self._builder.runnable()
def run_iter(self, timeout=None):
"""Runs the nodes using a built state machine."""
machine, memory = self.builder.build(timeout=timeout)
for (_prior_state, new_state) in machine.run_iter(_START):
# NOTE(harlowja): skip over meta-states.
if new_state not in _META_STATES:
if new_state == st.FAILURE:
yield (new_state, memory.failures)
else:
yield (new_state, [])