79d25e69e8
Instead of the added complexity of discarding flow nodes we can simplify the compilation process by just retaining them and jumping over them in further iteration and graph and tree runtime usage. This change moves toward a model that does just this, which makes it also easier to in the future use the newly added flow graph nodes to do meaningful things (like use them as a point to change which flow_detail is used). Change-Id: Icb1695f4b995a0392f940837514774768f222db4
217 lines
8.3 KiB
Python
217 lines
8.3 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2014 Yahoo! Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# 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, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import abc
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import weakref
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from oslo_utils import reflection
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import six
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from taskflow.engines.action_engine import compiler as co
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from taskflow.engines.action_engine import executor as ex
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from taskflow import logging
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from taskflow import retry as retry_atom
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from taskflow import states as st
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from taskflow import task as task_atom
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from taskflow.types import failure
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LOG = logging.getLogger(__name__)
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@six.add_metaclass(abc.ABCMeta)
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class Strategy(object):
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"""Failure resolution strategy base class."""
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strategy = None
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def __init__(self, runtime):
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self._runtime = runtime
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@abc.abstractmethod
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def apply(self):
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"""Applies some algorithm to resolve some detected failure."""
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def __str__(self):
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base = reflection.get_class_name(self, fully_qualified=False)
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if self.strategy is not None:
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strategy_name = self.strategy.name
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else:
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strategy_name = "???"
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return base + "(strategy=%s)" % (strategy_name)
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class RevertAndRetry(Strategy):
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"""Sets the *associated* subflow for revert to be later retried."""
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strategy = retry_atom.RETRY
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def __init__(self, runtime, retry):
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super(RevertAndRetry, self).__init__(runtime)
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self._retry = retry
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def apply(self):
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tweaked = self._runtime.reset_atoms([self._retry], state=None,
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intention=st.RETRY)
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tweaked.extend(self._runtime.reset_subgraph(self._retry, state=None,
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intention=st.REVERT))
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return tweaked
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class RevertAll(Strategy):
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"""Sets *all* nodes/atoms to the ``REVERT`` intention."""
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strategy = retry_atom.REVERT_ALL
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def __init__(self, runtime):
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super(RevertAll, self).__init__(runtime)
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self._analyzer = runtime.analyzer
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def apply(self):
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return self._runtime.reset_atoms(
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self._analyzer.iterate_nodes(co.ATOMS),
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state=None, intention=st.REVERT)
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class Revert(Strategy):
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"""Sets atom and *associated* nodes to the ``REVERT`` intention."""
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strategy = retry_atom.REVERT
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def __init__(self, runtime, atom):
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super(Revert, self).__init__(runtime)
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self._atom = atom
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def apply(self):
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tweaked = self._runtime.reset_atoms([self._atom], state=None,
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intention=st.REVERT)
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tweaked.extend(self._runtime.reset_subgraph(self._atom, state=None,
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intention=st.REVERT))
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return tweaked
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class Completer(object):
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"""Completes atoms using actions to complete them."""
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def __init__(self, runtime):
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self._runtime = weakref.proxy(runtime)
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self._analyzer = runtime.analyzer
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self._storage = runtime.storage
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self._task_action = runtime.task_action
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self._retry_action = runtime.retry_action
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self._undefined_resolver = RevertAll(self._runtime)
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def _complete_task(self, task, event, result):
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"""Completes the given task, processes task failure."""
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if event == ex.EXECUTED:
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self._task_action.complete_execution(task, result)
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else:
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self._task_action.complete_reversion(task, result)
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def _complete_retry(self, retry, event, result):
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"""Completes the given retry, processes retry failure."""
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if event == ex.EXECUTED:
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self._retry_action.complete_execution(retry, result)
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else:
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self._retry_action.complete_reversion(retry, result)
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def resume(self):
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"""Resumes atoms in the contained graph.
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This is done to allow any previously completed or failed atoms to
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be analyzed, there results processed and any potential atoms affected
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to be adjusted as needed.
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This should return a set of atoms which should be the initial set of
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atoms that were previously not finished (due to a RUNNING or REVERTING
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attempt not previously finishing).
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"""
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for atom in self._analyzer.iterate_nodes(co.ATOMS):
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if self._analyzer.get_state(atom) == st.FAILURE:
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self._process_atom_failure(atom, self._storage.get(atom.name))
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for retry in self._analyzer.iterate_retries(st.RETRYING):
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self._runtime.retry_subflow(retry)
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unfinished_atoms = set()
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for atom in self._analyzer.iterate_nodes(co.ATOMS):
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if self._analyzer.get_state(atom) in (st.RUNNING, st.REVERTING):
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unfinished_atoms.add(atom)
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return unfinished_atoms
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def complete(self, node, event, result):
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"""Performs post-execution completion of a node.
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Returns whether the result should be saved into an accumulator of
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failures or whether this should not be done.
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"""
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if isinstance(node, task_atom.BaseTask):
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self._complete_task(node, event, result)
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else:
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self._complete_retry(node, event, result)
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if isinstance(result, failure.Failure):
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if event == ex.EXECUTED:
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self._process_atom_failure(node, result)
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else:
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# Reverting failed, always retain the failure...
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return True
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return False
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def _determine_resolution(self, atom, failure):
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"""Determines which resolution strategy to activate/apply."""
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retry = self._analyzer.find_retry(atom)
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if retry is not None:
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# Ask retry controller what to do in case of failure.
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strategy = self._retry_action.on_failure(retry, atom, failure)
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if strategy == retry_atom.RETRY:
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return RevertAndRetry(self._runtime, retry)
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elif strategy == retry_atom.REVERT:
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# Ask parent retry and figure out what to do...
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parent_resolver = self._determine_resolution(retry, failure)
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# Ok if the parent resolver says something not REVERT, and
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# it isn't just using the undefined resolver, assume the
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# parent knows best.
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if parent_resolver is not self._undefined_resolver:
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if parent_resolver.strategy != retry_atom.REVERT:
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return parent_resolver
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return Revert(self._runtime, retry)
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elif strategy == retry_atom.REVERT_ALL:
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return RevertAll(self._runtime)
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else:
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raise ValueError("Unknown atom failure resolution"
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" action/strategy '%s'" % strategy)
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else:
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return self._undefined_resolver
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def _process_atom_failure(self, atom, failure):
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"""Processes atom failure & applies resolution strategies.
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On atom failure this will find the atoms associated retry controller
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and ask that controller for the strategy to perform to resolve that
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failure. After getting a resolution strategy decision this method will
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then adjust the needed other atoms intentions, and states, ... so that
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the failure can be worked around.
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"""
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resolver = self._determine_resolution(atom, failure)
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LOG.debug("Applying resolver '%s' to resolve failure '%s'"
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" of atom '%s'", resolver, failure, atom)
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tweaked = resolver.apply()
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# Only show the tweaked node list when blather is on, otherwise
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# just show the amount/count of nodes tweaks...
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if LOG.isEnabledFor(logging.BLATHER):
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LOG.blather("Modified/tweaked %s nodes while applying"
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" resolver '%s'", tweaked, resolver)
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else:
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LOG.debug("Modified/tweaked %s nodes while applying"
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" resolver '%s'", len(tweaked), resolver)
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