def execute(self, pipeline_context, execution_plan):
check.inst_param(pipeline_context, 'pipeline_context',
SystemPipelineExecutionContext)
check.inst_param(execution_plan, 'execution_plan', ExecutionPlan)
limit = self.max_concurrent
yield DagsterEvent.engine_event(
pipeline_context,
'Executing steps using multiprocess engine: parent process (pid: {pid})'
.format(pid=os.getpid()),
event_specific_data=EngineEventData.multiprocess(
os.getpid(),
step_keys_to_execute=execution_plan.step_keys_to_execute),
)
# It would be good to implement a reference tracking algorithm here so we could
# garbage collection results that are no longer needed by any steps
# https://github.com/dagster-io/dagster/issues/811
with time_execution_scope() as timer_result:
active_execution = execution_plan.start(retries=self.retries)
active_iters = {}
errors = {}
term_events = {}
stopping = False
while (not stopping
and not active_execution.is_complete) or active_iters:
try:
# start iterators
while len(active_iters) < limit and not stopping:
steps = active_execution.get_steps_to_execute(
limit=(limit - len(active_iters)))
if not steps:
break
for step in steps:
step_context = pipeline_context.for_step(step)
term_events[
step.key] = get_multiprocessing_context(
).Event()
active_iters[
step.key] = execute_step_out_of_process(
step_context, step, errors, term_events)
# process active iterators
empty_iters = []
for key, step_iter in active_iters.items():
try:
event_or_none = next(step_iter)
if event_or_none is None:
continue
else:
yield event_or_none
active_execution.handle_event(event_or_none)
except StopIteration:
empty_iters.append(key)
# clear and mark complete finished iterators
for key in empty_iters:
del active_iters[key]
if term_events[key].is_set():
stopping = True
del term_events[key]
active_execution.verify_complete(pipeline_context, key)
# process skips from failures or uncovered inputs
for event in active_execution.skipped_step_events_iterator(
pipeline_context):
yield event
# In the very small chance that we get interrupted in this coordination section and not
# polling the subprocesses for events - try to clean up gracefully
except KeyboardInterrupt:
yield DagsterEvent.engine_event(
pipeline_context,
'Multiprocess engine: received KeyboardInterrupt - forwarding to active child processes',
EngineEventData.interrupted(list(term_events.keys())),
)
stopping = True
for event in term_events.values():
event.set()
errs = {pid: err for pid, err in errors.items() if err}
if errs:
raise DagsterSubprocessError(
'During multiprocess execution errors occurred in child processes:\n{error_list}'
.format(error_list='\n'.join([
'In process {pid}: {err}'.format(pid=pid,
err=err.to_string())
for pid, err in errs.items()
])),
subprocess_error_infos=list(errs.values()),
)
yield DagsterEvent.engine_event(
pipeline_context,
'Multiprocess engine: parent process exiting after {duration} (pid: {pid})'
.format(duration=format_duration(timer_result.millis),
pid=os.getpid()),
event_specific_data=EngineEventData.multiprocess(os.getpid()),
)
def execute(self, plan_context, execution_plan):
check.inst_param(plan_context, "plan_context",
PlanOrchestrationContext)
check.inst_param(execution_plan, "execution_plan", ExecutionPlan)
pipeline = plan_context.reconstructable_pipeline
limit = self.max_concurrent
yield DagsterEvent.engine_event(
plan_context,
"Executing steps using multiprocess executor: parent process (pid: {pid})"
.format(pid=os.getpid()),
event_specific_data=EngineEventData.multiprocess(
os.getpid(),
step_keys_to_execute=execution_plan.step_keys_to_execute),
)
# It would be good to implement a reference tracking algorithm here so we could
# garbage collect results that are no longer needed by any steps
# https://github.com/dagster-io/dagster/issues/811
with time_execution_scope() as timer_result:
with execution_plan.start(
retry_mode=self.retries) as active_execution:
active_iters = {}
errors = {}
term_events = {}
stopping = False
while (not stopping
and not active_execution.is_complete) or active_iters:
if active_execution.check_for_interrupts():
yield DagsterEvent.engine_event(
plan_context,
"Multiprocess executor: received termination signal - "
"forwarding to active child processes",
EngineEventData.interrupted(
list(term_events.keys())),
)
stopping = True
active_execution.mark_interrupted()
for key, event in term_events.items():
event.set()
# start iterators
while len(active_iters) < limit and not stopping:
steps = active_execution.get_steps_to_execute(
limit=(limit - len(active_iters)))
if not steps:
break
for step in steps:
step_context = plan_context.for_step(step)
term_events[step.key] = multiprocessing.Event()
active_iters[
step.key] = self.execute_step_out_of_process(
pipeline,
step_context,
step,
errors,
term_events,
active_execution.get_known_state(),
)
# process active iterators
empty_iters = []
for key, step_iter in active_iters.items():
try:
event_or_none = next(step_iter)
if event_or_none is None:
continue
else:
yield event_or_none
active_execution.handle_event(event_or_none)
except ChildProcessCrashException as crash:
serializable_error = serializable_error_info_from_exc_info(
sys.exc_info())
yield DagsterEvent.engine_event(
plan_context,
("Multiprocess executor: child process for step {step_key} "
"unexpectedly exited with code {exit_code}"
).format(step_key=key,
exit_code=crash.exit_code),
EngineEventData.engine_error(
serializable_error),
step_handle=active_execution.get_step_by_key(
key).handle,
)
step_failure_event = DagsterEvent.step_failure_event(
step_context=plan_context.for_step(
active_execution.get_step_by_key(key)),
step_failure_data=StepFailureData(
error=serializable_error,
user_failure_data=None),
)
active_execution.handle_event(step_failure_event)
yield step_failure_event
empty_iters.append(key)
except StopIteration:
empty_iters.append(key)
# clear and mark complete finished iterators
for key in empty_iters:
del active_iters[key]
del term_events[key]
active_execution.verify_complete(plan_context, key)
# process skipped and abandoned steps
yield from active_execution.plan_events_iterator(
plan_context)
errs = {pid: err for pid, err in errors.items() if err}
# After termination starts, raise an interrupted exception once all subprocesses
# have finished cleaning up (and the only errors were from being interrupted)
if (stopping and (not active_iters) and all([
err_info.cls_name == "DagsterExecutionInterruptedError"
for err_info in errs.values()
])):
yield DagsterEvent.engine_event(
plan_context,
"Multiprocess executor: interrupted all active child processes",
event_specific_data=EngineEventData(),
)
raise DagsterExecutionInterruptedError()
elif errs:
raise DagsterSubprocessError(
"During multiprocess execution errors occurred in child processes:\n{error_list}"
.format(error_list="\n".join([
"In process {pid}: {err}".format(
pid=pid, err=err.to_string())
for pid, err in errs.items()
])),
subprocess_error_infos=list(errs.values()),
)
yield DagsterEvent.engine_event(
plan_context,
"Multiprocess executor: parent process exiting after {duration} (pid: {pid})"
.format(duration=format_duration(timer_result.millis),
pid=os.getpid()),
event_specific_data=EngineEventData.multiprocess(os.getpid()),
)
def execute(pipeline_context, execution_plan):
check.inst_param(pipeline_context, 'pipeline_context',
SystemPipelineExecutionContext)
check.inst_param(execution_plan, 'execution_plan', ExecutionPlan)
step_key_set = set(step.key
for step in execution_plan.execution_steps())
yield DagsterEvent.engine_event(
pipeline_context,
'Executing steps in process (pid: {pid})'.format(pid=os.getpid()),
event_specific_data=EngineEventData.in_process(
os.getpid(), step_key_set),
)
with time_execution_scope() as timer_result:
check.param_invariant(
isinstance(pipeline_context.executor_config, ExecutorConfig),
'pipeline_context',
'Expected executor_config to be ExecutorConfig got {}'.format(
pipeline_context.executor_config),
)
for event in copy_required_intermediates_for_execution(
pipeline_context, execution_plan):
yield event
failed_or_skipped_steps = set()
step_levels = execution_plan.execution_step_levels()
# It would be good to implement a reference tracking algorithm here to
# garbage collect results that are no longer needed by any steps
# https://github.com/dagster-io/dagster/issues/811
for step_level in step_levels:
for step in step_level:
step_context = pipeline_context.for_step(step)
with mirror_step_io(step_context):
# capture all of the logs for this step
failed_inputs = []
for step_input in step.step_inputs:
failed_inputs.extend(
failed_or_skipped_steps.intersection(
step_input.dependency_keys))
if failed_inputs:
step_context.log.info((
'Dependencies for step {step} failed: {failed_inputs}. Not executing.'
).format(step=step.key,
failed_inputs=failed_inputs))
failed_or_skipped_steps.add(step.key)
yield DagsterEvent.step_skipped_event(step_context)
continue
uncovered_inputs = pipeline_context.intermediates_manager.uncovered_inputs(
step_context, step)
if uncovered_inputs:
# In partial pipeline execution, we may end up here without having validated the
# missing dependent outputs were optional
_assert_missing_inputs_optional(
uncovered_inputs, execution_plan, step.key)
step_context.log.info((
'Not all inputs covered for {step}. Not executing. Output missing for '
'inputs: {uncovered_inputs}').format(
uncovered_inputs=uncovered_inputs,
step=step.key))
failed_or_skipped_steps.add(step.key)
yield DagsterEvent.step_skipped_event(step_context)
continue
for step_event in check.generator(
dagster_event_sequence_for_step(step_context)):
check.inst(step_event, DagsterEvent)
if step_event.is_step_failure:
failed_or_skipped_steps.add(step.key)
yield step_event
yield DagsterEvent.engine_event(
pipeline_context,
'Finished steps in process (pid: {pid}) in {duration_ms}'.format(
pid=os.getpid(),
duration_ms=format_duration(timer_result.millis)),
event_specific_data=EngineEventData.in_process(
os.getpid(), step_key_set),
)