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"""EvaluationContext tracks global state, triggers and watermarks."""
from __future__ import absolute_import
import collections
import threading
from builtins import object
from apache_beam.runners.direct.direct_metrics import DirectMetrics
from apache_beam.runners.direct.executor import TransformExecutor
from apache_beam.runners.direct.watermark_manager import WatermarkManager
from apache_beam.transforms import sideinputs
from apache_beam.transforms.trigger import InMemoryUnmergedState
from apache_beam.utils import counters
class _ExecutionContext(object):
def __init__(self, watermarks, keyed_states):
self.watermarks = watermarks
self.keyed_states = keyed_states
self._step_context = None
def get_step_context(self):
if not self._step_context:
self._step_context = DirectStepContext(self.keyed_states)
return self._step_context
def reset(self):
self._step_context = None
class _SideInputView(object):
def __init__(self, view):
self._view = view
self.blocked_tasks = collections.deque()
self.elements = []
self.value = None
self.watermark = None
def __repr__(self):
elements_string = (', '.join(str(elm) for elm in self.elements)
if self.elements else '[]')
return '_SideInputView(elements=%s)' % elements_string
class _SideInputsContainer(object):
"""An in-process container for side inputs.
It provides methods for blocking until a side-input is available and writing
to a side input.
"""
def __init__(self, side_inputs):
self._lock = threading.Lock()
self._views = {}
self._transform_to_side_inputs = collections.defaultdict(list)
self._side_input_to_blocked_tasks = collections.defaultdict(list)
for side in side_inputs:
self._views[side] = _SideInputView(side)
self._transform_to_side_inputs[side.pvalue.producer].append(side)
def __repr__(self):
views_string = (', '.join(str(elm) for elm in self._views.values())
if self._views.values() else '[]')
return '_SideInputsContainer(_views=%s)' % views_string
def get_value_or_block_until_ready(self, side_input, task, block_until):
"""Returns the value of a view whose task is unblocked or blocks its task.
It gets the value of a view whose watermark has been updated and
surpasses a given value.
Args:
side_input: ``_UnpickledSideInput`` value.
task: ``TransformExecutor`` task waiting on a side input.
block_until: Timestamp after which the task gets unblocked.
Returns:
The ``SideInputMap`` value of a view when the tasks it blocks are
unblocked. Otherwise, None.
"""
with self._lock:
view = self._views[side_input]
if view.watermark and view.watermark.output_watermark >= block_until:
view.value = self._pvalue_to_value(side_input, view.elements)
return view.value
else:
view.blocked_tasks.append((task, block_until))
task.blocked = True
def add_values(self, side_input, values):
with self._lock:
view = self._views[side_input]
view.elements.extend(values)
def update_watermarks_for_transform_and_unblock_tasks(self,
ptransform,
watermark):
"""Updates _SideInputsContainer after a watermark update and unbloks tasks.
It traverses the list of side inputs per PTransform and calls
_update_watermarks_for_side_input_and_unblock_tasks to unblock tasks.
Args:
ptransform: Value of a PTransform.
watermark: Value of the watermark after an update for a PTransform.
Returns:
Tasks that get unblocked as a result of the watermark advancing.
"""
unblocked_tasks = []
for side in self._transform_to_side_inputs[ptransform]:
unblocked_tasks.extend(
self._update_watermarks_for_side_input_and_unblock_tasks(
side, watermark))
return unblocked_tasks
def _update_watermarks_for_side_input_and_unblock_tasks(self,
side_input,
watermark):
"""Helps update _SideInputsContainer after a watermark update.
For each view of the side input, it updates the value of the watermark
recorded when the watermark moved and unblocks tasks accordingly.
Args:
side_input: ``_UnpickledSideInput`` value.
watermark: Value of the watermark after an update for a PTransform.
Returns:
Tasks that get unblocked as a result of the watermark advancing.
"""
with self._lock:
view = self._views[side_input]
view.watermark = watermark
unblocked_tasks = []
tasks_just_unblocked = []
for task, block_until in view.blocked_tasks:
if watermark.output_watermark >= block_until:
view.value = self._pvalue_to_value(side_input, view.elements)
unblocked_tasks.append(task)
tasks_just_unblocked.append((task, block_until))
task.blocked = False
for task in tasks_just_unblocked:
view.blocked_tasks.remove(task)
return unblocked_tasks
def _pvalue_to_value(self, side_input, values):
"""Given a side input, returns the associated value in its requested form.
Args:
side_input: _UnpickledSideInput object.
values: Iterable values associated with the side input.
Returns:
The side input in its requested form.
Raises:
ValueError: If values cannot be converted into the requested form.
"""
return sideinputs.SideInputMap(type(side_input),
side_input._view_options(),
values)
[docs]class EvaluationContext(object):
"""Evaluation context with the global state information of the pipeline.
The evaluation context for a specific pipeline being executed by the
DirectRunner. Contains state shared within the execution across all
transforms.
EvaluationContext contains shared state for an execution of the
DirectRunner that can be used while evaluating a PTransform. This
consists of views into underlying state and watermark implementations, access
to read and write side inputs, and constructing counter sets and
execution contexts. This includes executing callbacks asynchronously when
state changes to the appropriate point (e.g. when a side input is
requested and known to be empty).
EvaluationContext also handles results by committing finalizing
bundles based on the current global state and updating the global state
appropriately. This includes updating the per-(step,key) state, updating
global watermarks, and executing any callbacks that can be executed.
"""
def __init__(self, pipeline_options, bundle_factory, root_transforms,
value_to_consumers, step_names, views, clock):
self.pipeline_options = pipeline_options
self._bundle_factory = bundle_factory
self._root_transforms = root_transforms
self._value_to_consumers = value_to_consumers
self._step_names = step_names
self.views = views
self._pcollection_to_views = collections.defaultdict(list)
for view in views:
self._pcollection_to_views[view.pvalue].append(view)
self._transform_keyed_states = self._initialize_keyed_states(
root_transforms, value_to_consumers)
self._side_inputs_container = _SideInputsContainer(views)
self._watermark_manager = WatermarkManager(
clock, root_transforms, value_to_consumers,
self._transform_keyed_states)
self._pending_unblocked_tasks = []
self._counter_factory = counters.CounterFactory()
self._metrics = DirectMetrics()
self._lock = threading.Lock()
def _initialize_keyed_states(self, root_transforms, value_to_consumers):
transform_keyed_states = {}
for transform in root_transforms:
transform_keyed_states[transform] = {}
for consumers in value_to_consumers.values():
for consumer in consumers:
transform_keyed_states[consumer] = {}
return transform_keyed_states
[docs] def metrics(self):
# TODO. Should this be made a @property?
return self._metrics
[docs] def is_root_transform(self, applied_ptransform):
return applied_ptransform in self._root_transforms
[docs] def handle_result(
self, completed_bundle, completed_timers, result):
"""Handle the provided result produced after evaluating the input bundle.
Handle the provided TransformResult, produced after evaluating
the provided committed bundle (potentially None, if the result of a root
PTransform).
The result is the output of running the transform contained in the
TransformResult on the contents of the provided bundle.
Args:
completed_bundle: the bundle that was processed to produce the result.
completed_timers: the timers that were delivered to produce the
completed_bundle.
result: the TransformResult of evaluating the input bundle
Returns:
the committed bundles contained within the handled result.
"""
with self._lock:
committed_bundles, unprocessed_bundles = self._commit_bundles(
result.uncommitted_output_bundles,
result.unprocessed_bundles)
self._metrics.commit_logical(completed_bundle,
result.logical_metric_updates)
# If the result is for a view, update side inputs container.
if (result.uncommitted_output_bundles
and result.uncommitted_output_bundles[0].pcollection
in self._pcollection_to_views):
for view in self._pcollection_to_views[
result.uncommitted_output_bundles[0].pcollection]:
for committed_bundle in committed_bundles:
# side_input must be materialized.
self._side_inputs_container.add_values(
view,
committed_bundle.get_elements_iterable(make_copy=True))
# Tasks generated from unblocked side inputs as the watermark progresses.
tasks = self._watermark_manager.update_watermarks(
completed_bundle, result.transform, completed_timers,
committed_bundles, unprocessed_bundles, result.keyed_watermark_holds,
self._side_inputs_container)
self._pending_unblocked_tasks.extend(tasks)
if result.counters:
for counter in result.counters:
merged_counter = self._counter_factory.get_counter(
counter.name, counter.combine_fn)
merged_counter.accumulator.merge([counter.accumulator])
# Commit partial GBK states
existing_keyed_state = self._transform_keyed_states[result.transform]
for k, v in result.partial_keyed_state.items():
existing_keyed_state[k] = v
return committed_bundles
[docs] def get_aggregator_values(self, aggregator_or_name):
return self._counter_factory.get_aggregator_values(aggregator_or_name)
[docs] def schedule_pending_unblocked_tasks(self, executor_service):
if self._pending_unblocked_tasks:
with self._lock:
for task in self._pending_unblocked_tasks:
executor_service.submit(task)
self._pending_unblocked_tasks = []
def _commit_bundles(self, uncommitted_bundles, unprocessed_bundles):
"""Commits bundles and returns a immutable set of committed bundles."""
for in_progress_bundle in uncommitted_bundles:
producing_applied_ptransform = in_progress_bundle.pcollection.producer
watermarks = self._watermark_manager.get_watermarks(
producing_applied_ptransform)
in_progress_bundle.commit(watermarks.synchronized_processing_output_time)
for unprocessed_bundle in unprocessed_bundles:
unprocessed_bundle.commit(None)
return tuple(uncommitted_bundles), tuple(unprocessed_bundles)
[docs] def get_execution_context(self, applied_ptransform):
return _ExecutionContext(
self._watermark_manager.get_watermarks(applied_ptransform),
self._transform_keyed_states[applied_ptransform])
[docs] def create_bundle(self, output_pcollection):
"""Create an uncommitted bundle for the specified PCollection."""
return self._bundle_factory.create_bundle(output_pcollection)
[docs] def create_empty_committed_bundle(self, output_pcollection):
"""Create empty bundle useful for triggering evaluation."""
return self._bundle_factory.create_empty_committed_bundle(
output_pcollection)
[docs] def is_done(self, transform=None):
"""Checks completion of a step or the pipeline.
Args:
transform: AppliedPTransform to check for completion.
Returns:
True if the step will not produce additional output. If transform is None
returns true if all steps are done.
"""
if transform:
return self._is_transform_done(transform)
for applied_ptransform in self._step_names:
if not self._is_transform_done(applied_ptransform):
return False
return True
def _is_transform_done(self, transform):
tw = self._watermark_manager.get_watermarks(transform)
return tw.output_watermark == WatermarkManager.WATERMARK_POS_INF
[docs] def get_value_or_block_until_ready(self, side_input, task, block_until):
assert isinstance(task, TransformExecutor)
return self._side_inputs_container.get_value_or_block_until_ready(
side_input, task, block_until)
[docs]class DirectUnmergedState(InMemoryUnmergedState):
"""UnmergedState implementation for the DirectRunner."""
def __init__(self):
super(DirectUnmergedState, self).__init__(defensive_copy=False)
[docs]class DirectStepContext(object):
"""Context for the currently-executing step."""
def __init__(self, existing_keyed_state):
self.existing_keyed_state = existing_keyed_state
# In order to avoid partial writes of a bundle, every time
# existing_keyed_state is accessed, a copy of the state is made
# to be transferred to the bundle state once the bundle is committed.
self.partial_keyed_state = {}
[docs] def get_keyed_state(self, key):
if not self.existing_keyed_state.get(key):
self.existing_keyed_state[key] = DirectUnmergedState()
if not self.partial_keyed_state.get(key):
self.partial_keyed_state[key] = self.existing_keyed_state[key].copy()
return self.partial_keyed_state[key]