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https://issues.apache.org/jira/browse/BEAM-1630?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16275267#comment-16275267
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ASF GitHub Bot commented on BEAM-1630:
--------------------------------------
chamikaramj commented on a change in pull request #4064: [BEAM-1630] Adds
support for processing Splittable DoFns using DirectRunner.
URL: https://github.com/apache/beam/pull/4064#discussion_r153971590
##########
File path: sdks/python/apache_beam/runners/direct/sdf_direct_runner.py
##########
@@ -0,0 +1,264 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+#
+
+"""This module contains Splittable DoFn logic that is specific to DirectRunner.
+"""
+
+from threading import Lock
+from threading import Timer
+
+import apache_beam as beam
+from apache_beam import TimeDomain
+from apache_beam import pvalue
+from apache_beam.io.iobase import RestrictionTracker
+from apache_beam.pipeline import PTransformOverride
+from apache_beam.runners.common import DoFnContext
+from apache_beam.runners.common import DoFnInvoker
+from apache_beam.runners.common import DoFnSignature
+from apache_beam.runners.common import OutputProcessor
+from apache_beam.runners.direct.evaluation_context import DirectStepContext
+from apache_beam.runners.direct.util import KeyedWorkItem
+from apache_beam.runners.direct.watermark_manager import WatermarkManager
+from apache_beam.runners.sdf_common import ElementAndRestriction
+from apache_beam.runners.sdf_common import ProcessKeyedElements
+from apache_beam.transforms.core import ProcessContinuation
+from apache_beam.transforms.ptransform import PTransform
+from apache_beam.transforms.trigger import _ValueStateTag
+from apache_beam.utils.windowed_value import WindowedValue
+
+
+class ProcessKeyedElementsViaKeyedWorkItemsOverride(PTransformOverride):
+ """A transform override for ProcessElements transform."""
+
+ def get_matcher(self):
+ def _matcher(applied_ptransform):
+ return isinstance(
+ applied_ptransform.transform, ProcessKeyedElements)
+
+ return _matcher
+
+ def get_replacement_transform(self, ptransform):
+ return ProcessKeyedElementsViaKeyedWorkItems(ptransform)
+
+
+class ProcessKeyedElementsViaKeyedWorkItems(PTransform):
+ """A transform that processes Splittable DoFn input via KeyedWorkItems.
+ """
+
+ def __init__(self, process_keyed_elements_transform):
+ self._process_keyed_elements_transform = process_keyed_elements_transform
+
+ def expand(self, pcoll):
+ return pcoll | beam.core.GroupByKey() | ProcessElements(
+ self._process_keyed_elements_transform)
+
+
+class ProcessElements(PTransform):
+ """Processes keyed input via Splittable DoFn objects."""
+
+ def __init__(self, process_keyed_elements_transform):
+ self._process_keyed_elements_transform = process_keyed_elements_transform
+ self.sdf = self._process_keyed_elements_transform.sdf
+
+ def expand(self, pcoll):
+ return pvalue.PCollection(pcoll.pipeline)
+
+ def new_process_fn(self, sdf):
+ return ProcessFn(
+ sdf,
+ self._process_keyed_elements_transform.ptransform_args,
+ self._process_keyed_elements_transform.ptransform_kwargs)
+
+
+class ProcessFn(beam.DoFn):
+
+ def __init__(
+ self, sdf, args_for_invoker, kwargs_for_invoker):
+ self.sdf = sdf
+ self._element_tag = _ValueStateTag('element')
+ self._restriction_tag = _ValueStateTag('restriction')
+ self.watermark_hold_tag = _ValueStateTag('watermark_hold')
+ self._process_element_invoker = None
+
+ self.sdf_invoker = DoFnInvoker.create_invoker(
+ DoFnSignature(self.sdf), context=DoFnContext('unused_context'),
+ input_args=args_for_invoker, input_kwargs=kwargs_for_invoker)
+
+ def set_step_context(self, step_context):
+ assert isinstance(step_context, DirectStepContext)
+ self._step_context = step_context
+
+ def set_process_element_invoker(self, process_element_invoker):
+ assert isinstance(process_element_invoker, SDFProcessElementInvoker)
+ self._process_element_invoker = process_element_invoker
+
+ def start_bundle(self):
+ # TODO: support start_bundle() method for SDFs.
+ pass
+
+ def finish_bundle(self):
+ # TODO: support finish_bundle() method for SDFs.
+ pass
+
+ def process(self, element, timestamp=beam.DoFn.TimestampParam,
+ window=beam.DoFn.WindowParam, * args, **kwargs):
+ if isinstance(element, KeyedWorkItem):
+ # Must be a timer firing.
+ key = element.encoded_key
+ else:
+ key, values = element
+ values = list(values)
+ assert len(values) == 1
+ value = values[0]
+
+ state = self._step_context.get_keyed_state(key)
+ element_state = state.get_state(window, self._element_tag)
+ is_seed_call = not element_state # Initially element_state is an empty
list.
+
+ if not is_seed_call:
+ element = state.get_state(window, self._element_tag)
+ restriction = state.get_state(window, self._restriction_tag)
+ windowed_element = WindowedValue(element, timestamp, [window])
+ else:
+ element_and_restriction = (
+ value.value if isinstance(value, WindowedValue) else value)
+ assert isinstance(element_and_restriction, ElementAndRestriction)
+ element = element_and_restriction.element
+ restriction = element_and_restriction.restriction
+
+ if isinstance(value, WindowedValue):
+ windowed_element = WindowedValue(
+ element, value.timestamp, value.windows)
+ else:
+ windowed_element = WindowedValue(element, timestamp, [window])
+
+ tracker = self.sdf_invoker.invoke_create_tracker(restriction)
+ assert self._process_element_invoker
+ assert isinstance(self._process_element_invoker,
+ SDFProcessElementInvoker)
+
+ output_values = self._process_element_invoker.invoke_process_element(
+ self.sdf_invoker, windowed_element, tracker)
+
+ sdf_result = None
+ for output in output_values:
+ if isinstance(output, SDFProcessElementInvoker.Result):
+ # SDFProcessElementInvoker.Result should be the last item yielded.
+ sdf_result = output
+ break
+ yield output
+
+ if not sdf_result.residual_restriction:
+ # All work for current residual and restriction pair is complete.
+ state.clear_state(window, self._element_tag)
+ state.clear_state(window, self._restriction_tag)
+ # Releasing output watermark by setting it to positive infinity.
+ state.add_state(window, self.watermark_hold_tag,
+ WatermarkManager.WATERMARK_POS_INF)
+ else:
+ state.add_state(window, self._element_tag, element)
+ state.add_state(window, self._restriction_tag,
+ sdf_result.residual_restriction)
+ state.add_state(window, self.watermark_hold_tag,
+ WatermarkManager.WATERMARK_NEG_INF)
Review comment:
Yeah, Python currently does not support this. Added a comment.
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> Add Splittable DoFn to Python SDK
> ---------------------------------
>
> Key: BEAM-1630
> URL: https://issues.apache.org/jira/browse/BEAM-1630
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Chamikara Jayalath
> Assignee: Chamikara Jayalath
>
> Splittable DoFn [1] is currently being implemented for Java SDK [2]. We
> should add this to Python SDK as well.
> Following document proposes an API for this.
> https://docs.google.com/document/d/1h_zprJrOilivK2xfvl4L42vaX4DMYGfH1YDmi-s_ozM/edit?usp=sharing
> [1] https://s.apache.org/splittable-do-fn
> [2]
> https://lists.apache.org/thread.html/0ce61ac162460a149d5c93cdface37cc383f8030fe86ca09e5699b18@%3Cdev.beam.apache.org%3E
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