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Date: Sat, 2 Dec 2017 00:28:11 +0000 (UTC)
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Subject: [jira] [Commented] (BEAM-1630) Add Splittable DoFn to Python SDK
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archived-at: Sat, 02 Dec 2017 00:28:23 -0000


    [ https://issues.apache.org/jira/browse/BEAM-1630?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16275270#comment-16275270 ] 

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_r153970950
 
 
 ##########
 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)
 
 Review comment:
   Looks like Python SDK does not always wrap elements with WindowdValue objects so this can be an ElementAndRestriction object.

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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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