[GitHub] [beam] pabloem commented on a change in pull request #11296: [BEAM-9640] Sketching watermark tracking on FnApiRunner

[GitBox <gi...@apache.org>]

pabloem commented on a change in pull request #11296:
URL: https://github.com/apache/beam/pull/11296#discussion_r441156972



##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/fn_runner.py
##########
@@ -384,13 +409,25 @@ def _collect_written_timers_and_add_to_fired_timers(
         out = create_OutputStream()
         for decoded_timer in timers_by_key_and_window.values():
           timer_coder_impl.encode_to_stream(decoded_timer, out, True)
+          if (transform_id, timer_family_id) not in timer_watermark_data:
+            timer_watermark_data[(transform_id,
+                                  timer_family_id)] = timestamp.MAX_TIMESTAMP
+          timer_watermark_data[(transform_id, timer_family_id)] = min(
+              timer_watermark_data[(transform_id, timer_family_id)],
+              decoded_timer.fire_timestamp)
         fired_timers[(transform_id, timer_family_id)] = ListBuffer(
             coder_impl=timer_coder_impl)
         fired_timers[(transform_id, timer_family_id)].append(out.get())
         written_timers.clear()
 
+    return timer_watermark_data
+
   def _add_sdk_delayed_applications_to_deferred_inputs(
       self, bundle_context_manager, bundle_result, deferred_inputs):
+    # type: (...) -> Set[str]
+
+    """Returns a set of PCollections with delayed applications."""

Review comment:
       PCollection IDs. Added to Pydoc.

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/watermark_manager.py
##########
@@ -0,0 +1,206 @@
+#
+# 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.
+#
+
+"""Utilities for managing watermarks for a pipeline execution by FnApiRunner."""
+
+from __future__ import absolute_import
+
+from apache_beam.portability.api import beam_runner_api_pb2
+from apache_beam.runners.portability.fn_api_runner import translations
+from apache_beam.runners.portability.fn_api_runner.translations import split_buffer_id
+from apache_beam.runners.worker import bundle_processor
+from apache_beam.utils import proto_utils
+from apache_beam.utils import timestamp
+
+
+class WatermarkManager(object):
+  """Manages the watermarks of a pipeline's stages.
+    It works by constructing an internal graph representation of the pipeline,
+    and keeping track of dependencies."""
+  class WatermarkNode(object):
+    def __init__(self, name):
+      self.name = name
+
+  class PCollectionNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.PCollectionNode, self).__init__(name)
+      self._watermark = timestamp.MIN_TIMESTAMP
+      self.producers = set()
+
+    def __str__(self):
+      return 'PCollectionNode<producers=[%s]' % ([i for i in self.producers])
+
+    def set_watermark(self, wm):
+      # print('setting watermark for %s to %s' % (self, wm))
+      self._watermark = min(self.upstream_watermark(), wm)
+
+    def upstream_watermark(self):
+      if self.producers:
+        return min(p.output_watermark() for p in self.producers)
+      else:
+        return timestamp.MAX_TIMESTAMP
+
+    def watermark(self):
+      if self._watermark:
+        return self._watermark
+      else:
+        return self.upstream_watermark()
+
+  class StageNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.StageNode, self).__init__(name)
+      # We keep separate inputs and side inputs because side inputs
+      # should hold back a stage's input watermark, to hold back execution
+      # for that stage; but they should not be considered when calculating
+      # the output watermark of the stage, because only the main input
+      # can actually advance that watermark.
+      self.inputs = set()
+      self.side_inputs = set()
+
+    def __str__(self):
+      return 'StageNode<inputs=[%s],side_inputs=[%s]' % (
+          [i.name for i in self.inputs], [i.name for i in self.side_inputs])
+
+    def set_watermark(self, wm):
+      raise NotImplementedError('Stages do not have a watermark')
+
+    def output_watermark(self):
+      w = min(i.watermark() for i in self.inputs)
+      return w
+
+    def input_watermark(self):
+      w = min(i.upstream_watermark() for i in self.inputs)
+
+      if self.side_inputs:
+        w = min(w, min(i.upstream_watermark() for i in self.side_inputs))
+      return w
+
+  def __init__(self, stages):
+    # type: (List[translations.Stage]) -> None
+    self._watermarks_by_name = {}
+    for s in stages:
+      stage_name = s.name
+      stage_node = WatermarkManager.StageNode(stage_name)
+      self._watermarks_by_name[stage_name] = stage_node
+
+      # 1. Get stage inputs, create nodes for them, add to _watermarks_by_name,
+      #    and add as inputs to stage node.
+      for transform in s.transforms:
+        if transform.spec.urn == bundle_processor.DATA_INPUT_URN:
+          buffer_id = transform.spec.payload
+          if buffer_id == translations.IMPULSE_BUFFER:

Review comment:
       I'd like to make this change on the next step, when we switch from per-stage execution to work-queue-based per-bundle execution. Is that reasonable?

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/watermark_manager.py
##########
@@ -0,0 +1,206 @@
+#
+# 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.
+#
+
+"""Utilities for managing watermarks for a pipeline execution by FnApiRunner."""
+
+from __future__ import absolute_import
+
+from apache_beam.portability.api import beam_runner_api_pb2
+from apache_beam.runners.portability.fn_api_runner import translations
+from apache_beam.runners.portability.fn_api_runner.translations import split_buffer_id
+from apache_beam.runners.worker import bundle_processor
+from apache_beam.utils import proto_utils
+from apache_beam.utils import timestamp
+
+
+class WatermarkManager(object):
+  """Manages the watermarks of a pipeline's stages.
+    It works by constructing an internal graph representation of the pipeline,
+    and keeping track of dependencies."""
+  class WatermarkNode(object):
+    def __init__(self, name):
+      self.name = name
+
+  class PCollectionNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.PCollectionNode, self).__init__(name)
+      self._watermark = timestamp.MIN_TIMESTAMP
+      self.producers = set()
+
+    def __str__(self):
+      return 'PCollectionNode<producers=[%s]' % ([i for i in self.producers])
+
+    def set_watermark(self, wm):
+      # print('setting watermark for %s to %s' % (self, wm))
+      self._watermark = min(self.upstream_watermark(), wm)
+
+    def upstream_watermark(self):
+      if self.producers:
+        return min(p.output_watermark() for p in self.producers)
+      else:
+        return timestamp.MAX_TIMESTAMP
+
+    def watermark(self):
+      if self._watermark:
+        return self._watermark
+      else:
+        return self.upstream_watermark()
+
+  class StageNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.StageNode, self).__init__(name)
+      # We keep separate inputs and side inputs because side inputs
+      # should hold back a stage's input watermark, to hold back execution
+      # for that stage; but they should not be considered when calculating
+      # the output watermark of the stage, because only the main input
+      # can actually advance that watermark.
+      self.inputs = set()
+      self.side_inputs = set()
+
+    def __str__(self):
+      return 'StageNode<inputs=[%s],side_inputs=[%s]' % (
+          [i.name for i in self.inputs], [i.name for i in self.side_inputs])
+
+    def set_watermark(self, wm):
+      raise NotImplementedError('Stages do not have a watermark')
+
+    def output_watermark(self):
+      w = min(i.watermark() for i in self.inputs)
+      return w
+
+    def input_watermark(self):

Review comment:
       That makes sense. I've changed the output_watermark to be calculated based on downstream PCollections.

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/watermark_manager.py
##########
@@ -0,0 +1,206 @@
+#
+# 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.
+#
+
+"""Utilities for managing watermarks for a pipeline execution by FnApiRunner."""
+
+from __future__ import absolute_import
+
+from apache_beam.portability.api import beam_runner_api_pb2
+from apache_beam.runners.portability.fn_api_runner import translations
+from apache_beam.runners.portability.fn_api_runner.translations import split_buffer_id
+from apache_beam.runners.worker import bundle_processor
+from apache_beam.utils import proto_utils
+from apache_beam.utils import timestamp
+
+
+class WatermarkManager(object):
+  """Manages the watermarks of a pipeline's stages.
+    It works by constructing an internal graph representation of the pipeline,
+    and keeping track of dependencies."""
+  class WatermarkNode(object):
+    def __init__(self, name):
+      self.name = name
+
+  class PCollectionNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.PCollectionNode, self).__init__(name)
+      self._watermark = timestamp.MIN_TIMESTAMP
+      self.producers = set()
+
+    def __str__(self):
+      return 'PCollectionNode<producers=[%s]' % ([i for i in self.producers])
+
+    def set_watermark(self, wm):
+      # print('setting watermark for %s to %s' % (self, wm))
+      self._watermark = min(self.upstream_watermark(), wm)
+
+    def upstream_watermark(self):
+      if self.producers:
+        return min(p.output_watermark() for p in self.producers)
+      else:
+        return timestamp.MAX_TIMESTAMP
+
+    def watermark(self):
+      if self._watermark:
+        return self._watermark
+      else:
+        return self.upstream_watermark()
+
+  class StageNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.StageNode, self).__init__(name)
+      # We keep separate inputs and side inputs because side inputs
+      # should hold back a stage's input watermark, to hold back execution
+      # for that stage; but they should not be considered when calculating
+      # the output watermark of the stage, because only the main input
+      # can actually advance that watermark.
+      self.inputs = set()
+      self.side_inputs = set()
+
+    def __str__(self):
+      return 'StageNode<inputs=[%s],side_inputs=[%s]' % (
+          [i.name for i in self.inputs], [i.name for i in self.side_inputs])
+
+    def set_watermark(self, wm):
+      raise NotImplementedError('Stages do not have a watermark')
+
+    def output_watermark(self):

Review comment:
       I've changed this implementation to rely on the watermark from downstream PCollections.

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/execution.py
##########
@@ -296,6 +297,12 @@ def __init__(self,
     self.safe_coders = safe_coders
     self.data_channel_coders = data_channel_coders
 
+    self.transform_id_to_buffer_id = {

Review comment:
       Done

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/watermark_manager.py
##########
@@ -0,0 +1,206 @@
+#
+# 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.
+#
+
+"""Utilities for managing watermarks for a pipeline execution by FnApiRunner."""
+
+from __future__ import absolute_import
+
+from apache_beam.portability.api import beam_runner_api_pb2
+from apache_beam.runners.portability.fn_api_runner import translations
+from apache_beam.runners.portability.fn_api_runner.translations import split_buffer_id
+from apache_beam.runners.worker import bundle_processor
+from apache_beam.utils import proto_utils
+from apache_beam.utils import timestamp
+
+
+class WatermarkManager(object):
+  """Manages the watermarks of a pipeline's stages.
+    It works by constructing an internal graph representation of the pipeline,
+    and keeping track of dependencies."""
+  class WatermarkNode(object):
+    def __init__(self, name):
+      self.name = name
+
+  class PCollectionNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.PCollectionNode, self).__init__(name)
+      self._watermark = timestamp.MIN_TIMESTAMP
+      self.producers = set()
+
+    def __str__(self):
+      return 'PCollectionNode<producers=[%s]' % ([i for i in self.producers])
+
+    def set_watermark(self, wm):
+      # print('setting watermark for %s to %s' % (self, wm))
+      self._watermark = min(self.upstream_watermark(), wm)
+
+    def upstream_watermark(self):
+      if self.producers:
+        return min(p.output_watermark() for p in self.producers)
+      else:
+        return timestamp.MAX_TIMESTAMP
+
+    def watermark(self):
+      if self._watermark:
+        return self._watermark
+      else:
+        return self.upstream_watermark()
+
+  class StageNode(WatermarkNode):
+    def __init__(self, name):
+      super(WatermarkManager.StageNode, self).__init__(name)
+      # We keep separate inputs and side inputs because side inputs

Review comment:
       I believe only side inputs have this effect, no? I am considering timers one of the main inputs for a PTransform, and thus they would hold the watermark.

##########
File path: sdks/python/apache_beam/runners/portability/fn_api_runner/fn_runner.py
##########
@@ -363,16 +387,17 @@ def _run_bundle_multiple_times_for_testing(
       finally:
         runner_execution_context.state_servicer.restore()
 
+  @staticmethod
   def _collect_written_timers_and_add_to_fired_timers(
-      self,
       bundle_context_manager,  # type: execution.BundleContextManager
       fired_timers  # type: Dict[Tuple[str, str], ListBuffer]

Review comment:
       Great observation. Fixed.




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