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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2020/05/05 21:15:00 UTC
[jira] [Work logged] (BEAM-9640) Track PCollection watermark across
bundle executions
[ https://issues.apache.org/jira/browse/BEAM-9640?focusedWorklogId=430902&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-430902 ]
ASF GitHub Bot logged work on BEAM-9640:
----------------------------------------
Author: ASF GitHub Bot
Created on: 05/May/20 21:14
Start Date: 05/May/20 21:14
Worklog Time Spent: 10m
Work Description: robertwb commented on a change in pull request #11296:
URL: https://github.com/apache/beam/pull/11296#discussion_r420388089
##########
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:
Are these fired_timers, or timers_to_fire?
##########
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:
Different transforms may have different input/output buffers associated with them. Perhaps name this `input_transform_to_buffer_id` or `buffer_id_by_consumer` or similar.
##########
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:
Set of PCollection ids? Buffer ids?
##########
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))
Review comment:
Leftover debugging?
##########
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])
Review comment:
`list(self.producers)` (Also, won't this give double brackets?) Also, '<' is unmatched and not typically for string representations.
##########
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)
Review comment:
I suppose timers are considered an input?
##########
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)
Review comment:
Nit: `return min(...)`
##########
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
Review comment:
Does initializing this hear mean that we never use the watermark of the producers. (I have to admit, I'm not quite understanding why the watermark of a PCollection would ever be different than that of its producers.)
##########
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:
+ pcoll_name = transform.unique_name
+ else:
+ _, pcoll_name = split_buffer_id(buffer_id)
+ if pcoll_name not in self._watermarks_by_name:
+ self._watermarks_by_name[
+ pcoll_name] = WatermarkManager.PCollectionNode(pcoll_name)
+ stage_node.inputs.add(self._watermarks_by_name[pcoll_name])
+
+ # 2. Get stage timers, and add them as inputs to the stage.
+ for transform in s.transforms:
+ if transform.spec.urn in translations.PAR_DO_URNS:
+ payload = proto_utils.parse_Bytes(
+ transform.spec.payload, beam_runner_api_pb2.ParDoPayload)
+ for timer_family_id in payload.timer_family_specs.keys():
+ timer_pcoll_name = (transform.unique_name, timer_family_id)
+ self._watermarks_by_name[
+ timer_pcoll_name] = WatermarkManager.PCollectionNode(
+ timer_pcoll_name)
+ stage_node.inputs.add(self._watermarks_by_name[timer_pcoll_name])
+
+ # 3. Get stage outputs, create nodes for them, add to _watermarks_by_name,
+ # and add stage as their producer
+ for transform in s.transforms:
+ if transform.spec.urn == bundle_processor.DATA_OUTPUT_URN:
+ buffer_id = transform.spec.payload
+ _, pcoll_name = split_buffer_id(buffer_id)
+ if pcoll_name not in self._watermarks_by_name:
+ self._watermarks_by_name[
+ pcoll_name] = WatermarkManager.PCollectionNode(pcoll_name)
+ self._watermarks_by_name[pcoll_name].producers.add(stage_node)
+
+ # 4. Get stage side inputs, create nodes for them, add to
+ # _watermarks_by_name, and add them as side inputs of the stage.
+ for pcoll_name in s.side_inputs():
+ if pcoll_name not in self._watermarks_by_name:
+ self._watermarks_by_name[
+ pcoll_name] = WatermarkManager.PCollectionNode(pcoll_name)
+ stage_node.side_inputs.add(self._watermarks_by_name[pcoll_name])
+
+ def get_node(self, name):
+ # type: (str) -> WatermarkNode
+ return self._watermarks_by_name[name]
+
+ def get_watermark(self, name):
+ element = self._watermarks_by_name[name]
Review comment:
Nit: (here and below): elide unneeded intermediate assignments and just chain.
##########
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:
Review comment:
What about self._watermark = 0?
##########
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:
side inputs and timers all have this effect, right?
##########
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:
This doesn't seem to take into account data that's "in flight." E.g. all the input watermarks could be at max-timestamp, but that doesn't mean that all the inputs' data has been consumed.
##########
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:
This doesn't seem right, the input watermarks should always be an upper bound on the output watermark.
##########
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:
Should we change `IMPULSE_BUFFER` to conform to the spec of all other buffer ids rather than branching on it? (Or at least push this branch into split_buffer_id)?
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Issue Time Tracking
-------------------
Worklog Id: (was: 430902)
Time Spent: 1h 10m (was: 1h)
> Track PCollection watermark across bundle executions
> ----------------------------------------------------
>
> Key: BEAM-9640
> URL: https://issues.apache.org/jira/browse/BEAM-9640
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Pablo Estrada
> Assignee: Pablo Estrada
> Priority: Major
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
> This can be done without relying on the watermark manager for execution.
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