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https://issues.apache.org/jira/browse/BEAM-7825?focusedWorklogId=289026&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-289026
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ASF GitHub Bot logged work on BEAM-7825:
----------------------------------------
Author: ASF GitHub Bot
Created on: 05/Aug/19 16:08
Start Date: 05/Aug/19 16:08
Worklog Time Spent: 10m
Work Description: aaltay commented on pull request #9164: [BEAM-7825] Add
test showing inconsistent stream processing with DirectRunner
URL: https://github.com/apache/beam/pull/9164#discussion_r310678621
##########
File path: sdks/python/apache_beam/examples/streaming_wordgroup.py
##########
@@ -0,0 +1,123 @@
+#
+# 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.
+#
+"""A streaming word-group workflow.
+
+In this somewhat contrived example, we emit a group of words that we accumulate
+in every window.
+
+This example is based on streaming_wordcount.py.
Review comment:
This is not really an example at this point. It will be confusing for the
reader if they are looking for examples. Maybe we can put these files under
testing/integration.
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Issue Time Tracking
-------------------
Worklog Id: (was: 289026)
Time Spent: 3h 50m (was: 3h 40m)
> Python's DirectRunner emits multiple panes per window and does not discard
> late data
> ------------------------------------------------------------------------------------
>
> Key: BEAM-7825
> URL: https://issues.apache.org/jira/browse/BEAM-7825
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Affects Versions: 2.13.0
> Environment: OS: Debian rodete.
> Beam versions: 2.15.0.dev.
> Python versions: Python 2.7, Python 3.7
> Reporter: Alexey Strokach
> Priority: Major
> Time Spent: 3h 50m
> Remaining Estimate: 0h
>
> The documentation for Beam's Windowing and Triggers functionality [states
> that|https://beam.apache.org/documentation/programming-guide/#triggers] _"if
> you use Beam’s default windowing configuration and default trigger, Beam
> outputs the aggregated result when it estimates all data has arrived, and
> discards all subsequent data for that window"_. However, it seems that the
> current behavior of Python's DirectRunner is inconsistent with both of those
> points. As the {{StreamingWordGroupIT.test_discard_late_data}} test shows,
> DirectRunner appears to process every data point that it reads from the input
> stream, irrespective of whether or not the timestamp of that data point is
> older than the timestamps of the windows that have already been processed.
> Furthermore, as the {{StreamingWordGroupIT.test_single_output_per_window}}
> test shows, DirectRunner generates multiple "panes" for the same window,
> apparently disregarding the notion of a watermark?
> The Dataflow runner passes both of those end-to-end tests.
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