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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=409202&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-409202
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 25/Mar/20 00:04
Start Date: 25/Mar/20 00:04
Worklog Time Spent: 10m
Work Description: rohdesamuel commented on pull request #11148:
[BEAM-8335] Adds a streaming wordcount integration test
URL: https://github.com/apache/beam/pull/11148#discussion_r397534523
##########
File path:
sdks/python/apache_beam/runners/interactive/interactive_runner_test.py
##########
@@ -147,6 +150,97 @@ def process(self, element):
]
self.assertEqual(actual_reified, expected_reified)
+ def test_streaming_wordcount(self):
+ class WordExtractingDoFn(beam.DoFn):
+ def process(self, element):
+ text_line = element.strip()
+ words = text_line.split()
+ return words
+
+ # Add the TestStream so that it can be cached.
+ ib.options.capturable_sources.add(TestStream)
+ ib.options.capture_duration = timedelta(seconds=1)
+
+ p = beam.Pipeline(
+ runner=interactive_runner.InteractiveRunner(),
+ options=StandardOptions(streaming=True))
+
+ data = (
+ p
+ | TestStream()
+ .advance_watermark_to(0)
+ .advance_processing_time(1)
+ .add_elements(['to', 'be', 'or', 'not', 'to', 'be'])
+ .advance_watermark_to(20)
+ .advance_processing_time(1)
+ .add_elements(['to', 'be', 'or', 'not', 'to', 'be'])
+ .advance_watermark_to(40)
+ .advance_processing_time(1)
+ .add_elements(['to', 'be', 'or', 'not', 'to', 'be'])
+ | beam.WindowInto(beam.window.FixedWindows(10))) # yapf: disable
+
+ counts = (
+ data
+ | 'split' >> beam.ParDo(WordExtractingDoFn())
+ | 'pair_with_one' >> beam.Map(lambda x: (x, 1))
+ | 'group' >> beam.GroupByKey()
+ | 'count' >> beam.Map(lambda wordones: (wordones[0],
sum(wordones[1]))))
+
+ # Watch the local scope for Interactive Beam so that referenced
PCollections
+ # will be cached.
+ ib.watch(locals())
+
+ # This is normally done in the interactive_utils when a transform is
+ # applied but needs an IPython environment. So we manually run this here.
+ ie.current_env().track_user_pipelines()
+
+ # This tests that the data was correctly cached.
+ pane_info = PaneInfo(True, True, PaneInfoTiming.UNKNOWN, 0, 0)
+ expected_data_df = pd.DataFrame(
+ [('to', 0, [beam.window.IntervalWindow(0, 10)], pane_info),
Review comment:
Ohhh I see, I misread your comment. I changed it to a smaller set of data
that doesn't have duplicates to test the windowing.
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Issue Time Tracking
-------------------
Worklog Id: (was: 409202)
Time Spent: 114h 50m (was: 114h 40m)
> Add streaming support to Interactive Beam
> -----------------------------------------
>
> Key: BEAM-8335
> URL: https://issues.apache.org/jira/browse/BEAM-8335
> Project: Beam
> Issue Type: Improvement
> Components: runner-py-interactive
> Reporter: Sam Rohde
> Assignee: Sam Rohde
> Priority: Major
> Time Spent: 114h 50m
> Remaining Estimate: 0h
>
> This issue tracks the work items to introduce streaming support to the
> Interactive Beam experience. This will allow users to:
> * Write and run a streaming job in IPython
> * Automatically cache records from unbounded sources
> * Add a replay experience that replays all cached records to simulate the
> original pipeline execution
> * Add controls to play/pause/stop/step individual elements from the cached
> records
> * Add ability to inspect/visualize unbounded PCollections
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