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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=352183&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-352183
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 02/Dec/19 20:36
Start Date: 02/Dec/19 20:36
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #10236: [BEAM-8335]
Add method to PipelineInstrument to create background caching pipline
URL: https://github.com/apache/beam/pull/10236#discussion_r352815419
##########
File path:
sdks/python/apache_beam/runners/interactive/pipeline_instrument_test.py
##########
@@ -178,14 +183,48 @@ def test_has_unbounded_source(self):
p = beam.Pipeline(interactive_runner.InteractiveRunner())
_ = p | 'ReadUnboundedSource' >> beam.io.ReadFromPubSub(
subscription='projects/fake-project/subscriptions/fake_sub')
- self.assertTrue(instr.has_unbounded_source(p))
+ self.assertTrue(instr.has_unbounded_sources(p))
def test_not_has_unbounded_source(self):
p = beam.Pipeline(interactive_runner.InteractiveRunner())
with tempfile.NamedTemporaryFile(delete=False) as f:
f.write(b'test')
_ = p | 'ReadBoundedSource' >> beam.io.ReadFromText(f.name)
- self.assertFalse(instr.has_unbounded_source(p))
+ self.assertFalse(instr.has_unbounded_sources(p))
+
+ def test_background_caching_pipeline_proto(self):
+ p = beam.Pipeline(interactive_runner.InteractiveRunner())
+
+ # Test that the two ReadFromPubSub are correctly cut out.
+ a = p | 'ReadUnboundedSourceA' >> beam.io.ReadFromPubSub(
+ subscription='projects/fake-project/subscriptions/fake_sub')
+ b = p | 'ReadUnboundedSourceB' >> beam.io.ReadFromPubSub(
+ subscription='projects/fake-project/subscriptions/fake_sub')
+
+ # Add some extra PTransform afterwards to make sure that only the unbounded
+ # sources remain.
+ c = (a, b) | beam.CoGroupByKey()
+ _ = c | beam.Map(lambda x: x)
+
+ instrumenter = instr.PipelineInstrument(p)
+ instrumenter.instrument()
+ actual_pipeline = instrumenter.background_caching_pipeline_proto()
+
+ # Now recreate the expected pipeline, which should only have the unbounded
+ # sources.
+ p = beam.Pipeline(interactive_runner.InteractiveRunner())
+ a = p | 'ReadUnboundedSourceA' >> beam.io.ReadFromPubSub(
+ subscription='projects/fake-project/subscriptions/fake_sub')
+ instrumenter._write_cache(p, a)
Review comment:
If you want to use `_write_cache` as a static function in tests, maybe we
can extract the logic into `write_cache` in the module and reuse it in
`_write_cache` so that everything is self contained in `PipelineInstrument`
while those logic are also available as static functions outside of
`PipelineInstrument`.
An example is static `cacheable_key` in `pipeline_instrument` module and
`_cacheable_key` in `PipelineInstrument` class.
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Issue Time Tracking
-------------------
Worklog Id: (was: 352183)
Time Spent: 37h 20m (was: 37h 10m)
> 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: 37h 20m
> 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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