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Attempt prism for pipelines with unbounded PCollections. #34721

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Attempt prism for pipelines with unbounded PCollections. #34721

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f0f7a42
Attempt prism for pipelines with unbounded PCollections.
robertwb Apr 24, 2025
9cc1da4
Consider small periodic impulses as bounded.
robertwb Apr 25, 2025
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Consider small periodic impulses as bounded.
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@robertwb
robertwb committed Apr 28, 2025
commit 9cc1da4b2322f71dc9a373c84f79519ebb8f2a71
1 change: 1 addition & 0 deletions sdks/python/apache_beam/transforms/combiners_test.py
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Expand Up @@ -991,6 +991,7 @@ def test_combine_globally_for_unbounded_source_with_default(self):
stop_timestamp=time.time() + 4,
fire_interval=1,
apply_windowing=False,
is_bounded=False,
)
| beam.Map(lambda x: ('c', 1))
| beam.WindowInto(
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16 changes: 13 additions & 3 deletions sdks/python/apache_beam/transforms/periodicsequence.py
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Expand Up @@ -178,25 +178,35 @@ def __init__(
start_timestamp=Timestamp.now(),
stop_timestamp=MAX_TIMESTAMP,
fire_interval=360.0,
apply_windowing=False):
apply_windowing=False,
is_bounded=None):
'''
:param start_timestamp: Timestamp for first element.
:param stop_timestamp: Timestamp after which no elements will be output.
:param fire_interval: Interval in seconds at which to output elements.
:param apply_windowing: Whether each element should be assigned to
individual window. If false, all elements will reside in global window.
:param is_bounded: whether to treat the output PCollection as bounded.
Defaults to True for small timestamp ranges and False for large ones.
'''
self.start_ts = start_timestamp
self.stop_ts = stop_timestamp
self.interval = fire_interval
self.apply_windowing = apply_windowing
self.is_bounded = (
stop_timestamp - start_timestamp < 60
if is_bounded is None else is_bounded)

def expand(self, pbegin):
result = (
sequence = (
pbegin
| 'ImpulseElement' >> beam.Create(
[(self.start_ts, self.stop_ts, self.interval)])
| 'GenSequence' >> beam.ParDo(ImpulseSeqGenDoFn())
| 'GenSequence' >> beam.ParDo(ImpulseSeqGenDoFn()))
if self.is_bounded:
sequence.is_bounded = True
result = (
sequence
| 'MapToTimestamped' >> beam.Map(lambda tt: TimestampedValue(tt, tt)))
if self.apply_windowing:
result = result | 'ApplyWindowing' >> beam.WindowInto(
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3 changes: 2 additions & 1 deletion sdks/python/apache_beam/transforms/periodicsequence_test.py
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Expand Up @@ -91,7 +91,8 @@ def test_periodicimpulse_default_start(self):
assert is_same_type, error

with TestPipeline() as p:
result = p | 'PeriodicImpulse' >> PeriodicImpulse(it, et, interval)
result = p | 'PeriodicImpulse' >> PeriodicImpulse(
it, et, interval, is_bounded=False)

k = [it + x * interval for x in range(0, int(duration / interval))]
self.assertEqual(result.is_bounded, False)
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