使用 Python 3.9 和 Apache Beam 2.38.0,下面的最小工作示例工作正常。
但是,当我使用 Apache Beam 2.39.0(或 2.44.0)时,该示例失败并显示错误
AssertionError: A total of 2 watermark-pending bundles did not execute.
。当我将日志记录切换到 DEBUG
时,我看到形式为 Unable to add bundle for stage
的消息以及两个包的 Stage input watermark: Timestamp(-9223372036854.775000)
(即 timestamp.MIN_TIMESTAMP
)和 Bundle schedule watermark: Timestamp(9223372036854.775000)
(即 timestamp.MAX_TIMESTAMP
)。
import logging
import apache_beam as beam
def setup_logging():
log_format = '[%(asctime)-15s] [%(name)s] [%(levelname)s]: %(message)s'
logging.basicConfig(format=log_format, level=logging.INFO)
logging.info("Pipeline Started")
class CreateKvPCollectWithSideInputDoFn(beam.DoFn):
def __init__(self):
super().__init__()
def process(self, element, side_input):
print(f"side_input_type: {type(side_input)}")
yield "b", "2"
class CreateKvPCollectDoFn(beam.DoFn):
def __init__(self):
super().__init__()
def process(self, element):
yield "a", "1"
def main():
setup_logging()
pipeline = beam.Pipeline()
pcollect_input = (
pipeline
| "Input/Create" >> beam.Create(["input"])
)
kvpcollect_1 = (
pcollect_input | "PCollection_1" >> beam.ParDo(CreateKvPCollectDoFn())
)
beamdict_1 = beam.pvalue.AsDict(kvpcollect_1)
kvpcollect_2 = (
pcollect_input
| "PCollection_2" >> beam.ParDo(
CreateKvPCollectWithSideInputDoFn(), side_input=beamdict_1
)
)
kvpcollect_3 = (
(kvpcollect_1, kvpcollect_2)
| "Flatten" >> beam.Flatten()
)
beamdict_3 = beam.pvalue.AsDict(kvpcollect_3)
(
pcollect_input
| "UseBeamDict_3" >> beam.ParDo(CreateKvPCollectWithSideInputDoFn(), side_input=beamdict_3)
| "PrintResult" >> beam.Map(print)
)
result = pipeline.run()
result.wait_until_finish()
if __name__ == '__main__':
main()
我想知道为什么这个错误似乎是在高于 2.38.0 的 Apache Beam Python 版本上触发的,以及是否有某种方法可以避免它。