learning/katas/python/Streaming/Triggers/Window Accumulation Modes/task.py

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# beam-playground:
#   name: WindowAccumulationMode
#   description: Task from katas to count events using ACCUMULATING as accumulation mode
#   multifile: true
#   files:
#    - name: generate_event.py
#   context_line: 60
#   categories:
#     - Streaming
#   complexity: ADVANCED
#   tags:
#     - windowing
#     - triggers
#     - count
#     - accumulation
#     - event

import apache_beam as beam
from generate_event import GenerateEvent
from apache_beam.transforms.window import FixedWindows
from apache_beam.transforms.trigger import AfterWatermark
from apache_beam.transforms.trigger import AfterCount
from apache_beam.transforms.trigger import AccumulationMode
from apache_beam.utils.timestamp import Duration
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.options.pipeline_options import StandardOptions
from apache_beam.transforms.util import LogElements


class CountEventsWithAccumulating(beam.PTransform):
  def expand(self, events):
    return (events
            | beam.WindowInto(FixedWindows(1 * 24 * 60 * 60),  # 1 Day Window
                              trigger=AfterWatermark(early=AfterCount(1)),
                              accumulation_mode=AccumulationMode.ACCUMULATING,
                              allowed_lateness=Duration(seconds=0))
            | beam.CombineGlobally(beam.combiners.CountCombineFn()).without_defaults())


options = PipelineOptions()
options.view_as(StandardOptions).streaming = True
with beam.Pipeline(options=options) as p:
  (p | GenerateEvent.sample_data()
   | CountEventsWithAccumulating()
   | LogElements(with_window=True))