import apache_beam as beam from apache_beam.transforms.window import IntervalWindow from datetime import datetime interval = beam.window.IntervalWindow( start=datetime(2021, 1, 1, 0, 0, 0), end=datetime(2021, 1, 1, 1, 0, 0))
import apache_beam as beam from apache_beam.transforms.window import IntervalWindow from datetime import datetime, timedelta class AssignHourlyInterval(beam.DoFn): def process(self, element): hour = element.timestamp.hour start = datetime(element.timestamp.year, element.timestamp.month, element.timestamp.day, hour) end = start + timedelta(hours=1) yield beam.window.TimestampedValue(element, start), IntervalWindow(start, end) data = (...) grouped_data = (data | beam.ParDo(AssignHourlyInterval()) | beam.WindowInto(beam.window.Sessions(gap_size=timedelta(minutes=10))))In this example, we use a custom DoFn to assign each element with an appropriate hourly interval window based on its timestamp. Then, we use the WindowInto transform to group the data into session windows with a gap size of 10 minutes. The IntervalWindow class is part of the apache_beam.transforms.window package library in Apache Beam.