Windowing
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Cheatsheet: Windowing
Recommended reading: 4 mins
Core Description
Group unbounded streaming data into logical time intervals.
beam.WindowInto()
returns: PCollectionPurpose
Binds PCollection elements into time-based logical windows.
Syntax Signature
beam.WindowInto(windowfn, *args, **kwargs)Usage Example
import apache_beam as beam
from apache_beam.transforms.window import FixedWindows
# Group records into 60-second fixed intervals
windowed = stream | beam.WindowInto(FixedWindows(60))Used In
Aggregating metrics in real-time streaming pipelines.
Related Methods
FixedWindows(), SlidingWindows(), Sessions()
Remember:
Windowing divides unbounded streams into bounded slices, which is mandatory before using Combine or GroupByKey.
Windowing Types Comparison
Review typical real-world properties of temporal window structures.
| Window Type | Overlapping | Alignment | Use Case |
|---|---|---|---|
| Fixed Windows | No | Aligned globally | Hourly/daily summaries |
| Sliding Windows | Yes | Aligned globally | 10-minute moving average every 1 minute |
| Session Windows | No | Unaligned (per-key) | User behavior tracking (idle timeout) |
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