Data driven triggers

A data-driven trigger is a type of trigger in Apache Beam that fires when specific conditions on the data being processed are met. Unlike processing time triggers, which fire at regular intervals based on the current system time, data-driven triggers are based on the data itself.

For example, a data-driven trigger might fire when a certain number of elements have been processed, or when the values of the elements reach a specific threshold. Data-driven triggers are particularly useful when processing time-sensitive data where it's important to respond to changes in the data as they happen.

Apache Beam provides several options for data-driven triggers, including element count triggers, processing time triggers, and custom triggers. By using a combination of these triggers, you can implement complex processing logic that takes into account both processing time and the state of the data.

{{if (eq .Sdk “go”)}}

fixedWindowedItems := beam.WindowInto(s, window.NewFixedWindows(2*time.Second), input,
  		beam.Trigger(trigger.AfterCount(2)),
  		beam.AllowedLateness(30*time.Minute),
      beam.PanesDiscard(),
    )

{{end}} {{if (eq .Sdk “java”)}}

Trigger trigger = AfterPane.elementCountAtLeast(100);
PCollection<String> windowed = input.apply(window.triggering(trigger).withAllowedLateness(Duration.ZERO).discardingFiredPanes());

{{end}} {{if (eq .Sdk “python”)}}

(p | beam.Create(['Hello Beam','It`s trigger'])
     | 'window' >> beam.WindowInto(FixedWindows(2),trigger=trigger.AfterCount(2),accumulation_mode=trigger.AccumulationMode.DISCARDING) \
     | ... )

{{end}}