Flink can perform statistics based on which of the following windows? (Multiple choice)

Question

Options

• ATime windows
• BSliding window
• CSession window
• DCount window

• A
  100% (41)

Explanation

All four options are correct because Apache Flink natively supports four fundamental window types for stream processing statistics. Time windows (A) partition a stream into fixed-duration buckets (e.g., every 5 minutes), triggering computation when time advances. Sliding windows (B) are time-based windows that overlap - defined by both a size and a slide interval (e.g., a 10-min window sliding every 2 min), so an event can belong to multiple windows. Session windows (C) group events by activity gaps - a new window starts when a configurable idle period elapses, making them ideal for user-session analytics. Count windows (D) trigger based on element count rather than time (e.g., compute stats every 100 events), useful when event rate matters more than clock time.

Since every choice is correct, there are no wrong distractors - the question tests whether you know Flink is not limited to just time-based windowing.

Memory tip: Use the acronym TSSC - Time, Sliding, Session, Count - and remember that Flink covers "all the bases": two time-oriented types (Time + Sliding), one behavior-oriented type (Session), and one data-volume-oriented type (Count).

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