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Bounded stream

As explained in Kafka for Architects

A bounded stream is a finite data sequence with a clearly defined start and end.

A bounded stream has a defined start and end. Unlike an unbounded stream, whose events keep arriving, it represents a complete dataset: all events are ingested before computations are applied. This makes processing batch-like rather than continuous. section 8.4.2

Choosing a Flink source

A Flink job can read a file or run a batch database query as a bounded source. A Kafka topic is an unbounded source when events arrive continuously. The choice determines whether the job processes a complete dataset or an ongoing flow. section 8.4.2

How Kafka for Architects covers it

How deep it goes
Defines stream boundaries and explains their batch-like behavior, without detailing bounded-source implementation.
Examples
Contrasts files and batch database queries with continuously arriving events from Kafka topics.
What you can do after
Apply it via Apache Flink to choose finite sources when processing requires a complete dataset.
How it connects
Connects bounded streams to unbounded streams, batch processing, Flink jobs, and connectors.
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Kafka for Architects. The section links point to the parts of the book it draws on.