KStream
KStream is a Kafka Streams abstraction representing an unbounded stream of key-value records processed as independent events.
Kafka Streams in Action, Second Edition
KStream is a Kafka Streams abstraction representing an unbounded stream of key-value records and supporting record-by-record processing operations.
- How it is used
- Builds Kafka topology paths that consume, transform, route, inspect, and publish key-value event records.
- How deep it goes
- Explains source creation, transformations, branching, terminal operations, and KTable contrast; defers lower-level Processor API control.
- Examples
- Uses masked retail purchases, branching coffee and electronics purchases, sensor streams, yelling text, and stock-ticker quotes.
- What you can do after
- Apply it via Kafka Streams DSL to construct chained topic-processing pipelines and inspect or route their records.
Read how Kafka Streams in Action, Second Edition explains KStream →
Apache Kafka in Action
A KStream is a Kafka Streams abstraction representing an unbounded stream of records, where each record is treated as an independent event.
- How it is used
- Uses KStreams to process topic records as events before joining current state or detecting patterns in incoming activity.
- How deep it goes
- Shows topic creation and worked grouping, aggregation, joins, and windowing; stops short of KStream implementation internals.
- Examples
- Demonstrates device-targeted notifications and one-minute counts of authentication attempts.
- What you can do after
- Build it from scratch with Kafka Streams to read topic events, aggregate by key, join state, and publish filtered results.
Kafka for Architects
KStream is the Kafka Streams abstraction representing a continuous stream of records and their transformations.
- How it is used
- Uses continuous Kafka event flows as inputs and outputs for transformations, filtering, mapping, and downstream processing.
- How deep it goes
- Defines the stream abstraction and DSL role, but stops short of low-level consumer, producer, offset, and partition management.
- Examples
- Demonstrates an order stream that filters totals, maps values, and writes processed records to another topic.
- What you can do after
- Apply Kafka Streams to declare a small event-processing topology without manually creating producers and consumers.
Related concepts
- data streamkind of · A data stream is an ordered sequence of data items or events made available incrementally for consumption or processing.
- KTablecontrasts with · KTable is a Kafka Streams abstraction representing the latest value associated with each key as a continuously updated table.
- Kafka Streamsused by · Kafka Streams is a client library for building applications that continuously process data from and write data to Apache Kafka topics.
- windowingused by · Windowing is the division of data or events into bounded subsets, often based on time or other constraints, for separate processing and result association.
- GlobalKTableused by · GlobalKTable is a Kafka Streams abstraction that replicates all records from an underlying topic to every application instance for read-only access.
- sink nodeused by · A sink node is a terminal or receiving component in a data or flow system that accepts incoming data, messages, or flow for consumption, processing, or storage.
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