Streaming table
A streaming table is a continuously updated relation that retains the latest value associated with each key in a data stream.
Apache Kafka in Action
A stream processing table is a continuously updated key-value representation of current state derived from records in a stream.
- How it is used
- Provides queryable current state alongside real-time stream processing, avoiding external database queries for state held in the application.
- How deep it goes
- Explains key-value structure, topic replay, partitioning, local state, changelog recovery, aggregations, and joins.
- Examples
- Uses product state, account transaction totals, count aggregations, topic compaction, and stream-table joins as concrete examples.
- What you can do after
- Apply it via Kafka Streams or Flink to derive, query, aggregate, join, and recover current state from topics.
Kafka for Architects
A stream-processing table is a view that retains the latest value associated with each key rather than treating every update as an independent event.
- How it is used
- Supports stream-table joins by retaining the latest customer value for lookups triggered by incoming orders.
- How deep it goes
- Explains latest-value semantics, lookup triggers, non-reprocessing, copartitioning, and GlobalKTable, while deferring advanced join types.
- Examples
- Uses customer data joined with orders, contrasted with payment and order stream-to-stream joins.
- What you can do after
- Apply it via Kafka Streams to look up customer data for incoming orders with aligned keys and partitions.
Related concepts
- KTableincludes · KTable is a Kafka Streams abstraction representing the latest value associated with each key as a continuously updated table.
- key-value storekind of · A key-value store is a data-storage system that associates keys with values and supports storing, retrieving, or updating values by key.
- database tablecontrasts with · A database table is a relational database structure that organizes records into rows and defined columns.
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