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An increasingly important system requirement for distributed stream processing applications is to provide strong correctness guarantees under unexpected failures and out-of-order data so that its results can be authoritative (not needing complementary batch results).
Kafka Streams, a scalable stream processing client library in Apache Kafka, defines the processing logic as read-process-write cycles in which all processing state updates and result outputs are captured as log appends.
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