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Join semantics are inspired by SQL join semantics, however, because Kafka Streams offers stream instead of batch processing, semantics do no align completely. In the following, we give a details explanation of the offered join semantics in Kafka Streams.

Below, we describe the semantic semantics of each operator on two input streams/tables. We assume that all messages do have the same key in this these examples and thus omit the key to improve readability. For window joins, we assume that all records belong to a single window. Nevertheless, time (and processing order) is an important factor in stream-joins and thus we also show the timestamp for each record and assume that all records are processed in timestamp order. The format below will be ts:value for each record and null indicates a missing value.

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