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• none — establishes a null-key baseline for topics where ordering and co-partitioning are not required, such as log aggregation pipelines.
• range — models workloads where a bounded, predictable set of keys cycles repeatedly, such as Kafka Streams joins or MirrorMaker 2 replication, where the same key must consistently land on the same partition to preserve ordering guarantees.
• random — models workloads with a bounded but unpredictably distributed key space, where keys arrive in non-deterministic order rather than cycling sequentially. A large range (e.g., 1,000,000) approximates unique-key workloads such as IoT device data without the overhead of UUID generation.

Note: that both range and random produce a uniform key distribution. Skewed distributions are out of scope for this proposal and may be addressed in a future KIP.

Public Interfaces

This proposal adds two new command-line arguments to kafka-producer-perf-test:

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