Status

Current state: Accepted

Discussion thread: https://lists.apache.org/thread/vdp8scrrzdq7ofvl0mm84dhphq8kmzgc

Vote threadhttps://lists.apache.org/thread/5280h24g205vn69dxr44lc15dt3ncrvz

JIRA: KAFKA-967 - Getting issue details... STATUS

Motivation

In production, producers commonly send keyed records to leverage semantic partitioning for ordering guarantees, stream joins, and cross-cluster replication. However, kafka-producer-perf-test always produces records with null keys, making benchmark results systematically optimistic and unable to reflect the performance characteristics of real keyed workloads. Additionally, since log compaction requires non-null keys, the tool currently cannot benchmark compacted topics at all. Adding key support removes this limitation.

This proposal adds key distribution support to kafka-producer-perf-test, allowing engineers to benchmark keyed workloads with configurable key ranges and distribution strategies.

The three distribution modes cover the most common real-world keyed workload patterns:

  • 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:

--key-distribution <none|range|random> (optional, default: none)

Controls how record keys are assigned:

  • none — null key (current behavior, default)
  • range — keys cycle through integers 0, 1, ..., KEY-RANGE-1 in round-robin order
  • random — each record gets a randomly selected integer from [0, KEY-RANGE)

--record-key-range <KEY-RANGE> (optional, required when --key-distribution is range or random)

Defines the size of the key space. Must be a positive integer.

--random-seed <seed> (optional, default 0)

Controls the seed for the pseudo-random number generator used by --key-distribution random and random payload generation. The default value of 0 ensures deterministic, reproducible benchmark runs. Set to a different value when non-repeating sequences are required.

Proposed Changes

New Enum: KeyDistribution

public enum KeyDistribution {
  NONE, RANGE, RANDOM
}

Generate key

Keys are serialized as their decimal string representation encoded in UTF-8, consistent with the ByteArraySerializer already configured for the producer. This keeps keys human-readable in tools like kafka-console-consumer.

DistributionKey value
NONEnull
RANGEInteger.toString(recordIndex % keyRange)  
RANDOM
Integer.toString(random.nextInt(keyRange))

Performance note: The random distribution reuses a single SplittableRandom instance that is already constructed for payload generation. SplittableRandom.nextInt() is a lightweight, non-thread-safe PRNG with no allocation overhead, so key generation adds negligible latency to the hot path.

Validation

ConfigPostProcessor enforces mutual consistency between the two new arguments:

ConditionError
--key-distribution range or random without --record-key-range--record-key-range is required when --key-distribution is 'range' or 'random'.
--record-key-range specified with --key-distribution none--key-distribution must be 'range' or 'random' when --record-key-range is specified.
--record-key-range ≤ 0--record-key-range should be greater than zero.

Example Usage

  • Null keys — existing behavior (default)
    bin/kafka-producer-perf-test.sh \
      --topic my-topic --num-records 1000000 --record-size 1024 \
      --throughput -1 --bootstrap-server localhost:9092
  • Round-robin across 100 distinct keys
    bin/kafka-producer-perf-test.sh \
      --topic my-topic --num-records 1000000 --record-size 1024 \
      --throughput -1 --bootstrap-server localhost:9092 \
      --key-distribution range --record-key-range 100
  • Random keys from a space of 10,000
    bin/kafka-producer-perf-test.sh \
      --topic my-topic --num-records 1000000 --record-size 1024 \
      --throughput -1 --bootstrap-server localhost:9092 \
      --key-distribution random --record-key-range 10000

Compatibility, Deprecation, and Migration Plan

The default value of --key-distribution is none, which preserves the current behavior of sending null-key records. Existing scripts and benchmarks continue to work without modification.

Test Plan

All remaining tests should pass, and new unit test.

Rejected Alternatives

UUID keys for random distribution

An alternative design would use UUID.randomUUID().toString()  as the key for the random distribution, providing globally unique keys with no repeated values across the entire benchmark run.

This was rejected for two reasons:

  1. Unbounded key space defeats the purpose. The primary use case for random keys is to benchmark workloads with a known, bounded key space (e.g., 10,000 customer IDs). UUID keys give every record a unique key, making partition distribution identical to round-robin and eliminating the ability to model hot-key or skewed-partition scenarios.
  2. Performance overhead. UUID.randomUUID()  uses SecureRandom internally, which is significantly slower than SplittableRandom.nextInt()  and could become a bottleneck in high-throughput benchmarks — the opposite of what a perf tool should do.

Engineers who genuinely need globally unique keys can use --key-distribution random --record-key-range <large-number> (e.g., 2^31−1) to approximate the same effect without the overhead.

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8 Comments

  1. ViquarKhan

    Please update KIP no 1299 already have KIP -KIP-1317:Mandatory DLQ Disposition Header for Share Groups

  2. Ken Huang

    You didn’t follow the guideline to update the KIP number, so I won’t change it.

  3. ViquarKhan

    Please check creation date else bring separate thread for discussion 

    1. Unknown User (chia7712)

      hi Vaquar

      Thanks for submitting these recent KIPs! I noticed that the KIP numbers aren't updated sequentially, which is causing a few conflicts on the wiki.

      Just wanted to check if you have any strict restrictions on using those specific numbers (e.g., for an internal dashboard)? If not, we normally just pick the number from "Next KIP Number" rather than the creation date.

      thanks.


      1. ViquarKhan

        I've created this on March 14th when 1298 and 1299 were the latest numbers. Unfortunately, I've been out sick and couldn't provide updates until now, and I see there are two new KIPs as of today . each new KIP author should check if existing KIP with same no exist  , we have already running 1300 + series . 


        I have both KIP 1298 and 1299 in draft so i will change my no to avoid conflict and confusion.

  4. PoAn Yang

    ViquarKhan You put KIP in wrong directory. Please move it to Kafka Improvement Proposals.

  5. ViquarKhan

    Thanks Yang , accepted wrong directory and let me change my KIP no as its still move  in discussion later .

  6. ViquarKhan

    No action required i have updated my KIP