Hello chia, Thanks for the feedback. I have updated the KIP.
Best Regards, Jiunn-Yang > Chia-Ping Tsai <[email protected]> 於 2026年5月26日 晚上11:42 寫道： > > hi Jiunn-Yang > > Thanks for the KIP. It looks like this proposal enables testing on compacted > topics. If so, would you mind updating the Motivation section to include this? > > Best, > Chia-Ping > > On 2026/05/26 11:46:16 黃竣陽 wrote: >> Hello PoAn, >> >> Thanks for the feedback >> >> poan_00: In range mode, keys are generated by `recordIndex % keyRange`, >> which is fully deterministic and not affected by `--random-seed`. The seed >> only controls >> the PRNG used for random payload generation in that case. The example is >> misleading, >> I will remove it. >> >> poan_01: According to the JDK documentation, `SplittableRandom` generates >> uniformly >> distributed pseudorandom values. With a sufficiently large number of >> records, each key >> in random mode appears roughly the same number of times, so the partition >> distribution s >> tatistically converges toward behavior similar to range mode. >> >> The main difference is that random mode introduces short-term burstiness, >> where the same >> key may appear consecutively for a period of time, while range mode produces >> a perfectly >> even round-robin pattern. However, neither mode inherently creates a truly >> skewed (hot-partition) >> distribution. >> >> I’ll update the motivation section to remove the hot-partition claim for >> random mode. >> >> Best Regards, >> Jiunn-Yang >> >>> PoAn Yang <[email protected]> 於 2026年5月26日 晚上7:18 寫道： >>> >>> Hi Jiunn, >>> >>> Thanks for the KIP. >>> >>> poan_00: In example usage, there is a case use --key-distribution range >>> with --random-seed. >>> In this case, does the --random-seed parameter take effect? If not, can we >>> remove it? >>> >>> poan_01: In motivation, one use case of random distribution is >>> hot-partition scenario. >>> However, in JDK document, the SplittableRandom is a generator of uniform >>> pseudorandom values [0]. >>> If hot-partition scenario is just because small key range, can we do it >>> with range key distribution directly? >>> >>> https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/SplittableRandom.html >>> >>> Best, >>> PoAn >>> >>>> On May 20, 2026, at 8:56 PM, 黃竣陽 <[email protected]> wrote: >>>> >>>> Hi chia, >>>> >>>> Thanks for the feedback, >>>> >>>> chia_00: I have added a new optional argument --random-seed <SEED> >>>> (default: 0) >>>> to let users set the seed manually. The default value of 0 ensures >>>> deterministic, reproducible >>>> benchmark runs by default. >>>> >>>> chia_01: I have updated the Motivation section in the KIP to elaborate on >>>> the practical >>>> use cases for each key distribution mode. >>>> >>>> Best Regards, >>>> Jiunn-Yang >>>> >>>>> Chia-Ping Tsai <[email protected]> 於 2026年5月20日 上午11:48 寫道： >>>>> >>>>> hi Jiunn >>>>> >>>>> thanks for this KIP! >>>>> >>>>> chia_00: Regarding the random seed, what are your thoughts on its >>>>> initialization? >>>>> >>>>> chia_01: Could you elaborate on the practical use cases for each key >>>>> distribution mode in the Motivation section? >>>>> >>>>> Best,Chia-Ping >>>>> >>>>> On 2026/03/30 13:06:05 黃竣陽 wrote: >>>>>> Hello everyone, >>>>>> >>>>>> I would like to start a discussion on KIP-1299 Use key range in >>>>>> ProducerPerformance >>>>>> <https://cwiki.apache.org/confluence/x/XpQ8G> >>>>>> >>>>>> This proposal aims to add configurable key distribution support to >>>>>> kafka-producer-perf-test. >>>>>> Currently, the tool always produces records with null keys, which does >>>>>> not reflect real-world >>>>>> keyed workloads. This KIP introduces two new arguments — >>>>>> --key-distribution and --message-key-range >>>>>> — enabling engineers to benchmark with round-robin or random key >>>>>> strategies over a bounded >>>>>> key space, providing more realistic performance measurements. >>>>>> >>>>>> Best regards, >>>>>> Jiunn-Yang >>>> >>> >> >>
