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From Tom Brown <tombrow...@gmail.com>
Subject Re: More partitions => less throughput?
Date Sat, 30 Nov 2019 16:57:10 GMT
I think the number of partitions needs to be tuned to the size of the
cluster; 64 partitions on what is essentially a single box seems high. Do
you know what hardware you will be deploying on in production? Can you run
your benchmark on that instead of a vm?


On Thursday, November 28, 2019, Craig Pastro <siyopao@gmail.com> wrote:

> Hello there,
> I was wondering if anyone here could help me with some insight into a
> conundrum that I am facing.
> Basically, the story is that I am running three Kafka brokers via docker on
> a single vm with log.flush.interval.messages = 1 and min.insync.replicas =
> 2. Then I create two topics: both with replication factor = 3, but one with
> one partition and the other with 64.
> Then I try to run a benchmark using these topics and what I find is as
> follows:
> 1 partition, 1381.02 records/sec,  685.87 ms average latency
> 64 partitions, 601.00 records/sec, 1298.18 ms average latency
> This is the opposite of what I expected. In neither case am I even close to
> the IOPS of what the disk can handle. So what I would like to know is if
> there is any obvious reason that I am missing for the slow down with more
> partitions?
> If it is helpful the docker-compose file and the code to do the
> benchmarking can be found at https://github.com/siyopao/kafka-benchmark.
> (Any comments or advice on how to make the code better are greatly
> appreciated!) The benchmarking code is inspired by and very similar to what
> the bin/kafka-producer-perf-test.sh script does.
> Thank you!
> Best wishes,
> Craig

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