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From Craig Pastro <siyo...@gmail.com>
Subject Re: More partitions => less throughput?
Date Mon, 02 Dec 2019 00:42:16 GMT
Dear Tom, Peter and Eric,

Thank you very much for your answers!

What I think is that I need to play around with more configurations.
Actually I had not thought that 64 partitions on a single box was very
large. Thank you!

I had thought that when I set log.flush.interval.message = 1, that I could
send a lot of records to the brokers and have the throughput determined by
the IOPS of the disk, but this was not the case at all. Nor CPU, nor
memory, nor network it seems. So I am wondering what is throttling the
throughput...? In any case, I'll create some new environments and play
around a bit more.

Thank you!

Best wishes,
Craig





On Sun, Dec 1, 2019 at 2:53 AM Eric Owhadi <eric.owhadi@esgyn.com> wrote:

> What is happening imho is that when you have multiple partitions, each
> consumer will fetch data from its partition and find only 1/64th the amount
> of data (compared to the single partition case) to send every time it is
> its turn to send stuff. Therefore you end up having a more chatty
> situation, where each push to broker carry too small number of messages,
> compared to the single partition case that optimize can perform the same
> function but each set of message send to broker contains higher message
> count.
> Eric
>
> -----Original Message-----
> From: Craig Pastro <siyopao@gmail.com>
> Sent: Thursday, November 28, 2019 9:10 PM
> To: users@kafka.apache.org
> Subject: More partitions => less throughput?
>
> External
>
> 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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