WellŠ not to be contrarian, but latency depends much more on the latency between the producer and the broker that is the leader for the partition you are publishing to. At least when your brokers are not saturated with messages, and acks are set to 1. If acks are set to ALL, latency on an non-saturated kafka cluster will be: Round Trip Latency from producer to leader for partition + Max( slowest Round Trip Latency to a replicas of that partition). If a cluster is saturated with messages, we have to assume that all partitions receive an equal distribution of messages to avoid linear algebra and queueing theory models. I don¹t like linear algebra :P
Since you are probably putting all your latencies into a single histogram per producer, or worse, just an average, this pattern would have been obscured. Obligatory lecture about measuring latency by Gil Tene (https://www.youtube.com/watch?v=9MKY4KypBzg). To verify this hypothesis, you should re-write the benchmark to plot the latencies for each write to a partition for each producer into a histogram. (HRD histogram is pretty good for that). This would give you producers*partitions histograms, which might be unwieldy for that many producers. But wait, there is hope! To verify that this hypothesis holds, you just have to see that there is a significant difference between different partitions on a SINGLE producing client. So, pick one producing client at random and use the data from that. The easy way to do that is just plot all the partition latency histograms on top of each other in the same plot, that way you have a pretty plot to show people. If you don¹t want to setup plotting, you can just compare the medians (50¹th percentile) of the partitions¹ histograms. If there is a lot of variance, your latency anomaly is explained by brokers 4-7 being slower than nodes 0-3! If there isn¹t a lot of variance at 50%, look at higher percentiles. And if higher percentiles for all the partitions look the same, this hypothesis is disproved. If you want to make a general statement about latency of writing to kafka, you can merge all the histograms into a single histogram and plot that. To Yuheng¹s credit, more brokers always results in more throughput. But throughput and latency are two different creatures. Its worth noting that kafka is designed to be high throughput first and low latency second. And it does a really good job at both. Disclaimer: I might not like linear algebra, but I do like statistics. Let me know if there are topics that need more explanation above that aren¹t covered by Gil¹s lecture. -Erik On 9/4/15, 9:03 AM, "Yuheng Du" <yuheng.du.h...@gmail.com> wrote: >When I using 32 partitions, the 4 brokers latency becomes larger than the >8 >brokers latency. > >So is it always true that using more brokers can give less latency when >the >number of partitions is at least the size of the brokers? > >Thanks. > >On Thu, Sep 3, 2015 at 10:45 PM, Yuheng Du <yuheng.du.h...@gmail.com> >wrote: > >> I am running a producer latency test. When using 92 producers in 92 >> physical node publishing to 4 brokers, the latency is slightly lower >>than >> using 8 brokers, I am using 8 partitions for the topic. >> >> I have rerun the test and it gives me the same result, the 4 brokers >> scenario still has lower latency than the 8 brokers scenarios. >> >> It is weird because I tested 1broker, 2 brokers, 4 brokers, 8 brokers, >>16 >> brokers and 32 brokers. For the rest of the case the latency decreases >>as >> the number of brokers increase. >> >> 4 brokers/8 brokers is the only pair that doesn't satisfy this rule. >>What >> could be the cause? >> >> I am using a 200 bytes message, the test let each producer publishes >>500k >> messages to a given topic. Every test run when I change the number of >> brokers, I use a new topic. >> >> Thanks for any advices. >>
