Hi Jamie,
Thanks for the hint. I played with these parameters, and found only linger.ms
is playing a significant role for my test case.
It is very sensitive and highly non linear.
I get these results:
Linger.ms message per second
80 100
84 205
85 215
Hello All,
Any inputs?
Thanks
On Tue, Oct 1, 2019 at 12:40 PM Navneeth Krishnan
wrote:
> Hi All,
>
> I found the below example on how branching can be achieved with kafka
> streams. I want to implement the same with processor API and the way I get
> it is to have the same input topic
I am planning to have a producer writing payment messages to a Kafka
topic. One attribute of the messages would be process date, which could be
in the future, i.e. the payment is not to be sent for collection until this
date.
How can I configure Kafka so that a stream will only contain the
Hi Eric,
I found increasing the linger.ms to between 50-100 ms significantly increases
performance (fewer larger requests instead of many small ones), I'd also
increase the batch size and the buffer.memory.
Thanks,
Jamie
-Original Message-
From: Eric Owhadi
To:
Hi All,
I'm doing smoke testing with my Kafka Streams app(V2.1.0). I noticed
that below behaviors:
1) Out throughput of changelog topic could go up to 70mb/s while the
in-traffic is around 10mb/s.
2) When traffic is bumpy, either due to producer/consumer throttle or
some other reasons I'm still
Hi Kafka users,
I am new to Kafka and am struggling with getting acceptable producing rate.
I am using a cluster of 2 nodes, 40 CPU cores/ 80 if counting hyperthreading.
256GB memory on a 10Gbit network
Kafka is installed as part of cloudera parcel, with 5GB java heap.
Producer version: Kafka