Hi,
I am now in the process of deciding partitions and replicas for my cluster.
I am making use of perf test utilities and it really helps a lot.
Just measure perf by creating multiple topics with same number of recodrs
with diff partitions and replicas.
Then compare the througput and also look at
Thanks, it helps a lot.
Peter Bukowinski 于2020年2月28日周五 上午5:18写道:
> No, it’s not bad. Kafka is designed to serve data to many consumers at the
> same time, whether they are independent of each other or in the same
> consumer group.
>
> I would encourage you to play with different partition
Hi All,
Sorry to bother you all.
It was simple.
Just put one line in required .sh file
export JMX_PORT=
and it will run
thanks,
Sunil.
From: Sunil CHAUDHARI
Sent: Friday, February 28, 2020 10:06 AM
To: users@kafka.apache.org
Subject: HELP in Usage of JMX port in Kafka
Hi all,
I have used
Hi all,
I have used JMX_PORT 9099 in environment variable and started Kafka.
There is not problem till now. I can see metrics on kafka-manager console. This
is fine.
However when I run kafka-consumer-perf-test.sh and kafka-producer-perf-test.sh
and similar utility under /bin then I get error
No, it’s not bad. Kafka is designed to serve data to many consumers at the same
time, whether they are independent of each other or in the same consumer group.
I would encourage you to play with different partition counts and use kafka’s
performance testing tools (kafka-producer-perf-test.sh
Hey Carl, that's what my team has done for our internal tooling, and I
designed MirrorClient with that in mind. Given a single mm2.properties file
you can create MirrorClients for each cluster and those in turn give you
Admin/Consumer/Producer clients if you need them. Our internal tooling
All:
I was tinkering around with the MirrorClient and was curious about the
configs. I see that I can use the MirrorMaker config to pull in the same
configs that were used to spin up the MM2 cluster. Seeing as MM2 is started
with these configs in a property file and it is passed in on command
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Hi,
If there is an operation downstream that needs key co-location (e.g.
aggregation), stream.transformValues(/*return null for values that
don't need to be
forwarded downstream*/).filter((k,v) -> return v !=null) would be more
efficient, because for the stream.transform(/*return null for records
I believe no matter the partition count exceeds the broker count, we can
always have the same number of consumer instances as the partition count.
So what I want to know is when two partition exists on the same broker, two
consumer instances will be talking to same broker, is that bad ?
张祥
Hi,
Yes I get that when I am using the apis provided by kstream I can basically
use both:
- Tumbling time window (non-overlapping, gap-less windows)
- Hopping time window (Time-based Fixed-size, overlapping windows)
I wanted to know if I am using state store directly when created using a
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