Hi,
In general, we recommend one StreamThread per core, so 48 threads sounds
excessive; I don't think that a single pod would get 48 cores? So using
more pods with fewer threads each, might be a first good step.
The only config that sticks out is
> - max.poll.records = 1
Not sure why you reduce it to 1. This should reduce the throughput a
single thread can achieve. Why does the default not work for you?
However, in the end, the first thing you need to figure out it, why
rebalancing starts. Are heartbeats getting lost? Do instances hit
`max.poll.interval.ms`? -- If threads get more busy with increasing
load, I could imagine that you run into thread contention, destabilizing
the system.
Next, you should inspect metrics to get a idea how the system performs.
What metrics increase/decrease while you increase throughput, and at
what point it starts to fail over.
Both together should give you a starting point to understand what the
issue could be, and what the appropriate change (more KS instance, fewer
threads, more memory, config change) should help.
-Matthias
On 1/9/25 7:30 PM, Martinus Elvin wrote:
Hello,
We have a kafka streams service that performs a left join (KStreams)
operation by their message key. The message size is 1 KB more or less.
The left topic has around two hundred thousand (200,000) messages per
second, while the right topic has around two thousand (2000) message per
second.
Each topic has 96 partitions with 3 hours retention time.
The join operation has 15 minutes time window.
We have a very concerning problem that the consumer keep getting
rebalancing after some time and the consumer lag can accumulate to 200
millions or more.
We have doing a lot of tuning and test on our service but the problem
still persist. The consumer start rebalancing when we have 100,000 tps
or more.
Below are the latest configuration we use:
- auto.offset.reset = latest
- session.timeout.ms = 300000
- heartbeat.interval.ms = 75000
- fetch.max.wait.ms = 500
- fetch.min.bytes = 1048576
- fetch.max.bytes = 52428800
- max.partition.fetch.bytes = 1048576
- max.poll.interval.ms = 300000
- max.poll.records = 1
- request.timeout.ms = 120000
- default.api.timeout.ms = 60000
- cache.max.bytes.buffering = 104857600
- num.stream.threads = 48 (each pod)
Below are some info regarding kafka cluster we are using:
- 10 brokers (8 core 2.3GHz, 16GB RAM)
- kafka version = 3.8.0
- kafka-streams library = 3.1.2
The service running in a dockerized container with 2 pods (we have tried
up to 4 pods too).
Could someone provide inside or solutions so we can have a stable and
fast consumer to handle this kind of messages?
Thank you!
Martinus Elvin
