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EventHub timeouts leads to Kafka producer clients getting stuck and always failing with InvalidPidMappingException
(with default enable.idempotence=true
)
#261
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Ah, seems like KIP-588 is relevant. It doesn't seem to be resolved, but does have a couple changes related to it. It's still a mystery to me why we're only seeing this for EventHub when it's likely we're also seeing timeouts on other clients but without thel asting impact. |
We're hitting this issue as well, and not having transactions enabled. |
We were advised that our retries/timeouts were simply too low and our options were to either increase closer to the defaults (which I believe were simply unacceptably high for our use-case) or set |
(and to be clear this is about having idempotence enabled which does some internal ID management, hence my earlier mention of transactions, rather than the public facing transactional commits feature of Kafka) |
Yea we have added the recommended configs as well, and will have to wait and see if we hit it again. But we also aren't using transactions, so it seems weird to me that we would ever get this error. We don't set the so my thinking is we shouldn't even get this... odd |
I'm reporting this as I've hit this a number of times and while I've worked around it, I'm filing this for two reasons:
I have a relatively low set of timeouts configured provided specific requirements on some topics, with the following Kafka producer client configuration:
In several situations (e.g. EventHub server restarts due to upgrades, excess consumer load hammering EventHub), we've observed that after we have any timeouts the Kafka producer client will get stuck and always fail with the following error:
The Kafka client in this situation will not self-recover, even if EventHub has recovered. Recovery is manual, through re-initialize the Kafka producer client. Of course, this only occurs with the default Kafka setting of
enable.idempotence=true
which introduces client transaction IDs. I've found this easy to reproduce by inducing a high load on EventHub such as having an amplified Kafka consumption rate, say a consumer deployed 100s of times or a Spark streaming job with many tasks.The text was updated successfully, but these errors were encountered: