Hi,
I am using flink cdc to stream CDC changes in an iceberg table. When I first run the flink job for a topic which has all the data for a table, it get out of heap memory as flink try to load all the data during my 15mins checkpointing interval. Right now, only solution I have is to pass -ytm 8192 -yjm 2048m for a table with 10M rows and then reduce it after flink has consumed all the data. Is there a way to tell flink cdc code to trigger checkpoint or throttle the consumption speed(I think backpressure should have handled this)?
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Hi Ayush, Which state backend have you configured [1]? Have you considered trying out RocksDB [2]? RocksDB might help with persisting at least keyed state. Best, Matthias On Thu, Apr 22, 2021 at 7:52 AM Ayush Chauhan <[hidden email]> wrote:
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Hi Matthias, I am using RocksDB as a state backend. I think the iceberg sink is not able to propagate back pressure to the source which is resulting in OOM for my CDC pipeline. Please refer to this - https://github.com/apache/iceberg/issues/2504 On Thu, Apr 22, 2021 at 8:44 PM Matthias Pohl <[hidden email]> wrote:
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Got it. Thanks for clarifying. On Fri, Apr 23, 2021 at 6:36 AM Ayush Chauhan <[hidden email]> wrote:
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