I also tried different settings for *yarn.per-job-cluster.include-user-jar* and *classloader.resolve-order* But none of them worked.
Leon On Wed, Nov 30, 2022 at 11:17 PM Leon Xu <[email protected]> wrote: > Hi Biao, > > Thanks for getting back to me. > Here's the command I used: > > /usr/bin/flink run-application -t yarn-application \ > -Dtaskmanager.numberOfTaskSlots=1 \ > -Djobmanager.memory.process.size=4096m \ > -Dtaskmanager.memory.process.size=4096m \ > -Dyarn.application.name=backup-enriched-events-r0 \ > -c com.xyz.source.SourceDataStream \ > /tmp/lib-event-platform-core-7c7cc8ca9fc.jar \ > --datastreamName=backup-enriched-events-r0 --environment=dev > > And with the following configuration in flink config: > yarn.per-job-cluster.include-user-jar: FIRST > classloader.resolve-order: parent-first > > Thanks > Leon > > > On Wed, Nov 30, 2022 at 10:14 PM Biao Geng <[email protected]> wrote: > >> Hi Leon, >> >> Can you share your full command for submission? >> >> >> Best, >> Biao Geng >> >> Leon Xu <[email protected]> 于2022年12月1日周四 06:27写道： >> >>> Hi Flink Users, >>> >>> We ran into java.lang.ClassCastException after moving the flink job from >>> session mode to application mode. >>> >>> >>> *java.lang.ClassCastException: class [B cannot be cast to class >>> java.lang.String ([B and java.lang.String are in module java.base of loader >>> 'bootstrap') at >>> com.xyz.common.io.sink.HivePartitionedBucketAssigner.getBucketId(HivePartitionedBucketAssigner.java:35)* >>> >>> Here *HivePartitionedBucketAssigner* is a template class: >>> class HivePartitionedBucketAssigner<T> implements BucketAssigner<T, >>> String> >>> >>> >>> We tried disabling the invert class loading based on this doc >>> <https://nightlies.apache.org/flink/flink-docs-master/docs/ops/debugging/debugging_classloading/#x-cannot-be-cast-to-x-exceptions>but >>> it didn't help. In session-mode it works fine. So I wonder what's different >>> between session-mode and application mode in terms of class loading? And >>> what would be a solution for this situation? >>> Our setup: >>> 1. Flink version: 1.12.7 >>> 2. Java: JDK 11 >>> >>> >>> Thanks >>> Leon >>> >>
