Flink job cant use savepoint in a batch job - scala

Question

Let me start in a generic fashion to see if I somehow missed some concepts: I have a streaming flink job from which I created a savepoint. Simplified version of this job looks like this
Pseduo-Code:
val flink = StreamExecutionEnvironment.getExecutionEnvironment
val stream = if (batchMode) {
flink.readFile(path)
}
else {
flink.addKafkaSource(topicName)
}
stream.keyBy(key)
stream.process(new ProcessorWithKeyedState())
CassandraSink.addSink(stream)
This works fine as long as I run the job without a savepoint. If I start the job from a savepoint I get an exception which looks like this
Caused by: java.lang.UnsupportedOperationException: Checkpoints are not supported in a single key state backend
at org.apache.flink.streaming.api.operators.sorted.state.NonCheckpointingStorageAccess.resolveCheckpoint(NonCheckpointingStorageAccess.java:43)
at org.apache.flink.runtime.checkpoint.CheckpointCoordinator.restoreSavepoint(CheckpointCoordinator.java:1623)
at org.apache.flink.runtime.scheduler.SchedulerBase.tryRestoreExecutionGraphFromSavepoint(SchedulerBase.java:362)
at org.apache.flink.runtime.scheduler.SchedulerBase.createAndRestoreExecutionGraph(SchedulerBase.java:292)
at org.apache.flink.runtime.scheduler.SchedulerBase.<init>(SchedulerBase.java:249)
I could work around this if I set the option:
execution.batch-state-backend.enabled: false
but this eventually results in another error:
Caused by: java.lang.IllegalArgumentException: The fraction of memory to allocate should not be 0. Please make sure that all types of managed memory consumers contained in the job are configured with a non-negative weight via `taskmanager.memory.managed.consumer-weights`.
at org.apache.flink.util.Preconditions.checkArgument(Preconditions.java:160)
at org.apache.flink.runtime.memory.MemoryManager.validateFraction(MemoryManager.java:673)
at org.apache.flink.runtime.memory.MemoryManager.computeMemorySize(MemoryManager.java:653)
at org.apache.flink.runtime.memory.MemoryManager.getSharedMemoryResourceForManagedMemory(MemoryManager.java:526)
Of course I tried to set the config key taskmanager.memory.managed.consumer-weights (used DATAPROC:70,PYTHON:30) but this doesn't seems to have any effects.
So I wonder if I have a conceptual error and can't reuse savepoints from a streaming job in a batch job or if I simply have a problem in my configuration. Any hints?

Answer 1

After a hint from the flink user-group it turned out that it is NOT possible to reuse a savepoint from the streaming job (https://ci.apache.org/projects/flink/flink-docs-master/docs/dev/datastream/execution_mode/#state-backends--state). So instead of running the job as in batch-mode (flink.setRuntimeMode(RuntimeExecutionMode.BATCH)) I just run it in the default execution mode (STREAMING). This has the minor downside that it will run forever and have to be stopped by someone once all data was processed.