Looks like this response did go to the list.
As far as OffsetOutOfRange goes, right now that's an unrecoverable error,
because it breaks the underlying invariants (e.g. that the number of
messages in a partition is deterministic once the RDD is defined)
If you want to do some hacking for your own
Hey Cody, I would have responded to the mailing list but it looks like this
thread got aged off. I have the problem where one of my topics dumps more
data than my spark job can keep up with. We limit the input rate with
maxRatePerPartition Eventually, when the data is aged off, I get the
OffsetOutO
