Github user mridulm commented on the issue:
https://github.com/apache/spark/pull/15422
@zsxwing You are right, NewHadoopRDD is not handling this case.
Probably would be good to add exception handling there when nextKeyValue
throws exception ?
Context is, for large jobs/data, it is not unexpected to see some data
corruption at times. We dont want to throw out the entire job due to a few bad
records.
For example, in MR you have the ability to even set the percentage of bad
records you want to tolerate (we dont have that in spark).
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