Github user pwendell commented on the pull request:
https://github.com/apache/spark/pull/194#issuecomment-38392478
I looked at this a bit more closely. I'm definitely +1 on having some
utility functions like this for writing to HBase.
It seems a bit brittle to me that we expect people to go through a textual
representation of the records in order to save to HBase. I think a nicer way to
do this would be to go through a SchemaRDD (which is a new feature recently
merged into Spark) or even a Scala case class or Scala tuples. And then have an
automatic conversion into HBase types based on the runtime type of the RDD. And
you'd just need to give a mapping of the attribute names to the hbase column
names (/cc @marmbrust).
This approach here seems a little bit more ad-hoc and like something we may
not want to support for a long time going forward. So it might make sense to
slot this for Spark 1.1 and re-work it to have more integrated support for
schemas.
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