Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/4998#issuecomment-78893597
I think the difference is that Hadoop profiles build Spark for different,
but fixed, deployment contexts. This is trying to accommodate two different
types of _user_ app. This build of Spark won't run apps that "normal" builds
will, and vice versa (right?). This is why I don't think a build profile helps
people solve this problem (without creating a bigger one).
I'd really hope there's a flavor of log4j that supports old and new code
and config; that would be much more ideal. Or, another answer is just that you
can't use log4j 2 with Spark and need to use slf4j.
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