Github user mridulm commented on the pull request:
https://github.com/apache/spark/pull/148#issuecomment-37748592
But that would be to debug yarn/hadoop api's primarily - and no easy way to
inject spark specific logging levels. I am curious why this was required
actually.
Currently, we have fairly fine grained control over logging from various
packages/classes by redirecting logging output to stdout/stderr - which is
actually quite heavily used (mute most of spark, enable user code; enable
specific parts of spark for debug, etc) in user applications.
Having said that, @tgravescs did the initial logging integration in yarn,
so will defer to him though.
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