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From "Seth Hendrickson (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-18253) ML Instrumentation logging requires too much manual implementation
Date Thu, 03 Nov 2016 15:06:58 GMT
Seth Hendrickson created SPARK-18253:
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             Summary: ML Instrumentation logging requires too much manual implementation
                 Key: SPARK-18253
                 URL: https://issues.apache.org/jira/browse/SPARK-18253
             Project: Spark
          Issue Type: Improvement
          Components: ML
            Reporter: Seth Hendrickson
            Priority: Minor


[SPARK-14567|https://issues.apache.org/jira/browse/SPARK-14567] introduced an {{Instrumentation}}
class for standardized logging of ML training sessions. Right now, we manually log individual
params for each algorithm, partly because we don't want to log all params since some params
can be huge in size, and we could flood the logs. We should find a more sustainable way of
logging params in ML algos. The current approach does not seem sustainable.



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