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Posted to issues@spark.apache.org by "Seth Hendrickson (JIRA)" <ji...@apache.org> on 2016/11/03 15:06:58 UTC
[jira] [Created] (SPARK-18253) ML Instrumentation logging requires
too much manual implementation
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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