[jira] [Commented] (SPARK-23859) Initial PR for Instrumentation improvements: UUID and logging levels

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-23859?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16426727#comment-16426727 ] 

Apache Spark commented on SPARK-23859:
--------------------------------------

User 'WeichenXu123' has created a pull request for this issue:
https://github.com/apache/spark/pull/20982

> Initial PR for Instrumentation improvements: UUID and logging levels
> --------------------------------------------------------------------
>
>                 Key: SPARK-23859
>                 URL: https://issues.apache.org/jira/browse/SPARK-23859
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML
>    Affects Versions: 2.3.0
>            Reporter: Joseph K. Bradley
>            Assignee: Weichen Xu
>            Priority: Major
>
> This is a subtask for an initial PR to improve MLlib's Instrumentation class for logging.  It will address a couple of issues and use the changes in LogisticRegression as an example class.
> Issues:
> * The UUID is currently generated from an atomic integer.  This is a problem since the integer is reset whenever a persisted Estimator is loaded on a new cluster.  We should just use a random UUID to get a new UUID each time with high probability.
> * We use both Instrumentation and Logging to log stuff.  Let's standardize around Instrumentation in MLlib since it can associate logs with the Estimator or Transformer which produced the logs (via a prefix with the algorithm's name or UUID).



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