[jira] [Resolved] (SPARK-17768) Small {Sum,Count,Mean}Evaluator problems and suboptimalities

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-17768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-17768.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

Issue resolved by pull request 15341
[https://github.com/apache/spark/pull/15341]

> Small {Sum,Count,Mean}Evaluator problems and suboptimalities
> ------------------------------------------------------------
>
>                 Key: SPARK-17768
>                 URL: https://issues.apache.org/jira/browse/SPARK-17768
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.0.1
>            Reporter: Sean Owen
>            Assignee: Sean Owen
>             Fix For: 2.1.0
>
>
> This tracks a few related issues with org.apache.spark.partial.(Count,Mean,Sum)Evaluator and their "Grouped" counterparts:
> - GroupedMeanEvaluator and GroupedSumEvaluator are unused, as is the StudentTCacher support class
> - CountEvaluator can return a lower bound < 0, when counts can't be negative
> - MeanEvaluator will actually fail on exactly 1 datum (yields t-test with 0 DOF)
> - CountEvaluator uses a normal distribution, which may be an inappropriate approximation (leading to above)
> - Test for SumEvaluator asserts incorrect expected sums -- e.g. after observing 10% of data has sum of 2, expectation should be 20, not 38
> - CountEvaluator, MeanEvaluator have no unit tests to catch these
> - Duplication of distribution code across CountEvaluator, GroupedCountEvaluator
> - The stats in each could use a bit of documentation as I had to guess at them
> - (Code could use a few cleanups and optimizations too)



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