You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2019/07/20 00:08:00 UTC

[jira] [Commented] (SPARK-28433) Incorrect assertion in scala test for aarch64 platform

    [ https://issues.apache.org/jira/browse/SPARK-28433?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16889263#comment-16889263 ] 

Dongjoon Hyun commented on SPARK-28433:
---------------------------------------

I removed `2.4.3` from the affected versions because there is no test using those assertions in `branch-2.4`.

> Incorrect assertion in scala test for aarch64 platform
> ------------------------------------------------------
>
>                 Key: SPARK-28433
>                 URL: https://issues.apache.org/jira/browse/SPARK-28433
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.0.0
>            Reporter: huangtianhua
>            Assignee: huangtianhua
>            Priority: Minor
>             Fix For: 3.0.0
>
>
> We ran unit tests of spark on aarch64 server, here are two sql scala tests failed: 
> - SPARK-26021: NaN and -0.0 in grouping expressions *** FAILED ***
>    2143289344 equaled 2143289344 (DataFrameAggregateSuite.scala:732)
>  - NaN and -0.0 in window partition keys *** FAILED ***
>    2143289344 equaled 2143289344 (DataFrameWindowFunctionsSuite.scala:704)
> we found the values of floatToRawIntBits(0.0f / 0.0f) and floatToRawIntBits(Float.NaN) on aarch64 are same(2143289344),  first we thought it's something about jdk or scala, but after discuss with jdk-dev and scala community see https://users.scala-lang.org/t/the-value-of-floattorawintbits-0-0f-0-0f-is-different-on-x86-64-and-aarch64-platforms/4845 , we believe the value depends on the architecture.



--
This message was sent by Atlassian JIRA
(v7.6.14#76016)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org