[jira] [Updated] (SPARK-14051) Implement `Double.NaN==Float.NaN` for consistency

["Dongjoon Hyun (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14051?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dongjoon Hyun updated SPARK-14051:
----------------------------------
    Summary: Implement `Double.NaN==Float.NaN` for consistency  (was: Implement `Double.NaN==Float.NaN` in `row.equals` for consistency)

> Implement `Double.NaN==Float.NaN` for consistency
> -------------------------------------------------
>
>                 Key: SPARK-14051
>                 URL: https://issues.apache.org/jira/browse/SPARK-14051
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Dongjoon Hyun
>            Priority: Minor
>
> Since SPARK-9079 and SPARK-9145, `NaN = NaN` returns true and works well. The only exception case is direct comparison between  `Row(Float.NaN)` and `Row(Double.NaN)`. The following is the example: the last expression should be true for consistency.
> {code}
> scala> Seq((1d,1f),(Double.NaN,Float.NaN)).toDF("a","b").registerTempTable("tmp")
> scala> sql("select a,b,a=b from tmp").collect()
> res1: Array[org.apache.spark.sql.Row] = Array([1.0,1.0,true], [NaN,NaN,true])
> scala> val row_a = sql("select a from tmp").collect()
> row_a: Array[org.apache.spark.sql.Row] = Array([1.0], [NaN])
> scala> val row_b = sql("select b from tmp").collect()
> row_b: Array[org.apache.spark.sql.Row] = Array([1.0], [NaN])
> scala> row_a(0) == row_b(0)
> res2: Boolean = true
> scala> row_a(1) == row_b(1)
> res3: Boolean = false
> {code}



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