Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/11868#issuecomment-199982128
Oh, I see what is the point here now. @rxin , may I explain a little bit
more?
Mathematically, `NaN` equality is defined `false`. The followings are all
**false** in Scala (and Java).
* row_a(1).getDouble(0) == row_a(1).getDouble(0)
* row_b(1).getFloat(0) == row_b(1).getFloat(0)
* row_a(1).getDouble(0) == row_b(1).getFloat(0)
* Double.NaN == Double.NaN
* Float.NaN == Float.NaN
* Double.NaN == Float.NaN
However, Spark `Row` on master branch already returns **true** for the
followings.
* Row(Double.NaN) == Row(Double.NaN)
* Row(Float.NaN) == Row(Float.NaN)
As you guess easily, the followings are still **false**.
* Row(Float.NaN).getFloat(0) == Row(Float.NaN).getFloat(0)
* Row(Double.NaN).getDouble(0) == Row(Double.NaN).getDouble(0)
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