[jira] [Created] (SPARK-9971) MaxFunction not working correctly with columns containing Double.NaN

["Frank Rosner (JIRA)" <ji...@apache.org>]

Frank Rosner created SPARK-9971:
-----------------------------------

             Summary: MaxFunction not working correctly with columns containing Double.NaN
                 Key: SPARK-9971
                 URL: https://issues.apache.org/jira/browse/SPARK-9971
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 1.4.1
            Reporter: Frank Rosner


h5. Problem Description

When using the {{max}} function on a {{DoubleType}} column that contains {{Double.NaN}} values, the returned maximum value will be {{Double.NaN}}. 

This is because it compares all values with the running maximum. However, {{x < Double.NaN}} will always lead false for all {{x: Double}}, so will {{x > Double.NaN}}.

h5. How to Reproduce

{code}
import org.apache.spark.sql.{SQLContext, Row}
import org.apache.spark.sql.types._

val sql = new SQLContext(sc)
val rdd = sc.makeRDD(List(Row(Double.NaN), Row(-10d), Row(0d)))
val dataFrame = sql.createDataFrame(rdd, StructType(List(
  StructField("col", DoubleType, false)
)))
dataFrame.select(max("col")).first
// returns org.apache.spark.sql.Row = [NaN]
{code}

h5. Solution

The {{max}} and {{min}} functions should ignore NaN values, as they are not numbers. If a column contains only NaN values, then the maximum and minimum is not defined.



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