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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