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https://issues.apache.org/jira/browse/SPARK-9971?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14698078#comment-14698078
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Yin Huai commented on SPARK-9971:
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Seems our behaviors of min, max, sum, avg, and count are the same as postgresql
(see http://www.postgresql.org/docs/9.1/static/datatype-numeric.html).
> 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
> Priority: Minor
>
> h4. 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}}.
> h4. 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}
> h4. 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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