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https://issues.apache.org/jira/browse/SPARK-21900?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-21900:
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Priority: Minor (was: Major)
Summary: Numerical Error in simple Skewness Computation (was: Error in
Skewness Computation)
Try {{.show(truncate=false)}}. I think you'll find that it's actually something
like "5.95...e-17", which is nearly 0.
Still, I find it does return 0 if the input is 1,2,3,4, and return differently
nearly-0 values for different orderings. That's not quite ideal for such a
simple example where the result is obviously 0, even if it's
It also, however, seems to return 0 on the original input in Spark 2.2.
On a different input like 1,2,3,10,20,30 it gives 0.7256411823021005, which
matches scipy (with bias correction) and e1071 in R ("type 1" definition). I
suspect the calculation is correct, but this is slightly unfortunate
manifestation of numerical error.
[~mengxr] wrote a whole paper on this (!) https://arxiv.org/pdf/1510.04923.pdf
> Numerical Error in simple Skewness Computation
> ----------------------------------------------
>
> Key: SPARK-21900
> URL: https://issues.apache.org/jira/browse/SPARK-21900
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Jakob Bach
> Priority: Minor
>
> The skewness() aggregate SQL function in the Scala implementation
> (org.apache.spark.sql.skewness) seems to be buggy .The following code
> {code:java}
> import org.apache.spark.sql.functions
> import org.apache.spark.sql.SparkSession
> object SkewTest {
> def main(args: Array[String]): Unit = {
> val spark = SparkSession.
> builder().
> appName("Skewness example").
> master("local[1]").
> getOrCreate()
>
> spark.createDataFrame(Seq(4,1,2,3).map(Tuple1(_))).agg(functions.skewness("_1")).show()
> }
> }
> {code}
> should output 0 (as it does for Seq(1,2,3,4)), but outputs
> {code:none}
> +--------------------+
> | skewness(_1)|
> +--------------------+
> |5.958081967793454...|
> +--------------------+
> {code}
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