[jira] [Resolved] (SPARK-11725) Let UDF to handle null value

["Michael Armbrust (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-11725?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust resolved SPARK-11725.
--------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.6.0

Issue resolved by pull request 9770
[https://github.com/apache/spark/pull/9770]

> Let UDF to handle null value
> ----------------------------
>
>                 Key: SPARK-11725
>                 URL: https://issues.apache.org/jira/browse/SPARK-11725
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Jeff Zhang
>            Priority: Blocker
>              Labels: releasenotes
>             Fix For: 1.6.0
>
>
> I notice that currently spark will take the long field as -1 if it is null.
> Here's the sample code.
> {code}
> sqlContext.udf.register("f", (x:Int)=>x+1)
> df.withColumn("age2", expr("f(age)")).show()
> //////////////// Output ///////////////////////
> +----+-------+----+
> | age|   name|age2|
> +----+-------+----+
> |null|Michael|   0|
> |  30|   Andy|  31|
> |  19| Justin|  20|
> +----+-------+----+
> {code}
> I think for the null value we have 3 options
> * Use a special value to represent it (what spark does now)
> * Always return null if the udf input has null value argument 
> * Let udf itself to handle null
> I would prefer the third option 



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