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https://issues.apache.org/jira/browse/SPARK-11725?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15005391#comment-15005391
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Herman van Hovell commented on SPARK-11725:
-------------------------------------------
I'd rather add a warning than prevent this from happening.
I cannot reproduce the {{-1}} default values on Spark 1.5.2. For example:
{noformat}
val id = udf((x: Int) => {
x
})
val q = sqlContext
.range(1 << 10)
.select($"id", when(($"id" mod 2) === 1, $"id").as("val1"))
.select($"id", $"val1", id($"val1").as("val2"))
q.show
// Result:
id: org.apache.spark.sql.UserDefinedFunction =
UserDefinedFunction(<function1>,IntegerType,List(IntegerType))
q: org.apache.spark.sql.DataFrame = [id: bigint, val1: bigint, val2: int]
+---+----+----+
| id|val1|val2|
+---+----+----+
| 0|null| 0|
| 1| 1| 1|
| 2|null| 0|
| 3| 3| 3|
| 4|null| 0|
| 5| 5| 5|
| 6|null| 0|
| 7| 7| 7|
| 8|null| 0|
| 9| 9| 9|
| 10|null| 0|
| 11| 11| 11|
| 12|null| 0|
| 13| 13| 13|
| 14|null| 0|
| 15| 15| 15|
| 16|null| 0|
| 17| 17| 17|
| 18|null| 0|
| 19| 19| 19|
+---+----+----+
only showing top 20 rows
{noformat}
What version of Spark are you using?
> Let UDF to handle null value
> ----------------------------
>
> Key: SPARK-11725
> URL: https://issues.apache.org/jira/browse/SPARK-11725
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Jeff Zhang
>
> 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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