[jira] [Assigned] (SPARK-11725) Let UDF to handle null value
[
https://issues.apache.org/jira/browse/SPARK-11725?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-11725:
Assignee: Apache Spark
> 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
>Assignee: Apache Spark
>Priority: Blocker
>
> 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
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-11725) Let UDF to handle null value
[
https://issues.apache.org/jira/browse/SPARK-11725?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-11725:
Assignee: (was: Apache Spark)
> 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
>
> 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
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
