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https://issues.apache.org/jira/browse/SPARK-7696?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-7696:
-----------------------------------
Assignee: Apache Spark
> Aggregate function's result should be nullable only if the input expression
> is nullable
> ---------------------------------------------------------------------------------------
>
> Key: SPARK-7696
> URL: https://issues.apache.org/jira/browse/SPARK-7696
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.0, 1.3.1
> Reporter: Haopu Wang
> Assignee: Apache Spark
> Priority: Minor
>
> In SparkSQL, the aggregate function's result currently is always nullable.
> It will make sense to change the behavior as: if the input expression is
> nullable, the result is nullable; Otherwise, the result is non-nullable.
> Please see the following discussion:
> >>>>>>>>>>>>>>>
> From: Olivier Girardot [mailto:ssab...@gmail.com]
> Sent: Tuesday, May 12, 2015 5:12 AM
> To: Reynold Xin
> Cc: Haopu Wang; user
> Subject: Re: [SparkSQL 1.4.0] groupBy columns are always nullable?
>
> I'll look into it - not sure yet what I can get out of exprs :p
>
> Le lun. 11 mai 2015 à 22:35, Reynold Xin <r...@databricks.com> a écrit :
> Thanks for catching this. I didn't read carefully enough.
>
> It'd make sense to have the udaf result be non-nullable, if the exprs are
> indeed non-nullable.
>
> On Mon, May 11, 2015 at 1:32 PM, Olivier Girardot <ssab...@gmail.com> wrote:
> Hi Haopu,
> actually here `key` is nullable because this is your input's schema :
> scala> result.printSchema
> root
> |-- key: string (nullable = true)
> |-- SUM(value): long (nullable = true)
> scala> df.printSchema
> root
> |-- key: string (nullable = true)
> |-- value: long (nullable = false)
>
> I tried it with a schema where the key is not flagged as nullable, and the
> schema is actually respected. What you can argue however is that SUM(value)
> should also be not nullable since value is not nullable.
>
> @rxin do you think it would be reasonable to flag the Sum aggregation
> function as nullable (or not) depending on the input expression's schema ?
>
> Regards,
>
> Olivier.
> Le lun. 11 mai 2015 à 22:07, Reynold Xin <r...@databricks.com> a écrit :
> Not by design. Would you be interested in submitting a pull request?
>
> On Mon, May 11, 2015 at 1:48 AM, Haopu Wang <hw...@qilinsoft.com> wrote:
> I try to get the result schema of aggregate functions using DataFrame
> API.
> However, I find the result field of groupBy columns are always nullable
> even the source field is not nullable.
> I want to know if this is by design, thank you! Below is the simple code
> to show the issue.
> ======
> import sqlContext.implicits._
> import org.apache.spark.sql.functions._
> case class Test(key: String, value: Long)
> val df = sc.makeRDD(Seq(Test("k1",2),Test("k1",1))).toDF
> val result = df.groupBy("key").agg($"key", sum("value"))
> // From the output, you can see the "key" column is nullable, why??
> result.printSchema
> // root
> // |-- key: string (nullable = true)
> // |-- SUM(value): long (nullable = true)
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