You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/06/06 20:39:21 UTC

[jira] [Commented] (SPARK-15204) Improve nullability inference for Aggregator

    [ https://issues.apache.org/jira/browse/SPARK-15204?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15317187#comment-15317187 ] 

Apache Spark commented on SPARK-15204:
--------------------------------------

User 'koertkuipers' has created a pull request for this issue:
https://github.com/apache/spark/pull/13532

> Improve nullability inference for Aggregator
> --------------------------------------------
>
>                 Key: SPARK-15204
>                 URL: https://issues.apache.org/jira/browse/SPARK-15204
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>         Environment: spark-2.0.0-SNAPSHOT
>            Reporter: koert kuipers
>            Priority: Minor
>
> {noformat}
> object SimpleSum extends Aggregator[Row, Int, Int] {
>   def zero: Int = 0
>   def reduce(b: Int, a: Row) = b + a.getInt(1)
>   def merge(b1: Int, b2: Int) = b1 + b2
>   def finish(b: Int) = b
>   def bufferEncoder: Encoder[Int] = Encoders.scalaInt
>   def outputEncoder: Encoder[Int] = Encoders.scalaInt
> }
> val df = List(("a", 1), ("a", 2), ("a", 3)).toDF("k", "v")
> val df1 = df.groupBy("k").agg(SimpleSum.toColumn as "v1")
> df1.printSchema
> df1.show
> root
>  |-- k: string (nullable = true)
>  |-- v1: integer (nullable = true)
> +---+---+
> |  k| v1|
> +---+---+
> |  a|  6|
> +---+---+
> {noformat}
> notice how v1 has nullable set to true. the default (and expected) behavior for spark sql is to give an int column false for nullable. for example if i had uses a built-in aggregator like "sum" instead if would have reported nullable = false.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org