[jira] [Commented] (SPARK-15204) Improve nullability inference for Aggregator
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https://issues.apache.org/jira/browse/SPARK-15204?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15317187#comment-15317187
]
Apache Spark commented on SPARK-15204:
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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.
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[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=15277600#comment-15277600
]
Koert Kuipers commented on SPARK-15204:
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Makes sense
> 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.
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