[jira] [Commented] (SPARK-25381) Stratified sampling by Column argument

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-25381?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16608108#comment-16608108 ] 

Apache Spark commented on SPARK-25381:
--------------------------------------

User 'MaxGekk' has created a pull request for this issue:
https://github.com/apache/spark/pull/22365

> Stratified sampling by Column argument
> --------------------------------------
>
>                 Key: SPARK-25381
>                 URL: https://issues.apache.org/jira/browse/SPARK-25381
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.4.0
>            Reporter: Maxim Gekk
>            Priority: Minor
>
> Currently the sampleBy method accepts the first argument of string type only. Need to provide overloaded method which accepts Column type too. So, it will allow sampling by multiple columns , for example:
> {code:scala}
> import org.apache.spark.sql.Row
> import org.apache.spark.sql.functions.struct
> val df = spark.createDataFrame(Seq(("Bob", 17), ("Alice", 10), ("Nico", 8), ("Bob", 17),
>   ("Alice", 10))).toDF("name", "age")
> val fractions = Map(Row("Alice", 10) -> 0.3, Row("Nico", 8) -> 1.0)
> df.stat.sampleBy(struct($"name", $"age"), fractions, 36L).show()
>        +-----+---+
>        | name|age|
>        +-----+---+
>        | Nico|  8|
>        |Alice| 10|
>        +-----+---+
> {code} 



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