[jira] [Commented] (SPARK-22283) withColumn should replace multiple instances with a single one

["Jen-Ming Chung (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-22283?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16206988#comment-16206988 ] 

Jen-Ming Chung commented on SPARK-22283:
----------------------------------------

Hi [~kitbellew],
I found the `withColumn` has already reimplemented in this [PR|https://github.com/apache/spark/pull/19229].

> withColumn should replace multiple instances with a single one
> --------------------------------------------------------------
>
>                 Key: SPARK-22283
>                 URL: https://issues.apache.org/jira/browse/SPARK-22283
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: Albert Meltzer
>
> Currently, {{withColumn}} claims to do the following: _"adding a column or replacing the existing column that has the same name."_
> Unfortunately, if multiple existing columns have the same name (which is a normal occurrence after a join), this results in multiple replaced -- and retained --
>  columns (with the same value), and messages about an ambiguous column.
> The current implementation of {{withColumn}} contains this:
> {noformat}
>   def withColumn(colName: String, col: Column): DataFrame = {
>     val resolver = sparkSession.sessionState.analyzer.resolver
>     val output = queryExecution.analyzed.output
>     val shouldReplace = output.exists(f => resolver(f.name, colName))
>     if (shouldReplace) {
>       val columns = output.map { field =>
>         if (resolver(field.name, colName)) {
>           col.as(colName)
>         } else {
>           Column(field)
>         }
>       }
>       select(columns : _*)
>     } else {
>       select(Column("*"), col.as(colName))
>     }
>   }
> {noformat}
> Instead, suggest something like this (which replaces all matching fields with a single instance of the new one):
> {noformat}
>   def withColumn(colName: String, col: Column): DataFrame = {
>     val resolver = sparkSession.sessionState.analyzer.resolver
>     val output = queryExecution.analyzed.output
>     val existing = output.filterNot(f => resolver(f.name, colName)).map(new Column(_))
>     select(existing :+ col.as(colName): _*)
>   }
> {noformat}



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