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https://issues.apache.org/jira/browse/SPARK-36858?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17428596#comment-17428596
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Armand BERGES commented on SPARK-36858:
---------------------------------------
Honestly, I feel a little dumb to not to have think at it earlier ...
I fix our implementation and it is way better ! :)
To be clear, our method is like that :
{code:java}
def withColumns(cols: Seq[String], columnTransform: String => Column,
nameTransform: String => String = identity): DataFrame = {
// See https://issues.apache.org/jira/browse/SPARK-36858
cols.foreach((colName: String) => df = df.withColumn(nameTransform(colName),
columnTransform(colName)))
df
}
{code}
I think the method signature could easily be improved, and we could discuss
about it.
Based on your comment, this ticket could probably change in "Add a question in
some Tutorial" to avoid some noobies to fell into the trap I mention.
Of course, if Spark implements this method with some nice API it could be more
easier to avoid this trap :)
> Spark API to apply same function to multiple columns
> ----------------------------------------------------
>
> Key: SPARK-36858
> URL: https://issues.apache.org/jira/browse/SPARK-36858
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 2.4.8, 3.1.2
> Reporter: Armand BERGES
> Priority: Minor
>
> Hi
> My team and I have regularly need to apply the same function to multiple
> columns at once.
> For example, we want to remove all non alphanumerical characters to each
> columns of our dataframes.
> When we hit this use case first, some people in my team were using this kind
> of code :
> {code:java}
> val colListToClean = .... ## Generate some list, could be very long.
> val dfToClean: DataFrame = ... ## This is the dataframe we want to clean
> def cleanFunction(colName: String): Column = ... ## Write some function to
> manipulate column based on its name.
> val dfCleaned = colListToClean.foldLeft(dfToClean)((df, colName) =>
> df.withColumn(colName, cleanFunction(colName)){code}
> This kind of code when applied on a large set of columns overloaded our
> driver (because a Dataframe is generated for each column to clean).
> Based on this issue, we developed some code to add two functions :
> * One to apply the same function to multiple columns
> * One to rename multiple columns based on a Map.
>
> I wonder if your ever ask your team to add such kind of API ? If you did, had
> you any kind of issue regarding the implementation ? If you didn't, is this
> any idea you could add to Spark ?
> Best regards,
>
> LvffY
>
>
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