[jira] [Assigned] (SPARK-35173) Support columns batch adding in PySpark.dataframe

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

     [ https://issues.apache.org/jira/browse/SPARK-35173?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-35173:
------------------------------------

    Assignee:     (was: Apache Spark)

> Support columns batch adding in PySpark.dataframe
> -------------------------------------------------
>
>                 Key: SPARK-35173
>                 URL: https://issues.apache.org/jira/browse/SPARK-35173
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark, SQL
>    Affects Versions: 3.2.0
>            Reporter: Yikun Jiang
>            Priority: Major
>
> Now, the pyspark can only use withColumn to do column adding a column or replacing the existing column that has the same name. The scala withColumn can adding columns at one pass. [1]
>  
> Before this added, the user can only use withColumn again and again like:
>  
> {code:java}
> self.df.withColumn("key1", col("key1")).withColumn("key2", col("key2")).withColumn("key3", col("key3")){code}
>  
> After the support, you user can use the with_columns complete batch operations:
>  
> {code:java}
> self.df.withColumn(["key1", "key2", "key3"], [col("key1"), col("key2"), col("key3")]){code}
>  
> [1] [https://github.com/apache/spark/blob/b5241c97b17a1139a4ff719bfce7f68aef094d95/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala#L2402]



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