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https://issues.apache.org/jira/browse/SPARK-35173?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17338808#comment-17338808
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Apache Spark commented on SPARK-35173:
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User 'Yikun' has created a pull request for this issue:
https://github.com/apache/spark/pull/32431
> 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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