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https://issues.apache.org/jira/browse/SPARK-47845?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ruifeng Zheng reassigned SPARK-47845:
-------------------------------------
Assignee: Liu Cao
> Support column type in split function in scala and python
> ---------------------------------------------------------
>
> Key: SPARK-47845
> URL: https://issues.apache.org/jira/browse/SPARK-47845
> Project: Spark
> Issue Type: New Feature
> Components: Connect, Spark Core
> Affects Versions: 3.5.1
> Reporter: Liu Cao
> Assignee: Liu Cao
> Priority: Major
> Labels: pull-request-available
>
> I have a use case to split a String typed column with different delimiters
> defined in other columns of the dataframe. SQL already supports this, but
> scala / python functions currently don't.
>
> A hypothetical example to illustrate:
> {code:java}
> import org.apache.spark.sql.functions.{col, split}
> val example = spark.createDataFrame(
> Seq(
> ("Doe, John", ", ", 2),
> ("Smith,Jane", ",", 2),
> ("Johnson", ",", 1)
> )
> )
> .toDF("name", "delim", "expected_parts_count")
> example.createOrReplaceTempView("test_data")
> // works for SQL
> spark.sql("SELECT split(name, delim, expected_parts_count) AS name_parts FROM
> test_data").show()
> // currently doesn't compile for scala, but easy to support
> example.withColumn("name_parts", split(col("name"), col("delim"),
> col("expected_parts_count"))).show() {code}
>
> Pretty simple patch that I can make a PR soon
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