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Posted to issues@spark.apache.org by "Goun Na (JIRA)" <ji...@apache.org> on 2018/09/14 10:58:00 UTC
[jira] [Updated] (SPARK-25430) Add map parameter for
withColumnRenamed
[ https://issues.apache.org/jira/browse/SPARK-25430?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Goun Na updated SPARK-25430:
----------------------------
Description:
WithColumnRenamed method should work with map parameter. It removes code redundancy.
{code:java}
// example
df.withColumnRenamed(Map( "c1" -> "first_column", "c2" -> "second_column" )){code}
{code:java}
// from abbr columns to desc columns
val m = Map( "c1" -> "first_column", "c2" -> "second_column" )
df1.withColumnRenamed(m)
df2.withColumnRenamed(m)
{code}
It is useful for CJK users when they are working on analysis in notebook environment such as Zeppelin, Databricks, Apache Toree.
{code:java}
// for CJK users once define dictionary into map, reuse column map to translate columns whenever report visualization is required
val m = Map( "c1" -> "컬럼_1", "c2" -> "컬럼_2")
df1.withColumnRenamed(m)
df2.withColumnRenamed(m)
{code}
was:
WithColumnRenamed method should work with map parameter. It removes code redundancy.
{code:java}
// example
df.withColumnRenamed(Map( "c1" -> "first_column", "c2" -> "second_column" )){code}
{code:java}
// from abbr columns to desc columns
val m = Map( "c1" -> "first_column", "c2" -> "second_column" ) df1.withColumnRenamed(m)
df2.withColumnRenamed(m){code}
It is useful for CJK users when they are working on analysis in notebook environment such as Zeppelin, Databricks, Apache Toree.
{code:java}
// for CJK users once define dictionary into map, reuse column map to translate columns whenever report visualization is required
val m = Map( "c1" -> "컬럼_1", "c2" -> "컬럼_2")
df1.withColumnRenamed(m)
df2.withColumnRenamed(m)
{code}
> Add map parameter for withColumnRenamed
> ---------------------------------------
>
> Key: SPARK-25430
> URL: https://issues.apache.org/jira/browse/SPARK-25430
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.1
> Reporter: Goun Na
> Priority: Major
>
> WithColumnRenamed method should work with map parameter. It removes code redundancy.
> {code:java}
> // example
> df.withColumnRenamed(Map( "c1" -> "first_column", "c2" -> "second_column" )){code}
> {code:java}
> // from abbr columns to desc columns
> val m = Map( "c1" -> "first_column", "c2" -> "second_column" )
> df1.withColumnRenamed(m)
> df2.withColumnRenamed(m)
> {code}
> It is useful for CJK users when they are working on analysis in notebook environment such as Zeppelin, Databricks, Apache Toree.
> {code:java}
> // for CJK users once define dictionary into map, reuse column map to translate columns whenever report visualization is required
> val m = Map( "c1" -> "컬럼_1", "c2" -> "컬럼_2")
> df1.withColumnRenamed(m)
> df2.withColumnRenamed(m)
> {code}
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