[jira] [Resolved] (SPARK-20660) Not able to merge Dataframes with different column orders

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-20660?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-20660.
----------------------------------
    Resolution: Incomplete

> Not able to merge Dataframes with different column orders
> ---------------------------------------------------------
>
>                 Key: SPARK-20660
>                 URL: https://issues.apache.org/jira/browse/SPARK-20660
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.1.0
>            Reporter: Michel Lemay
>            Priority: Minor
>              Labels: bulk-closed
>
> Union on two dataframes with different column orders is not supported and lead to hard to find issues.
> Here is an example showing the issue.
> {code}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.Row
> var inputSchema = StructType(StructField("key", StringType, nullable=true) :: StructField("value", IntegerType, nullable=true) :: Nil)
> var a = spark.createDataFrame(sc.parallelize((1 to 10)).map(x => Row(x.toString, 555)), inputSchema)
> var b = a.select($"value" * 2 alias "value", $"key")  // any transformation changing column order will show the problem.
> a.union(b).show
> // in order to make it work, we need to reorder columns
> val bCols = a.columns.map(aCol => b(aCol))
> a.union(b.select(bCols:_*)).show
> {code}



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