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Posted to issues@spark.apache.org by "Michel Lemay (JIRA)" <ji...@apache.org> on 2017/05/08 20:23:04 UTC
[jira] [Updated] (SPARK-20660) Not able to merge Dataframes with
different column orders
[ https://issues.apache.org/jira/browse/SPARK-20660?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michel Lemay updated SPARK-20660:
---------------------------------
Description:
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", $"key") // any transformation changing column order will show the problem.
a.union(b).show
// in order to make it work, we need to reorder columns
val bCols = a.columns.map(aCol => b(aCol))
a.union(b.select(bCols:_*)).show
{code}
was:
Union on two dataframes with different column orders is not supported and lead to hard to find issues.
Here is an example showing the issue.
{code}
import org.apache.spark.sql.types._
import org.apache.spark.sql.Row
var inputSchema = StructType(StructField("key", StringType, nullable=true) :: StructField("value", IntegerType, nullable=true) :: Nil)
var a = spark.createDataFrame(sc.parallelize((1 to 10)).map(x => Row(x.toString, 555)), inputSchema)
var b = a.select($"value", $"key") // any transformation changing column order will show the problem.
a.union(c).show
// in order to make it work, we need to reorder columns
val bCols = a.columns.map(aCol => b(aCol))
a.union(b.select(bCols:_*)).show
{code}
> Not able to merge Dataframes with different column orders
> ---------------------------------------------------------
>
> Key: SPARK-20660
> URL: https://issues.apache.org/jira/browse/SPARK-20660
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.0
> Reporter: Michel Lemay
> Priority: Minor
>
> Union on two dataframes with different column orders is not supported and lead to hard to find issues.
> Here is an example showing the issue.
> {code}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.Row
> var inputSchema = StructType(StructField("key", StringType, nullable=true) :: StructField("value", IntegerType, nullable=true) :: Nil)
> var a = spark.createDataFrame(sc.parallelize((1 to 10)).map(x => Row(x.toString, 555)), inputSchema)
> var b = a.select($"value", $"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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