[jira] [Commented] (SPARK-23157) withColumn fails for a column that is a result of mapped DataSet

["Henry Robinson (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-23157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16340412#comment-16340412 ] 

Henry Robinson commented on SPARK-23157:
----------------------------------------

I'm not sure if this should actually be expected to work. {{Dataset.map()}} will always return a dataset with a logical plan that's different to the original, so {{ds.map(a => a).col("id")}} has an expression that refers to an attribute ID that isn't produced by the original dataset. It seems like the requirement for {{ds.withColumn()}} is that the column argument is an expression over {{ds}}'s logical plan.

You get the same error doing the following, which is more explicit about these being two separate datasets.
{code:java}
scala> val ds = spark.createDataset(Seq(R("1")))
ds: org.apache.spark.sql.Dataset[R] = [id: string]

scala> val ds2 = spark.createDataset(Seq(R("1")))
ds2: org.apache.spark.sql.Dataset[R] = [id: string]

scala> ds.withColumn("id2", ds2.col("id"))
org.apache.spark.sql.AnalysisException: Resolved attribute(s) id#113 missing from id#1 in operator !Project [id#1, id#113 AS id2#115]. Attribute(s) with the same name appear in the operation: id. Please check if the right attribute(s) are used.;;
!Project [id#1, id#113 AS id2#115]
+- LocalRelation [id#1]

  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:41)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:91)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:297)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:91)
  at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:52)
  at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:70)
  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:3286)
  at org.apache.spark.sql.Dataset.select(Dataset.scala:1303)
  at org.apache.spark.sql.Dataset.withColumns(Dataset.scala:2185)
  at org.apache.spark.sql.Dataset.withColumn(Dataset.scala:2152)
  ... 49 elided
{code}
If the {{map}} function weren't the identity, would you expect this still to work?

> withColumn fails for a column that is a result of mapped DataSet
> ----------------------------------------------------------------
>
>                 Key: SPARK-23157
>                 URL: https://issues.apache.org/jira/browse/SPARK-23157
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.2.1
>            Reporter: Tomasz Bartczak
>            Priority: Minor
>
> Having 
> {code:java}
> case class R(id: String)
> val ds = spark.createDataset(Seq(R("1")))
> {code}
> This works:
> {code}
> scala> ds.withColumn("n", ds.col("id"))
> res16: org.apache.spark.sql.DataFrame = [id: string, n: string]
> {code}
> but when we map over ds it fails:
> {code}
> scala> ds.withColumn("n", ds.map(a => a).col("id"))
> org.apache.spark.sql.AnalysisException: resolved attribute(s) id#55 missing from id#4 in operator !Project [id#4, id#55 AS n#57];;
> !Project [id#4, id#55 AS n#57]
> +- LocalRelation [id#4]
>   at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:39)
>   at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:91)
>   at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:347)
>   at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:78)
>   at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
>   at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:78)
>   at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:91)
>   at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:52)
>   at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:67)
>   at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2884)
>   at org.apache.spark.sql.Dataset.select(Dataset.scala:1150)
>   at org.apache.spark.sql.Dataset.withColumn(Dataset.scala:1905)
>   ... 48 elided
> {code}



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