Failure when resolving conflicting references in Join:

val numsDF = sc.parallelize(Seq(1,2,3,4,5,6)).toDF("nums")


val cubeDF = numsDF
    .cube("nums")
    .agg(
        max(lit(0)).as("agcol"),
        grouping_id().as("gid")
    )
    
val group0 = cubeDF.filter(col("gid") <=> lit(0))
val group1 = cubeDF.filter(col("gid") <=> lit(1))

cubeDF.printSchema
group0.printSchema
group1.printSchema


//Recreating cubeDf
cubeDF.select("nums").distinct
    .join(group0, Seq("nums"), "inner")
    .join(group1, Seq("nums"), "inner")
    .show

numsDF: org.apache.spark.sql.DataFrame = [nums: int]
cubeDF: org.apache.spark.sql.DataFrame = [nums: int, agcol: int ... 1 more field]
group0: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [nums: int, agcol: int ... 1 more field]
group1: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [nums: int, agcol: int ... 1 more field]
root
 |-- nums: integer (nullable = true)
 |-- agcol: integer (nullable = true)
 |-- gid: integer (nullable = false)
root
 |-- nums: integer (nullable = true)
 |-- agcol: integer (nullable = true)
 |-- gid: integer (nullable = false)
root
 |-- nums: integer (nullable = true)
 |-- agcol: integer (nullable = true)
 |-- gid: integer (nullable = false)
org.apache.spark.sql.AnalysisException:
Failure when resolving conflicting references in Join:
'Join Inner
:- Deduplicate [nums#220]
:  +- Project [nums#220]
:     +- Aggregate [nums#220, spark_grouping_id#218], [nums#220, max(0) AS agcol#216, spark_grouping_id#218 AS gid#217]
:        +- Expand [List(nums#212, nums#219, 0), List(nums#212, null, 1)], [nums#212, nums#220, spark_grouping_id#218]
:           +- Project [nums#212, nums#212 AS nums#219]
:              +- Project [value#210 AS nums#212]
:                 +- SerializeFromObject [input[0, int, false] AS value#210]
:                    +- ExternalRDD [obj#209]
+- Filter (gid#217 <=> 0)
   +- Aggregate [nums#220, spark_grouping_id#218], [nums#220, max(0) AS agcol#216, spark_grouping_id#218 AS gid#217]
      +- Expand [List(nums#212, nums#219, 0), List(nums#212, null, 1)], [nums#212, nums#220, spark_grouping_id#218]
         +- Project [nums#212, nums#212 AS nums#219]
            +- Project [value#210 AS nums#212]
               +- SerializeFromObject [input[0, int, false] AS value#210]
                  +- ExternalRDD [obj#209]
Conflicting attributes: nums#220
;;
'Join Inner
:- Deduplicate [nums#220]
:  +- Project [nums#220]
:     +- Aggregate [nums#220, spark_grouping_id#218], [nums#220, max(0) AS agcol#216, spark_grouping_id#218 AS gid#217]
:        +- Expand [List(nums#212, nums#219, 0), List(nums#212, null, 1)], [nums#212, nums#220, spark_grouping_id#218]
:           +- Project [nums#212, nums#212 AS nums#219]
:              +- Project [value#210 AS nums#212]
:                 +- SerializeFromObject [input[0, int, false] AS value#210]
:                    +- ExternalRDD [obj#209]
+- Filter (gid#217 <=> 0)
   +- Aggregate [nums#220, spark_grouping_id#218], [nums#220, max(0) AS agcol#216, spark_grouping_id#218 AS gid#217]
      +- Expand [List(nums#212, nums#219, 0), List(nums#212, null, 1)], [nums#212, nums#220, spark_grouping_id#218]
         +- Project [nums#212, nums#212 AS nums#219]
            +- Project [value#210 AS nums#212]
               +- SerializeFromObject [input[0, int, false] AS value#210]
                  +- ExternalRDD [obj#209]
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:42)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:96)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:335)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:125)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:85)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:96)
  at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:109)
  at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:106)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:202)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:106)
  at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:68)
  at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:66)
  at org.apache.spark.sql.Dataset.join(Dataset.scala:939)
  ... 46 elided