Self-join after cogroup applyInPandas fails due to unresolved conflicting attributes

df = spark.createDataFrame([(1, 1)], ("column", "value"))row = df.groupby("ColUmn").cogroup(
    df.groupby("COLUMN")
).applyInPandas(lambda r, l: r + l, "column long, value long")
row.join(row).show()

Conflicting attributes: column#163321L,value#163322L
;;
’Join Inner
:- FlatMapCoGroupsInPandas [ColUmn#163312L], [COLUMN#163312L], <lambda>(column#163312L, value#163313L, column#163312L, value#163313L), [column#163321L, value#163322L]
:  :- Project [ColUmn#163312L, column#163312L, value#163313L]
:  :  +- LogicalRDD [column#163312L, value#163313L], false
:  +- Project [COLUMN#163312L, column#163312L, value#163313L]
:     +- LogicalRDD [column#163312L, value#163313L], false
+- FlatMapCoGroupsInPandas [ColUmn#163312L], [COLUMN#163312L], <lambda>(column#163312L, value#163313L, column#163312L, value#163313L), [column#163321L, value#163322L]
   :- Project [ColUmn#163312L, column#163312L, value#163313L]
   :  +- LogicalRDD [column#163312L, value#163313L], false
   +- Project [COLUMN#163312L, column#163312L, value#163313L]
      +- LogicalRDD [column#163312L, value#163313L], false