How about this:

df.select(expr("transform( b, v1 -> struct(v1) )")).show()

--------------------------------------------------------------------------------------------+
|transform(b, lambdafunction(named_struct(v1, namedlambdavariable()),
namedlambdavariable()))|
+--------------------------------------------------------------------------------------------+
|
               [[[1]]]|
+--------------------------------------------------------------------------------------------+


On Thu, Nov 15, 2018 at 6:47 AM François Sarradin <fsarra...@gmail.com>
wrote:

> Hi,
>
> I've this JSON document :
>
> { "b": [ { "e": 1 } ] }
>
> When I do :
>
> df.select(expr("transform( b, v1 -> struct(v1.e) )"))
>
> I get this error :
>
> cannot resolve 'named_struct(NamePlaceholder(), namedlambdavariable().e)'
> due to data type mismatch: Only foldable string expressions are allowed to
> appear at odd position, got: NamePlaceholder; line 1 pos 20; 'Project
> [unresolvedalias(transform(b#5,
> lambdafunction(named_struct(NamePlaceholder, lambda v1#7.e), lambda v1#7,
> false)), Some(<function1>))] +- LogicalRDD [b#5], false
>
> org.apache.spark.sql.AnalysisException: cannot resolve 
> 'named_struct(NamePlaceholder(), namedlambdavariable().`e`)' due to data type 
> mismatch: Only foldable string expressions are allowed to appear at odd 
> position, got: NamePlaceholder; line 1 pos 20;
> 'Project [unresolvedalias(transform(b#5, 
> lambdafunction(named_struct(NamePlaceholder, lambda v1#7.e), lambda v1#7, 
> false)), Some(<function1>))]
> +- LogicalRDD [b#5], false
>       at 
> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$3.applyOrElse(CheckAnalysis.scala:115)
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$3.applyOrElse(CheckAnalysis.scala:107)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)
>       at 
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:277)
> ...
>
> By doing some investigations, it seems that this error is due to the fact 
> that v1.e is seen as a NamePlaceHolder and not as a Literal. This is somewhat 
> understandable, as v1 is not resolved here. But, isn't it possible that 
> struct(v1.e) uses v1.e as a field name?
>
> regards,
>
> françois-
>
>

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