Yong,
Thanks for the response. While those are good examples, they are able to
leverage the keytype/valuetype structure of Maps to specify an explicit
return type.
I guess maybe the more fundamental issue is that I want to support
heterogenous maps/arrays allowed by JSON: [1, "str", 2.345] or
{"name":"Chris","value":123}. Given the Spark SQL constraints that
ArrayType and MapType need explicit and consistent element types, I don't
see any way to support this in the current type system short of falling
back to binary data.
Open to other suggestions,
Chris
On Tue, Jul 26, 2016 at 9:42 AM Yong Zhang <java8...@hotmail.com> wrote:
> I don't know the if "ANY" will work or not, but do you take a look about
> how "map_values" UDF implemented in Spark, which return map values of an
> array/seq of arbitrary type.
>
>
> https://issues.apache.org/jira/browse/SPARK-16279
>
>
> Yong
>
>
> ------------------------------
> *From:* Chris Beavers <cbeav...@trifacta.com>
> *Sent:* Monday, July 25, 2016 10:32 PM
> *To:* user@spark.apache.org
> *Subject:* UDF returning generic Seq
>
> Hey there,
>
> Interested in writing a UDF that returns an ArrayType column of unknown
> subtype. My understanding is that this translated JVM-type-wise be a Seq of
> generic templated type: Seq[Any]. I seem to be hitting the constraint at
> https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala:657
> that
> basically necessitates a fully qualified schema on the return type (i.e.
> the templated Any is hitting the default exception throwing case at the end
> of schemaFor).
>
> Is there any more canonical way have a UDF produce an ArrayType column of
> unknown type? Or is my only alternative here to reduce this to BinaryType
> and use whatever encoding/data structures I want under the covers there and
> in subsequent UDFs?
>
> Thanks,
> Chris
>
