Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/3062#issuecomment-72567721
@srowen Yes, the implementation would live under the `mllib.pmml` package
and we add `toPMML` to models that we support. For the return type, exposing
third-party APIs is not recommended in Spark. We used Guava's Optional, which
turned out to be a bad choice for maintenance. There are pros/cons for other
types.
1. String. Easy to save/load, but it may not be able to handle super large
XML.
2. `Result` from `javax.xml`. Officially supported by Java, but most users
don't know how to use it.
So it really depends on how big the model is and whether it is necessary to
output XML as a stream.
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