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Closing this in favor of the approach taken in
https://github.com/apache/spark/pull/19876
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@MLNick: Do you have the bandwith to revisit this? I'm open to refactoring
to a more plug-gable approach if we've got the review bandwidth for it.
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Ping @jkbradley / @mlnick - we are coming up on a year since we told people
we would add PMML export to Spark in about a year so I figured I'd try and
update this again. I'll update this PR tonight
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ping @MLnick now that 2.0 is out for awhile.
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Now that 2.0 RC5 has passed - maybe it would be an OK time to revisit this?
I think it can also be an ok base for adding more formats if we need to.
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HiveSubmit failures seem unrelated, jenkins retest this please.
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@MLnick I like that idea! I've done the shortcut approach on the root
(since thats the shortcut we already had) - but I'll look at adding the
shortcut on the MLWriter its self as well. Thanks!
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Github user MLnick commented on the issue:
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@holden that's true for the fully generic approach. But `DataFrameWriter`
for example exposes `json` as a shortcut (type-safe in a way) for
`format("json")`.
I think we can achieve something
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@mengxr One downside of going the generic writer way is we loose compile
time checking as to if the requested format is supported.
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So I guess I'm wondering what our plans for PMML look like - I'm happy to
update this or go in the direction @MLnick suggested if thats what we want?
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