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For future reference: Merged into master
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Github user BryanCutler commented on the issue:
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Ah, I see.. No worries then, I though maybe you had forgotten.
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Github user holdenk commented on the issue:
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I'd love to - however my JIRA account still doesn't have those permissions.
My plan was to bug people in person next week to get that sorted out and go
back and update the JIRAs.
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Github user BryanCutler commented on the issue:
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Thanks @holdenk! Would you mind assigning the JIRA to me?
https://issues.apache.org/jira/browse/SPARK-17161
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Github user BryanCutler commented on the issue:
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Thanks @holdenk! I updated the description. I'll follow up with
`CountVectorizerModel` after this merged and ping you.
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Github user holdenk commented on the issue:
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LGTM - thanks for doing this - please ping me on the follow up PRs with the
`CountVectorizerModel`. Before merge would you mind updating the PR description
for how this was tested to remove the
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Github user BryanCutler commented on the issue:
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ya good idea, I'll add that
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Github user holdenk commented on the issue:
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This looks good, how about also adding a test for an empty array given that
it was a consideration in the earlier iteration (not anymore but good to have
as a test incase we forget or someone else
Github user BryanCutler commented on the issue:
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Hey @holdenk , I removed the attempt at type inference so now must be
specified explicitly and added a docstring showing common examples. Please
take another look when you can, thanks!
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Github user holdenk commented on the issue:
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I don't think the wrappers are public APIs per-se, but I agree reducing the
amount of boilerplate scala code required to expose the ML stuff is good if we
can make it robust :)
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Github user BryanCutler commented on the issue:
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Sure, I can add a better docstring. This is just for developers and
doesn't have to be used, but it can be used to avoid creating more
Java-friendly functions only because they have arrays -
Github user holdenk commented on the issue:
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Maybe it could be cleared up a bit with a good docstring? Although if the
result is too confusing to be used then it's probably not worth doing.
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Github user BryanCutler commented on the issue:
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Thanks @holdenk for taking a look! Yeah, I think you're right about the
issues trying to infer a type. It would be nice if there was some easy way to
specify a primitive type since that would
Github user holdenk commented on the issue:
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cc @davies perhaps - what are your thoughts?
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Jenkins, retest this please
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Github user BryanCutler commented on the issue:
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ping @jkbradley @yanboliang @MLnick . This seems to have gone stale, but I
think it would be great to get in to add things like CountVectorizer
constructor from vocab list to PySpark. If any
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ping @jkbradley @yanboliang
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Github user BryanCutler commented on the issue:
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ping @yanboliang, mind taking a look? I'd like to have this to create a
CountVectorizerModel from a vocabulary list from SPARK-15009, thanks!
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Thanks @holdenk. I have an example usage for primitive arrays in the PR
description, let me know if that is not clear enough to show how this change
useful. I also added usage for
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Github user holdenk commented on the issue:
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Maybe it would be useful to see in the PR where this is going to simplify
the current PySpark ML code? (Need not be every model right away since if we
decide to make design changes that could
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@yanboliang, @jkbradley what do you think of this proposal?
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