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https://issues.apache.org/jira/browse/SPARK-11234?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15023916#comment-15023916
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Xusen Yin commented on SPARK-11234:
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1. Thanks for pointing it out, it solves the problem.
2. SQLTransformer is useful, but may not cover my case in the example code.
Currently SQLTransformer only supports SELECT * from __THIS__.
3. Yes. It may useful, like my ParamSampler code here
https://github.com/yinxusen/hyperband_spark/blob/master/src/main/scala/org/apache/spark/ml/tuning/bandit/ParamSampler.scala#L25
4. I mean (a). Yes summary is good.
5. Maybe we can try to write an "implicit" transformer to transform other
Numeric types into Double type, just like implicit type cast in Scala. When
finding something that cannot be parsed in transformSchema, the transformer can
look up in a implicit transformation list. If it finds something can cast
current type into Double type, then it can add the implicit transformer in
front of current transformer.
> What's cooking classification
> -----------------------------
>
> Key: SPARK-11234
> URL: https://issues.apache.org/jira/browse/SPARK-11234
> Project: Spark
> Issue Type: Sub-task
> Components: ML
> Reporter: Xusen Yin
>
> I add the subtask to post the work on this dataset:
> https://www.kaggle.com/c/whats-cooking
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