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https://issues.apache.org/jira/browse/SPARK-11234?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14973674#comment-14973674
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Xusen Yin commented on SPARK-11234:
-----------------------------------
The last comment is based on my trial on Avito dataset
(https://issues.apache.org/jira/browse/SPARK-10935). It is only a beginning of
the trial, because Kristina Plazonic is already work on it. Look at here
https://github.com/yinxusen/incubator-project/blob/master/avito/src/main/scala/org/apache/spark/examples/main.scala#L48.
I want to load some of the columns as Int type, because they are Int type
variables in the dataset. But when I was using Assembler to assemble these
columns here
https://github.com/yinxusen/incubator-project/blob/master/avito/src/main/scala/org/apache/spark/examples/main.scala#L62,
the Spark code throws an exception for Int type should be Double. That's why I
think we should release the limitation, making Int/Float auto-cast to Double.
> 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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