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https://issues.apache.org/jira/browse/SPARK-9062?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14631865#comment-14631865
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Joseph K. Bradley commented on SPARK-9062:
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I guess we will be forced to support nullable types. Looking at Catalyst
schema inference, it looks like the assumption of nullability is buried pretty
deep. I agree with you that Tokenizer (and any other transformers which use
Array/Seq) will need to be changed to use nullable = true.
Thanks for looking into this!
> Change output type of Tokenizer to Array(String, true)
> ------------------------------------------------------
>
> Key: SPARK-9062
> URL: https://issues.apache.org/jira/browse/SPARK-9062
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: yuhao yang
> Priority: Minor
>
> Currently output type of Tokenizer is Array(String, false), which is not
> compatible with Word2Vec and Other transformers since their input type is
> Array(String, true). Seq[String] in udf will be treated as Array(String,
> true) by default.
> I'm also thinking for Nullable columns, maybe tokenizer should return
> Array(null) for null value in the input.
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