[jira] [Assigned] (SPARK-22974) CountVectorModel does not attach attributes to output column

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22974?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-22974:
------------------------------------

    Assignee: Apache Spark

> CountVectorModel does not attach attributes to output column
> ------------------------------------------------------------
>
>                 Key: SPARK-22974
>                 URL: https://issues.apache.org/jira/browse/SPARK-22974
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.2.1
>            Reporter: William Zhang
>            Assignee: Apache Spark
>            Priority: Major
>
> If CountVectorModel transforms columns, the output column will not have attributes attached to them. If later on, those columns are used in Interaction transformer, an exception will be thrown:
> {quote}"org.apache.spark.SparkException: Vector attributes must be defined for interaction."
> {quote}
> To reproduce it:
> {quote}import org.apache.spark.ml.feature._
> import org.apache.spark.sql.functions._
> val df = spark.createDataFrame(Seq(
>   (0, Array("a", "b", "c"), Array("1", "2")),
>   (1, Array("a", "b", "b", "c", "a", "d"),  Array("1", "2", "3"))
> )).toDF("id", "words", "nums")
> val cvModel: CountVectorizerModel = new CountVectorizer()
>   .setInputCol("nums")
>   .setOutputCol("features2")
>   .setVocabSize(4)
>   .setMinDF(0)
>   .fit(df)
> ]val cvm = new CountVectorizerModel(Array("a", "b", "c"))
>   .setInputCol("words")
>   .setOutputCol("features1")
>   
> val df1 = cvm.transform(df)
> val df2 = cvModel.transform(df1)
> val interaction = new Interaction().setInputCols(Array("features1", "features2")).setOutputCol("features")
> val df3  = interaction.transform(df2)
> {quote}



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