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From jaceklaskowski <>
Subject [GitHub] spark issue #18523: [SPARK-21285][ML] VectorAssembler reports the column nam...
Date Wed, 05 Jul 2017 08:38:15 GMT
Github user jaceklaskowski commented on the issue:
    Thanks @facaiy for the changes. I wonder if the code could `collect` all the columns with
incorrect type in one go (rather than reporting issues column by column until a user fixed
    Something along the lines:
    val incorrectColumns = inputColNames
      .map { name => (name, schema(name).dataType) }
      .collect {
        case (_, _: NumericType | BooleanType) =>
        case t if t.isInstanceOf[VectorUDT] =>
        case other => other }
    // report issue with incorrectColumns

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