diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala index b9e2144c0ad4..fab3e74f3d1f 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala @@ -70,7 +70,8 @@ private[feature] trait CountVectorizerParams extends Params with HasInputCol wit /** Validates and transforms the input schema. */ protected def validateAndTransformSchema(schema: StructType): StructType = { - SchemaUtils.checkColumnType(schema, $(inputCol), new ArrayType(StringType, true)) + val typeCandidates = List(ArrayType(StringType, true), ArrayType(StringType, false)) + SchemaUtils.checkColumnTypes(schema, $(inputCol), typeCandidates) SchemaUtils.appendColumn(schema, $(outputCol), new VectorUDT) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala index 7decbbd0b96b..76021ad8f4e6 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala @@ -43,6 +43,23 @@ private[spark] object SchemaUtils { s"Column $colName must be of type $dataType but was actually $actualDataType.$message") } + /** + * Check whether the given schema contains a column of one of the require data types. + * @param colName column name + * @param dataTypes required column data types + */ + def checkColumnTypes( + schema: StructType, + colName: String, + dataTypes: Seq[DataType], + msg: String = ""): Unit = { + val actualDataType = schema(colName).dataType + val message = if (msg != null && msg.trim.length > 0) " " + msg else "" + require(dataTypes.exists(actualDataType.equals), + s"Column $colName must be of type equal to one of the following types: " + + s"${dataTypes.mkString("[", ", ", "]")} but was actually of type $actualDataType.$message") + } + /** * Appends a new column to the input schema. This fails if the given output column already exists. * @param schema input schema