[jira] [Created] (SPARK-14023) Make descriptions in exceptions thrown consistent regarding fields and columns

["Jacek Laskowski (JIRA)" <ji...@apache.org>]

Jacek Laskowski created SPARK-14023:
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             Summary: Make descriptions in exceptions thrown consistent regarding fields and columns
                 Key: SPARK-14023
                 URL: https://issues.apache.org/jira/browse/SPARK-14023
             Project: Spark
          Issue Type: Improvement
          Components: MLlib
    Affects Versions: 2.0.0
            Reporter: Jacek Laskowski
            Priority: Minor


As you can see below, a column is called a field depending on where an exception is thrown. I think it should be "column" everywhere (since that's what has a type from a schema).

{code}
scala> lr
res32: org.apache.spark.ml.regression.LinearRegression = linReg_d9bfe808e743

scala> lr.fit(ds)
java.lang.IllegalArgumentException: Field "features" does not exist.
  at org.apache.spark.sql.types.StructType$$anonfun$apply$1.apply(StructType.scala:214)
  at org.apache.spark.sql.types.StructType$$anonfun$apply$1.apply(StructType.scala:214)
  at scala.collection.MapLike$class.getOrElse(MapLike.scala:128)
  at scala.collection.AbstractMap.getOrElse(Map.scala:59)
  at org.apache.spark.sql.types.StructType.apply(StructType.scala:213)
  at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:40)
  at org.apache.spark.ml.PredictorParams$class.validateAndTransformSchema(Predictor.scala:50)
  at org.apache.spark.ml.Predictor.validateAndTransformSchema(Predictor.scala:71)
  at org.apache.spark.ml.Predictor.transformSchema(Predictor.scala:116)
  at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:67)
  at org.apache.spark.ml.Predictor.fit(Predictor.scala:89)
  ... 51 elided

scala> lr.fit(ds)
java.lang.IllegalArgumentException: requirement failed: Column label must be of type DoubleType but was actually StringType.
  at scala.Predef$.require(Predef.scala:219)
  at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:42)
  at org.apache.spark.ml.PredictorParams$class.validateAndTransformSchema(Predictor.scala:53)
  at org.apache.spark.ml.Predictor.validateAndTransformSchema(Predictor.scala:71)
  at org.apache.spark.ml.Predictor.transformSchema(Predictor.scala:116)
  at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:67)
  at org.apache.spark.ml.Predictor.fit(Predictor.scala:89)
  ... 51 elided

{code}



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