[jira] [Created] (SPARK-15746) SchemaUtils.checkColumnType with VectorUDT prints instance details

["Nick Pentreath (JIRA)" <ji...@apache.org>]

Nick Pentreath created SPARK-15746:
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             Summary: SchemaUtils.checkColumnType with VectorUDT prints instance details
                 Key: SPARK-15746
                 URL: https://issues.apache.org/jira/browse/SPARK-15746
             Project: Spark
          Issue Type: Improvement
          Components: ML
            Reporter: Nick Pentreath
            Priority: Minor


Currently, many feature transformers in {{ml}} use {{SchemaUtils.checkColumnType(schema, ..., new VectorUDT)}} to check the column type is a ({{ml.linalg}}) vector.

The resulting error message contains "instance" info for the {{VectorUDT}}, i.e. something like this:
{code}
java.lang.IllegalArgumentException: requirement failed: Column features must be of type org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7 but was actually StringType.
{code}

A solution would either be to amend {{SchemaUtils.checkColumnType}} to print the error message using {{getClass.getName}}, or to create a {{private[spark] case object VectorUDT extends VectorUDT}} for convenience, since it is used so often (and incidentally this would make it easier to put {{VectorUDT}} into lists of data types e.g. schema validation, UDAFs etc).



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