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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