[jira] [Updated] (SPARK-15746) SchemaUtils.checkColumnType with VectorUDT prints instance details in error message

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-15746?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-15746:
---------------------------------
    Labels: bulk-closed  (was: )

> SchemaUtils.checkColumnType with VectorUDT prints instance details in error message
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-15746
>                 URL: https://issues.apache.org/jira/browse/SPARK-15746
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Nick Pentreath
>            Priority: Minor
>              Labels: bulk-closed
>
> 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).



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org