spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-19425) Make df.except work for UDT
Date Wed, 01 Feb 2017 15:20:51 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19425?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-19425:
------------------------------------

    Assignee:     (was: Apache Spark)

> Make df.except work for UDT
> ---------------------------
>
>                 Key: SPARK-19425
>                 URL: https://issues.apache.org/jira/browse/SPARK-19425
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.1.0
>            Reporter: Liang-Chi Hsieh
>
> DataFrame.except doesn't work for UDT columns. It is because ExtractEquiJoinKeys will
run Literal.default against UDT. However, we don't handle UDT in Literal.default and an exception
will throw like:
> java.lang.RuntimeException: no default for type 
> org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7
>   at org.apache.spark.sql.catalyst.expressions.Literal$.default(literals.scala:179)
>   at org.apache.spark.sql.catalyst.planning.ExtractEquiJoinKeys$$anonfun$4.apply(patterns.scala:117)
>   at org.apache.spark.sql.catalyst.planning.ExtractEquiJoinKeys$$anonfun$4.apply(patterns.scala:110)
> We should simply skip using the columns whose types don't provide default literal as
joining key.



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

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


Mime
View raw message