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https://issues.apache.org/jira/browse/SPARK-3572?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14182389#comment-14182389
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Apache Spark commented on SPARK-3572:
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User 'jkbradley' has created a pull request for this issue:
https://github.com/apache/spark/pull/2919
> Support register UserType in SQL
> --------------------------------
>
> Key: SPARK-3572
> URL: https://issues.apache.org/jira/browse/SPARK-3572
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Reporter: Xiangrui Meng
> Assignee: Joseph K. Bradley
>
> If a user knows how to map a class to a struct type in Spark SQL, he should
> be able to register this mapping through sqlContext and hence SQL can figure
> out the schema automatically.
> {code}
> trait RowSerializer[T] {
> def dataType: StructType
> def serialize(obj: T): Row
> def deserialize(row: Row): T
> }
> sqlContext.registerUserType[T](clazz: classOf[T], serializer:
> classOf[RowSerializer[T]])
> {code}
> In sqlContext, we can maintain a class-to-serializer map and use it for
> conversion. The serializer class can be embedded into the metadata, so when
> `select` is called, we know we want to deserialize the result.
> {code}
> sqlContext.registerUserType(classOf[Vector], classOf[VectorRowSerializer])
> val points: RDD[LabeledPoint] = ...
> val features: RDD[Vector] = points.select('features).map { case Row(v:
> Vector) => v }
> {code}
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