将 ADT/密封特征层次结构编码到 Spark DataSet 列中 [英] Encode an ADT / sealed trait hierarchy into Spark DataSet column

问题描述

如果我想在 Spark DataSet 列，最佳编码策略是什么?

If I want to store an Algebraic Data Type (ADT) (ie a Scala sealed trait hierarchy) within a Spark DataSet column, what is the best encoding strategy?

例如，如果我有一个 ADT，其中叶类型存储不同类型的数据:

For example, if I have an ADT where the leaf types store different kinds of data:

sealed trait Occupation
case object SoftwareEngineer extends Occupation
case class Wizard(level: Int) extends Occupation
case class Other(description: String) extends Occupation

构建一个的最佳方法是什么:

Whats the best way to construct a:

org.apache.spark.sql.DataSet[Occupation]

推荐答案

TL;DR 目前没有好的解决方案，鉴于 Spark SQL/Dataset 的实现，在可预见的未来，不太可能有.

TL;DR There is no good solution right now, and given Spark SQL / Dataset implementation, it is unlikely there will be one in the foreseeable future.

您可以使用通用的kryo 或java 编码器

You can use generic kryo or java encoder

val occupation: Seq[Occupation] = Seq(SoftwareEngineer, Wizard(1), Other("foo"))
spark.createDataset(occupation)(org.apache.spark.sql.Encoders.kryo[Occupation])

但在实践中几乎没有用.

but is hardly useful in practice.

UDT API 目前提供了另一种可能的方法(Spark 1.6、2.0、2.1-SNAPSHOT)，它是私有的，需要相当多的大量样板代码(您可以检查 oasml.linalg.VectorUDT 以查看示例实现).

UDT API provides another possible approach as for now (Spark 1.6, 2.0, 2.1-SNAPSHOT) it is private and requires quite a lot boilerplate code (you can check o.a.s.ml.linalg.VectorUDT to see example implementation).

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