5

我正在使用 Spark 2.2,在尝试spark.createDataset调用Seq.Map

我的 Spark Shell 会话的代码和输出如下:

// createDataSet on Seq[T] where T = Int works
scala> spark.createDataset(Seq(1, 2, 3)).collect
res0: Array[Int] = Array(1, 2, 3)

scala> spark.createDataset(Seq(Map(1 -> 2))).collect
<console>:24: error: Unable to find encoder for type stored in a Dataset.  
Primitive types (Int, String, etc) and Product types (case classes) are 
supported by importing spark.implicits._
Support for serializing other types will be added in future releases.
       spark.createDataset(Seq(Map(1 -> 2))).collect
                          ^

// createDataSet on a custom case class containing Map works
scala> case class MapHolder(m: Map[Int, Int])
defined class MapHolder

scala> spark.createDataset(Seq(MapHolder(Map(1 -> 2)))).collect
res2: Array[MapHolder] = Array(MapHolder(Map(1 -> 2)))

我试过import spark.implicits._了,虽然我相当肯定这是由 Spark shell 会话隐式导入的。

这是当前编码器未涵盖的情况吗?

4

2 回答 2

7

它不在 2.2 中涵盖,但可以很容易地解决。您可以显式添加 required Encoderusing ExpressionEncoder

import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder  
import org.apache.spark.sql.Encoder

spark
  .createDataset(Seq(Map(1 -> 2)))(ExpressionEncoder(): Encoder[Map[Int, Int]])

implicitly

implicit def mapIntIntEncoder: Encoder[Map[Int, Int]] = ExpressionEncoder()
spark.createDataset(Seq(Map(1 -> 2)))
于 2017-10-16T21:13:11.827 回答
2

仅供参考,上述表达式仅适用于 Spark 2.3(如果我没记错的话,截至本次提交)。

scala> spark.version
res0: String = 2.3.0

scala> spark.createDataset(Seq(Map(1 -> 2))).collect
res1: Array[scala.collection.immutable.Map[Int,Int]] = Array(Map(1 -> 2))

我认为这是因为newMapEncoder现在是spark.implicits.

scala> :implicits
...
  implicit def newMapEncoder[T <: scala.collection.Map[_, _]](implicit evidence$3: reflect.runtime.universe.TypeTag[T]): org.apache.spark.sql.Encoder[T]

您可以使用以下技巧“禁用”隐式并尝试上述表达式(这将导致错误)。

trait ThatWasABadIdea
implicit def newMapEncoder(ack: ThatWasABadIdea) = ack

scala> spark.createDataset(Seq(Map(1 -> 2))).collect
<console>:26: error: Unable to find encoder for type stored in a Dataset.  Primitive types (Int, String, etc) and Product types (case classes) are supported by importing spark.implicits._  Support for serializing other types will be added in future releases.
       spark.createDataset(Seq(Map(1 -> 2))).collect
                          ^
于 2018-05-04T20:41:37.350 回答