如何创建地图数据集

Question

我正在使用Spark 2.2，并且在尝试在Map Seq上调用spark.createDataset时遇到麻烦。

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)))

我已经尝试过import spark.implicits._，尽管我相当确定这是由 Spark shell 会话隐式导入的。

这是电流编码器未涵盖的情况吗？

Answer 1

2.2 中没有涉及它，但可以轻松解决。您可以使用 ExpressionEncoder 显式添加所需的Encoder：

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]])

或implicitly ：

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

Answer 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，截至此提交）。

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的一部分。

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，并尝试使用上述表达式（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
                          ^