我正在使用Apache Spark 2.0，并为DataSet创建case class以提及模式。 当我尝试根据如何在Dataset中存储自定义对象? 定义自定义编码器时，对于java.time.LocalDate，我遇到了以下异常：
java.lang.UnsupportedOperationException: No Encoder found for java.time.LocalDate
- field (class: "java.time.LocalDate", name: "callDate")
- root class: "FireService"
at org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor(ScalaReflection.scala:598)
at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$9.apply(ScalaReflection.scala:592)
at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$9.apply(ScalaReflection.scala:583)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
............
以下是代码：
case class FireService(callNumber: String, callDate: java.time.LocalDate)
implicit val localDateEncoder: org.apache.spark.sql.Encoder[java.time.LocalDate] = org.apache.spark.sql.Encoders.kryo[java.time.LocalDate]
val fireServiceDf = df.map(row => {
val dateFormatter = java.time.format.DateTimeFormatter.ofPattern("MM/dd /yyyy")
FireService(row.getAs[String](0), java.time.LocalDate.parse(row.getAs[String](4), dateFormatter))
})
df.map.. 将对象映射为二进制，如下所示：implicit val fireServiceEncoder: org.apache.spark.sql.Encoder[FireService] = org.apache.spark.sql.Encoders.kryo[FireService]
val fireServiceDf = df.map(row => {
val dateFormatter = java.time.format.DateTimeFormatter.ofPattern("MM/dd/yyyy")
FireService(row.getAs[String](0), java.time.LocalDate.parse(row.getAs[String](4), dateFormatter))
})
fireServiceDf: org.apache.spark.sql.Dataset[FireService] = [value: binary]
我期望得到FireService的地图，但返回的是地图的二进制数据。