Question

我正在使用带有Spark 2.0预览版的Databricks Community Edition。我尝试了以下（简单）代码：

import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql.Encoder
import java.util.Calendar
import spark.implicits._

case class C1(f1: String, f2: String, f3: String, f4:java.sql.Date, f5: Double)
val teams = sc.parallelize(Seq(C1("hash1", "NLC", "Cubs", Java.sql.Date.valueOf("2016-01-23"), 3253.21), C1("hash1", "NLC", "Cubs", java.sql.Date.valueOf("2014-01-23"), 353.88), C1("hash3", "NLW", "Dodgers", java.sql.Date.valueOf("2013-08-15"), 4322.12),C1("hash4", "NLE", "Red Sox", java.sql.Date.valueOf("2010-03-14"), 10283.72))).toDS

object C1Agg extends Aggregator[C1, Seq[C1], Seq[C1]]  {
  def zero: Seq[C1] = Seq.empty[C1] //Nil
  def reduce(b: Seq[C1], a: C1): Seq[C1] = b :+ a
  def merge(b1: Seq[C1], b2: Seq[C1]): Seq[C1] = b1 ++ b2
  def finish(r: Seq[C1]): Seq[C1] = r

  override def bufferEncoder: Encoder[Seq[C1]] = newProductSeqEncoder[C1]
  override def outputEncoder: Encoder[Seq[C1]] = newProductSeqEncoder[C1]
}
val g_c1 = teams.groupByKey(_.f1).agg[Seq[C1]](C1Agg.toColumn).collect

我收到以下错误消息：

错误：类型不匹配;
  发现：org.apache.spark.sql.TypedColumn [C1，Seq [C1]]
  必需：org.apache.spark.sql.TypedColumn [C1，Seq [C1]]
  val g_c1 = teams.groupByKey（_。f1）.aggSeq [C1]

当我使用

时

val g_c1 = teams.groupByKey(_.f1).agg(C1Agg.toColumn).collect

我明白了：

错误：类型不匹配;
  发现：org.apache.spark.sql.TypedColumn [C1，Seq [C1]]
  必需：org.apache.spark.sql.TypedColumn [C1，？]
  val g_c1 = teams.groupByKey（_。f1）.aggSeq [C1]

任何提示？

Answer 1

我找到了原因：这是因为我在一个单元格（笔记本）上声明了案例类，然后在不同的后续单元格中使用它。

将整个代码放在同一个单元格中可以解决这个问题。（不幸的是，现在我面临另一个问题MissingRequirementError）

SparkSQL聚合器：类型不匹配错误

1 个答案: