如何重命名通过 Apache Spark 中的 GroupedDataset 操作创建的新列？

Question

如何在不将结果转换为 DataFrame 的情况下重命名 count 操作的列？

case class LogRow(id: String, location: String, time: Long)
case class KeyValue(key: (String, String), value: Long)

val log = LogRow("1", "a", 1) :: LogRow("1", "a", 2) :: LogRow("1", "b", 3) :: LogRow("1", "a", 4) :: LogRow("1", "b", 5) :: LogRow("1", "b", 6) :: LogRow("1", "c", 7) :: LogRow("2", "a", 1) :: LogRow("2", "b", 2) :: LogRow("2", "b", 3) :: LogRow("2", "a", 4) :: LogRow("2", "a", 5) :: LogRow("2", "a", 6) :: LogRow("2", "c", 7) :: Nil
log.toDS().groupBy(l => {
  (l.id, l.location)
}).count().toDF().toDF("key", "value").as[KeyValue].show

+-----+-----+
|  key|value|
+-----+-----+
|[1,a]|    3|
|[1,b]|    3|
|[1,c]|    1|
|[2,a]|    4|
|[2,b]|    2|
|[2,c]|    1|
+-----+-----+

Answer 1

直接映射到需要的类型即可：

log.toDS.groupBy(l => {
  (l.id, l.location)
}).count.as[KeyValue]