apache-spark - 如何使用数据集进行分组

Question

我有一个使用 rdd 的请求:

val test = Seq(("New York", "Jack"),
    ("Los Angeles", "Tom"),
    ("Chicago", "David"),
    ("Houston", "John"),
    ("Detroit", "Michael"),
    ("Chicago", "Andrew"),
    ("Detroit", "Peter"),
    ("Detroit", "George")
  )
sc.parallelize(test).groupByKey().mapValues(_.toList).foreach(println)

结果是:

(New York,List(Jack))

(Detroit,List(Michael, Peter, George))

(Los Angeles,List(Tom))

(Houston,List(John))

(Chicago,List(David, Andrew))

如何在 spark2.0 中使用数据集？
我有自定义函数的使用方法，但是感觉好复杂，有没有简单点的方法？

Answer 1

我建议您从创建 case class 开始作为

case class Monkey(city: String, firstName: String)

此 case class应该在主类之外定义。然后你就可以使用 toDS功能及用途groupBy和 aggregation函数调用 collect_list如下

import sqlContext.implicits._
import org.apache.spark.sql.functions._

val test = Seq(("New York", "Jack"),
  ("Los Angeles", "Tom"),
  ("Chicago", "David"),
  ("Houston", "John"),
  ("Detroit", "Michael"),
  ("Chicago", "Andrew"),
  ("Detroit", "Peter"),
  ("Detroit", "George")
)
sc.parallelize(test)
  .map(row => Monkey(row._1, row._2))
  .toDS()
  .groupBy("city")
  .agg(collect_list("firstName") as "list")
  .show(false)

你将有输出

+-----------+------------------------+
|city       |list                    |
+-----------+------------------------+
|Los Angeles|[Tom]                   |
|Detroit    |[Michael, Peter, George]|
|Chicago    |[David, Andrew]         |
|Houston    |[John]                  |
|New York   |[Jack]                  |
+-----------+------------------------+

您可以随时转换回 RDD只需调用 .rdd功能