spark - 加入一对多关系数据帧

The*_*0s3 6 apache-spark

让我们采取以下玩具问题,我有以下案例类:

case class Order(id: String, name: String, status: String)
case class TruncatedOrder(id: String)
case class Org(name: String, ord: Seq[TruncatedOrder])
Run Code Online (Sandbox Code Playgroud)

我现在有了以下定义的变量

val ordersDF = Seq(Order("or1", "stuff", "shipped"), Order("or2", "thigns", "delivered") , Order("or3", "thingamabobs", "never received"), Order("or4", "???", "what?")).toDS()
val orgsDF = Seq(Org("tupper", Seq(TruncatedOrder("or1"), TruncatedOrder("or2"), TruncatedOrder("or3"))), Org("ware", Seq(TruncatedOrder("or3"), TruncatedOrder("or4")))).toDS()  
Run Code Online (Sandbox Code Playgroud)

我想要的是例如具有如下的数据点
Ord("tupper", Array(Joined("or1", "stuff", "shipped"), Joined("or2", "things", "delivered"), ...)

我想知道如何格式化我的join语句和过滤语句.

The*_*0s3 3

这是我如何将数据转换为我想要的格式的方法。这个答案受到@ulrich 和@Mariusz 提供的答案的很大启发。

val ud = udf((col: String, name: String, status: String) => { Seq(col, name, status)})

orgsDF
  .select($"name".as("ordName"),explode($"ord.id"))
  .join(ordersDF, $"col" === $"id").drop($"id")
  .select($"ordName", ud($"col", $"name", $"status"))
  .groupBy($"ordName")
  .agg(collect_set($"order"))
  .show()

    +-------+--------------------------------------------------------------------------------------------------------------------------+
    |ordName|orders                                                                                                                    |
    +-------+--------------------------------------------------------------------------------------------------------------------------+
    |ware   |[WrappedArray(or4, ???, what?), WrappedArray(or3, thingamabobs, never received)]                                          |
    |tupper |[WrappedArray(or1, stuff, shipped), WrappedArray(or2, thigns, delivered), WrappedArray(or3, thingamabobs, never received)]|
    +-------+--------------------------------------------------------------------------------------------------------------------------+
Run Code Online (Sandbox Code Playgroud)