我希望从一系列事件中投射出一个潜在的非常大的状态。这就是我如何以一种强制性的方式实现这一点：

class ImperativeFooProcessor {

  val state: mutable.Map[UUID, BarState] = mutable.HashMap.empty[UUID, BarState]

  def handle(event: InputEvent) = {
    event match {
      case FooAdded(fooId, barId) => {
        // retrieve relevant state and do some work on it
        val barState = state(barId)

        // let the world know about what may have happened
        publish(BarOccured(fooId, barId))
        // or maybe rather
        publish(BazOccured(fooId, barId))
      }
      case FooRemoved(fooId, barId) => {
        // retrieve relevant state and do some work on it
        val barState = state(barId)

        // let the world know about what may have happened
        publish(BarOccured(fooId, barId))
        // or maybe rather
        publish(BazOccured(fooId, barId))
      }
    }
  }

  private def publish(event: OutputEvent): Unit = {
    // push event to downstream sink
  }
}

在最坏的情况下，barstate的大小将随着它被用户提及的次数而增长 FooAdded 相对于每个barid的事件总数，唯一barid的数量非常少。
我将如何开始在flink中表示这个处理结构？
如何处理每个巴态都可能变得非常大的事实？