PairDStreamFunctions.updateStateByKey

updateState by key 可用于根据即将到来的数据创建有状态的 DStream。它需要一个功能：

object UpdateStateFunctions {
  def updateState(current: Seq[Double], previous: Option[StatCounter]) = {
    previous.map(s => s.merge(current)).orElse(Some(StatCounter(current)))
  }
}

它接受一系列 current 值，一个先前状态的 Option 并返回更新状态的 Option。把这一切放在一起：

import org.apache.spark._
import org.apache.spark.streaming.dstream.DStream
import scala.collection.mutable.Queue
import org.apache.spark.util.StatCounter
import org.apache.spark.streaming._

object UpdateStateByKeyApp {
  def main(args: Array[String]) {

    val sc = new SparkContext("local", "updateStateByKey", new SparkConf())
    val ssc = new StreamingContext(sc, Seconds(10))
    ssc.checkpoint("/tmp/chk")

    val queue = Queue(
      sc.parallelize(Seq(("foo", 5.0), ("bar", 1.0))),
      sc.parallelize(Seq(("foo", 1.0), ("foo", 99.0))),
      sc.parallelize(Seq(("bar", 22.0), ("foo", 1.0))),
      sc.emptyRDD[(String, Double)],
      sc.emptyRDD[(String, Double)],
      sc.emptyRDD[(String, Double)],
      sc.parallelize(Seq(("foo", 1.0), ("bar", 1.0)))
    )

    val inputStream: DStream[(String, Double)] = ssc.queueStream(queue)

    inputStream.updateStateByKey(UpdateStateFunctions.updateState _).print()

    ssc.start()
    ssc.awaitTermination()
    ssc.stop()
  }
}