帶狀態的更新是使用的updateStateByKey方法，裡面傳入一個函式，函式要自己寫，注意需要設定checkpoint

import org.apache.spark.streaming.kafka.KafkaUtils
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.{SparkConf, SparkContext}

/**
  * 需要設定checkpoint
  * 有狀態的計算
  */
class UpdataByKey {

}
object UpdataByKey{
    //自定義函式進行帶狀態更新
  def addFunc (currValue:Seq[Int],point:Option[Int])={
    Some(currValue.sum+point.getOrElse(0));
  }

  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("UpdataByKey").setMaster("local[*]")
    val sc = new SparkContext(conf)
    val ssc = new StreamingContext(sc,Seconds(10))
    val topics = "xiaopeng";
    val topicMap = topics.split(",").map((_,2)).toMap
    val lines = KafkaUtils.createStream(ssc,"192.168.10.219:2181","han",topicMap)
    val words = lines.flatMap(line =>line._2.split(" ")).map(word =>(word,1))
    words.updateStateByKey[Int](addFunc _)
    words.print()
    ssc.start()
    ssc.awaitTermination()
  }
}