flink状态编程的例子

package redo.state

import org.apache.flink.api.common.functions.{IterationRuntimeContext, RichFlatMapFunction, RichFunction, RichMapFunction, RuntimeContext}
import org.apache.flink.api.common.state.{ListState, ListStateDescriptor, MapState, MapStateDescriptor, ValueState, ValueStateDescriptor}
import org.apache.flink.api.scala._
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.scala.{DataStream, StreamExecutionEnvironment}
import org.apache.flink.util.Collector


import java.util
case class user(id:String,item:String,group:String,bea:String,timestamp:Long)

object StateTest {
  def main(args: Array[String]): Unit = {
    val eal = StreamExecutionEnvironment.getExecutionEnvironment
    val input_Stream:DataStream[String] = eal.socketTextStream("hadoop101",7777)
    val info = input_Stream.map(x=>{
      val gh = x.split(",").filter(_.nonEmpty)
      user(gh(0),gh(1),gh(2),gh(3), gh(4).toLong)
    })
    val alterStream = info.keyBy(_.id)
    //  .flatMap(new TempChangeAlert(2))
      .flatMapWithState[(String,String,String,String,Long), Long] {
        //值为none返回当前的值
        case (data: user, None) => ( List.empty, Some(data.timestamp) )
        case (data: user, lastTemp: Some[Long]) => {
          // 跟最新的温度值求差值作比较
          val diff = (data.timestamp - lastTemp.get).abs
          if( diff > 10.0 )
            ( List((data.id, data.item,data.group, data.bea,data.timestamp)), Some(data.timestamp) )
          else
            ( List.empty, Some(data.timestamp))
        }
      }
    alterStream.print()

    eal.execute("state test")
  }

}
// 实现自定义RichFlatmapFunction
class TempChangeAlert(threshold: Long) extends RichFlatMapFunction[user, (String, Long,Long)]{
  // 定义状态保存上一次的温度值
  lazy val lastTempState: ValueState[Long] = getRuntimeContext.getState(new ValueStateDescriptor[Long]("last-temp", classOf[Long]))
  lazy val flagState: ValueState[Boolean] = getRuntimeContext.getState(new ValueStateDescriptor[Boolean]("flag", classOf[Boolean]))

  override def flatMap(value: user, out: Collector[(String, Long,Long)]): Unit = {
    // 获取上次的温度值
    val lastTemp = lastTempState.value()

    // 跟最新的温度值求差值作比较
    val diff = (value.timestamp - lastTemp).abs

    println("最后 "+lastTemp+ " 保  持   "+threshold+" "+flagState.value()+ " 绝对值 "+diff)
    /*if( !flagState.value() && diff > threshold )
      out.collect( (value.id, lastTemp, value.timestamp) )*/
    if(  diff > threshold )
      out.collect( (value.id, lastTemp, value.timestamp) )

    // 更新状态
    lastTempState.update(value.timestamp)
    flagState.update(true)
  }
}
class RichMapper extends RichMapFunction[user,String] {
  var valueState: ValueState[Double] = _
  lazy val listState: ListState[Int] = getRuntimeContext.getListState( new ListStateDescriptor[Int]("liststate", classOf[Int]) )
  //lazy val mapState: MapState[String, Double] = getRuntimeContext.getMapState( new MapStateDescriptor[String, Double]("mapstate", classOf[String], classOf[Double]))
  override def map(in: user): String = {
    // 状态的读写
    val myV = valueState.value()
    valueState.update(in.timestamp)
    listState.add(1)
    val list = new util.ArrayList[Int]()
    list.add(2)
    list.add(3)
    listState.addAll(list)
    listState.update(list)
    listState.get()

    in.id

  }

  override def open(parameters: Configuration): Unit = {
    valueState = getRuntimeContext.getState( new ValueStateDescriptor[Double]("valuestate", classOf[Double]))
  }
}