[大数据]10-flink-1.10.1- flink Sink api 输出算子

1 flink sink

?2 file sink

package com.study.liucf.unbounded.sink

import com.study.liucf.bean.LiucfSensorReding
import org.apache.flink.api.common.serialization.SimpleStringEncoder
import org.apache.flink.core.fs.Path
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink
import org.apache.flink.streaming.api.scala._

/**
 * @Author liucf
 * @Date 2021/9/13
 */
object FileSink {
  def main(args: Array[String]): Unit = {
    //创建flink执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    //读取数据
    val inputStream: DataStream[String] = env.readTextFile("src\\main\\resources\\sensor.txt")
    //转换数据类型 string 类型转换成LiucfSensorReding,求最小值
    val ds = inputStream.map(r=>{
      val arr = r.split(",")
      LiucfSensorReding(arr(0),arr(1).toLong,arr(2).toDouble)
    })
    //输出到控制台
    ds.print()
    //输出到文件
//    ds
//      .writeAsCsv("src\\main\\resources\\sensor.csv")
//      .setParallelism(1)//默认会分布式并行执行根据多少并行度生成多少文件，这里我让它生成一个文件
    ds.addSink(StreamingFileSink.forRowFormat(
      new Path("src\\main\\resources\\sensor2.csv"),
      new SimpleStringEncoder[LiucfSensorReding]()
    ).build())
    //可见writeAsCSV已经被弃用了
    //启动flink执行
    env.execute("liucf sink api")
  }
}