3、Flink Source(文件、socket、集合）

DataSource：是程序的数据源输入，可以通过StreamExecutionEnvironment.addSource(sourceFuntion)为程序添加一个数据源

import org.apache.flink.streaming.api.scala._

object SourceTest {
  def main(args: Array[String]): Unit = {
    // 创建执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.setParallelism(1)

   
    // 2. 从文件中读取数据
    val resource = getClass.getResource("/test.txt")
    val inputStream = env.readTextFile(resource.getPath)
    // val inputPath = "D:\Projects\BigData\FlinkTutorial\src\main\resources\test.txt"

    val stream = env.readTextFile(inputPath)

  
    stream.print()

    // 执行
    env.execute("source test")
  }
}

nc -l 7777

import org.apache.flink.streaming.api.scala._
import scala.util.Random


object SourceTest {
  def main(args: Array[String]): Unit = {
    // 创建执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.setParallelism(1)
    
    val stream=env.socketTextStream("localhost",7777)

    stream.print()

    // 执行
    env.execute("source test")
  }
}

import org.apache.flink.streaming.api.scala._



object SourceTest {
  def main(args: Array[String]): Unit = {
    // 创建执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.setParallelism(1)

    // 1. 从集合中读取数据
    val dataList = List(
      SensorReading("id_1", 1547718199, 35.8),
      SensorReading("id_6", 1547718201, 15.4),
      SensorReading("id_7", 1547718202, 6.7),
      SensorReading("id_10", 1547718205, 38.1)
    )
    val stream = env.fromCollection(dataList)
    
    // 测试的时候可以方便使用
//    env.fromElements(1.0, 35, "hello")
    
    stream.print()


    // 执行
    env.execute("source test")
  }
}