IDEA Spark Streaming Flume数据源 --解决无法转化为实际输入数据，及中文乱码(Scala)

需要三步：

1.shell：往 1234 端口写数据

nc localhost 1234

2.shell： 启动flume服务

cd /usr/local2/flume/bin

./flume-ng agent --conf /usr/local2/flume/conf -f /usr/local2/flume/conf/flume-to-spark.conf  --name a1

3.IDEA：

import org.apache.spark.SparkConf
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.flume.FlumeUtils
import org.apache.spark.streaming.{Seconds, StreamingContext}

object DStream_Flume_source {
  def main(args: Array[String]): Unit = {
    val host="localhost"
    val port=
    val setIntervalTime=Seconds()
    val sparkConf=new SparkConf().setAppName("flume 数据源").setMaster("local[2]")
    val ssc=new StreamingContext(sparkConf,setIntervalTime)
    val stream=FlumeUtils.createStream(ssc,host,port,StorageLevel.MEMORY_ONLY_SER_2)
        stream.count().map(x=>"收到"+x+"个 flume events").print()
    val words=stream.flatMap(x=>new String(x.event.getBody.array()).split(" ")).map(x=>(x,))
         words.reduceByKey((x,y)=>x+y).print()
      ssc.start()
    ssc.awaitTermination()
  }

}

在IDEA中可以看到输入的数据，中文也可以照常显示

/usr/local2/flume/conf/flume-to-spark.conf：

     a1.sources = r1
        a1.sinks = k1
        a1.channels = c1

        # Describe/configure the source
        a1.sources.r1.type = netcat
        a1.sources.r1.bind = localhost
        a1.sources.r1.port = 

        # Describe the sink
        a1.sinks.k1.type = avro
        a1.sinks.k1.hostname = localhost
        a1.sinks.k1.port = 

        # Use a channel which buffers events in memory
        a1.channels.c1.type = memory
        a1.channels.c1.capacity =
        a1.channels.c1.transactionCapacity = 

        # Bind the source and sink to the channel
        a1.sources.r1.channels = c1
        a1.sinks.k1.channel = c1

注意整个启动顺序：IDEA>>>>shell2>>>>shell1 否则报错