Spark实例

1、入门

object HelloSpark {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("Simple Application").setMaster("local")
    val sc = new SparkContext(conf)
    sc.addJar("C:\Users\asus\IdeaProjects\HelloSpark\target\HelloSpark-1.0-SNAPSHOT.jar")

    val res = sc.textFile("D://info.log").map(line => {
      val f = line.split("	")
      (f(1),1)
    }).reduceByKey(_+_).map(x => {
      val host = new URL(x._1).getHost
      (host,x._2)
    }).filter(_._1 == "java").sortBy(_._2,false).saveAsTextFile("D://out2")
    //println(res)D

    sc.stop()
  }
}

2、Parallelize

object H{
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("Simple Application").setMaster("local")
    val sc = new SparkContext(conf)
    val a = sc.parallelize(List((
      "A",90,27
    ),(
      "B",91,22
    ),(
      "C",90,25
    ))).sortBy(x => Girl(x._2,x._3),false).collect().toBuffer
    println(a)
  }
}

case class Girl(val a:Int,val b:Int) extends Ordered[Girl] with Serializable{
  override def compare(that: Girl): Int = {
    if(this.a == that.a){
      that.b - this.b
    } else {
      this.a - that.a
    }
  }
}

3、Spark Streaming（Socket）

object SocketSparkStreaming{
  val updateFunc = (iter: Iterator[(String, Seq[Int], Option[Int])]) => {
    //iter.flatMap(it=>Some(it._2.sum + it._3.getOrElse(0)).map(x=>(it._1,x)))
    //iter.map{case(x,y,z)=>Some(y.sum + z.getOrElse(0)).map(m=>(x, m))}
    iter.map(t => (t._1, t._2.sum + t._3.getOrElse(0)))
  }
  def main(args: Array[String]): Unit = {
    LoggerLevels.setStreamingLogLevels()
    val conf = new SparkConf().setAppName("Spark Streaming").setMaster("local[2]")
    val sc = new SparkContext(conf)
    sc.setCheckpointDir("d://ck")
    val ssc = new StreamingContext(sc,Seconds(5))
    val rdd = ssc.socketTextStream("192.168.1.101",8888)
    val res = rdd.flatMap(_.split(" ")).map((_,1)).updateStateByKey(updateFunc,new HashPartitioner(sc.defaultParallelism),true)
    res.print()
    ssc.start()
    ssc.awaitTermination()
  }
}

4、Spark Streaming（Flume）

object FlumeSparkStreaming{
  def main(args: Array[String]): Unit = {
    LoggerLevels.setStreamingLogLevels()
    val conf = new SparkConf().setAppName("Spark Streaming").setMaster("local[2]")
    val sc = new SparkContext(conf)
    sc.setCheckpointDir("d://ck")
    val ssc = new StreamingContext(sc,Seconds(5))
    val address = Seq(new InetSocketAddress("192.168.1.101",8888))
    val flumeStream = FlumeUtils.createPollingStream(ssc,address,StorageLevel.MEMORY_AND_DISK_SER)
    val words = flumeStream.flatMap(x => new String(x.event.getBody.array()).split(" ")).map((_,1))
    val result = words.reduceByKey(_+_)
    result.print()
    ssc.start()
    ssc.awaitTermination()
  }
}

5、Kafka WordCount

object KafkaWordCount{
  val updateFunc = (iter: Iterator[(String, Seq[Int], Option[Int])]) => {
    //iter.flatMap(it=>Some(it._2.sum + it._3.getOrElse(0)).map(x=>(it._1,x)))
    //iter.map{case(x,y,z)=>Some(y.sum + z.getOrElse(0)).map(m=>(x, m))}
    iter.map(t => (t._1, t._2.sum + t._3.getOrElse(0)))
  }
  def main(args: Array[String]): Unit = {
    LoggerLevels.setStreamingLogLevels()
    val Array(zkQuorum,group,topics,numThreads) = args
    val conf = new SparkConf().setAppName("Spark Streaming").setMaster("local[2]")
    val ssc = new StreamingContext(conf,Seconds(5))
    ssc.checkpoint("d://ckkafka")
    val topicMap = topics.split(",").map((_,numThreads.toInt)).toMap
    val result = KafkaUtils.createStream(ssc,zkQuorum,group,topicMap).map(_._2)
      .flatMap(_.split(" ")).map((_,1))
      .updateStateByKey(updateFunc,new HashPartitioner(
        ssc.sparkContext.defaultParallelism),rememberPartitioner = true)
    result.print()
    ssc.start()
    ssc.awaitTermination()
  }
}

6、窗口函数

object WindowFunc{
  def main(args: Array[String]): Unit = {
    LoggerLevels.setStreamingLogLevels()
    val conf = new SparkConf().setAppName("Spark Streaming").setMaster("local[2]")
    val ssc = new StreamingContext(conf,Seconds(5))
    ssc.checkpoint("d://ck")
    val lines = ssc.socketTextStream("192.168.1.101",8888)
    val result = lines.flatMap(_.split(" ")).map((_,1)).reduceByKeyAndWindow(
      (a:Int,b:Int) => (a+b),
      Seconds(15),
      Seconds(5)
    )
    result.print()
    ssc.start()
    ssc.awaitTermination()
  }
}