累加器

1.累加器

object AccCode {
  def main(args: Array[String]): Unit = {
    val sparkConf = new SparkConf().setMaster("local[2]").setAppName("sum")
    val sc = new SparkContext(sparkConf)
    val accumulator = sc.longAccumulator("word_seconds")
    val rdd:RDD[String] = sc.textFile("hdfs://node1:9000/wc.txt")
    val flatmap = rdd.flatMap((line: String) => {
      val wordArray = line.split(" ")
      accumulator.add(wordArray.length)
      wordArray
    })
    flatmap.collect()
    // RDD中一共有 20 个单词
    println(s"RDD中一共有 ${accumulator.value} 个单词")
    sc.stop()
  }
}

2. 自定义累加器

• MyAccumulator.scala

package accumulator
 
import org.apache.spark.util.AccumulatorV2
 
/*
继承AccumulatorV2类，
传递两个泛型，第一个泛型代表的是累加器add的时候传递数据类型
第二泛型代表的是累加器最终value给你返回的数据类型
 */
class MyAccumulator extends AccumulatorV2[Int, Int] {
  // 自定义的累加器属性   累加器的累加值
  var sum: Int = 0
 
  /**
   * 判断累加器是否为空的
   * @return
   */
  override def isZero: Boolean = {
    if (sum == 0) {
      true
    } else {
      false
    }
  }
 
  /**
   * 先在每一个分区累加数据
   * 将每一个分区累加器的结果复制到driver节点合并，
   * 调用copy方法给driver节点传递一个分区累加器
   * @return
   */
  override def copy(): AccumulatorV2[Int, Int] = {
    val myAccumulator = new MyAccumulator()
    myAccumulator.sum = sum
    myAccumulator
  }
 
  /**
   * 重置累加器
   */
  override def reset(): Unit = {
    sum = 0
  }
 
  /**
   * 每一个分区如果取增加累加器的值
   * @param v 累加器输入的类型
   */
  override def add(v: Int): Unit = {
    sum += v
  }
 
  /**
   * 核心，每个分区累加器执行完成，
   * 最后需要将多个分区累加器的结果合并
   * @param other
   */
  override def merge(other: AccumulatorV2[Int, Int]): Unit = {
    val accumulator = other.asInstanceOf[MyAccumulator]
    sum = sum + accumulator.sum
  }
 
  /**
   * 获取累加的值
   * @return
   */
  override def value: Int = {
    sum
  }
}

• AccCode.scala

object AccCode {
  def main(args: Array[String]): Unit = {
    val sparkConf = new SparkConf().setMaster("local[2]").setAppName("sum")
    val sc = new SparkContext(sparkConf)
    // val accumulator = sc.longAccumulator("word_seconds")
    // 设置自定义累加器
    val accumulator = new MyAccumulator()
    sc.register(accumulator)
    val rdd:RDD[String] = sc.textFile("hdfs://node1:9000/wc.txt")
    val flatmap = rdd.flatMap((line: String) => {
      val wordArray = line.split(" ")
      accumulator.add(wordArray.length)
      wordArray
    })
    flatmap.collect()
    // RDD中一共有 20 个单词
    println(s"RDD中一共有 ${accumulator.value} 个单词")
    sc.stop()
  }
}