java - 相同的 Scala 和 Java spark 函数产生不同的结果

Question

我根据 Spark 快速入门指南执行了用 Java 编写的简单代码:

public static void main(String[] args) {
        SparkConf conf = new SparkConf().setAppName("Simple Application").setMaster("local[4]");
        JavaSparkContext sc = new JavaSparkContext(conf);
        Accumulator<Integer> counter = sc.accumulator(0);
        List<Integer> data = Arrays.asList(1, 2, 3, 4, 5);
        JavaRDD<Integer> rdd = sc.parallelize(data);
        rdd.foreach(counter::add);
        System.out.println("Counter value " + counter);
}

它按预期打印 "Counter value 15"。我有用 Scala 编写的具有相同逻辑的代码:

object Counter extends App {
    val conf = new SparkConf().setAppName("Simple Application").setMaster("local[4]")
    val sc = new SparkContext(conf)
    val counter = sc.accumulator(0)
    val data = Array(1, 2, 3, 4, 5)
    val rdd = sc.parallelize(data)
    rdd.foreach(x => counter += x)
    println(s"Counter value: $counter")
}

但它每次都打印不正确的结果 (<15)。我的 Scala 代码有什么问题？

Java spark lib "org.apache.spark:spark-core_2.10:1.6.1"
Scala spark lib "org.apache.spark" %% "spark-core" % "1.6.1"

Answer 1

quick-start 中的建议文档说:

Note that applications should define a main() method instead of extending scala.App. Subclasses of scala.App may not work correctly.

也许这就是问题所在？

尝试:

object Counter {
    def main(args: Array[String]): Unit = {
      val conf = new SparkConf().setAppName("Simple Application").setMaster("local[4]")
      val sc = new SparkContext(conf)
      val counter = sc.accumulator(0)
      val data = Array(1, 2, 3, 4, 5)
      val rdd = sc.parallelize(data)
      rdd.foreach(x => counter += x)
      println(s"Counter value: $counter")
    }
}