Question

我测试了spark默认的PageRank示例并将迭代设置为1024，然后抛出stackoverflower。我也在我的其他程序中遇到了这个问题。我怎么能解决它。

object SparkPageRank {
  def main(args: Array[String]) {
    if (args.length < 3) {
      System.err.println("Usage: PageRank <master> <file> <number_of_iterations>")
      System.exit(1)
    }
    var iters = args(2).toInt
    val ctx = new SparkContext(args(0), "PageRank",System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass))
    val lines = ctx.textFile(args(1), 1)
    val links = lines.map{ s => val parts = s.split("\\s+")
    (parts(0), parts(1))
    }.distinct().groupByKey().cache()
    var ranks = links.mapValues(v => 1.0)

    for (i <- 1 to iters) {
        val contribs = links.join(ranks).values.flatMap{ case (urls, rank) =>
        val size = urls.size
        urls.map(url => (url, rank / size))
      }
    ranks = contribs.reduceByKey(_ + _).mapValues(0.15 + 0.85 * _)
    }

    val output = ranks.collect()
    output.foreach(tup => println(tup._1 + " has rank: " + tup._2 + "."))

    System.exit(0)
  }
}

我在这里发布错误。

    [spark-akka.actor.default-dispatcher-15] ERROR LocalActorRefProvider(akka://spark) - guardian failed, shutting down system
java.lang.StackOverflowError
    at scala.collection.mutable.FlatHashTable$class.containsEntry(FlatHashTable.scala:119)
    at scala.collection.mutable.HashSet.containsEntry(HashSet.scala:41)
    at scala.collection.mutable.HashSet.contains(HashSet.scala:58)
    at scala.collection.GenSetLike$class.apply(GenSetLike.scala:43)
    at scala.collection.mutable.AbstractSet.apply(Set.scala:45)
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$visit$1(DAGScheduler.scala:312)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$visit$1$1.apply(DAGScheduler.scala:321)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$visit$1$1.apply(DAGScheduler.scala:316)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$visit$1(DAGScheduler.scala:316)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$visit$1$1.apply(DAGScheduler.scala:321)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$visit$1$1.apply(DAGScheduler.scala:316)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$visit$1(DAGScheduler.scala:316)
    at org.apache.spark.scheduler.DAGScheduler.getParentStages(DAGScheduler.scala:326)

Answer 1

这是因为for循环中的这些转换在你的rdd中产生了很长的依赖性。当您尝试运行spark作业时，递归访问您的rdd将导致stackoverflow错误。

要解决此问题，您可以在rdd上使用checkpoint()。 cache()无法帮助您立即评估您的rdd。

因此，您应该在某些迭代后调用中间rdd上的cache()和checkpoint()，并手动评估它以清除其依赖关系。

Answer 2

我的猜测是错误发生，因为中间RDD在collect()之前不会被评估。收集后，他们会递归评估。

尝试添加cache()来评估每次迭代的RDD，它可能会有所帮助：

ranks = contribs.reduceByKey(_ + _).mapValues(0.15 + 0.85 * _).cache

Spark：当迭代太大时，PageRank示例抛出stackoverflowError

2 个答案: