apache-spark – 没有正在运行的阶段,但numRunningTasks！= 0

2023年7月26日 439次阅读

我的任务完成了,我得到了计算RDD的预期结果.我正在运行一个交互式PySpark
shell.我想了解这个警告意味着什么：

WARN ExecutorAllocationManager: No stages are running, but
numRunningTasks != 0

从Spark的内部code我发现：

    // If this is the last stage with pending tasks, mark the scheduler queue as empty
    // This is needed in case the stage is aborted for any reason
    if (stageIdToNumTasks.isEmpty) {
      allocationManager.onSchedulerQueueEmpty()
      if (numRunningTasks != 0) {
        logWarning("No stages are running, but numRunningTasks != 0")
        numRunningTasks = 0
      }
    }

有人可以解释一下吗？

我说的是Id 0的任务.

《apache-spark – 没有正在运行的阶段,但numRunningTasks！= 0》

我可以使用KMeans()报告使用Spark的MLlib体验此行为,其中the one of the two samples据说完成的任务较少.我不确定这份工作是否会失败……

2  takeSample at KMeans.scala:355 2016/08/27 21:39:04   7 s 1/1 9600/9600
1  takeSample at KMeans.scala:355 2016/08/27 21:38:57   6 s 1/1 6608/9600

输入集为100m点,256维.

PySpark的一些参数：master是yarn,mode是cluster,

spark.dynamicAllocation.enabled             false
# Better serializer - https://spark.apache.org/docs/latest/tuning.html#data-serialization
spark.serializer                            org.apache.spark.serializer.KryoSerializer
spark.kryoserializer.buffer.max             2000m

# Bigger PermGen space, use 4 byte pointers (since we have < 32GB of memory)
spark.executor.extraJavaOptions             -XX:MaxPermSize=512m -XX:+UseCompressedOops

# More memory overhead
spark.yarn.executor.memoryOverhead          4096
spark.yarn.driver.memoryOverhead            8192

spark.executor.cores                        8
spark.executor.memory                       8G

spark.driver.cores                          8
spark.driver.memory                         8G
spark.driver.maxResultSize                  4G

最佳答案 我们得到的是这段代码：

    ...
    // If this is the last stage with pending tasks, mark the scheduler queue as empty
    // This is needed in case the stage is aborted for any reason
    if (stageIdToNumTasks.isEmpty) {
      allocationManager.onSchedulerQueueEmpty()
      if (numRunningTasks != 0) {
        logWarning("No stages are running, but numRunningTasks != 0")
        numRunningTasks = 0
      }
    }
  }
}

来自Spark的GitHub,评论是目前为止最好的解释.

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