没有阶段正在运行,但numRunningTasks!=0

WARN ExecutorAllocationManager:没有阶段正在运行,但 numRunningTasks!=0

来自Spark的内部 code 我发现了这个:

    // 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
      }
    }

有人能解释一下吗?

我正在谈论Id为0的任务。

我可以报告,在Spark的MLlib中 KMeans() 哪里 the one of the two samples 据说完成任务更少。我不确定这项工作是否会失败。。

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100米点,256个维度。

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