我正在尝试在以独立模式设置的 2 节点集群上运行一个简单的 python 应用程序。一个主人和一个工人，而主人也扮演着工人的角色。
在下面的代码中，我试图计算 500MB 文本文件中出现的蛋糕数量，但它因 ExecutorLostFailure 而失败。
有趣的是，如果我采用 100MB 的输入文件，应用程序就会运行。
我将 CDH5.4.4 的包版本与 YARN 一起使用，并且正在运行 Spark 1.3.0。每个节点都有 8GB 内存，这些是我的一些配置：
- 执行器内存：4g
- 驱动内存：2g
- 每个工人的核心数：1
- 序列化器：Kryo
简单应用程序.py：
from pyspark import SparkContext, SparkConf
sc = SparkContext(appName="Simple App")
logFile = "/user/ubuntu/largeTextFile500m.txt"
logData = sc.textFile(logFile)
cakes = logData.filter(lambda s: "cake" in s).count()
print "Number of cakes: %i" % cakes
sc.stop()
提交申请：
spark-submit --master spark://master:7077 /home/ubuntu/SimpleApp.py
日志摘录：
15/08/13 09:04:59 WARN ThreadLocalRandom: Failed to generate a seed from SecureRandom within 3 seconds. Not enough entrophy?
...
15/08/13 09:05:09 ERROR TaskSchedulerImpl: Lost executor 1 on master: remote Akka client disassociated
15/08/13 09:05:09 INFO TaskSetManager: Re-queueing tasks for 1 from TaskSet 0.0
15/08/13 09:05:09 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, master): ExecutorLostFailure (executor 1 lost)
...
15/08/13 09:05:09 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 1
...
15/08/13 09:05:13 ERROR TaskSchedulerImpl: Lost executor 0 on worker: remote Akka client disassociated
15/08/13 09:05:13 INFO TaskSetManager: Re-queueing tasks for 0 from TaskSet 0.0
15/08/13 09:05:13 WARN TaskSetManager: Lost task 0.1 in stage 0.0 (TID 5, worker): ExecutorLostFailure (executor 0 lost)
...
15/08/13 09:05:13 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 0
...
15/08/13 09:05:21 ERROR TaskSchedulerImpl: Lost executor 2 on master: remote Akka client disassociated
15/08/13 09:05:21 INFO TaskSetManager: Re-queueing tasks for 2 from TaskSet 0.0
15/08/13 09:05:21 WARN TaskSetManager: Lost task 0.2 in stage 0.0 (TID 6, master): ExecutorLostFailure (executor 2 lost)
...
15/08/13 09:05:21 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 2
...
15/08/13 09:05:29 ERROR TaskSchedulerImpl: Lost executor 3 on worker: remote Akka client disassociated
15/08/13 09:05:29 INFO TaskSetManager: Re-queueing tasks for 3 from TaskSet 0.0
15/08/13 09:05:29 WARN TaskSetManager: Lost task 0.3 in stage 0.0 (TID 7, worker): ExecutorLostFailure (executor 3 lost)
...
15/08/13 09:05:29 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 3
...
15/08/13 09:05:29 INFO DAGScheduler: Job 0 failed: count at /home/ubuntu/SimpleApp.py:6, took 28.156765 s
Traceback (most recent call last):
File "/home/ubuntu/Michael/SimpleApp2.py", line 6, in
cakes = logData.filter(lambda s: "cake" in s).count()
File "/usr/lib/spark/python/pyspark/rdd.py", line 933, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "/usr/lib/spark/python/pyspark/rdd.py", line 924, in sum
return self.mapPartitions(lambda x: [sum(x)]).reduce(operator.add)
File "/usr/lib/spark/python/pyspark/rdd.py", line 740, in reduce
vals = self.mapPartitions(func).collect()
File "/usr/lib/spark/python/pyspark/rdd.py", line 701, in collect
bytesInJava = self._jrdd.collect().iterator()
File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError15/08/13 09:05:29 INFO DAGScheduler: Executor lost: 3 (epoch 3)
15/08/13 09:05:29 INFO BlockManagerMasterActor: Trying to remove executor 3 from BlockManagerMaster.
15/08/13 09:05:29 INFO AppClient$ClientActor: Executor updated: app-20150813090456-0000/5 is now RUNNING
15/08/13 09:05:29 INFO BlockManagerMasterActor: Removing block manager BlockManagerId(3, worker, 4075)
: An error occurred while calling o41.collect.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 7, worker): ExecutorLostFailure (executor 3 lost)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1203)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1191)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1191)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
15/08/13 09:05:29 INFO BlockManagerMaster: Removed 3 successfully in removeExecutor
15/08/13 09:05:29 INFO AppClient$ClientActor: Executor updated: app-20150813090456-0000/5 is now LOADING
15/08/12 15:23:28 DEBUG DFSClient: DFSClient seqno: 20 status: SUCCESS status: SUCCESS downstreamAckTimeNanos: 857203
numAs = logData.filter(lambda s: "cake" in s).count()
File "/usr/lib/spark/python/pyspark/rdd.py", line 933, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "/usr/lib/spark/python/pyspark/rdd.py", line 924, in sum
return self.mapPartitions(lambda x: [sum(x)]).reduce(operator.add)
File "/usr/lib/spark/python/pyspark/rdd.py", line 740, in reduce
vals = self.mapPartitions(func).collect()
File "/usr/lib/spark/python/pyspark/rdd.py", line 701, in collect
bytesInJava = self._jrdd.collect().iterator()
File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o43.collect.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 4, master): ExecutorLostFailure (executor 4 lost)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1203)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1191)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1191)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
有什么建议么？