Question

我在s3上有一个名为“mybucket”的桶。我曾经能够使用pyspark来加载文件，例如：

>>> rdd = sc.wholeTextFiles('s3n://mybucket/mydirectory/*.txt')
>>> rdd.count()
108

有效。

现在，当我执行完全相同的操作时，我得到以下java.lang.NullPointerException错误而不是获取文件数：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/root/spark/python/pyspark/rdd.py", line 1008, in count
    return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
  File "/root/spark/python/pyspark/rdd.py", line 999, in sum
    return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
  File "/root/spark/python/pyspark/rdd.py", line 873, in fold
    vals = self.mapPartitions(func).collect()
  File "/root/spark/python/pyspark/rdd.py", line 776, in collect
    port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
  File "/root/spark/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
  File "/root/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/root/spark/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.lang.NullPointerException
    at org.apache.hadoop.fs.s3native.NativeS3FileSystem.listStatus(NativeS3FileSystem.java:479)
    at org.apache.hadoop.fs.Globber.listStatus(Globber.java:69)
    at org.apache.hadoop.fs.Globber.glob(Globber.java:217)
    at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:1642)
    at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:291)
    at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:263)
    at org.apache.spark.input.WholeTextFileInputFormat.setMinPartitions(WholeTextFileInputFormat.scala:55)
    at org.apache.spark.rdd.WholeTextFileRDD.getPartitions(WholeTextFileRDD.scala:49)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:53)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1911)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:893)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:892)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:211)
    at java.lang.Thread.run(Thread.java:748)

停止和启动导致此错误的群集时可能会发生什么变化？我使用这个小脚本启动，停止并登录ec2：

#!/bin/bash

if [[ "$1" =~ ^(login|start|stop)$ ]]; then
    /usr/local/spark/spark-ec2/spark-ec2 -k aws1 --identity-file=/home/myusername/mydirectory/aws1.pem --region=us-west-2 --zone=us-west-2a --copy-aws-credentials "$1" my_cluster
else
    echo "\"$1\" is not a valid command"
fi

重启ec2集群后，我无法再从s3读取数据

0 个答案: