PySpark错误："输入路径不存在"。

Question

PySpark错误："输入路径不存在"。

7

我是初学者，使用Python编程，想了解Spark相关知识。

按照我的“学习Spark”指南，我看到“你不需要安装Hadoop来运行Spark”。

但是，当我尝试使用Pyspark计算一个文件中的行数时，出现了以下错误。我错过了什么？

>>> lines = sc.textFile("README.md")
15/02/01 13:27:12 INFO MemoryStore: ensureFreeSpace(32728) called with curMem=0,
 maxMem=278019440
15/02/01 13:27:12 INFO MemoryStore: Block broadcast_0 stored as values in memory
 (estimated size 32.0 KB, free 265.1 MB)
>>> lines.count()
15/02/01 13:27:18 WARN NativeCodeLoader: Unable to load native-hadoop library fo
r your platform... using builtin-java classes where applicable
15/02/01 13:27:18 WARN LoadSnappy: Snappy native library not loaded
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 847, in co
unt
    return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 838, in su
m
    return self.mapPartitions(lambda x: [sum(x)]).reduce(operator.add)
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 759, in re
duce
    vals = self.mapPartitions(func).collect()
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 723, in co
llect
    bytesInJava = self._jrdd.collect().iterator()
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\lib\py4j-0.8.2.1-src.zip\py4j\ja
va_gateway.py", line 538, in __call__
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\lib\py4j-0.8.2.1-src.zip\py4j\pr
otocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o26.collect.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: fil
e:/C:/Spark/spark-1.1.0-bin-hadoop1/bin/README.md
        at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.j
ava:197)
        at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.ja
va:208)
        at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:179)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
        at org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
        at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:5
6)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1135)
        at org.apache.spark.rdd.RDD.collect(RDD.scala:774)
        at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala
:305)
        at org.apache.spark.api.java.JavaRDD.collect(JavaRDD.scala:32)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.lang.reflect.Method.invoke(Unknown Source)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
        at py4j.Gateway.invoke(Gateway.java:259)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:207)
        at java.lang.Thread.run(Unknown Source)

>>> lines.first()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 1167, in f
irst
    return self.take(1)[0]
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\pyspark\rdd.py", line 1126, in t
ake
    totalParts = self._jrdd.partitions().size()
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\lib\py4j-0.8.2.1-src.zip\py4j\ja
va_gateway.py", line 538, in __call__
  File "C:\Spark\spark-1.1.0-bin-hadoop1\python\lib\py4j-0.8.2.1-src.zip\py4j\pr
otocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o20.partitions.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: fil
e:/C:/Spark/spark-1.1.0-bin-hadoop1/bin/README.md
        at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.j
ava:197)
        at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.ja
va:208)
        at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:179)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
        at org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
        at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.sc
ala:50)
        at org.apache.spark.api.java.JavaRDD.partitions(JavaRDD.scala:32)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.lang.reflect.Method.invoke(Unknown Source)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
        at py4j.Gateway.invoke(Gateway.java:259)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:207)
        at java.lang.Thread.run(Unknown Source)

>>>

- Alexis Eggermont

2

您可以更改问题的标题。来自Hadoop的警告可以忽略。这些只是来自Hadoop客户端库的消息，该库仍在使用中，但并不意味着您需要运行Hadoop。Javier的答案是正确的。 - Sean Owen

4个回答

2

这是我在Windows上托管的Spark集群中遇到的错误的解决方案：

加载原始的HVAC.csv文件，使用该函数对其进行解析

data = sc.textFile("wasb:///HdiSamples/SensorSampleData/hvac/HVAC.csv")

我们使用(wasb:///)来允许Hadoop访问Azure博客存储文件，三个斜杠是相对于正在运行的节点容器文件夹的引用。

例如：如果在Spark集群仪表板中的文件资源管理器中，您的文件路径为：

sflcc1\sflccspark1\HdiSamples\SensorSampleData\hvac

因此，描述路径如下： sflcc1：是存储帐户的名称。 sflccspark：是群集节点名称。

因此，我们使用相对的三个斜杠来引用当前群集节点名称。

希望这可以帮助到您。

- Mostafa

1

我有点晚了。我遇到了类似的问题（ec2 spark集群）。在我的情况下，hdfs没有我要找的文件。因此，我必须使用以下命令手动添加我想要的文件。

~/ephemeral-hdfs/bin/hadoop fs -put /dir/filename.txt filename.txt

希望那有所帮助。

- Rahul

1

我遇到了同样的问题，并通过以下方式解决了它

scala> val textFile = spark.read.textFile("file:///usr/local/spark-3.1.2/README.md")
textFile: org.apache.spark.sql.Dataset[String] = [value: string]

- zhuguowei

网页内容由stack overflow 提供, 点击上面的

可以查看英文原文，
原文链接

- Javier Cortejoso · Accepted Answer

我还没有尝试在Windows系统中运行Spark, 但我觉得问题可能是: py4j.protocol.Py4JJavaError: 调用 o26.collect 时发生错误。: org.apache.hadoop.mapred.InvalidInputException: 输入路径不存在: file:/C:/Spark/spark-1.1.0-bin-hadoop1/bin/README.md

您必须正确引用要加载的文件。如果您从Spark文件夹（即：C:\spark）运行Pyspark，则 lines = sc.textFile("README.md") 是正确的。但是，如果您从bin（即：C:\spark\bin）运行Pyspark，则必须将它引用为：lines = sc.textFile("../README.md") 或使用文件的绝对路径。