PySpark错误：“输入路径不存在”

Alexis Eggermont 发表于 Dev

亚历克西斯·埃格蒙特

我是Spark的新手，我用Python编写代码。

严格按照我的“ Learning Spark”指南，我看到“您不需要安装Hadoop即可运行Spark”

但是，当我仅尝试使用Pyspark对一个文件中的行进行计数时，会出现以下错误。我想念什么？

>>> 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)

>>>

哈维尔·科尔特霍索（Javier Cortejoso）

我没有尝试在Windows系统中运行spark，但是在我看来，问题是：

py4j.protocol.Py4JJavaError：调用o26.collect时发生错误。：org.apache.hadoop.mapred.InvalidInputException：输入路径不存在：fil e：/ 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，如果从bin（即：）运行pyspark，则C:\spark\bin必须将其引用为：lines = sc.textFile("../README.md")，或使用文件的绝对路径。