PySpark错误:输入路径不存在 [英] PySpark Error: Input path does not exist

问题描述

我正在尝试使用PySpark进行数据转换.

I am trying to perform data transformations using PySpark.

我有一个带有数据的文本文件(CHANGES.txt)

I have a text file with data(CHANGES.txt)

我能够执行以下命令:

RDDread = sc.textFile("file:///home/test/desktop/CHANGES.txt")

但是当我跑步时: RDDread.first()

然后我得到了错误:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/srv/spark/python/pyspark/rdd.py", line 1328, in first
    rs = self.take(1)
  File "/srv/spark/python/pyspark/rdd.py", line 1280, in take
    totalParts = self.getNumPartitions()
  File "/srv/spark/python/pyspark/rdd.py", line 356, in getNumPartitions
    return self._jrdd.partitions().size()
  File "/srv/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py", line 1133, in __call__
  File "/srv/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/srv/spark/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o256.partitions.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/home/test/desktop/CHANGES.txt
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:287)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
    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$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:60)
    at org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:45)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    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:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:745)

似乎是提到文件路径不存在.我该如何解决.我在Linux机器上安装了python，Java和spark.

It seems that is mentions the file path does not exist. How can I resolve this. I have python, Java, and spark installed on my linux machine.

推荐答案

如果以集群模式运行，则需要在同一共享文件系统的所有节点上复制文件.然后spark会读取该文件，否则您应该使用HDFS

If your running in a clustered mode you need to copy the file across all the nodes of same shared file system. Then spark reads that file otherwise you should use HDFS

我将txt文件复制到HDFS中，而spark从HDFS中获取文件.

I copied txt file into HDFS and spark takes file from HDFS.

我将txt文件复制到所有节点的共享文件系统上，然后开始读取该文件.

I copied txt file on the shared filesystem of all nodes then spark read that file.

都为我工作

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