EMR中PySpark读取HDFS CSV文件报错：An error occurred while calling o32.csv

我在HDFS中存储了一个CSV文件，尝试通过EMR上的PySpark脚本将其加载至Spark DataFrame，但出现报错：

py4j.protocol.Py4JJavaError: An error occurred while calling o32.csv 

我的实现代码：

df = spark.read.csv("http://localhost:9870/foo/tsla_202210_min.csv", schema = stockSchema)

请问是否是文件路径设置有误？

完整报错信息：

File "/home/hadoop/.local/lib/python3.7/site-packages/pyspark/sql/readwriter.py", line 535, in csv
    return self._df(self._jreader.csv(self._spark._sc._jvm.PythonUtils.toSeq(path)))
  File "/home/hadoop/.local/lib/python3.7/site-packages/py4j/java_gateway.py", line 1322, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/home/hadoop/.local/lib/python3.7/site-packages/pyspark/sql/utils.py", line 190, in deco
    return f(*a, **kw)
  File "/home/hadoop/.local/lib/python3.7/site-packages/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o32.csv.
: java.lang.UnsupportedOperationException
    at org.apache.hadoop.fs.http.AbstractHttpFileSystem.listStatus(AbstractHttpFileSystem.java:95)
    at org.apache.hadoop.fs.http.HttpFileSystem.listStatus(HttpFileSystem.java:23)
    at org.apache.spark.util.HadoopFSUtils$.listLeafFiles(HadoopFSUtils.scala:225)
    at org.apache.spark.util.HadoopFSUtils$.$anonfun$parallelListLeafFilesInternal$1(HadoopFSUtils.scala:95)
    at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at scala.collection.TraversableLike.map(TraversableLike.scala:286)
    at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
    at scala.collection.AbstractTraversable.map(Traversable.scala:108)
    at org.apache.spark.util.HadoopFSUtils$.parallelListLeafFilesInternal(HadoopFSUtils.scala:85)
    at org.apache.spark.util.HadoopFSUtils$.parallelListLeafFiles(HadoopFSUtils.scala:69)
    at org.apache.spark.sql.execution.datasources.InMemoryFileIndex$.bulkListLeafFiles(InMemoryFileIndex.scala:158)
    at org.apache.spark.sql.execution.datasources.InMemoryFileIndex.listLeafFiles(InMemoryFileIndex.scala:131)
    at org.apache.spark.sql.execution.datasources.InMemoryFileIndex.refresh0(InMemoryFileIndex.scala:94)
    at org.apache.spark.sql.execution.datasources.InMemoryFileIndex.<init>(InMemoryFileIndex.scala:66)
    at org.apache.spark.sql.execution.datasources.DataSource.createInMemoryFileIndex(DataSource.scala:567)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:409)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:228)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:210)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:210)
    at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:537)
    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:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.lang.Thread.run(Thread.java:750)

我已尝试修改EMR上HDFS的地址和端口，但问题仍未解决。

问题核心是你误用了HDFS的HTTP WebUI端口（9870）读取文件，Spark无法通过HTTP协议操作HDFS文件系统，必须使用HDFS的RPC协议路径。

修改路径格式为以下任一方式即可：

1. 指定完整HDFS协议路径（替换<namenode-hostname>为实际NameNode主机名）：

df = spark.read.csv("hdfs://<namenode-hostname>:8020/foo/tsla_202210_min.csv", schema = stockSchema)

2. 集群内部直接使用绝对路径（EMR默认配置了HDFS为默认文件系统）：

df = spark.read.csv("/foo/tsla_202210_min.csv", schema = stockSchema)

3. 简化的HDFS协议路径：

df = spark.read.csv("hdfs:///foo/tsla_202210_min.csv", schema = stockSchema)

补充说明 #

• 9870是HDFS NameNode的Web控制台端口，仅用于浏览器查看HDFS状态，不能用来读取文件。
• EMR集群中HDFS的默认RPC端口是8020，若你修改过端口，替换为对应端口即可。
• 集群内节点访问HDFS时，直接使用绝对路径就能自动识别HDFS文件系统，无需额外指定协议和主机名。

内容的提问来源于stack exchange，提问作者AnthonyK