我在HDFS中有一个csv文件，并试图将其加载到Spark数据框架中，使用EMR中的pyspark和python脚本。
我得到以下错误(完整错误在末尾)
py4j.protocol.Py4JJavaError: An error occurred while calling o32.csv
我是这样做的
df = spark.read.csv("http://localhost:9870/foo/tsla_202210_min.csv", schema = stockSchema)
我是否在文件路径中设置了错误的内容?
完全错误
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)
尝试更改EMR上查找HDFS的地址和端口，但仍然没有运气
原来我错误地设置了文件路径。了解了如何按照本文正确设置它
专门
与其他文件系统不同，要从HDFS访问文件，您需要提供Hadoop名称节点路径，您可以在Hadoop配置文件夹下的Hadoop core-site.xml文件中找到它。在此文件中查找fs.defaultFS属性并从该属性中选择值。例如，您将拥有以下格式的值。从fs.defaultFS属性中替换nn1home和port。
从那里，找到.xml，我使用这个