将csv导入pyspark数据帧时出错

Question

我正在使用conda环境，通过ssh/PyCharm在远程主机上运行python代码。
尝试将csv文件导入PySpark数据帧时，如下所示

from pyspark.sql import SparkSession
url = "https://github.com/BigDaMa/COCOA/raw/master/dataset/movie.csv"
self.spark = SparkSession.builder.getOrCreate() 
df = self.spark.read.format("csv").load(url)

我收到以下错误消息：

Traceback (most recent call last):
  File "/home/meike/anaconda3/envs/py3/lib/python3.9/site-packages/pyspark/sql/utils.py", line 111, in deco
    return f(*a, **kw)
  File "/home/meike/anaconda3/envs/py3/lib/python3.9/site-packages/py4j/protocol.py", line 326, in get_return_value
    raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o28.load.
: java.lang.UnsupportedOperationException
    at org.apache.hadoop.fs.http.AbstractHttpFileSystem.listStatus(AbstractHttpFileSystem.java:91)
    at org.apache.hadoop.fs.http.HttpsFileSystem.listStatus(HttpsFileSystem.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$1(TraversableLike.scala:238)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at scala.collection.TraversableLike.map(TraversableLike.scala:238)
    at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
    at scala.collection.AbstractTraversable.map(Traversable.scala:108)
    at org.apache.spark.util.HadoopFSUtils$.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:581)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:417)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:325)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$3(DataFrameReader.scala:307)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:307)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:239)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:566)
    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.GatewayConnection.run(GatewayConnection.java:238)
    at java.base/java.lang.Thread.run(Thread.java:829)

我已成功地将相同的csv导入熊猫数据框，这里没有问题。
我还能够创建一个空数据框并手动填充它

我在StackOverflow上找到了this，但作为评论员之一，我需要能够使用PySpark进行调试。我不能简单地使用spark submit在终端中运行代码

我还尝试导入findspark并添加MySQL包，但这并不能解决问题

有什么想法吗？如果需要更多信息，我很乐意添加

附言： 这些是我收到的一些警告，但它们并没有阻止我的代码运行到目前为止

Connected to pydev debugger (build 212.4746.96)
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/home/meike/anaconda3/envs/py3/lib/python3.9/site-packages/pyspark/jars/spark-unsafe_2.12-3.1.2.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
21/08/23 23:07:06 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark´s default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).

缴费灵： 我还通过将csv复制到与main.py相同的目录并“从本地”读取来导入csv。但是脚本是用一个URL作为输入来执行的。为什么不起作用

Answer 1

您不能从url将csv直接加载到pyspark中。试试这个：

url = "https://github.com/BigDaMa/COCOA/raw/master/dataset/movie.csv"
from pyspark import SparkFiles
spark.sparkContext.addFile(url)
df = spark.read.csv("file://"+SparkFiles.get("movie.csv"), header=True, inferSchema= True)

另一种方法是通过pandas读取url，然后创建spark数据帧：

import pandas as pd
df = spark.createDataFrame(pd.read_csv(url)))