在 PySpark 中使用来自 GitHub 的 csv

Question

通常，要读取本地

.csv

文件，我使用这个：

from pyspark.sql import SparkSession
spark = SparkSession.builder \
    .appName("github_csv") \
        .getOrCreate()
df = spark.read.csv("path_to_file", inferSchema = True)

但是尝试使用 github 中

csv

原始文件的链接时，我收到以下错误：

url_github = r"https://raw.githubusercontent.com/AISCIENCES/course-master-big-data-with-pyspark-and-aws/main/Code/03-Spark%20DFs/StudentData.csv"
df = spark.read.csv(url_github, inferSchema = True)

#Error
Py4JJavaError: An error occurred while calling o47.csv.
: java.lang.UnsupportedOperationException
    at org.apache.hadoop.fs.http.AbstractHttpFileSystem.listStatus(AbstractHttpFileSystem.java:94)
    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$1(TraversableLike.scala:286)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(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:565)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:409)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:274)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$3(DataFrameReader.scala:245)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:245)
    at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:571)
    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:748)

Answer 1

无法从驱动程序访问外部数据。有一些解决方法，例如简单地使用 pandas：

import pandas as pd

url_github = 'https://raw.githubusercontent.com/AISCIENCES/course-master-big-data-with-pyspark-and-aws/main/Code/03-Spark%20DFs/StudentData.csv'


pd_df = pd.read_csv(url_github)
spark_df = spark.createDataFrame(pd_df)

spark_df.limit(5).show()

+---+------+----------------+------+-----+-----+--------------------+
|age|gender|            name|course| roll|marks|               email|
+---+------+----------------+------+-----+-----+--------------------+
| 28|Female| Hubert Oliveras|    DB| 2984|   59|Annika Hoffman_Na...|
| 29|Female|Toshiko Hillyard| Cloud|12899|   62|Margene Moores_Ma...|
| 28|  Male|  Celeste Lollis|    PF|21267|   45|Jeannetta Golden_...|
| 29|Female|    Elenore Choy|    DB|32877|   29|Billi Clore_Mitzi...|
| 28|  Male|  Sheryll Towler|   DSA|41487|   41|Claude Panos_Judi...|
+---+------+----------------+------+-----+-----+--------------------+

Answer 2

让您用 SparkFiles 尝试一下。它适用于我任何需要从 github 获取 csv 的时候

from pyspark import SparkFiles
url_github = 'https://raw.githubusercontent.com/AISCIENCES/course-master-big-data-with-pyspark-and-aws/main/Code/03-Spark%20DFs/StudentData.csv'

spark.sparkContext.addFile(url_github)
df = spark.read.csv(SparkFiles.get("StudentData.csv"),inferSchema=True, header=True)
df.show()