本地环境下使用PySpark读取S3中CSV文件的配置问题

环境与操作步骤 #

• 通过Homebrew安装Apache Spark 3.5.1
• 下载Hadoop AWS连接器jar包，将其复制到/opt/homebrew/Cellar/apache-spark/3.5.1/libexec/jars目录
• 执行以下代码尝试读取S3存储桶中的CSV文件：

import pyspark.sql.functions as F
import pyspark.sql.types as T

from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("Base Spark Template").getOrCreate()
spark.sparkContext.setLogLevel("WARN")

df2 = spark.read.csv("s3://arapbi/polygon/tickers/", header=True)

第一次报错信息 #

Py4JJavaError: An error occurred while calling o40.csv.
: org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme "s3"
    at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3443)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3466)
    at org.apache.hadoop.fs.FileSystem.access$300(FileSystem.java:174)
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3574)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3521)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:540)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:365)
    at org.apache.spark.sql.execution.datasources.DataSource$.$anonfun$checkAndGlobPathIfNecessary$1(DataSource.scala:724)
    at scala.collection.immutable.List.map(List.scala:293)
    at org.apache.spark.sql.execution.datasources.DataSource$.checkAndGlobPathIfNecessary(DataSource.scala:722)
    at org.apache.spark.sql.execution.datasources.DataSource.checkAndGlobPathIfNecessary(DataSource.scala:551)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:404)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:211)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
    at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:538)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:568)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
    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.base/java.lang.Thread.run(Thread.java:840)

关键问题：Spark无法识别S3协议。原本以为将连接器jar包放入Spark jars目录即可正常识别，此前用相同步骤配置Google Storage连接器时可以正常工作。怀疑是不是选错了Jar包，或者整体配置方式有误。已搜索谷歌和Stack Overflow但未找到解决方案，求成功配置过Homebrew版PySpark连接S3的方法。

2024年4月4日更新 #

将代码中的路径修改为s3a://arapbi/polygon/tickers/后，报错信息变化，但问题仍未解决：

Py4JJavaError: An error occurred while calling o68.csv.
: java.lang.NoClassDefFoundError: software/amazon/awssdk/core/exception/SdkException
    at java.base/java.lang.Class.forName0(Native Method)
    at java.base/java.lang.Class.forName(Class.java:467)
    at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:2625)
    at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2590)
    at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2686)
    at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3431)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3466)
    at org.apache.hadoop.fs.FileSystem.access$300(FileSystem.java:174)
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3574)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3521)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:540)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:365)
    at org.apache.spark.sql.execution.streaming.FileStreamSink$.hasMetadata(FileStreamSink.scala:53)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:366)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:211)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
    at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:538)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:568)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.base/java.lang.Thread.run(Thread.java:840)
Caused by: java.lang.ClassNotFoundException: software.amazon.awssdk.core.exception.SdkException
    at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)
    at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)
    at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:525)
    ... 31 more

内容的提问来源于stack exchange，提问作者Evan Volgas