从 pyspark 访问 S3 存储桶中的文件

Posted 2023-04-15

【中文标题】从 pyspark 访问 S3 存储桶中的文件

【英文标题】：Accessing files in S3 bucket from pyspark

【发布时间】：2017-10-20 00:05:41

【问题描述】：

我正在尝试从 pyspark 代码访问存储在 S3 存储桶中的文件。它给了我附加的错误消息。 该程序在处理本地存储的文件时运行良好。 我尝试使用 s3://、s3a:// 和 s3n://，但它们似乎都不起作用。

代码：

ACCESS_KEY = "*********"
SECRET_KEY = "**********"
EncodedSecretKey = SECRET_KEY.replace("/", "%2F")
s3url="s3n://"+ACCESS_KEY+":"+EncodedSecretKey+"@"+bucket_name+"/"+file_name

sqlContext.read.option("delimiter",delimiter).load(s3url, 
                  format='com.databricks.spark.csv', 
                  header='true', 
                  inferSchema='true')

错误信息

    Traceback (most recent call last):
  File "C:\Users\sachari\AppData\Local\Temp\zeppelin_pyspark-5481670497409059953.py", line 367, in <module>
    raise Exception(traceback.format_exc())
Exception: Traceback (most recent call last):
  File "C:\Users\sachari\AppData\Local\Temp\zeppelin_pyspark-5481670497409059953.py", line 355, in <module>
    exec(code, _zcUserQueryNameSpace)
  File "<stdin>", line 14, in <module>
  File "<stdin>", line 10, in get_df
  File "C:\zeppelin\interpreter\spark\pyspark\pyspark.zip\pyspark\sql\readwriter.py", line 149, in load
    return self._df(self._jreader.load(path))
  File "C:\zeppelin\interpreter\spark\pyspark\py4j-0.10.4-src.zip\py4j\java_gateway.py", line 1133, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "C:\zeppelin\interpreter\spark\pyspark\pyspark.zip\pyspark\sql\utils.py", line 63, in deco
    return f(*a, **kw)
  File "C:\zeppelin\interpreter\spark\pyspark\py4j-0.10.4-src.zip\py4j\protocol.py", line 319, in get_return_value
    format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o537.load.
: java.io.IOException: No FileSystem for scheme: s3n
    at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2584)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591)
    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:372)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:370)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
    at scala.collection.immutable.List.flatMap(List.scala:344)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:370)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:135)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
    at java.lang.reflect.Method.invoke(Unknown Source)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Unknown Source)

【问题讨论】：

不要使用s3n。使用方案s3a或s3

Spark read file from S3 using sc.textFile ("s3n://...)的可能重复

【参考方案1】：

你必须加载 aws 包， 对于 pyspark shell，您必须按如下方式加载包，它也可以用于 spark-submit 命令。

 pyspark --packages org.apache.hadoop:hadoop-aws:2.7.1

或

您必须按照以下链接设置凭据。

https://hadoop.apache.org/docs/r2.7.2/hadoop-aws/tools/hadoop-aws/index.html