从Spark使用S3a协议访问S3使用Hadoop版本2.7.2

Question

我试图从pyspark（版本2.2.0）访问s3（s3a协议），并且遇到了一些困难。

我正在使用Hadoop和AWS sdk包。

pyspark --packages com.amazonaws:aws-java-sdk-pom:1.10.34,org.apache.hadoop:hadoop-aws:2.7.2 

这里是我的代码如下所示：

sc._jsc.hadoopConfiguration().set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem") 
sc._jsc.hadoopConfiguration().set("fs.s3a.access.key", AWS_ACCESS_KEY_ID) 
sc._jsc.hadoopConfiguration().set("fs.s3a.secret.key", AWS_SECRET_ACCESS_KEY) 

rdd = sc.textFile('s3a://spark-test-project/large-file.csv') 
print(rdd.first().show()) 

我得到这个：

Traceback (most recent call last): 
    File "<stdin>", line 1, in <module> 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/rdd.py", line 1361, in first 
    rs = self.take(1) 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/rdd.py", line 1313, in take 
    totalParts = self.getNumPartitions() 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/rdd.py", line 385, in getNumPartitions 
    return self._jrdd.partitions().size() 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__ 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/sql/utils.py", line 63, in deco 
    return f(*a, **kw) 
    File "/Users/attazadeh/DataEngine/env/lib/python3.4/site-packages/pyspark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value 
py4j.protocol.Py4JJavaError: An error occurred while calling o34.partitions. 
: com.amazonaws.services.s3.model.AmazonS3Exception: Status Code: 400, AWS Service: Amazon S3, AWS Request ID: 32750D3DED4067BD, AWS Error Code: null, AWS Error Message: Bad Request, S3 Extended Request ID: jAhO0tWTblPEUehF1Bul9WZj/9G7woaHFVxb8gzsOpekam82V/Rm9zLgdLDNsGZ6mPizGZmo6xI= 
    at com.amazonaws.http.AmazonHttpClient.handleErrorResponse(AmazonHttpClient.java:798) 
    at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:421) 
    at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232) 
    at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528) 
    at com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1031) 
    at com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994) 
    at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:297) 
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669) 
    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94) 
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703) 
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685) 
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373) 
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295) 
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:258) 
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229) 
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315) 
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:194) 
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) 
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) 
    at scala.Option.getOrElse(Option.scala:121) 
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) 
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) 
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) 
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) 
    at scala.Option.getOrElse(Option.scala:121) 
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) 
    at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:61) 
    at org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:45) 
    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: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(Thread.java:748) 

这是与AWS的Java SDK中的错误？我是新来的火花，所以我不知道是否有办法从AWS以外的地方获得更好的日志信息AWS Error Code: null

Answer 1

对于它的价值，我在aws的spark-defaults.conf文件中有这条线：

spark.jars.packages com.amazonaws:aws-java-sdk:1.11.99,org.apache.hadoop:hadoop-aws:2.7.2 

我还确保我在设置EC2时使用的安全组可以访问s3。

这两件事情之后，我已经没有问题，从S3读取文件：

%pyspark 
df = spark.read.csv("s3a://my_bucket/name/") 

另外，如果您使用AWS EMR，你应该能够访问S3开箱的：

%pyspark 
df = spark.read.csv("s3://my_bucket/name/") 

Answer 2

“不好的请求”是来自S3的恐惧信息，意思是“这不起作用，我们不会告诉你为什么”。

在the docs中有关于S3A故障排除的整段内容。

如果您的存储桶只有一个只支持S3“v4”auth协议（frankfurt，london，seoul）的人托管，那么您需要将fs.s3a.endpoint字段设置为特定区域的文档... doc有细节。

否则，请尝试使用s3a://landsat-pds/scene_list.gz作为来源。这是一个不需要身份验证的公共CSV文件。如果你看不到它，那么你会遇到严重的麻烦