Jeff,

Thanks for the suggestion. After I switch the URL to s3 an almost identical
exception is now encountered:

java.lang.IllegalArgumentException: AWS Access Key ID and Secret
Access Key must be specified as the username or password
(respectively) of a s3 URL, or by setting the *fs.s3.awsAccessKeyId*
or *fs.s3.awsSecretAccessKey* properties (respectively).



On Mon, Jan 4, 2016 at 12:46 PM, Jeff Quinn <[email protected]> wrote:

> Ah ok, I would try it with "s3://",and I think it should work as expected,
> assuming the machine role you are using for EMR has the proper permissions
> for writing to the bucket.
>
> You should not need to set fs.s3n.awsSecretAccessKey/fs.s3n.awsAccessKeyId
> or any other properties, EMR service should be taking care of that for you.
>
> On Mon, Jan 4, 2016 at 12:22 PM, Yan Yang <[email protected]> wrote:
>
>> Hi Jeff,
>>
>> We are using s3n://bucket/path
>>
>> Thanks
>> Yan
>>
>> On Mon, Jan 4, 2016 at 12:19 PM, Jeff Quinn <[email protected]> wrote:
>>
>>> Hey Yan,
>>>
>>> Just a hunch but from that stacktrace it looks like you might be using
>>> the outdated s3-hadoop filesystem, is the url you are trying to write to of
>>> the form s3://bucket/path or s3n://bucket/path?
>>>
>>> Thanks!
>>>
>>> Jeff
>>>
>>> On Mon, Jan 4, 2016 at 12:15 PM, Yan Yang <[email protected]> wrote:
>>>
>>>> Hi
>>>>
>>>> I have tried to set up a Sparkpipeline to run within AWS EMR.
>>>>
>>>> The code is as below:
>>>>
>>>> SparkConf sparkConf = new SparkConf().setAppName("JavaSparkPi");
>>>> JavaSparkContext jsc = new JavaSparkContext(sparkConf);
>>>> SparkPipeline pipeline = new SparkPipeline(jsc, "spark-app");
>>>>
>>>> PCollection<Input> input = pipeline.read(From.avroFile(inputPaths,
>>>> Input.class));
>>>> PCollection<Output> output = process(input);
>>>> pipeline.write(output, To.avroFile(outputPath));
>>>>
>>>> The read works and a simple spark write such as calling
>>>> saveAsTextFile() on an RDD object also works.
>>>>
>>>> However write using pipeline.write() hits below exceptions. I have
>>>> tried to set fs.s3n.awsAccessKeyId and fs.s3n.awsSecretAccessKey in 
>>>> sparkConf
>>>> with the same result:
>>>>
>>>> java.lang.IllegalArgumentException: AWS Access Key ID and Secret Access 
>>>> Key must be specified as the username or password (respectively) of a s3n 
>>>> URL, or by setting the fs.s3n.awsAccessKeyId or fs.s3n.awsSecretAccessKey 
>>>> properties (respectively).
>>>>    at 
>>>> org.apache.hadoop.fs.s3.S3Credentials.initialize(S3Credentials.java:70)
>>>>    at 
>>>> org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.initialize(Jets3tNativeFileSystemStore.java:80)
>>>>    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>    at 
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>    at 
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>    at java.lang.reflect.Method.invoke(Method.java:606)
>>>>    at 
>>>> org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
>>>>    at 
>>>> org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
>>>>    at org.apache.hadoop.fs.s3native.$Proxy9.initialize(Unknown Source)
>>>>    at 
>>>> org.apache.hadoop.fs.s3native.NativeS3FileSystem.initialize(NativeS3FileSystem.java:326)
>>>>    at 
>>>> org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2644)
>>>>    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:90)
>>>>    at 
>>>> org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2678)
>>>>    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2660)
>>>>    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:374)
>>>>    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
>>>>    at org.apache.avro.mapred.FsInput.<init>(FsInput.java:37)
>>>>    at 
>>>> org.apache.crunch.types.avro.AvroRecordReader.initialize(AvroRecordReader.java:54)
>>>>    at 
>>>> org.apache.crunch.impl.mr.run.CrunchRecordReader.initialize(CrunchRecordReader.java:150)
>>>>    at 
>>>> org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:153)
>>>>    at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:124)
>>>>    at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:65)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>>    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
>>>>    at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>>>    at 
>>>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
>>>>    at 
>>>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>>>>    at org.apache.spark.scheduler.Task.run(Task.scala:88)
>>>>    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>>>    at 
>>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>>>>    at 
>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>>>>    at java.lang.Thread.run(Thread.java:745)
>>>>
>>>> Thanks
>>>> Yan
>>>>
>>>
>>>
>>
>

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