Hi Tom,
Ian - Thanks for the detailed analysis. It was these issues that lead
me to create a temporary file in NativeS3FileSystem in the first
place. I think we can get NativeS3FileSystem to report progress
though, see https://issues.apache.org/jira/browse/HADOOP-5814.
Ken - I can't see why you would be getting that error. Does it work
with hadoop fs, but not hadoop distcp?
Neither worked, unfortunately.
See my original email re my first attempt using hadoop fs - the
result was similar to when I tried hadoop distcp. Seemed to be
working, then hung.
Eventually I copied the files to my master node's local disk, then
our ops guy used s3cmd to push the files to S3.
-- Ken
On Sat, May 9, 2009 at 6:48 AM, Nowland, Ian <nowl...@amazon.com> wrote:
Hi Tom,
Not creating a temp file is the ideal as it saves you from having
to "waste" using the local hard disk by writing an output file just
before uploading same to Amazon S3. There are a few problems though:
1) Amazon S3 PUTs need the file length up front. You could use a
chunked POST, but then you have the disadvantage of having to
Base64 encode all your data, increasing bandwidth usage, and also
you still have the next problems;
2) You would still want to have MD5 checking. In Amazon S3 both
PUT and POST require the MD5 to be supplied before the contents. To
work around this then you would have to upload the object without
MD5, then check its metadata to make sure the MD5 is correct, then
delete it if it is not. This is all possible, but would be
difficult to make bulletproof, whereas in the current version, if
the MD5 is different the PUT fails atomically and you can easily
just retry.
3) Finally, you would have to be careful in reducers that output
only very rarely. If there is too big a gap between data being
uploaded through the socket, then S3 may determine the connection
has timed out, closing the connection and meaning your task has to
rerun (perhaps just to hit the same problem again).
All of this means that the current solution may be best for now as
far as general upload. The best I think we can so is fix the fact
that the task is not progressed in close(). The best way I can see
to do this is introducing a new interface say called
ExtendedClosable which defines a close(Progressable p) method.
Then, have the various clients of FileSystem output streams (e.g.
Distcp, TextOutputFormat) test if their DataOutputStream supports
the interface, and if so call this in preference to the default. In
the case of NativeS3FileSystem then, this method spins up a thread
to keep the Progressable updated as the upload progresses.
As an additional optimization to Distcp, where the source file
already exists we could have some extended interface say
ExtendedWriteFileSystem that has a create() method that takes the
MD5 and the file size, then test for this interface in the Distcp
mapper call the extended method. The trade off here is the fact
that the checksum HDFS stored is not the MD5 needed by S3, and so
two (perhaps distributed) reads would be needed so the tradeoff is
these two distributed reads vs a distributed read and a local write
then local read.
What do you think?
Cheers,
Ian Nowland
Amazon.com
-----Original Message-----
From: Tom White [mailto:t...@cloudera.com]
Sent: Friday, May 08, 2009 1:36 AM
To: core-user@hadoop.apache.org
Subject: Re: HDFS to S3 copy problems
Perhaps we should revisit the implementation of NativeS3FileSystem so
that it doesn't always buffer the file on the client. We could have an
option to make it write directly to S3. Thoughts?
Regarding the problem with HADOOP-3733, you can work around it by
setting fs.s3.awsAccessKeyId and fs.s3.awsSecretAccessKey in your
hadoop-site.xml.
Cheers,
Tom
On Fri, May 8, 2009 at 1:17 AM, Andrew Hitchcock <adpow...@gmail.com> wrote:
Hi Ken,
S3N doesn't work that well with large files. When uploading a file to
>> S3, S3N saves it to local disk during write() and then uploads to S3
during the close(). Close can take a long time for large files and it
doesn't report progress, so the call can time out.
As a work around, I'd recommend either increasing the timeout or
uploading the files by hand. Since you only have a few large files,
you might want to copy the files to local disk and then use something
like s3cmd to upload them to S3.
Regards,
Andrew
On Thu, May 7, 2009 at 4:42 PM, Ken Krugler
<kkrugler_li...@transpac.com> wrote:
Hi all,
I have a few large files (4 that are 1.8GB+) I'm trying to copy
from HDFS to
S3. My micro EC2 cluster is running Hadoop 0.19.1, and has one master/two
slaves.
>>> I first tried using the hadoop fs -cp command, as in:
hadoop fs -cp output/<dir>/ s3n://<bucket>/<dir>/
This seemed to be working, as I could walk the network traffic spike, and
temp files were being created in S3 (as seen with CyberDuck).
But then it seemed to hang. Nothing happened for 30 minutes, so
I killed the
command.
>>>
Then I tried using the hadoop distcp command, as in:
hadoop distcp hdfs://<host>:50001/<path>/<dir>/ s3://<public key>:<private
key>@<bucket>/<dir2>/
This failed, because my secret key has a '/' in it
(http://issues.apache.org/jira/browse/HADOOP-3733)
Then I tried using hadoop distcp with the s3n URI syntax:
hadoop distcp hdfs://<host>:50001/<path>/<dir>/ s3n://<bucket>/<dir2>/
Similar to my first attempt, it seemed to work. Lots of network activity,
temp files being created, and in the terminal I got:
09/05/07 18:36:11 INFO mapred.JobClient: Running job:
job_200905071339_0004
09/05/07 18:36:12 INFO mapred.JobClient: map 0% reduce 0%
09/05/07 18:36:30 INFO mapred.JobClient: map 9% reduce 0%
09/05/07 18:36:35 INFO mapred.JobClient: map 14% reduce 0%
09/05/07 18:36:38 INFO mapred.JobClient: map 20% reduce 0%
But again it hung. No network traffic, and eventually it dumped out:
09/05/07 18:52:34 INFO mapred.JobClient: Task Id :
attempt_200905071339_0004_m_000001_0, Status : FAILED
Task attempt_200905071339_0004_m_000001_0 failed to report status for 601
seconds. Killing!
09/05/07 18:53:02 INFO mapred.JobClient: Task Id :
attempt_200905071339_0004_m_000004_0, Status : FAILED
Task attempt_200905071339_0004_m_000004_0 failed to report status for 602
seconds. Killing!
09/05/07 18:53:06 INFO mapred.JobClient: Task Id :
attempt_200905071339_0004_m_000002_0, Status : FAILED
Task attempt_200905071339_0004_m_000002_0 failed to report status for 602
seconds. Killing!
09/05/07 18:53:09 INFO mapred.JobClient: Task Id :
attempt_200905071339_0004_m_000003_0, Status : FAILED
Task attempt_200905071339_0004_m_000003_0 failed to report status for 601
seconds. Killing!
>>> In the task GUI, I can see the same tasks failing, and being
restarted. But
the restarted tasks seem to be just hanging w/o doing anything.
Eventually one of the tasks made a bit more progress, but then it finally
died with:
>>> Copy failed: java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:1232)
at org.apache.hadoop.tools.DistCp.copy(DistCp.java:647)
at org.apache.hadoop.tools.DistCp.run(DistCp.java:844)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:79)
at org.apache.hadoop.tools.DistCp.main(DistCp.java:871)
So - any thoughts on what's going wrong?
Thanks,
-- Ken
--
Ken Krugler
+1 530-210-6378
--
Ken Krugler
+1 530-210-6378
