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Upload archives to AWS Glacier using multiple connections for faster transfers

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Octocat-spinner-32 .gitignore
Octocat-spinner-32 AwsCredentials.properties.sample
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Octocat-spinner-32 ParallelGlacierUploader.java
Octocat-spinner-32 README
README
This is an upload tool for Amazon's Glacier storage service. It is based on
Amazon's example Java code, but implements parallel uploading of archive chunks
in order to increase the effective upload speed.

In my testing of the service immediately after its announcement, the upload of
a single chunk never went faster than 150KBps, hugely less than available
bandwidth. However, chunks can be uploaded in parallel over different HTTP
connections, potentially increasing the effective upload speed to the capacity
of your uplink.

This is a rudimentary command line tool; some knowledge of building and running
Java projects is required to use it.

Building:

First install Eclipse (http://www.eclipse.org/downloads/) and the AWS Toolkit
for Eclipse (http://aws.amazon.com/eclipse/). Follow the instructions at
http://docs.amazonwebservices.com/amazonglacier/latest/dev/using-aws-sdk-for-java.html
to create a new AWS Eclipse project, then copy ParallelGlacierUploader.java
into the project workspace. Enter your AWS credentials into
AwsCredentials.properties, then adjust the vaultName and maxThreads constants
to appropriate values for you. maxThreads should be set based on an empirical
measurement of your upload speed to Glacier, and the upstream speed of your
network connection. For example, if you have a 10MBps upload speed and
typically can upload at 128KBps to Glacier, maxThreads should be set no higher
than 80.

Running:

To run from within Eclipse, enter the path to your archive file as a command
line parameter under Run | Run configurations | Arguments, then click Run. The
progress of the upload will be printed in the Console tab.

Notes:

* Since this may still be a long-running process, the program attempts to
  conserve memory by using the smallest chunk size that Glacier will allow and
  only keeping in-flight chunks in memory at any time. But of course, more
  parallel threads means more memory.
* This process does not appear to cause problems with the API, however, Amazon
  might not like it. Review the terms of service yourself before trusting your
  data.
* Retrieval of an archive created this way has not been tested. Caveat emptor.
* The program is not particularly robust; if an error occurs, everything is
  aborted. Retries and recovery of partially completed uploads are not
  implemented.
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