Using the Hadoop S3a connector with Gateway S3

The Apache Hadoop S3 connector "S3A" works with Content Gateway S3. Here is a small but complete example, using a single-node Hadoop system that can be easily run on any Docker server. It shows bucket listing, distcp, and a simple mapreduce job against a bucket in a Swarm domain.

Create a container using the docker image from https://github.com/sequenceiq/hadoop-docker.
```
$ docker run -it sequenceiq/hadoop-docker:2.7.0 /etc/bootstrap.sh -bash
```
At the container's shell prompt, add the path containing the "hadoop" binary:
```
PATH=/usr/local/hadoop/bin:$PATH
```

Copy the jar's needed for the S3A libraries:

cd /usr/local/hadoop-2.7.0/share/hadoop/tools/lib/ && cp -p hadoop-aws-2.7.0.jar aws-java-sdk-1.7.4.jar jackson-core-2.2.3.jar jackson-databind-2.2.3.jar jackson-annotations-2.2.3.jar /usr/local/hadoop-2.7.0/share/hadoop/hdfs/lib/

Make sure your domain (mydomain.example.com) and bucket (hadoop-test) have been created and that your /etc/hosts or DNS are configured to resolve http://mydomain.example.com/hadoop-test to your cloudgateway server's S3 port.

Create an S3 token:

curl -i -u USERNAME -X POST --data-binary '' -H 'X-User-Secret-Key-Meta: secret' -H 'X-User-Token-Expires-Meta: +90' http://mydomain.example.com/.TOKEN/

HTTP/1.1 201 Created
...
Token e181dcb1d01d5cf24f76dd276b95a638 issued for USERNAME in [root] with secret secret

List your bucket (it should be empty).
```
hadoop fs -Dfs.s3a.access.key=e181dcb1d01d5cf24f76dd276b95a638 -Dfs.s3a.secret.key=secret -Dfs.s3a.endpoint=mydomain.example.com -ls s3a://hadoop-test/
```
Note: You will get error "No such file or directory is expected" if the bucket is empty or the trailing slash is missing.

Copy the sample "input" files into your bucket:

hadoop distcp -Dfs.s3a.access.key=e181dcb1d01d5cf24f76dd276b95a638 -Dfs.s3a.secret.key=secret -Dfs.s3a.endpoint=jam.cloud.caringo.com input s3a://hadoop-test/input

Verify with "-ls" or in Content Gateway ui that the bucket now has ~31 objects.

hadoop fs -Dfs.s3a.access.key=e181dcb1d01d5cf24f76dd276b95a638 -Dfs.s3a.secret.key=secret -Dfs.s3a.endpoint=jam.cloud.caringo.com -ls s3a://hadoop-test/input/
Found 31 items
...

Run the sample mapreduce job that grep's the input files.

hadoop jar /usr/local/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.0.jar grep -Dfs.s3a.access.key=e181dcb1d01d5cf24f76dd276b95a638 -Dfs.s3a.secret.key=secret -Dfs.s3a.endpoint=mydomain.example.com s3a://hadoop-test/input s3a://hadoop-test/output 'dfs[a-z.]+'

Display the results in the "output" file.

hadoop fs -Dfs.s3a.access.key=e181dcb1d01d5cf24f76dd276b95a638 -Dfs.s3a.secret.key=secret -Dfs.s3a.endpoint=mydomain.example.com -cat s3a://hadoop-test/output/part-r-00000
6	dfs.audit.logger
4	dfs.class
3	dfs.server.namenode.
2	dfs.period
2	dfs.audit.log.maxfilesize
...

PS: https://wiki.apache.org/hadoop/AmazonS3 makes a good point:

S3 is not a filesystem. The Hadoop S3 filesystem bindings make it pretend to be a filesystem, but it is not. It can act as a source of data, and as a destination -though in the latter case, you must remember that the output may not be immediately visible.

Knowledge Base

Using the Hadoop S3a connector with Gateway S3

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