How to access s3a:// files from Apache Spark?

Question

Hadoop 2.6 doesn't support s3a out of the box, so I've tried a series of solutions and fixes, including:

deploy with hadoop-aws and aws-java-sdk => cannot read environment variable for credentials add hadoop-aws into maven => various transitive dependency conflicts

Has anyone successfully make both work?

Answer 1

Having experienced first hand the difference between s3a and s3n - 7.9GB of data transferred on s3a was around ~7 minutes while 7.9GB of data on s3n took 73 minutes [us-east-1 to us-west-1 unfortunately in both cases; Redshift and Lambda being us-east-1 at this time] this is a very important piece of the stack to get correct and it's worth the frustration.

Here are the key parts, as of December 2015:

1. Your Spark cluster will need a Hadoop version 2.x or greater. If you use the Spark EC2 setup scripts and maybe missed it, the switch for using something other than 1.0 is to specify --hadoop-major-version 2 (which uses CDH 4.2 as of this writing).

2. You'll need to include what may at first seem to be an out of date AWS SDK library (built in 2014 as version 1.7.4) for versions of Hadoop as late as 2.7.1 (stable): aws-java-sdk 1.7.4. As far as I can tell using this along with the specific AWS SDK JARs for 1.10.8 hasn't broken anything.

3. You'll also need the hadoop-aws 2.7.1 JAR on the classpath. This JAR contains the class org.apache.hadoop.fs.s3a.S3AFileSystem.

4. In spark.properties you probably want some settings that look like this:

   spark.hadoop.fs.s3a.access.key=ACCESSKEY
   spark.hadoop.fs.s3a.secret.key=SECRETKEY

I've detailed this list in more detail on a post I wrote as I worked my way through this process. In addition I've covered all the exception cases I hit along the way and what I believe to be the cause of each and how to fix them.