Currently, Hadoop exposes downstream clients to a variety of third party libraries. As our code base grows and matures we increase the set of libraries we rely on. At the same time, as our user base grows we increase the likelihood that some downstream project will run into a conflict while attempting to use a different version of some library we depend on. This has already happened with i.e. Guava several times for HBase, Accumulo, and Spark (and I'm sure others).
YARN-286 and MAPREDUCE-1700 provided an initial effort, they default to off and they don't do anything to help dependency conflicts on the driver side or for folks talking to HDFS directly. This should serve as an umbrella for changes needed to do things thoroughly on the next major version.
We should ensure that downstream clients
1) can depend on a client artifact for each of HDFS, YARN, and MapReduce that doesn't pull in any third party dependencies
2) only see our public API classes (or as close to this as feasible) when executing user provided code, whether client side in a launcher/driver or on the cluster in a container or within MR.
This provides us with a double benefit: users get less grief when they want to run substantially ahead or behind the versions we need and the project is freer to change our own dependency versions because they'll no longer be in our compatibility promises.
Project specific task jiras to follow after I get some justifying use cases written in the comments.