[SPARK-14288][SQL] Memory Sink for streaming

This PR exposes the internal testing `MemorySink` though the data source API.  This will allow users to easily test streaming applications in the Spark shell or other local tests.

Usage:
```scala
inputStream.write
  .format("memory")
  .queryName("memStream")
  .startStream()

// Now you can query the result of the stream here.
sqlContext.table("memStream")
```

The most complicated part of the logic is choosing the checkpoint directory.  There are a few requirements we are attempting to satisfy here:
 - when working in the shell locally, it should just work with no extra configuration.
 - when working on a cluster you should be able to make it easily create the checkpoint on a distributed file system so you can test aggregation (state checkpoints are also stored in this directory and must be accessible from workers).
 - it should be clear that you can't resume since the data is just in memory.

The chosen algorithm proceeds as follows:
 - the user gives a checkpoint directory, use it
 - if the conf has a checkpoint location, use `$location/$queryName`
 - if neither, create a local directory
 - always check to make sure there are no offsets written to the directory

Author: Michael Armbrust <michael@databricks.com>

Closes #12119 from marmbrus/memorySink.