[SPARK-13664][SQL] Add a strategy for planning partitioned and bucketed scans of files

This PR adds a new strategy, `FileSourceStrategy`, that can be used for planning scans of collections of files that might be partitioned or bucketed.

Compared with the existing planning logic in `DataSourceStrategy` this version has the following desirable properties:
 - It removes the need to have `RDD`, `broadcastedHadoopConf` and other distributed concerns  in the public API of `org.apache.spark.sql.sources.FileFormat`
 - Partition column appending is delegated to the format to avoid an extra copy / devectorization when appending partition columns
 - It minimizes the amount of data that is shipped to each executor (i.e. it does not send the whole list of files to every worker in the form of a hadoop conf)
 - it natively supports bucketing files into partitions, and thus does not require coalescing / creating a `UnionRDD` with the correct partitioning.
 - Small files are automatically coalesced into fewer tasks using an approximate bin-packing algorithm.

Currently only a testing source is planned / tested using this strategy.  In follow-up PRs we will port the existing formats to this API.

A stub for `FileScanRDD` is also added, but most methods remain unimplemented.

Other minor cleanups:
 - partition pruning is pushed into `FileCatalog` so both the new and old code paths can use this logic.  This will also allow future implementations to use indexes or other tricks (i.e. a MySQL metastore)
 - The partitions from the `FileCatalog` now propagate information about file sizes all the way up to the planner so we can intelligently spread files out.
 - `Array` -> `Seq` in some internal APIs to avoid unnecessary `toArray` calls
 - Rename `Partition` to `PartitionDirectory` to differentiate partitions used earlier in pruning from those where we have already enumerated the files and their sizes.

Author: Michael Armbrust <michael@databricks.com>

Closes #11646 from marmbrus/fileStrategy.