Fixes #56. The issue was the underlying flatbuffer array type was using
an `UInt32` for the byte position where the flatbuffer array was
located; in super large files, this overflowed. As this Array field is a
Julia-side controlled type, we can easily switch to an Int64 to avoid
this issue all together.

The bitpack encoding algorithm was allocating, which caused very large
tables to slow down considerably with so much memory recycling.
Rewriting it to avoid allocations leads to drastically fewer allocations
and much faster writing performance. For non-optimized array writing, we
also switch to writing to a buffer first to avoid hitting the global IO
lock too much, which can also hurt performance on large files.

Just a few minor cleanups to ensure dictionary encoding types are
consistent, and that variable names work correctly between writing
first-time dictionary encodings and deltas.