Use deterministic names for dask arrays from open_dataset

[shoyer]

This will allow xray users to take advantage of dask's nascent support for
caching intermediate results (dask/dask#502).

For example:

In [1]: import xray

In [2]: from dask.diagnostics.cache import Cache

In [3]: c = Cache(5e7)

In [4]: c.register()

In [5]: ds = xray.open_mfdataset('/Users/shoyer/data/era-interim/2t/2014-*.nc', engine='scipy')

In [6]: %time ds.sum().load()
CPU times: user 2.72 s, sys: 2.7 s, total: 5.41 s
Wall time: 3.85 s
Out[6]:
<xray.Dataset>
Dimensions:  ()
Coordinates:
    *empty*
Data variables:
    t2m      float64 5.338e+10

In [7]: %time ds.mean().load()
CPU times: user 5.31 s, sys: 1.86 s, total: 7.17 s
Wall time: 1.81 s
Out[7]:
<xray.Dataset>
Dimensions:  ()
Coordinates:
    *empty*
Data variables:
    t2m      float64 279.0

In [8]: %time ds.mean().load()
CPU times: user 7.73 ms, sys: 2.73 ms, total: 10.5 ms
Wall time: 8.45 ms
Out[8]:
<xray.Dataset>
Dimensions:  ()
Coordinates:
    *empty*
Data variables:
    t2m      float64 279.0

Still needs docs (probably in the dask section) and a what's new item.

Also, this will update the minimum required version of dask to 0.7 (which should be called out in docs).