BigQuery: to_arrow() method similar to to_dataframe()

Current there’s a to_dataframe() method that returns a pandas DataFrame from a query. DataFrames don’t efficiently support array and struct values, but pyarrow provides efficient support for them:

In [11]: import pyarrow as pa

In [13]: a = pa.array(
    ...:     [
    ...:         {'a': [1, 2, 3]}
    ...:     ],
    ...:     pa.struct([pa.field('a', pa.list_(pa.int64()))])
    ...: )

In [14]: a
Out[14]: 
<pyarrow.lib.StructArray object at 0x7f55f8764b88>
[
  {'a': [1, 2, 3]}
]

A to_arrow() method will make it easier to efficiently support more complex types going forward in downstream libraries like ibis.

[tswast]

FYI: results.to_arrow(bqstorage_client=bqstorage_client).to_pandas() is currently the fastest way to get a pandas DataFrame from your query results. About 4 seconds from results to DataFrame for a 125 MB table.

[tswast]

@plamut Remaining task to close out this FR is to add the bqstorage_client argument to QueryJob.to_arrow()

https://github.com/googleapis/google-cloud-python/blob/e4cf3f4458d13ce5b0203060dc4249d3e34e80a7/bigquery/google/cloud/bigquery/job.py#L2899

See RowIterator.to_arrow():

https://github.com/googleapis/google-cloud-python/blob/e4cf3f4458d13ce5b0203060dc4249d3e34e80a7/bigquery/google/cloud/bigquery/table.py#L1452

Also, we should add comments before to_arrow and to_dataframe in both QueryJob and RowIterator reminding us to add any additional arguments in the other class.