Possible performance issue when reading large datasets from BigQuery

[parthea]

An issue was reported on StackOverflow regarding an issue related to downloading 1,000,000 rows from BigQuery. See https://stackoverflow.com/questions/44868111/failed-to-import-large-data-as-dataframe-from-google-bigquery-to-google-cloud-d

Secondly I use:

data = pd.read_gbq(query='SELECT {ABOUT_30_COLUMNS...} FROM TABLE_NAME LIMIT 1000000', dialect ='standard', project_id='PROJECT_ID')

It runs well at first, but when it goes to about 450,000 rows (calculate using percentage and total row count), it gets stuck at:

Got page: 32; 45.0% done. Elapsed 293.1 s.

We have an integration test for test_download_dataset_larger_than_200k_rows https://github.com/pydata/pandas-gbq/blob/master/pandas_gbq/tests/test_gbq.py#L709 . It may be helpful to also include a performance test (and increase the dataset size).

[max-sixty]

Closing in preference of #133 given the detail there