使用用户帐户凭据从 BigQuery 读取数据

Created: November-22, 2018

In [1]: import pandas as pd

要在 BigQuery 中运行查询，你需要拥有自己的 BigQuery 项目。我们可以请求一些公共样本数据：

In [2]: data = pd.read_gbq('''SELECT title, id, num_characters
   ...:                       FROM [publicdata:samples.wikipedia]
   ...:                       LIMIT 5'''
   ...:                    , project_id='<your-project-id>')

这将打印出来：

Your browser has been opened to visit:

    https://accounts.google.com/o/oauth2/v2/auth...[looong url cutted]

If your browser is on a different machine then exit and re-run this
application with the command-line parameter

  --noauth_local_webserver

如果你使用的是本地计算机，则会弹出浏览器。授予权限后，pandas 将继续输出：

Authentication successful.
Requesting query... ok.
Query running...
Query done.
Processed: 13.8 Gb

Retrieving results...
Got 5 rows.

Total time taken 1.5 s.
Finished at 2016-08-23 11:26:03.

结果：

In [3]: data
Out[3]: 
               title       id  num_characters
0       Fusidic acid   935328            1112
1     Clark Air Base   426241            8257
2  Watergate scandal    52382           25790
3               2005    35984           75813
4               .BLP  2664340            1659

作为副作用，pandas 将创建 json 文件 bigquery_credentials.dat，这将允许你运行更多查询，而无需再授予权限：

In [9]: pd.read_gbq('SELECT count(1) cnt FROM [publicdata:samples.wikipedia]'
                   , project_id='<your-project-id>')
Requesting query... ok.
[rest of output cutted]

Out[9]: 
         cnt
0  313797035