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88 changes: 75 additions & 13 deletions docs/bigquery-usage.rst
Original file line number Diff line number Diff line change
Expand Up @@ -291,26 +291,88 @@ Run a query which can be expected to complete within bounded time:

>>> from gcloud import bigquery
>>> client = bigquery.Client()
>>> query = """\
SELECT count(*) AS age_count FROM dataset_name.person_ages
"""
>>> query = client.run_sync_query(query)
>>> QUERY = """\
... SELECT count(*) AS age_count FROM dataset_name.person_ages
... """
>>> query = client.run_sync_query(QUERY)
>>> query.timeout_ms = 1000
>>> query.run() # API request
>>> query.complete
True
>>> len(query.schema)
1
>>> field = query.schema[0]
>>> field.name
u'count'
>>> field.field_type
u'INTEGER'
>>> field.mode
u'NULLABLE'
>>> query.rows
[(15,)]
>>> query.total_rows
1

If the rows returned by the query do not fit into the inital response,
then we need to fetch the remaining rows via ``fetch_data``:

.. doctest::

>>> from gcloud import bigquery
>>> client = bigquery.Client()
>>> QUERY = """\
... SELECT * FROM dataset_name.person_ages
... """
>>> query = client.run_sync_query(QUERY)
>>> query.timeout_ms = 1000
>>> query.run() # API request
>>> query.complete
True
>>> query.total_rows
1234
>>> query.page_token
'8d6e452459238eb0fe87d8eb191dd526ee70a35e'
>>> do_something_with(query.schema, query.rows)
>>> token = query.page_token # for initial request
>>> while True:
... do_something_with(query.schema, rows)
... if token is None:
... break
... rows, _, token = query.fetch_data(page_token=token)


If the query takes longer than the timeout allowed, ``query.complete``
will be ``False``. In that case, we need to poll the associated job until
it is done, and then fetch the reuslts:

.. doctest::

>>> from gcloud import bigquery
>>> client = bigquery.Client()
>>> QUERY = """\
... SELECT * FROM dataset_name.person_ages
... """
>>> query = client.run_sync_query(QUERY)
>>> query.timeout_ms = 1000
>>> query.run() # API request
>>> query.complete
False
>>> job = query.job
>>> retry_count = 100
>>> while retry_count > 0 and not job.complete:
>>> while retry_count > 0 and job.state == 'running':
... retry_count -= 1
... time.sleep(10)
... query.reload() # API request
>>> query.schema
[{'name': 'age_count', 'type': 'integer', 'mode': 'nullable'}]
>>> query.rows
[(15,)]
... job.reload() # API call
>>> job.state
'done'
>>> token = None # for initial request
>>> while True:
... rows, _, token = query.fetch_data(page_token=token)
... do_something_with(query.schema, rows)
... if token is None:
... break

.. note::

If the query takes longer than the timeout allowed, ``job.complete``
will be ``False``: we therefore poll until it is completed.

Querying data (asynchronous)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Expand Down