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def test_arraysize_default(self, cursor):
self.assertEqual(cursor.arraysize, AthenaPandasResultSet.DEFAULT_FETCH_SIZE)
def __init__(self, connection, converter, query_execution, arraysize, retry_config):
super(AthenaPandasResultSet, self).__init__(
connection=connection,
converter=converter,
query_execution=query_execution,
arraysize=1, # Fetch one row to retrieve metadata
retry_config=retry_config)
self._arraysize = arraysize
self._client = self._connection.session.client(
's3', region_name=self._connection.region_name, **self._connection._client_kwargs)
if self._query_execution.state == AthenaQueryExecution.STATE_SUCCEEDED:
self._df = self._as_pandas()
else:
import pandas as pd
self._df = pd.DataFrame()
self._iterrows = self._df.iterrows()
def execute(self, operation, parameters=None, work_group=None, s3_staging_dir=None,
cache_size=0):
self._reset_state()
self._query_id = self._execute(operation,
parameters=parameters,
work_group=work_group,
s3_staging_dir=s3_staging_dir,
cache_size=cache_size)
query_execution = self._poll(self._query_id)
if query_execution.state == AthenaQueryExecution.STATE_SUCCEEDED:
self._result_set = AthenaPandasResultSet(
self._connection, self._converter, query_execution, self.arraysize,
self._retry_config)
else:
raise OperationalError(query_execution.state_change_reason)
return self