def update_query_to_limit_nb_points_for_query(backend_host, backend_port, user,
password, from_parts, query,
parsed_query,
aggregation_properties,
max_nb_points_per_query):
schema = from_parts['schema']
# counter_aggregation_mode = get_counter_aggregation_mode(from_parts, aggregation_properties)
# if counter_aggregation_mode is None:
# counter_aggregation_mode = 'mean'
expected_nb_points_per_query = get_expected_nb_points_for_query(
backend_host, backend_port, user, password, schema, query,
parsed_query)
if expected_nb_points_per_query is None:
return None
if expected_nb_points_per_query['nb_points'] > max_nb_points_per_query:
logging.info('Expected nb of points per query ' +
str(expected_nb_points_per_query['nb_points']) +
' is bigger than max allowed one (' +
str(max_nb_points_per_query) + ')')
my_factor = expected_nb_points_per_query[
'nb_points'] / max_nb_points_per_query
split_group_by_time_interval = influx_date_manipulation.split_influx_time(
expected_nb_points_per_query['group_by_time_interval'])
adjusted_group_by_time_value = int(
math.ceil(my_factor * split_group_by_time_interval['number']))
new_group_by_time_interval = str(
adjusted_group_by_time_value
) + split_group_by_time_interval['unit']
parsed_query = influx_query_modification.change_group_by_time_interval(
parsed_query, new_group_by_time_interval)
# if counter_aggregation_mode == 'sum' and influx_query_parsing.is_sum_group_by_time(parsed_query):
if influx_query_parsing.is_sum_group_by_time(parsed_query):
parsed_query = influx_query_modification.change_sum_group_by_time_factor(
parsed_query, '1/' + str(my_factor))
query = influx_query_parsing.stringify_sqlparsed(parsed_query)
logging.info('Reworked query (limit nb points per query): ' + query)
return query
return None
def update_query_with_right_rp(from_parts,
query,
parsed_query,
known_retention_policies,
aggregation_properties,
override_explicit_rp=False):
output = get_right_rp_for_query(from_parts['schema'], query, parsed_query,
known_retention_policies,
override_explicit_rp)
if output is None:
return None
counter_aggregation_mode = get_counter_aggregation_mode(
from_parts, aggregation_properties)
if counter_aggregation_mode is None:
counter_aggregation_mode = 'mean'
is_changed = False
if 'rp' in output:
from_id = influx_query_parsing.extract_from_helper(
parsed_query, 'index')
parsed_query.tokens[
from_id] = '"' + from_parts['schema'] + '"."' + output[
'rp'] + '"."' + from_parts['measurement'] + '"'
is_changed = True
if 'group_by_time_interval' in output:
parsed_query = influx_query_modification.change_group_by_time_interval(
parsed_query, output['group_by_time_interval'])
is_changed = True
if 'sum_group_by_time_interval_factor' in output:
if counter_aggregation_mode == 'sum':
parsed_query = influx_query_modification.change_sum_group_by_time_factor(
parsed_query, output['sum_group_by_time_interval_factor'])
is_changed = True
if is_changed:
query = influx_query_parsing.stringify_sqlparsed(parsed_query)
from_parts['rp'] = output['rp']
logging.info('Reworked query (auto RP): ' + query)
return query