def process_query(self, query: Query, query_settings: QuerySettings) -> None:
if not get_config(self.__killswitch, 1):
return
condition, cond_class = self.__get_reduced_and_classified_query_clause(
query.get_condition(), query
)
query.set_ast_condition(condition)
if cond_class == ConditionClass.NOT_OPTIMIZABLE:
return
having_cond, having_cond_class = self.__get_reduced_and_classified_query_clause(
query.get_having(), query
)
query.set_ast_having(having_cond)
if having_cond_class == ConditionClass.NOT_OPTIMIZABLE:
return
if not (
cond_class == ConditionClass.OPTIMIZABLE
or having_cond_class == ConditionClass.OPTIMIZABLE
):
return
metrics.increment("optimizable_query")
query.add_experiment("tags_hashmap_applied", 1)
if condition is not None:
query.set_ast_condition(condition.transform(self.__replace_with_hash))
if having_cond is not None:
query.set_ast_having(having_cond.transform(self.__replace_with_hash))
def test_query_experiments() -> None:
query = Query(
Table("my_table", ColumnSet([])),
limitby=LimitBy(100, [
Column(
alias=None, table_name="my_table", column_name="environment")
]),
limit=100,
offset=50,
granularity=60,
)
query.set_experiments({"optimization1": True})
assert query.get_experiments() == {"optimization1": True}
assert query.get_experiment_value("optimization1") == True
assert query.get_experiment_value("optimization2") is None
query.add_experiment("optimization2", "group1")
assert query.get_experiment_value("optimization2") == "group1"
query.set_experiments({"optimization3": 0.5})
assert query.get_experiments() == {"optimization3": 0.5}
