def __init__(self, query: Query, settings: RequestSettings,) -> None:
# Clickhouse query structure
# Referencing them here directly since it makes it easier
# to process this query independently from the Clickhouse Query
# and there is no risk in doing so since they are immutable.
self.__selected_columns = query.get_selected_columns_from_ast()
self.__condition = query.get_condition_from_ast()
self.__groupby = query.get_groupby_from_ast()
self.__having = query.get_having_from_ast()
self.__orderby = query.get_orderby_from_ast()
self.__data_source = query.get_data_source()
self.__arrayjoin = query.get_arrayjoin_from_ast()
self.__granularity = query.get_granularity()
self.__limit = query.get_limit()
self.__limitby = query.get_limitby()
self.__offset = query.get_offset()
if self.__having:
assert self.__groupby, "found HAVING clause with no GROUP BY"
self.__turbo = settings.get_turbo()
self.__final = query.get_final()
self.__sample = query.get_sample()
self.__hastotals = query.has_totals()
self.__prewhere = query.get_prewhere_ast()
self.__settings = settings
self.__sql_data_list: Optional[Sequence[Tuple[str, str]]] = None
self.__formatted_query: Optional[str] = None
self.__sql_data: Optional[Mapping[str, str]] = None
def _list_array_join(query: Query) -> Columnset:
ret = set()
query_arrayjoin = query.get_arrayjoin_from_ast()
if query_arrayjoin is not None:
ret |= _get_columns_from_expression(query_arrayjoin)
for e in query.get_all_expressions():
if isinstance(e, FunctionCallExpr) and e.function_name == "arrayJoin":
ret |= _get_columns_from_expression(e)
return ret
def test_translation(mappers: TranslationMappers, query: SnubaQuery,
expected: ClickhouseQuery) -> None:
translated = QueryTranslator(mappers).translate(query)
# TODO: consider providing an __eq__ method to the Query class. Or turn it into
# a dataclass.
assert (expected.get_selected_columns_from_ast() ==
translated.get_selected_columns_from_ast())
assert expected.get_groupby_from_ast() == translated.get_groupby_from_ast()
assert expected.get_condition_from_ast(
) == translated.get_condition_from_ast()
assert expected.get_arrayjoin_from_ast(
) == translated.get_arrayjoin_from_ast()
assert expected.get_having_from_ast() == translated.get_having_from_ast()
assert expected.get_orderby_from_ast() == translated.get_orderby_from_ast()
def process_query(self, query: Query,
request_settings: RequestSettings) -> None:
conditions = query.get_conditions()
if not conditions:
return
# Enable the processor only if we have enough data in the flattened
# columns. Which have been deployed at BEGINNING_OF_TIME. If the query
# starts earlier than that we do not apply the optimization.
if self.__beginning_of_time:
apply_optimization = False
for condition in conditions:
if (is_condition(condition) and isinstance(condition[0], str)
and condition[0] in self.__timestamp_cols
and condition[1] in (">=", ">")
and isinstance(condition[2], str)):
try:
start_ts = parse_datetime(condition[2])
if (start_ts -
self.__beginning_of_time).total_seconds() > 0:
apply_optimization = True
except Exception:
# We should not get here, it means the from timestamp is malformed
# Returning here is just for safety
logger.error(
"Cannot parse start date for NestedFieldOptimizer: %r",
condition,
)
return
if not apply_optimization:
return
# Do not use flattened tags if tags are being unpacked anyway. In that case
# using flattened tags only implies loading an additional column thus making
# the query heavier and slower
if self.__has_tags(query.get_arrayjoin_from_ast()):
return
if query.get_groupby_from_ast():
for expression in query.get_groupby_from_ast():
if self.__has_tags(expression):
return
if self.__has_tags(query.get_having_from_ast()):
return
if query.get_orderby_from_ast():
for orderby in query.get_orderby_from_ast():
if self.__has_tags(orderby.expression):
return
new_conditions = []
positive_like_expression: List[str] = []
negative_like_expression: List[str] = []
for c in conditions:
keyvalue = self.__is_optimizable(c, self.__nested_col)
if not keyvalue:
new_conditions.append(c)
else:
expression = f"{escape_field(keyvalue.nested_col_key)}={escape_field(keyvalue.value)}"
if keyvalue.operand == Operand.EQ:
positive_like_expression.append(expression)
else:
negative_like_expression.append(expression)
if positive_like_expression:
# Positive conditions "=" are all merged together in one LIKE expression
positive_like_expression = sorted(positive_like_expression)
like_formatted = f"%|{'|%|'.join(positive_like_expression)}|%"
new_conditions.append(
[self.__flattened_col, "LIKE", like_formatted])
for expression in negative_like_expression:
# Negative conditions "!=" cannot be merged together. We can still transform
# them into NOT LIKE statements, but each condition has to be one
# statement.
not_like_formatted = f"%|{expression}|%"
new_conditions.append(
[self.__flattened_col, "NOT LIKE", not_like_formatted])
query.set_conditions(new_conditions)
