def decomposition_to_plan(decomposition):
access_plans = []
for tp in decomposition:
access_plans.append(LogicalPlan(tp))
todo = sorted(access_plans, key=lambda x: x.cardinality)
plan = todo[0]
todo.remove(plan)
while len(todo):
for i in range(len(todo)):
if len(plan.variables.intersection(todo[i].variables)) > 0:
plan = LogicalPlan(plan, todo[i],
get_physical_operator(plan, todo[i]))
plan.compute_cardinality(cardinality_estimation)
todo.remove(todo[i])
break
else:
# In case we cannot find another join able triple pattern
next_tp = todo[0]
plan = LogicalPlan(plan, next_tp,
get_physical_operator(plan, next_tp))
plan.compute_cardinality(cardinality_estimation)
todo.remove(next_tp)
return plan
def optimize_subquery(self, subquery, filters):
plans = []
for tp_combination in product(*subquery):
access_plans = []
for tp in tp_combination:
access_plans.append(LogicalPlan(tp))
todo = sorted(access_plans, key=lambda x: x.cardinality)
plan = todo[0]
todo.remove(plan)
while len(todo):
for i in range(len(todo)):
if len(plan.variables.intersection(todo[i].variables)) > 0:
plan = LogicalPlan(
plan, todo[i],
self.get_physical_join_operator(plan, todo[i]))
plan.compute_cardinality(self.cardinality_estimation)
todo.remove(todo[i])
break
else:
# In case we cannot find another join able triple pattern
next_tp = todo[0]
plan = LogicalPlan(
plan, next_tp,
self.get_physical_join_operator(plan, next_tp))
plan.compute_cardinality(self.cardinality_estimation)
todo.remove(next_tp)
plan.filters = filters
plans.append(plan)
if len(plans) == 0:
return None
plan = self.union_subplans(plans)
return plan
def decomposition_to_plan(decomposition):
leafs = {}
for subquery, source, cardinality in decomposition:
if isinstance(subquery, TriplePattern):
if subquery in leafs.keys():
leafs[subquery].sources[source] = cardinality
leafs[subquery].cardinality += cardinality
else:
new_triple_pattern = TriplePattern(
subquery[0],
subquery[1],
subquery[2],
sources={source: cardinality})
new_triple_pattern.cardinality = cardinality
leafs[subquery] = new_triple_pattern
elif isinstance(subquery, BGP):
if subquery in leafs.keys():
for tp in leafs[subquery]:
for bgp_tp in subquery:
if tp == bgp_tp:
tp.sources[source] = bgp_tp.cardinality
leafs[subquery].cardinality += cardinality
else:
new_tps = []
for triple_pattern in subquery:
new_triple_pattern = TriplePattern(
triple_pattern[0],
triple_pattern[1],
triple_pattern[2],
sources={source: cardinality})
new_tps.append(new_triple_pattern)
new_bgp = BGP(new_tps)
new_bgp.cardinality = cardinality
leafs[subquery] = new_bgp
access_plans = []
for tp in leafs.values():
access_plans.append(LogicalPlan(tp))
todo = sorted(access_plans, key=lambda x: x.cardinality)
plan = todo[0]
todo.remove(plan)
while len(todo):
for i in range(len(todo)):
if len(plan.variables.intersection(todo[i].variables)) > 0:
plan = LogicalPlan(plan, todo[i],
get_physical_operator(plan, todo[i]))
plan.compute_cardinality(cardinality_estimation)
todo.remove(todo[i])
break
else:
# In case we cannot find another join able triple pattern
next_tp = todo[0]
plan = LogicalPlan(plan, next_tp,
get_physical_operator(plan, next_tp))
plan.compute_cardinality(cardinality_estimation)
todo.remove(next_tp)
return plan