async def test_filter_iterator_interrupt():
expression = "?p = <http://schema.org/eligibleRegion>"
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'],
triple['object'])
scan = ProjectionIterator(ScanIterator(iterator, triple, card))
iterator = FilterIterator(scan, expression)
(results, saved, done, _) = await engine.execute(iterator, 10e-7, 2)
assert len(results) <= 4
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country1',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country4',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
tmp = len(results)
reloaded = load(saved.SerializeToString(),
DummyDataset(hdtDoc, 'watdiv100'))
(results, saved, done, _) = await engine.execute(reloaded, 10e7)
assert len(results) + tmp == 4
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country1',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country4',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
assert done
def load_projection(saved_plan, dataset):
"""Load a ProjectionIterator from a protobuf serialization"""
default_graph = saved_plan.graph
sourceField = saved_plan.WhichOneof('source')
source = load(getattr(saved_plan, sourceField), dataset)
values = saved_plan.values if len(saved_plan.values) > 0 else None
return ProjectionIterator(source, dataset, default_graph, values)
async def test_filter_iterator_interrupt():
context = { 'quantum': 10e-7, 'max_results': 10e7 }
expression = "?p = <http://schema.org/eligibleRegion>"
scan = ProjectionIterator(ScanIterator(hdtDoc, triple, context), context)
iterator = FilterIterator(scan, expression, context)
(results, saved, done, _) = await engine.execute(iterator, context)
assert len(results) <= 4
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country1',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country4',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
tmp = len(results)
context['quantum'] = 10e7
reloaded = load(saved.SerializeToString(), DummyDataset(hdtDoc, 'watdiv100'), context)
(results, saved, done, _) = await engine.execute(reloaded, context)
assert len(results) + tmp == 4
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country1',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country4',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
assert done
async def test_operation_filter_iterator():
context = { 'quantum': 10e7, 'max_results': 10e7 }
expression = "10 = 5 * 2"
scan = ProjectionIterator(ScanIterator(hdtDoc, triple, context), context)
iterator = FilterIterator(scan, expression, context)
(results, saved, done, _) = await engine.execute(iterator, context)
assert len(results) == 9
async def test_function_filter_iterator():
expression = '?p = <http://purl.org/goodrelations/price> && isLiteral(?o) && !isNumeric(?o)'
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'],
triple['object'])
scan = ProjectionIterator(ScanIterator(iterator, triple, card))
iterator = FilterIterator(scan, expression)
(results, saved, done, _) = await engine.execute(iterator, math.inf)
assert len(results) == 1
async def test_operation_filter_iterator():
expression = "10 = 5 * 2"
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'],
triple['object'])
scan = ProjectionIterator(ScanIterator(iterator, triple, card))
iterator = FilterIterator(scan, expression)
(results, saved, done, _) = await engine.execute(iterator, math.inf)
assert len(results) == 9
async def test_projection_read_stopped():
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'],
triple['object'])
scan = ScanIterator(iterator, triple, card)
proj = ProjectionIterator(scan, ['?common'])
(results, saved, done, _) = await engine.execute(proj, 10e-4)
assert len(results) <= card
for res in results:
assert '?common' in res and '?s1' not in res
async def test_rowbind_join_proj():
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'], triple['object'])
scan=ScanIterator(iterator, triple, card)
bind=BindIterator(scan,"URI(CONCAT('http://',MD5(CONCAT(STR(?s),STR('http://isa'),STR(?o)))))",'?z')
join=IndexJoinIterator(bind,innerTriple,hdtDoc)
proj=ProjectionIterator(join,['?z'])
#print(proj)
(results, saved, done, _) = await engine.execute(proj, 10e7)
#print(results)
assert len(results) > 0
assert done
async def test_and_or_filter_iterator():
context = { 'quantum': 10e7, 'max_results': 10e7 }
expression = "?p = <http://schema.org/eligibleRegion> && (?o = <http://db.uwaterloo.ca/~galuc/wsdbm/Country0> || ?o = <http://db.uwaterloo.ca/~galuc/wsdbm/Country9>)"
scan = ProjectionIterator(ScanIterator(hdtDoc, triple, context), context)
iterator = FilterIterator(scan, expression, context)
(results, saved, done, _) = await engine.execute(iterator, context)
assert len(results) == 2
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
async def test_and_or_filter_iterator():
expression = "?p = <http://schema.org/eligibleRegion> && (?o = <http://db.uwaterloo.ca/~galuc/wsdbm/Country0> || ?o = <http://db.uwaterloo.ca/~galuc/wsdbm/Country9>)"
iterator, card = hdtDoc.search(triple['subject'], triple['predicate'],
triple['object'])
scan = ProjectionIterator(ScanIterator(iterator, triple, card))
iterator = FilterIterator(scan, expression)
(results, saved, done, _) = await engine.execute(iterator, math.inf)
assert len(results) == 2
for b in results:
assert b['?p'] == 'http://schema.org/eligibleRegion'
assert b['?o'] in [
'http://db.uwaterloo.ca/~galuc/wsdbm/Country0',
'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
]
def load_projection(saved_plan: SavedProjectionIterator, dataset: Dataset) -> PreemptableIterator:
"""Load a ProjectionIterator from a protobuf serialization.
Args:
* saved_plan: Saved query execution plan.
* dataset: RDF dataset used to execute the plan.
Returns:
The pipeline of iterator used to continue query execution.
"""
sourceField = saved_plan.WhichOneof('source')
source = load(getattr(saved_plan, sourceField), dataset)
values = saved_plan.values if len(saved_plan.values) > 0 else None
return ProjectionIterator(source, values)
def parse_query_node(node,
dataset,
current_graphs,
server_url,
cardinalities,
renaming_map=None):
"""
Recursively parse node in the query logical plan to build a preemptable physical query execution plan.
Args:
* node - Node of the logical plan to parse (in rdflib format)
* dataset - RDF dataset used to execute the query
* current_graphs - List of IRI of the current RDF graph queried
* server_url - URL of the SaGe server
* cardinalities - Map<triple,integer> used to track triple patterns cardinalities
"""
if node.name == 'SelectQuery':
# in case of a FROM clause, set the new default graphs used
graphs = current_graphs
if node.datasetClause is not None:
graphs = [
format_graph_uri(format_term(graph_iri.default), server_url)
for graph_iri in node.datasetClause
]
return parse_query_node(node.p, dataset, graphs, server_url,
cardinalities)
elif node.name == 'Project':
query_vars = list(map(lambda t: t.n3(), node.PV))
if node.p.name == 'AggregateJoin' or node.p.name == 'Extend':
# forward projection variables, as we need them for parsing an AggregateJoin
node.p['PV'] = query_vars
return parse_query_node(node.p, dataset, current_graphs,
server_url, cardinalities)
child = parse_query_node(node.p, dataset, current_graphs, server_url,
cardinalities)
return ProjectionIterator(child, dataset, current_graphs[0],
query_vars)
elif node.name == 'BGP':
# bgp_vars = node._vars
triples = list(localize_triple(node.triples, current_graphs))
# format triple patterns for the backend API
patterns = []
for triple in triples:
graph_uri = triple[
'graph'] if 'graph' in triple else current_graphs[0]
graph = dataset.get_graph(graph_uri)
patterns.append({
'subject':
triple['subject'] if triple['subject'].startswith('?') else
graph.get_identifiant(triple['subject']),
'predicate':
triple['predicate'] if triple['predicate'].startswith('?') else
graph.get_identifiant(triple['predicate']),
'object':
triple['object'] if triple['object'].startswith('?') else
graph.get_identifiant(triple['object']),
'graph':
graph_uri
})
iterator, query_vars, c = build_left_plan(patterns, dataset,
current_graphs)
# track cardinalities of every triple pattern
cardinalities += c
return iterator
elif node.name == 'Union':
left = parse_query_node(node.p1, dataset, current_graphs, server_url,
cardinalities)
right = parse_query_node(node.p2, dataset, current_graphs, server_url,
cardinalities)
return BagUnionIterator(left, right)
elif node.name == 'Filter':
expression = parse_filter_expr(node.expr)
iterator = parse_query_node(node.p, dataset, current_graphs,
server_url, cardinalities)
return FilterIterator(iterator, expression)
elif node.name == 'Join':
# only allow for joining BGPs from different GRAPH clauses
triples = fetch_graph_triples(node.p1, current_graphs, server_url)
triples += fetch_graph_triples(node.p2, current_graphs, server_url)
iterator, query_vars, c = build_left_plan(triples, dataset,
current_graphs)
# track cardinalities of every triple pattern
cardinalities += c
return iterator
elif node.name == 'Extend':
# remove all extend operators, as they are not needed
current = node
renaming = dict()
while current.name == 'Extend':
renaming[current.expr.n3()] = current.var.n3()
current = current.p
current['PV'] = node['PV']
return parse_query_node(current,
dataset,
current_graphs,
server_url,
cardinalities,
renaming_map=renaming)
elif node.name == 'AggregateJoin':
groupby_variables = list()
# build GROUP BY variables
last_groupby_var = None
if node.p.expr is None: # case 1: no explicit group BY, so we group by all variables in the query
last_groupby_var = list(node.p._vars)[0]
# for variable in node.p._vars:
# groupby_variables.append(variable.n3())
# last_groupby_var = variable
else: # case 2: there is an explicit group by
for variable in node.p.expr:
groupby_variables.append(variable.n3())
last_groupby_var = variable
# build aggregators for evaluating SPARQL aggregations (if any)
aggregators = list()
for agg in node.A:
if agg.vars == '*':
agg.vars = last_groupby_var
if agg.name != 'Aggregate_Sample':
aggregators.append(build_aggregator(dataset, agg,
renaming_map))
# build source iterator from child node
source = parse_query_node(node.p.p, dataset, current_graphs,
server_url, cardinalities)
# add the GROUP BY operator (with aggregators) to the pipeline
source = GroupByAggregator(source,
groupby_variables,
aggregators=aggregators,
max_size=dataset.max_group_by_size)
# add the projection to the pipeline, depending of the context
return AggregatesProjectionIterator(source, dataset, current_graphs[0],
node.PV)
else:
raise UnsupportedSPARQL("Unsupported SPARQL feature: {}".format(
node.name))
def parse_query_alt(node: dict,
dataset: Dataset,
current_graphs: List[str],
cardinalities: dict,
as_of: Optional[datetime] = None) -> PreemptableIterator:
"""Recursively parse node in the query logical plan to build a preemptable physical query execution plan.
Args:
* node: Node of the logical plan to parse (in rdflib format).
* dataset: RDF dataset used to execute the query.
* current_graphs: List of IRI of the current RDF graphs queried.
* cardinalities: A dict used to track triple patterns cardinalities.
* as_of: A timestamp used to perform all reads against a consistent version of the dataset. If `None`, use the latest version of the dataset, which does not guarantee snapshot isolation.
Returns: An iterator used to evaluate the input node.
Throws: `UnsupportedSPARQL` is the SPARQL query contains features not supported by the SaGe query engine.
"""
if node.name == 'SelectQuery':
# in case of a FROM clause, set the new default graphs used
graphs = current_graphs
if node.datasetClause is not None:
graphs = [
format_term(graph_iri.default)
for graph_iri in node.datasetClause
]
return parse_query_alt(node.p,
dataset,
graphs,
cardinalities,
as_of=as_of)
elif node.name == 'ConstructQuery':
graphs = current_graphs
if node.datasetClause is not None:
graphs = [
format_term(graph_iri.default)
for graph_iri in node.datasetClause
]
child = parse_query_alt(node.p,
dataset,
graphs,
cardinalities,
as_of=as_of)
return ConstructIterator(child,
convert_construct_template(node.template))
elif node.name == 'Reduced':
child = parse_query_alt(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return ReducedIterator(child)
elif node.name == 'Project':
query_vars = list(map(lambda t: '?' + str(t), node.PV))
child = parse_query_alt(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return ProjectionIterator(child, query_vars)
elif node.name == 'BGP':
# bgp_vars = node._vars
triples = list(localize_triples(node.triples, current_graphs))
iterator, query_vars, c = build_left_join_tree(triples,
dataset,
current_graphs,
as_of=as_of)
# track cardinalities of every triple pattern
cardinalities += c
return iterator
elif node.name == 'Union':
left = parse_query_alt(node.p1,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
right = parse_query_alt(node.p2,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return BagUnionIterator(left, right)
elif node.name == 'Filter':
expression = parse_filter_expr(node.expr)
iterator = parse_query_alt(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return FilterIterator(iterator, expression)
elif node.name == 'Extend':
bgp_iterator = parse_query_alt(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
expression = parse_bind_expr(node.expr)
#print("expression:"+str(expression))
if isinstance(bgp_iterator, EmptyIterator):
return BindIterator(None, expression, '?' + node.var)
else:
return BindIterator(bgp_iterator, expression, '?' + node.var)
elif node.name == 'Join':
left = parse_query_alt(node.p1,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
if node.p2.name == 'BGP':
triples = list(localize_triples(node.p2.triples, current_graphs))
variables = set(map(lambda t: t.n3(), node.p1._vars))
#print("Join P1 _vars"+str(variables))
iterator, query_vars, c = continue_left_join_tree(
left, variables, triples, dataset, current_graphs)
cardinalities += c
return iterator
else:
raise UnsupportedSPARQL(
f"Join Unsupported SPARQL feature: {node.p2.name}")
else:
raise UnsupportedSPARQL(f"Unsupported SPARQL feature: {node.name}")
def parse_query_node(node: dict,
dataset: Dataset,
current_graphs: List[str],
cardinalities: dict,
as_of: Optional[datetime] = None) -> PreemptableIterator:
"""Recursively parse node in the query logical plan to build a preemptable physical query execution plan.
Args:
* node: Node of the logical plan to parse (in rdflib format).
* dataset: RDF dataset used to execute the query.
* current_graphs: List of IRI of the current RDF graphs queried.
* cardinalities: A dict used to track triple patterns cardinalities.
* as_of: A timestamp used to perform all reads against a consistent version of the dataset. If `None`, use the latest version of the dataset, which does not guarantee snapshot isolation.
Returns: An iterator used to evaluate the input node.
Throws: `UnsupportedSPARQL` is the SPARQL query contains features not supported by the SaGe query engine.
"""
if node.name == 'SelectQuery':
# in case of a FROM clause, set the new default graphs used
graphs = current_graphs
if node.datasetClause is not None:
graphs = [
format_term(graph_iri.default)
for graph_iri in node.datasetClause
]
return parse_query_node(node.p,
dataset,
graphs,
cardinalities,
as_of=as_of)
elif node.name == 'Project':
query_vars = list(map(lambda t: '?' + str(t), node.PV))
child = parse_query_node(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return ProjectionIterator(child, query_vars)
elif node.name == 'BGP':
# bgp_vars = node._vars
triples = list(localize_triples(node.triples, current_graphs))
iterator, query_vars, c = build_left_join_tree(triples,
dataset,
current_graphs,
as_of=as_of)
# track cardinalities of every triple pattern
cardinalities += c
return iterator
elif node.name == 'Union':
left = parse_query_node(node.p1,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
right = parse_query_node(node.p2,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return BagUnionIterator(left, right)
elif node.name == 'Filter':
expression = parse_filter_expr(node.expr)
iterator = parse_query_node(node.p,
dataset,
current_graphs,
cardinalities,
as_of=as_of)
return FilterIterator(iterator, expression)
elif node.name == 'Join':
# only allow for joining BGPs from different GRAPH clauses
triples = get_triples_from_graph(
node.p1, current_graphs) + get_triples_from_graph(
node.p2, current_graphs)
iterator, query_vars, c = build_left_join_tree(triples, dataset,
current_graphs)
# track cardinalities of every triple pattern
cardinalities += c
return iterator
else:
raise UnsupportedSPARQL(f"Unsupported SPARQL feature: {node.name}")
def build_join_plan(bgp, dataset, default_graph):
"""Build a join plan with a projection at the end"""
iterator, query_vars, cardinalities = build_left_plan(
bgp, dataset, default_graph)
return ProjectionIterator(iterator, dataset, default_graph[0],
query_vars), cardinalities