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