def test_load_from_savedPlan():
bgp = [{
'subject': '?s',
'predicate': 'http://schema.org/eligibleRegion',
'object': 'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
}, {
'subject': '?s',
'predicate': 'http://purl.org/goodrelations/includes',
'object': '?includes'
}]
query = {'type': 'bgp', 'bgp': bgp}
plan, c = build_query_plan(query, datasets, 'watdiv100')
savedPlan = plan.save()
plan, c = build_query_plan(None, datasets, 'watdiv100', savedPlan)
assert type(plan) is ProjectionIterator
assert type(plan._source) is IndexJoinIterator
assert plan._source._innerTriple == bgp[1]
assert type(plan._source._source) is ScanIterator
assert plan._source._source._triple == bgp[0]
def test_empty_patterns():
bgp = [{
'subject': '?s',
'predicate': 'http://schema.org/unkwnownPredicate',
'object': '?o1'
}, {
'subject': '?s',
'predicate': 'http://schema.org/sillyPredicate',
'object': '?o2'
}]
query = {'type': 'bgp', 'bgp': bgp}
plan, c = build_query_plan(query, datasets, 'watdiv100')
assert not plan.has_next()
def test_build_union():
query = {
'type':
'union',
'union': [[{
'subject': '?s',
'predicate': 'http://schema.org/eligibleRegion',
'object': 'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
}],
[{
'subject': '?s',
'predicate': 'http://purl.org/goodrelations/includes',
'object': '?includes'
}]]
}
plan, c = build_query_plan(query, datasets, 'watdiv100')
assert type(plan) is BagUnionIterator
def test_build_left_linear_plan():
bgp = [{
'subject': '?s',
'predicate': 'http://schema.org/eligibleRegion',
'object': 'http://db.uwaterloo.ca/~galuc/wsdbm/Country9'
}, {
'subject': '?s',
'predicate': 'http://purl.org/goodrelations/includes',
'object': '?includes'
}]
query = {'type': 'bgp', 'bgp': bgp}
plan, c = build_query_plan(query, hdtDoc)
assert type(plan) is ProjectionIterator
assert type(plan._source) is IndexJoinIterator
assert plan._source._innerTriple == bgp[1]
assert type(plan._source._source) is ScanIterator
assert plan._source._source._triple == bgp[0]
def sparql_query(graph_name):
"""WARNING: old API, deprecated"""
graph = dataset.get_graph(graph_name)
if graph is None:
abort(404)
logger.debug('[/sparql/] Corresponding dataset found')
mimetype = request.accept_mimetypes.best_match([
"application/json", "application/xml",
"application/sparql-results+json", "application/sparql-results+xml"
])
url = secure_url(request.url)
try:
# A GET request always returns the homepage of the dataset
if request.method == "GET" or (not request.is_json):
dinfo = graph.describe(url)
dinfo['@id'] = url
void_desc = {
"nt": VoidDescriptor(url, graph).describe("ntriples"),
"ttl": VoidDescriptor(url, graph).describe("turtle"),
"xml": VoidDescriptor(url, graph).describe("xml")
}
return render_template("website/sage_dataset.html",
dataset_info=dinfo,
void_desc=void_desc)
engine = SageEngine()
post_query, err = QueryRequest().load(request.get_json())
if err is not None and len(err) > 0:
return Response(format_marshmallow_errors(err), status=400)
quota = graph.quota / 1000
max_results = graph.max_results
# Load next link
next_link = None
if 'next' in post_query:
next_link = decode_saved_plan(post_query["next"])
# build physical query plan, then execute it with the given quota
start = time()
plan, cardinalities = build_query_plan(post_query["query"],
dataset, graph_name,
next_link)
loading_time = (time() - start) * 1000 # convert in milliseconds
bindings, saved_plan, is_done = engine.execute(
plan, quota, max_results)
# compute controls for the next page
start = time()
next_page = None
if not is_done:
next_page = encode_saved_plan(saved_plan)
exportTime = (time() - start) * 1000 # convert in milliseconds
stats = {
"cardinalities": cardinalities,
"import": loading_time,
"export": exportTime
}
if mimetype == "application/sparql-results+json":
res = Response(responses.w3c_json_streaming(
bindings, next_page, stats, url),
content_type='application/json')
if mimetype == "application/xml" or mimetype == "application/sparql-results+xml":
res = Response(responses.w3c_xml(bindings, next_page, stats),
content_type="application/xml")
else:
res = Response(responses.raw_json_streaming(
bindings, next_page, stats, url),
content_type='application/json')
# set deprecation warning in headers
res.headers.add(
"Warning",
"199 SaGe/2.0 \"You are using a deprecated API. Consider uppgrading to the SaGe SPARQL query API. See http://sage.univ-nantes.fr/documentation fore more details.\""
)
return res
except Exception as e:
logger.error(e)
abort(500)
def lookup_entity(graph_name, entity):
"""Evaluates a DESCRIBE query over a RDF dataset"""
logger.debug('[IP: {}] [/lookup/] Querying {}'.format(
request.environ['REMOTE_ADDR'], graph_name))
graph = dataset.get_graph(graph_name)
if graph is None:
abort(404)
url = secure_url(request.url)
try:
engine = SageEngine()
# Get entity and possible next link
entity_uri = secure_url(request.base_url)
next_link = request.args.get("next", default=None)
post_query = build_describe_query(entity_uri)
logger.debug('[IP: {}] [/lookup/] Entity={}'.format(
request.environ['REMOTE_ADDR'], entity_uri))
quota = graph.quota / 1000
max_results = graph.max_results
# Load next link
if next_link is not None:
logger.debug(
'[/lookup/{}] Saved plan found, decoding "next" link'.
format(graph_name))
next_link = decode_saved_plan(next_link)
else:
logger.debug('[/lookup/{}] Query to evaluate: {}'.format(
graph_name, post_query))
# build physical query plan, then execute it with the given quota
logger.debug(
'[/lookup/{}] Starting query evaluation...'.format(graph_name))
# start = time()
plan, cardinalities = build_query_plan(post_query, dataset,
graph_name, next_link)
# loading_time = (time() - start) * 1000
bindings, saved_plan, is_done = engine.execute(
plan, quota, max_results)
logger.debug(
'[/lookup/{}] Query evaluation completed'.format(graph_name))
# compute controls for the next page
# start = time()
next_page = None
if is_done:
logger.debug(
'[/lookup/{}] Query completed under the time quota'.format(
graph_name))
else:
logger.debug(
'[/lookup/{}] The query was not completed under the time quota...'
.format(graph_name))
logger.debug(
'[/lookup/{}] Saving the execution to plan to generate a "next" link'
.format(graph_name))
next_page = encode_saved_plan(saved_plan)
logger.debug(
'[/lookup/{}] "next" link successfully generated'.format(
graph_name))
# exportTime = (time() - start) * 1000
# stats = {"import": loading_time, "export": exportTime}
triples = bindings_to_triple(entity_uri, bindings, url)
headers = dict()
if next_page is not None:
headers["X-Sage-Next"] = "{}?next={}".format(
entity_uri, next_page)
headers[
"Link"] = "<{}?next={}>; rel=\"next\"; title=\"Next page\"".format(
entity_uri, next_page)
return Response(responses.ntriples_streaming(triples),
content_type="application/ntriples",
headers=headers)
except Exception as e:
logger.error(e)
abort(500)
def sparql_query(dataset_name):
logger.info('[IP: {}] [/sparql/] Querying {}'.format(
request.environ['REMOTE_ADDR'], dataset_name))
dataset = datasets.get_dataset(dataset_name)
if dataset is None:
abort(404)
logger.debug('[/sparql/] Corresponding dataset found')
mimetype = request.accept_mimetypes.best_match([
"application/json", "application/xml",
"application/sparql-results+json", "application/sparql-results+xml"
])
url = secure_url(request.url)
try:
# A GET request always returns the homepage of the dataset
if request.method == "GET" or (not request.is_json):
dinfo = dataset.describe(url)
dinfo['@id'] = url
void_desc = {
"nt": VoidDescriptor(url, dataset).describe("ntriples"),
"ttl": VoidDescriptor(url, dataset).describe("turtle"),
"xml": VoidDescriptor(url, dataset).describe("xml")
}
return render_template("sage.html",
dataset_info=dinfo,
void_desc=void_desc)
engine = SageEngine()
post_query, err = QueryRequest().load(request.get_json())
if err is not None and len(err) > 0:
return Response(format_marshmallow_errors(err), status=400)
logger.info('[IP: {}] [/sparql/] Query={}'.format(
request.environ['REMOTE_ADDR'], post_query))
quota = dataset.quota / 1000
max_results = dataset.max_results
# Load next link
next_link = None
if 'next' in post_query:
logger.debug(
'[/sparql/{}] Saved plan found, decoding "next" link'.
format(dataset_name))
next_link = decode_saved_plan(post_query["next"])
else:
logger.debug('[/sparql/{}] Query to evaluate: {}'.format(
dataset_name, post_query))
# build physical query plan, then execute it with the given quota
logger.debug('[/sparql/{}] Starting query evaluation...'.format(
dataset_name))
start = time()
plan, cardinalities = build_query_plan(post_query["query"],
dataset, next_link)
loading_time = (time() - start) * 1000
bindings, saved_plan, is_done = engine.execute(
plan, quota, max_results)
logger.debug(
'[/sparql/{}] Query evaluation completed'.format(dataset_name))
# compute controls for the next page
start = time()
next_page = None
if is_done:
logger.debug(
'[/sparql/{}] Query completed under the time quota'.format(
dataset_name))
else:
logger.debug(
'[/sparql/{}] The query was not completed under the time quota...'
.format(dataset_name))
logger.debug(
'[/sparql/{}] Saving the execution to plan to generate a "next" link'
.format(dataset_name))
next_page = encode_saved_plan(saved_plan)
logger.debug(
'[/sparql/{}] "next" link successfully generated'.format(
dataset_name))
exportTime = (time() - start) * 1000
stats = {
"cardinalities": cardinalities,
"import": loading_time,
"export": exportTime
}
if mimetype == "application/sparql-results+json":
return json.jsonify(responses.json(bindings, next_page, stats))
if mimetype == "application/xml" or mimetype == "application/sparql-results+xml":
return Response(responses.xml(bindings, next_page, stats),
content_type="application/xml")
return json.jsonify(responses.raw_json(bindings, next_page, stats))
except Exception:
abort(500)