def append_search_filters(self, value, node, query, request):
try:
if value["val"] != "":
match_query = Match(field="tiles.data.%s" % (str(node.pk)),
type="phrase",
query=value["val"])
if "!" in value["op"]:
query.must_not(match_query)
query.filter(Exists(field="tiles.data.%s" %
(str(node.pk))))
else:
query.must(match_query)
except KeyError as e:
pass
def append_search_filters(self, value, node, query, request):
try:
if value['val'] != '':
match_query = Match(field='tiles.data.%s' % (str(node.pk)),
type="phrase",
query=value['val'])
if '!' in value['op']:
query.must_not(match_query)
query.filter(Exists(field="tiles.data.%s" %
(str(node.pk))))
else:
query.must(match_query)
except KeyError, e:
pass
def get_indexed_concepts(se, conceptid, concept_value):
"""
Searches for a conceptid from the database and confirms that the database concept value matches the indexed value
"""
result = 'failed: cannot find' + conceptid
query = Query(se, start=0, limit=100)
phrase = Match(field='conceptid', query=conceptid, type='phrase_prefix')
query.add_query(phrase)
results = query.search(index='concept_labels')
if len(results['hits']['hits']) > 0:
source = results['hits']['hits'][0]['_source']
if conceptid == source['conceptid'] or concept_value == source['value']:
result = 'passed'
else:
result = 'failed: concept value does not match'
return result
def append_search_filters(self, value, node, query, request):
# Match the label in the same manner as a String datatype
try:
if value["val"] != "":
match_type = "phrase_prefix" if "~" in value["op"] else "phrase"
if "~" in value["op"]:
match_query = Match(
field="tiles.data.%s.url" % (str(node.pk)),
query=value["val"],
type=match_type,
)
if "=" in value["op"]:
match_query = Term(field="tiles.data.%s.url.keyword" % (str(node.pk)), term=value["val"])
if "!" in value["op"]:
query.must_not(match_query)
query.filter(Exists(field="tiles.data.%s" % (str(node.pk))))
else:
query.must(match_query)
except KeyError as e:
pass
def append_search_filters(self, value, node, query, request):
try:
if value["op"] == "null" or value["op"] == "not_null":
self.append_null_search_filters(value, node, query, request)
elif value["val"] != "":
base_query = Bool()
base_query.filter(
Terms(field="graph_id", terms=[str(node.graph_id)]))
match_query = Nested(path="tiles",
query=Match(field="tiles.data.%s" %
(str(node.pk)),
type="phrase",
query=value["val"]))
if "!" in value["op"]:
base_query.must_not(match_query)
# base_query.filter(Exists(field="tiles.data.%s" % (str(node.pk))))
else:
base_query.must(match_query)
query.must(base_query)
except KeyError as e:
pass
def test_bulk_delete(self):
"""
Test bulk deleting of documents in Elasticsearch
"""
se = SearchEngineFactory().create()
# se.create_index(index='test')
for i in range(10):
x = {
'id': i,
'type': 'prefLabel',
'value': 'test pref label',
}
se.index_data(index='test',
doc_type='test',
body=x,
idfield='id',
refresh=True)
y = {
'id': i + 100,
'type': 'altLabel',
'value': 'test alt label',
}
se.index_data(index='test',
doc_type='test',
body=y,
idfield='id',
refresh=True)
query = Query(se, start=0, limit=100)
match = Match(field='type', query='altLabel')
query.add_query(match)
query.delete(index='test', refresh=True)
self.assertEqual(
se.es.count(index='test', doc_type='test')['count'], 10)
def test_delete_by_query(self):
"""
Test deleting documents by query in Elasticsearch
"""
se = SearchEngineFactory().create()
for i in range(10):
x = {"id": i, "type": "prefLabel", "value": "test pref label"}
se.index_data(index="test", body=x, idfield="id", refresh=True)
y = {"id": i + 100, "type": "altLabel", "value": "test alt label"}
se.index_data(index="test", body=y, idfield="id", refresh=True)
time.sleep(1)
query = Query(se, start=0, limit=100)
match = Match(field="type", query="altLabel")
query.add_query(match)
query.delete(index="test", refresh=True)
self.assertEqual(se.count(index="test"), 10)
def build_search_results_dsl(request):
# Results are sorted ascendingly by the value of SITE_ID.E42, which is displayed as primary name of Heritage Resources.
# Must go back to this method once new Automatic Resource ID has been fully developed (AZ 10/08/16) Update 06/09/16: EAMENA_ID.E42 now used as sorting criterion.
sorting = {
"child_entities.label": {
"order" : "asc",
"nested_path": "child_entities",
"nested_filter": {
"term": {"child_entities.entitytypeid" : "EAMENA_ID.E42"}
}
}
}
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(request.GET.get('spatialFilter', None))
export = request.GET.get('export', None)
page = 1 if request.GET.get('page') == '' else int(request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(request.GET.get('temporalFilter', None))
boolean_search = request.GET.get('booleanSearch', '')
filter_and_or = JSONDeserializer().deserialize(request.GET.get('termFilterAndOr', ''))
filter_grouping = JSONDeserializer().deserialize(request.GET.get('termFilterGroup', ''))
filter_combine_flags = JSONDeserializer().deserialize(request.GET.get('termFilterCombineWithPrev', ''))
#Ignore first entry as it is a dummy
filter_combine_flags = filter_combine_flags[1:]
# filter_combine_flags = [False, True, False, False, False]
# filter_groups = JSONDeserializer().deserialize(request.GET.get('termFilterGroups', ''))
# Not here yet, so put in some bogus data
# filter_groups = [
# 'NAME.E41',
# 'NAME.E41',
# 'DISTURBANCE_STATE.E3',
# 'THREAT_STATE.E3'
# ]
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit*int(page-1), limit=limit)
boolquery = Bool()
boolfilter = Bool()
is_empty_temporal_filter = True
# store each search term in an initially. These will be combined based on the global and/or and the optional groupings
terms_queries = [];
# logging.warning("-------QUERY-------")
if term_filter != '' or not is_empty_temporal_filter:
for index, select_box in enumerate(JSONDeserializer().deserialize(term_filter)):
selectbox_boolfilter = Bool()
groupid = filter_grouping[index]
if not groupid == 'No group':
# build a nested query against the nested_entities
# build a nested query for each resource type
for resourcetype in settings.RESOURCE_TYPE_CONFIGS().keys():
# trace the path from each term to the group root
term_paths = []
for term in select_box:
# trace path from group root to this term
if term['type'] == 'concept':
# get all the parent concepts for this value i.e. the field
concept_relations = models.ConceptRelations.objects.filter(conceptidto=term['value'], relationtype="member")
for relation in concept_relations:
term_parent_concept = models.Concepts.objects.get(conceptid=relation.conceptidfrom)
# get the steps from the root to that concept
if term_parent_concept.nodetype.nodetype == "Collection":
term_schema = Entity.get_mapping_schema_to(term_parent_concept.legacyoid)
elif term_parent_concept.nodetype.nodetype == 'Concept':
# need to get at the parent until we reach the root collection. concepts are arranged hierarchically
parent_relations_to = models.ConceptRelations.objects.filter(conceptidto=term_parent_concept.conceptid, relationtype='member')
grandparent = models.Concepts.objects.filter(conceptid=parent_relations_to[0].conceptidfrom)
term_schema = Entity.get_mapping_schema_to(grandparent[0].legacyoid)
#this path begins at the root, and ends up at the node in question
if resourcetype in term_schema:
term_path = term_schema[resourcetype]['steps']
term_paths.append({
'term': term,
'path': term_path
})
break
elif term['type'] == 'term':
concept = models.Concepts.objects.get(conceptid=term['context'])
term_schema = Entity.get_mapping_schema_to(concept.legacyoid)
if resourcetype in term_schema:
term_path = term_schema[resourcetype]['steps']
term_paths.append({
'term': term,
'path': term_path
})
elif term['type'] == 'string':
term_schema = Entity.get_mapping_schema_to(groupid)
if resourcetype in term_schema:
term_path = term_schema[resourcetype]['steps']
term_paths.append({
'term': term,
'path': term_path
})
if 'year_min_max' in temporal_filter[index] and len(temporal_filter[index]['year_min_max']) == 2:
start_date = date(temporal_filter[index]['year_min_max'][0], 1, 1)
end_date = date(temporal_filter[index]['year_min_max'][1], 12, 31)
if start_date:
start_date = start_date.isoformat()
if end_date:
end_date = end_date.isoformat()
if 'inverted' not in temporal_filter[index]:
inverted_temporal_filter = False
else:
if temporal_filter[index]['inverted']:
inverted_temporal_filter = True
else:
inverted_temporal_filter = False
term_paths.append({
'term': {
'date_operator': '3',
'start_date': start_date,
'end_date': end_date,
'type': 'date',
'inverted': inverted_temporal_filter
},
'path': term_path
})
if 'filters' in temporal_filter[index]:
term_schema = Entity.get_mapping_schema_to(groupid)
if resourcetype in term_schema:
term_path = term_schema[resourcetype]['steps']
for temporal_filter_item in temporal_filter[index]['filters']:
date_type = ''
searchdate = ''
date_operator = ''
for node in temporal_filter_item['nodes']:
if node['entitytypeid'] == 'DATE_COMPARISON_OPERATOR.E55':
date_operator = node['value']
elif node['entitytypeid'] == 'date':
searchdate = node['value']
else:
date_type = node['value']
date_value = datetime.strptime(searchdate, '%Y-%m-%d').isoformat()
if 'inverted' not in temporal_filter[index]:
inverted_temporal_filter = False
else:
if temporal_filter[index]['inverted']:
inverted_temporal_filter = True
else:
inverted_temporal_filter = False
term_paths.append({
'term': {
'date_operator': date_operator,
'date_value': date_value,
'type': 'date',
'inverted': inverted_temporal_filter
},
'path': term_path
})
# combine the traced path to build a nested query
group_query = nested_query_from_pathed_values(term_paths, 'nested_entity.child_entities')
# add nested query to overall query
selectbox_boolfilter.should(group_query)
# logging.warning("BOX QUERY - %s", JSONSerializer().serialize(selectbox_boolfilter, indent=2))
else:
for term in select_box:
if term['type'] == 'term':
entitytype = models.EntityTypes.objects.get(conceptid_id=term['context'])
boolfilter_nested = Bool()
boolfilter_nested.must(Terms(field='child_entities.entitytypeid', terms=[entitytype.pk]))
boolfilter_nested.must(Match(field='child_entities.value', query=term['value'], type='phrase'))
nested = Nested(path='child_entities', query=boolfilter_nested)
if filter_and_or[index] == 'or':
if not term['inverted']:
selectbox_boolfilter.should(nested)
else:
if term['inverted']:
selectbox_boolfilter.must_not(nested)
else:
selectbox_boolfilter.must(nested)
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
terms = Terms(field='domains.conceptid', terms=concept_ids)
nested = Nested(path='domains', query=terms)
if filter_and_or[index] == 'or':
if not term['inverted']:
selectbox_boolfilter.should(nested)
else:
if term['inverted']:
selectbox_boolfilter.must_not(nested)
else:
selectbox_boolfilter.must(nested)
elif term['type'] == 'string':
boolquery2 = Bool() #This bool contains the subset of nested string queries on both domains and child_entities paths
boolfilter_folded = Bool() #This bool searches by string in child_entities, where free text strings get indexed
boolfilter_folded2 = Bool() #This bool searches by string in the domains path,where controlled vocabulary concepts get indexed
boolfilter_folded.should(Match(field='child_entities.value', query=term['value'], type='phrase_prefix', fuzziness='AUTO', operator='and'))
boolfilter_folded.should(Match(field='child_entities.value.folded', query=term['value'], type='phrase_prefix', fuzziness='AUTO', operator='and'))
boolfilter_folded.should(Match(field='child_entities.value.folded', query=term['value'], fuzziness='AUTO', operator='and'))
nested = Nested(path='child_entities', query=boolfilter_folded)
boolfilter_folded2.should(Match(field='domains.label', query=term['value'], type='phrase_prefix', fuzziness='AUTO', operator='and'))
boolfilter_folded2.should(Match(field='domains.label.folded', query=term['value'], type='phrase_prefix', fuzziness='AUTO', operator='and'))
boolfilter_folded2.should(Match(field='domains.label.folded', query=term['value'], fuzziness='AUTO', operator='and'))
nested2 = Nested(path='domains', query=boolfilter_folded2)
boolquery2.should(nested)
boolquery2.should(nested2)
if filter_and_or[index] == 'or':
if not term['inverted']:
# use boolfilter here instead of boolquery because boolquery
# can't be combined with other boolfilters using boolean OR
selectbox_boolfilter.should(boolquery2)
else:
if term['inverted']:
selectbox_boolfilter.must_not(boolquery2)
else:
selectbox_boolfilter.must(boolquery2)
if 'year_min_max' in temporal_filter[index] and len(temporal_filter[index]['year_min_max']) == 2:
start_date = date(temporal_filter[index]['year_min_max'][0], 1, 1)
end_date = date(temporal_filter[index]['year_min_max'][1], 12, 31)
if start_date:
start_date = start_date.isoformat()
if end_date:
end_date = end_date.isoformat()
range = Range(field='dates.value', gte=start_date, lte=end_date)
nested = Nested(path='dates', query=range)
if 'inverted' not in temporal_filter[index]:
temporal_filter[index]['inverted'] = False
if temporal_filter[index]['inverted']:
selectbox_boolfilter.must_not(nested)
else:
selectbox_boolfilter.must(nested)
if 'filters' in temporal_filter[index]:
for temporal_filter_item in temporal_filter[index]['filters']:
date_type = ''
searchdate = ''
date_operator = ''
for node in temporal_filter_item['nodes']:
if node['entitytypeid'] == 'DATE_COMPARISON_OPERATOR.E55':
date_operator = node['value']
elif node['entitytypeid'] == 'date':
searchdate = node['value']
else:
date_type = node['value']
date_value = datetime.strptime(searchdate, '%Y-%m-%d').isoformat()
if date_operator == '1': # equals query
range = Range(field='dates.value', gte=date_value, lte=date_value)
elif date_operator == '0': # greater than query
range = Range(field='dates.value', lt=date_value)
elif date_operator == '2': # less than query
range = Range(field='dates.value', gt=date_value)
nested = Nested(path='dates', query=range)
if 'inverted' not in temporal_filter[index]:
temporal_filter[index]['inverted'] = False
if temporal_filter[index]['inverted']:
selectbox_boolfilter.must_not(nested)
else:
selectbox_boolfilter.must(nested)
terms_queries.append(selectbox_boolfilter)
# if not selectbox_boolfilter.empty:
# if boolean_search == 'or':
# boolfilter.should(selectbox_boolfilter)
# else:
# boolfilter.must(selectbox_boolfilter)
# We now have individual query terms for each of the search components. Combine into one group now
# Start by building a an array of groups which will be combined according to the global And/Or
# Queries within one of these groups will be combined by the complement of the global And/Or
# We may end up with [ [A,B], [C], [D,E] ], which would translate to either:
# (A || B) && C && (D || E)
# or
# (A && B) || C || (D && E)
# for global AND or OR respectively
# logging.warning("TERMS QUERIES %s", terms_queries)
bool_components = [];
for i, term_query in enumerate(terms_queries):
if i is 0:
bool_components.append([term_query])
else:
should_group_with_previous = filter_combine_flags[i-1]
if should_group_with_previous:
bool_components[-1].append(term_query)
else:
bool_components.append([term_query])
# logging.warning("BOOL COMPONENTS %s", bool_components)
# Now build the ES queries
for bool_component in bool_components:
if len(bool_component) is 1:
# just combine this on its own
q = bool_component[0]
else:
q = Bool()
for sub_component in bool_component:
if boolean_search == 'or':
#apply the OPPOSITE of the global boolean operator
q.must(sub_component)
else:
q.should(sub_component)
# combine to the overall query according to the global boolean operator
if boolean_search == 'or':
boolfilter.should(q)
else:
boolfilter.must(q)
if 'geometry' in spatial_filter and 'type' in spatial_filter['geometry'] and spatial_filter['geometry']['type'] != '':
geojson = spatial_filter['geometry']
if geojson['type'] == 'bbox':
coordinates = [[geojson['coordinates'][0],geojson['coordinates'][3]], [geojson['coordinates'][2],geojson['coordinates'][1]]]
geoshape = GeoShape(field='geometries.value', type='envelope', coordinates=coordinates )
nested = Nested(path='geometries', query=geoshape)
else:
buffer = spatial_filter['buffer']
geojson = JSONDeserializer().deserialize(_buffer(geojson,buffer['width'],buffer['unit']).json)
geoshape = GeoShape(field='geometries.value', type=geojson['type'], coordinates=geojson['coordinates'] )
nested = Nested(path='geometries', query=geoshape)
if 'inverted' not in spatial_filter:
spatial_filter['inverted'] = False
if spatial_filter['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
if not boolquery.empty:
query.add_query(boolquery)
if not boolfilter.empty:
query.add_filter(boolfilter)
# Sorting criterion added to query (AZ 10/08/16)
query.dsl.update({'sort': sorting})
# logging.warning("-=-==-=-===-=--=-==-=-===-=- query: -=-==-=-===-=--=-==-=-===-=-> %s", query)
return query
def search_terms(request):
lang = request.GET.get("lang", settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get("q", "")
user_is_reviewer = user_is_resource_reviewer(request.user)
i = 0
ret = {}
for index in ["terms", "concepts"]:
query = Query(se, start=0, limit=0)
boolquery = Bool()
boolquery.should(
Match(field="value",
query=searchString.lower(),
type="phrase_prefix"))
boolquery.should(
Match(field="value.folded",
query=searchString.lower(),
type="phrase_prefix"))
boolquery.should(
Match(field="value.folded",
query=searchString.lower(),
fuzziness="AUTO",
prefix_length=settings.SEARCH_TERM_SENSITIVITY))
if user_is_reviewer is False and index == "terms":
boolquery.filter(Terms(field="provisional", terms=["false"]))
query.add_query(boolquery)
base_agg = Aggregation(name="value_agg",
type="terms",
field="value.raw",
size=settings.SEARCH_DROPDOWN_LENGTH,
order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name="nodegroupid",
type="terms",
field="nodegroupid")
top_concept_agg = Aggregation(name="top_concept",
type="terms",
field="top_concept")
conceptid_agg = Aggregation(name="conceptid",
type="terms",
field="conceptid")
max_score_agg = MaxAgg(name="max_score", script="_score")
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
ret[index] = []
results = query.search(index=index)
if results is not None:
for result in results["aggregations"]["value_agg"]["buckets"]:
if len(result["top_concept"]["buckets"]) > 0:
for top_concept in result["top_concept"]["buckets"]:
top_concept_id = top_concept["key"]
top_concept_label = get_preflabel_from_conceptid(
top_concept["key"], lang)["value"]
for concept in top_concept["conceptid"]["buckets"]:
ret[index].append({
"type": "concept",
"context": top_concept_id,
"context_label": top_concept_label,
"id": i,
"text": result["key"],
"value": concept["key"],
})
i = i + 1
else:
ret[index].append({
"type":
"term",
"context":
"",
"context_label":
get_resource_model_label(result),
"id":
i,
"text":
result["key"],
"value":
result["key"],
})
i = i + 1
return JSONResponse(ret)
def build_search_results_dsl(request):
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(
request.GET.get('mapFilter', '{}'))
include_provisional = get_provisional_type(request)
export = request.GET.get('export', None)
mobile_download = request.GET.get('mobiledownload', None)
page = 1 if request.GET.get('page') == '' else int(
request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(
request.GET.get('temporalFilter', '{}'))
advanced_filters = JSONDeserializer().deserialize(
request.GET.get('advanced', '[]'))
search_buffer = None
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
elif mobile_download != None:
limit = settings.MOBILE_DOWNLOAD_RESOURCE_LIMIT
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit * int(page - 1), limit=limit)
search_query = Bool()
nested_agg = NestedAgg(path='points', name='geo_aggs')
nested_agg_filter = FiltersAgg(name='inner')
if include_provisional == True:
nested_agg_filter.add_filter(
Terms(field='points.provisional', terms=['false', 'true']))
else:
provisional_resource_filter = Bool()
if include_provisional == False:
provisional_resource_filter.filter(
Terms(field='provisional', terms=['false', 'partial']))
nested_agg_filter.add_filter(
Terms(field='points.provisional', terms=['false']))
elif include_provisional == 'only provisional':
provisional_resource_filter.filter(
Terms(field='provisional', terms=['true', 'partial']))
nested_agg_filter.add_filter(
Terms(field='points.provisional', terms=['true']))
search_query.must(provisional_resource_filter)
nested_agg_filter.add_aggregation(
GeoHashGridAgg(field='points.point',
name='grid',
precision=settings.HEX_BIN_PRECISION))
nested_agg_filter.add_aggregation(
GeoBoundsAgg(field='points.point', name='bounds'))
nested_agg.add_aggregation(nested_agg_filter)
query.add_aggregation(nested_agg)
permitted_nodegroups = get_permitted_nodegroups(request.user)
if term_filter != '':
for term in JSONDeserializer().deserialize(term_filter):
term_query = Bool()
provisional_term_filter = Bool()
if term['type'] == 'term' or term['type'] == 'string':
string_filter = Bool()
if term['type'] == 'term':
string_filter.must(
Match(field='strings.string',
query=term['value'],
type='phrase'))
elif term['type'] == 'string':
string_filter.should(
Match(field='strings.string',
query=term['value'],
type='phrase_prefix'))
string_filter.should(
Match(field='strings.string.folded',
query=term['value'],
type='phrase_prefix'))
if include_provisional == False:
string_filter.must_not(
Match(field='strings.provisional',
query='true',
type='phrase'))
elif include_provisional == 'only provisional':
string_filter.must_not(
Match(field='strings.provisional',
query='false',
type='phrase'))
string_filter.filter(
Terms(field='strings.nodegroup_id',
terms=permitted_nodegroups))
nested_string_filter = Nested(path='strings',
query=string_filter)
if term['inverted']:
search_query.must_not(nested_string_filter)
else:
search_query.must(nested_string_filter)
# need to set min_score because the query returns results with score 0 and those have to be removed, which I don't think it should be doing
query.min_score('0.01')
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
conceptid_filter = Bool()
conceptid_filter.filter(
Terms(field='domains.conceptid', terms=concept_ids))
conceptid_filter.filter(
Terms(field='domains.nodegroup_id',
terms=permitted_nodegroups))
if include_provisional == False:
conceptid_filter.must_not(
Match(field='domains.provisional',
query='true',
type='phrase'))
elif include_provisional == 'only provisional':
conceptid_filter.must_not(
Match(field='domains.provisional',
query='false',
type='phrase'))
nested_conceptid_filter = Nested(path='domains',
query=conceptid_filter)
if term['inverted']:
search_query.must_not(nested_conceptid_filter)
else:
search_query.filter(nested_conceptid_filter)
if 'features' in spatial_filter:
if len(spatial_filter['features']) > 0:
feature_geom = spatial_filter['features'][0]['geometry']
feature_properties = {}
if 'properties' in spatial_filter['features'][0]:
feature_properties = spatial_filter['features'][0][
'properties']
buffer = {'width': 0, 'unit': 'ft'}
if 'buffer' in feature_properties:
buffer = feature_properties['buffer']
search_buffer = _buffer(feature_geom, buffer['width'],
buffer['unit'])
feature_geom = JSONDeserializer().deserialize(search_buffer.json)
geoshape = GeoShape(field='geometries.geom.features.geometry',
type=feature_geom['type'],
coordinates=feature_geom['coordinates'])
invert_spatial_search = False
if 'inverted' in feature_properties:
invert_spatial_search = feature_properties['inverted']
spatial_query = Bool()
if invert_spatial_search == True:
spatial_query.must_not(geoshape)
else:
spatial_query.filter(geoshape)
# get the nodegroup_ids that the user has permission to search
spatial_query.filter(
Terms(field='geometries.nodegroup_id',
terms=permitted_nodegroups))
if include_provisional == False:
spatial_query.filter(
Terms(field='geometries.provisional', terms=['false']))
elif include_provisional == 'only provisional':
spatial_query.filter(
Terms(field='geometries.provisional', terms=['true']))
search_query.filter(Nested(path='geometries', query=spatial_query))
if 'fromDate' in temporal_filter and 'toDate' in temporal_filter:
now = str(datetime.utcnow())
start_date = ExtendedDateFormat(temporal_filter['fromDate'])
end_date = ExtendedDateFormat(temporal_filter['toDate'])
date_nodeid = str(
temporal_filter['dateNodeId']
) if 'dateNodeId' in temporal_filter and temporal_filter[
'dateNodeId'] != '' else None
query_inverted = False if 'inverted' not in temporal_filter else temporal_filter[
'inverted']
temporal_query = Bool()
if query_inverted:
# inverted date searches need to use an OR clause and are generally more complicated to structure (can't use ES must_not)
# eg: less than START_DATE OR greater than END_DATE
inverted_date_query = Bool()
inverted_date_ranges_query = Bool()
if start_date.is_valid():
inverted_date_query.should(
Range(field='dates.date', lt=start_date.lower))
inverted_date_ranges_query.should(
Range(field='date_ranges.date_range', lt=start_date.lower))
if end_date.is_valid():
inverted_date_query.should(
Range(field='dates.date', gt=end_date.upper))
inverted_date_ranges_query.should(
Range(field='date_ranges.date_range', gt=end_date.upper))
date_query = Bool()
date_query.filter(inverted_date_query)
date_query.filter(
Terms(field='dates.nodegroup_id', terms=permitted_nodegroups))
if include_provisional == False:
date_query.filter(
Terms(field='dates.provisional', terms=['false']))
elif include_provisional == 'only provisional':
date_query.filter(
Terms(field='dates.provisional', terms=['true']))
if date_nodeid:
date_query.filter(Term(field='dates.nodeid', term=date_nodeid))
else:
date_ranges_query = Bool()
date_ranges_query.filter(inverted_date_ranges_query)
date_ranges_query.filter(
Terms(field='date_ranges.nodegroup_id',
terms=permitted_nodegroups))
if include_provisional == False:
date_ranges_query.filter(
Terms(field='date_ranges.provisional',
terms=['false']))
elif include_provisional == 'only provisional':
date_ranges_query.filter(
Terms(field='date_ranges.provisional', terms=['true']))
temporal_query.should(
Nested(path='date_ranges', query=date_ranges_query))
temporal_query.should(Nested(path='dates', query=date_query))
else:
date_query = Bool()
date_query.filter(
Range(field='dates.date',
gte=start_date.lower,
lte=end_date.upper))
date_query.filter(
Terms(field='dates.nodegroup_id', terms=permitted_nodegroups))
if include_provisional == False:
date_query.filter(
Terms(field='dates.provisional', terms=['false']))
elif include_provisional == 'only provisional':
date_query.filter(
Terms(field='dates.provisional', terms=['true']))
if date_nodeid:
date_query.filter(Term(field='dates.nodeid', term=date_nodeid))
else:
date_ranges_query = Bool()
date_ranges_query.filter(
Range(field='date_ranges.date_range',
gte=start_date.lower,
lte=end_date.upper,
relation='intersects'))
date_ranges_query.filter(
Terms(field='date_ranges.nodegroup_id',
terms=permitted_nodegroups))
if include_provisional == False:
date_ranges_query.filter(
Terms(field='date_ranges.provisional',
terms=['false']))
if include_provisional == 'only provisional':
date_ranges_query.filter(
Terms(field='date_ranges.provisional', terms=['true']))
temporal_query.should(
Nested(path='date_ranges', query=date_ranges_query))
temporal_query.should(Nested(path='dates', query=date_query))
search_query.filter(temporal_query)
datatype_factory = DataTypeFactory()
if len(advanced_filters) > 0:
advanced_query = Bool()
grouped_query = Bool()
grouped_queries = [grouped_query]
for index, advanced_filter in enumerate(advanced_filters):
tile_query = Bool()
for key, val in advanced_filter.iteritems():
if key != 'op':
node = models.Node.objects.get(pk=key)
if request.user.has_perm('read_nodegroup', node.nodegroup):
datatype = datatype_factory.get_instance(node.datatype)
datatype.append_search_filters(val, node, tile_query,
request)
nested_query = Nested(path='tiles', query=tile_query)
if advanced_filter['op'] == 'or' and index != 0:
grouped_query = Bool()
grouped_queries.append(grouped_query)
grouped_query.must(nested_query)
for grouped_query in grouped_queries:
advanced_query.should(grouped_query)
search_query.must(advanced_query)
query.add_query(search_query)
if search_buffer != None:
search_buffer = search_buffer.geojson
return {'query': query, 'search_buffer': search_buffer}
def search_terms(request):
lang = request.GET.get('lang', settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get('q', '')
query = Query(se, start=0, limit=0)
user_is_reviewer = request.user.groups.filter(
name='Resource Reviewer').exists()
boolquery = Bool()
boolquery.should(
Match(field='value',
query=searchString.lower(),
type='phrase_prefix',
fuzziness='AUTO'))
boolquery.should(
Match(field='value.folded',
query=searchString.lower(),
type='phrase_prefix',
fuzziness='AUTO'))
boolquery.should(
Match(field='value.folded',
query=searchString.lower(),
fuzziness='AUTO'))
if user_is_reviewer is False:
boolquery.filter(Terms(field='provisional', terms=['false']))
query.add_query(boolquery)
base_agg = Aggregation(name='value_agg',
type='terms',
field='value.raw',
size=settings.SEARCH_DROPDOWN_LENGTH,
order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name='nodegroupid',
type='terms',
field='nodegroupid')
top_concept_agg = Aggregation(name='top_concept',
type='terms',
field='top_concept')
conceptid_agg = Aggregation(name='conceptid',
type='terms',
field='conceptid')
max_score_agg = MaxAgg(name='max_score', script='_score')
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
results = query.search(index='strings') or {'hits': {'hits': []}}
i = 0
ret = []
for result in results['aggregations']['value_agg']['buckets']:
if len(result['top_concept']['buckets']) > 0:
for top_concept in result['top_concept']['buckets']:
top_concept_id = top_concept['key']
top_concept_label = get_preflabel_from_conceptid(
top_concept['key'], lang)['value']
for concept in top_concept['conceptid']['buckets']:
ret.append({
'type': 'concept',
'context': top_concept_id,
'context_label': top_concept_label,
'id': i,
'text': result['key'],
'value': concept['key']
})
i = i + 1
else:
ret.append({
'type': 'term',
'context': '',
'context_label': get_resource_model_label(result),
'id': i,
'text': result['key'],
'value': result['key']
})
i = i + 1
return JSONResponse(ret)
def build_base_search_results_dsl(request):
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(request.GET.get('spatialFilter', None))
export = request.GET.get('export', None)
page = 1 if request.GET.get('page') == '' else int(request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(request.GET.get('temporalFilter', None))
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit*int(page-1), limit=limit)
boolquery = Bool()
boolfilter = Bool()
if term_filter != '':
# Ce uporabnik ni avtenticiran, prikazemo le veljavne (to je verjetno potrebno se dodelati (mogoce da vidijo le svoje???)!!!)
if (request.user.username == 'anonymous'):
auto_filter = []
for item in JSONDeserializer().deserialize(term_filter):
auto_filter.append(item)
# Poiscimo concept id in context za Published status
AUTO_TERM_FILTER = get_auto_filter(request)
auto_filter.append(AUTO_TERM_FILTER)
term_filter = JSONSerializer().serialize(auto_filter)
print 'term_filter'
if term_filter != '':
for term in JSONDeserializer().deserialize(term_filter):
print term
if term['type'] == 'term':
entitytype = models.EntityTypes.objects.get(conceptid_id=term['context'])
boolfilter_nested = Bool()
boolfilter_nested.must(Terms(field='child_entities.entitytypeid', terms=[entitytype.pk]))
boolfilter_nested.must(Match(field='child_entities.value', query=term['value'], type='phrase'))
nested = Nested(path='child_entities', query=boolfilter_nested)
if term['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
terms = Terms(field='domains.conceptid', terms=concept_ids)
nested = Nested(path='domains', query=terms)
if term['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
elif term['type'] == 'string':
boolfilter_folded = Bool()
boolfilter_folded.should(Match(field='child_entities.value', query=term['value'], type='phrase_prefix'))
boolfilter_folded.should(Match(field='child_entities.value.folded', query=term['value'], type='phrase_prefix'))
nested = Nested(path='child_entities', query=boolfilter_folded)
if term['inverted']:
boolquery.must_not(nested)
else:
boolquery.must(nested)
if 'geometry' in spatial_filter and 'type' in spatial_filter['geometry'] and spatial_filter['geometry']['type'] != '':
geojson = spatial_filter['geometry']
if geojson['type'] == 'bbox':
coordinates = [[geojson['coordinates'][0],geojson['coordinates'][3]], [geojson['coordinates'][2],geojson['coordinates'][1]]]
geoshape = GeoShape(field='geometries.value', type='envelope', coordinates=coordinates )
nested = Nested(path='geometries', query=geoshape)
else:
buffer = spatial_filter['buffer']
geojson = JSONDeserializer().deserialize(_buffer(geojson,buffer['width'],buffer['unit']).json)
geoshape = GeoShape(field='geometries.value', type=geojson['type'], coordinates=geojson['coordinates'] )
nested = Nested(path='geometries', query=geoshape)
if 'inverted' not in spatial_filter:
spatial_filter['inverted'] = False
if spatial_filter['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
if 'year_min_max' in temporal_filter and len(temporal_filter['year_min_max']) == 2:
start_date = date(temporal_filter['year_min_max'][0], 1, 1)
end_date = date(temporal_filter['year_min_max'][1], 12, 31)
if start_date:
start_date = start_date.isoformat()
if end_date:
end_date = end_date.isoformat()
range = Range(field='dates.value', gte=start_date, lte=end_date)
nested = Nested(path='dates', query=range)
if 'inverted' not in temporal_filter:
temporal_filter['inverted'] = False
if temporal_filter['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
if not boolquery.empty:
query.add_query(boolquery)
if not boolfilter.empty:
query.add_filter(boolfilter)
return query
def build_search_results_dsl(request):
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(
request.GET.get('mapFilter', '{}'))
export = request.GET.get('export', None)
page = 1 if request.GET.get('page') == '' else int(
request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(
request.GET.get('temporalFilter', '{}'))
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit * int(page - 1), limit=limit)
boolquery = Bool()
boolfilter = Bool()
if term_filter != '':
for term in JSONDeserializer().deserialize(term_filter):
if term['type'] == 'term':
term_filter = Bool()
term_filter.must(
Match(field='strings', query=term['value'], type='phrase'))
if term['inverted']:
boolfilter.must_not(term_filter)
else:
boolfilter.must(term_filter)
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
conceptid_filter = Terms(field='domains.conceptid',
terms=concept_ids)
if term['inverted']:
boolfilter.must_not(conceptid_filter)
else:
boolfilter.must(conceptid_filter)
elif term['type'] == 'string':
string_filter = Bool()
string_filter.should(
Match(field='strings',
query=term['value'],
type='phrase_prefix'))
string_filter.should(
Match(field='strings.folded',
query=term['value'],
type='phrase_prefix'))
if term['inverted']:
boolfilter.must_not(string_filter)
else:
boolfilter.must(string_filter)
if 'features' in spatial_filter:
if len(spatial_filter['features']) > 0:
feature_geom = spatial_filter['features'][0]['geometry']
feature_properties = spatial_filter['features'][0]['properties']
buffer = {'width': 0, 'unit': 'ft'}
if 'buffer' in feature_properties:
buffer = feature_properties['buffer']
feature_geom = JSONDeserializer().deserialize(
_buffer(feature_geom, buffer['width'], buffer['unit']).json)
geoshape = GeoShape(field='geometries.features.geometry',
type=feature_geom['type'],
coordinates=feature_geom['coordinates'])
invert_spatial_search = False
if 'inverted' in feature_properties:
invert_spatial_search = feature_properties['inverted']
if invert_spatial_search == True:
boolfilter.must_not(geoshape)
else:
boolfilter.must(geoshape)
if 'fromDate' in temporal_filter and 'toDate' in temporal_filter:
start_date = None
end_date = None
try:
start_date = parser.parse(temporal_filter['fromDate'])
start_date = start_date.isoformat()
except:
pass
try:
end_date = parser.parse(temporal_filter['toDate'])
end_date = end_date.isoformat()
except:
pass
if 'dateNodeId' in temporal_filter and temporal_filter[
'dateNodeId'] != '':
range = Range(field='tiles.data.%s' %
(temporal_filter['dateNodeId']),
gte=start_date,
lte=end_date)
time_query_dsl = Nested(path='tiles', query=range)
else:
time_query_dsl = Range(field='dates', gte=start_date, lte=end_date)
if 'inverted' not in temporal_filter:
temporal_filter['inverted'] = False
if temporal_filter['inverted']:
boolfilter.must_not(time_query_dsl)
else:
boolfilter.must(time_query_dsl)
if not boolquery.empty:
query.add_query(boolquery)
if not boolfilter.empty:
query.add_filter(boolfilter)
return query
def append_dsl(self, search_results_object, permitted_nodegroups,
include_provisional):
search_query = Bool()
querysting_params = self.request.GET.get(details["componentname"], "")
for term in JSONDeserializer().deserialize(querysting_params):
if term["type"] == "term" or term["type"] == "string":
string_filter = Bool()
if term["type"] == "term":
string_filter.must(
Match(field="strings.string",
query=term["value"],
type="phrase"))
elif term["type"] == "string":
string_filter.should(
Match(field="strings.string",
query=term["value"],
type="phrase_prefix"))
string_filter.should(
Match(field="strings.string.folded",
query=term["value"],
type="phrase_prefix"))
if include_provisional is False:
string_filter.must_not(
Match(field="strings.provisional",
query="true",
type="phrase"))
elif include_provisional == "only provisional":
string_filter.must_not(
Match(field="strings.provisional",
query="false",
type="phrase"))
string_filter.filter(
Terms(field="strings.nodegroup_id",
terms=permitted_nodegroups))
nested_string_filter = Nested(path="strings",
query=string_filter)
if term["inverted"]:
search_query.must_not(nested_string_filter)
else:
search_query.must(nested_string_filter)
# need to set min_score because the query returns results with score 0 and those have to be removed, which I don't think it should be doing
search_results_object["query"].min_score("0.01")
elif term["type"] == "concept":
concept_ids = _get_child_concepts(term["value"])
conceptid_filter = Bool()
conceptid_filter.filter(
Terms(field="domains.conceptid", terms=concept_ids))
conceptid_filter.filter(
Terms(field="domains.nodegroup_id",
terms=permitted_nodegroups))
if include_provisional is False:
conceptid_filter.must_not(
Match(field="domains.provisional",
query="true",
type="phrase"))
elif include_provisional == "only provisional":
conceptid_filter.must_not(
Match(field="domains.provisional",
query="false",
type="phrase"))
nested_conceptid_filter = Nested(path="domains",
query=conceptid_filter)
if term["inverted"]:
search_query.must_not(nested_conceptid_filter)
else:
search_query.filter(nested_conceptid_filter)
search_results_object["query"].add_query(search_query)
def nested_query_from_pathed_values(pathed_values, stem):
"""
Given an array of pathed values to query terms from the root, return a nested query
pathed_values: e.g.
[
{
val: '29430-4955-...'
path: [a, b, c]
}
]
stem: the path into the index for the nested terms. This will be of the form 'nested_entity.child_entities.child_entities'
"""
# f( [[A,B,C], [A,B,D] )
# = Nested( AND( f( [[B,C],[B,D]] ))
# = Nested( AND( Nested( AND( f([[C],[D]]) )) ))
# = Nested( AND( Nested( AND( valueC, valueD))))
# f( [[A,B,C], [A,B,D], [A,B,D] )
# = Nested( AND( f([[B,C],[B,D],[B,D]] ))
# = Nested( AND( Nested( AND( f([[C],[D],[D]]) )) ))
# = Nested( AND( Nested( AND( valueB, valueD))))
# group paths by their head of each paths list is the same, make a single nested query and recurse on the tails
branch_groups = {} # those groups with a continuing tail, where we will recursively build a nested query
leaf_groups = [] # those groups without a continuing tail, where we will use an ordinary term query
# build the groups
for v in pathed_values:
path = v['path']
if len(path) == 1:
# this goes in its own group
leaf_groups.append(v)
else:
# see if there is already a group using this head
head = v['path'][0]['entitytyperange']
if head not in branch_groups:
branch_groups[head] = []
branch_groups[head].append(v)
# We should now have a set of groups
# create the bool query
bool_term = Bool()
# add terms for any leaf groups
for leaf_group in leaf_groups:
if leaf_group['term']['type'] == 'concept':
if leaf_group['term']['inverted']:
terms = Terms(field=stem+'.conceptid', terms=leaf_group['term']['value'])
n_terms = Nested(path=stem, query=terms)
bool_term.must_not(n_terms)
else:
terms = Terms(field=stem+'.conceptid', terms=leaf_group['term']['value'])
n_terms = Nested(path=stem, query=terms)
bool_term.must(n_terms)
elif leaf_group['term']['type'] == 'term':
# boolfilter_nested.must(Terms(field='child_entities.entitytypeid', terms=[entitytype.pk]))
# boolfilter_nested.must(Match(field='child_entities.value', query=term['value'], type='phrase'))
entitytype = models.EntityTypes.objects.get(conceptid_id=leaf_group['term']['context'])
sub_bool = Bool()
if leaf_group['term']['inverted']:
sub_bool.must_not(Terms(field=stem+'.entitytypeid', terms=[entitytype.pk]))
sub_bool.must_not(Match(field=stem+'.value', query=leaf_group['term']['value'], type='phrase'))
else:
sub_bool.must(Terms(field=stem+'.entitytypeid', terms=[entitytype.pk]))
sub_bool.must(Match(field=stem+'.value', query=leaf_group['term']['value'], type='phrase'))
nsub_bool = Nested(path=stem, query=sub_bool)
bool_term.must(nsub_bool)
elif leaf_group['term']['type'] == 'string':
boolfilter_folded = Bool()
boolfilter_folded.should(Match(field=stem+'.flat_child_entities.label', query=leaf_group['term']['value'], type='phrase_prefix', fuzziness='AUTO'))
boolfilter_folded.should(Match(field=stem+'.flat_child_entities.label.folded', query=leaf_group['term']['value'], type='phrase_prefix', fuzziness='AUTO'))
boolfilter_folded.should(Match(field=stem+'.flat_child_entities.label.folded', query=leaf_group['term']['value'], fuzziness='AUTO'))
nested = Nested(path=stem+'.flat_child_entities', query=boolfilter_folded)
if leaf_group['term']['inverted']:
bool_term.must_not(nested)
else:
bool_term.must(nested)
elif leaf_group['term']['type'] == 'date':
if leaf_group['term']['date_operator'] == '1': # equals query
daterange = Range(field=stem+'.flat_child_entities.date', gte=leaf_group['term']['date_value'], lte=leaf_group['term']['date_value'])
elif leaf_group['term']['date_operator'] == '0': # greater than query
daterange = Range(field=stem+'.flat_child_entities.date', lt=leaf_group['term']['date_value'])
elif leaf_group['term']['date_operator'] == '2': # less than query
daterange = Range(field=stem+'.flat_child_entities.date', gt=leaf_group['term']['date_value'])
elif leaf_group['term']['date_operator'] == '3': # greater than and less than query
daterange = Range(field=stem+'.flat_child_entities.date', gte=leaf_group['term']['start_date'], lte=leaf_group['term']['end_date'])
nested_date = Nested(path=stem+'.flat_child_entities', query=daterange)
if leaf_group['term']['inverted']:
bool_term.must_not(nested_date)
else:
bool_term.must(nested_date)
# add terms for any branch groups
for key in branch_groups:
# add a nested term for each group
branch_group = branch_groups[key]
#remove head from each path and recurse
for value in branch_group:
value['path'] = value['path'][1:]
sub_query = nested_query_from_pathed_values(branch_group, stem+'.child_entities')
nsub_query = Nested(path=stem, query=sub_query)
bool_term.must(nsub_query)
return bool_term;
def search(request):
searchString = request.GET["q"]
removechildren = request.GET.get("removechildren", None)
query = Query(se, start=0, limit=100)
phrase = Match(field="value",
query=searchString.lower(),
type="phrase_prefix")
query.add_query(phrase)
results = query.search(index=CONCEPTS_INDEX)
ids = []
if removechildren is not None:
ids = [
concept[0] for concept in Concept().get_child_concepts(
removechildren, columns="conceptidto::text")
]
ids.append(removechildren)
newresults = []
cached_scheme_names = {}
for result in results["hits"]["hits"]:
if result["_source"]["conceptid"] not in ids:
# first look to see if we've already retrieved the top concept name
# else look up the top concept name with ES and cache the result
top_concept = result["_source"]["top_concept"]
if top_concept in cached_scheme_names:
result["in_scheme_name"] = cached_scheme_names[top_concept]
else:
query = Query(se, start=0, limit=100)
phrase = Match(field="conceptid",
query=top_concept,
type="phrase")
query.add_query(phrase)
scheme = query.search(index=CONCEPTS_INDEX)
for label in scheme["hits"]["hits"]:
if label["_source"]["type"] == "prefLabel":
cached_scheme_names[top_concept] = label["_source"][
"value"]
result["in_scheme_name"] = label["_source"]["value"]
newresults.append(result)
# Use the db to get the concept context but this is SLOW
# for result in results['hits']['hits']:
# if result['_source']['conceptid'] not in ids:
# concept = Concept().get(id=result['_source']['conceptid'], include_parentconcepts=True)
# pathlist = concept.get_paths()
# result['in_scheme_name'] = pathlist[0][0]['label']
# newresults.append(result)
# def crawl(conceptid, path=[]):
# query = Query(se, start=0, limit=100)
# bool = Bool()
# bool.must(Match(field='conceptto', query=conceptid, type='phrase'))
# bool.must(Match(field='relationtype', query='narrower', type='phrase'))
# query.add_query(bool)
# relations = query.search(index='concept_relations')
# for relation in relations['hits']['hits']:
# path.insert(0, relation)
# crawl(relation['_source']['conceptfrom'], path=path)
# return path
# for result in results['hits']['hits']:
# if result['_source']['conceptid'] not in ids:
# concept_relations = crawl(result['_source']['conceptid'], path=[])
# if len(concept_relations) > 0:
# conceptid = concept_relations[0]['_source']['conceptfrom']
# if conceptid in cached_scheme_names:
# result['in_scheme_name'] = cached_scheme_names[conceptid]
# else:
# result['in_scheme_name'] = get_preflabel_from_conceptid(conceptid, lang=request.LANGUAGE_CODE)['value']
# cached_scheme_names[conceptid] = result['in_scheme_name']
# newresults.append(result)
results["hits"]["hits"] = newresults
return JSONResponse(results)
def search(request):
se = SearchEngineFactory().create()
searchString = request.GET['q']
removechildren = request.GET.get('removechildren', None)
query = Query(se, start=0, limit=100)
phrase = Match(field='value',
query=searchString.lower(),
type='phrase_prefix')
query.add_query(phrase)
results = query.search(index='concept_labels')
ids = []
if removechildren != None:
concepts = Concept().get(id=removechildren,
include_subconcepts=True,
include=None)
def get_children(concept):
ids.append(concept.id)
concepts.traverse(get_children)
newresults = []
cached_scheme_names = {}
for result in results['hits']['hits']:
if result['_source']['conceptid'] not in ids:
# first look to see if we've already retrieved the scheme name
# else look up the scheme name with ES and cache the result
if result['_type'] in cached_scheme_names:
result['in_scheme_name'] = cached_scheme_names[result['_type']]
else:
query = Query(se, start=0, limit=100)
phrase = Match(field='conceptid',
query=result['_type'],
type='phrase')
query.add_query(phrase)
scheme = query.search(index='concept_labels')
for label in scheme['hits']['hits']:
if label['_source']['type'] == 'prefLabel':
cached_scheme_names[
result['_type']] = label['_source']['value']
result['in_scheme_name'] = label['_source']['value']
newresults.append(result)
# Use the db to get the concept context but this is SLOW
# for result in results['hits']['hits']:
# if result['_source']['conceptid'] not in ids:
# concept = Concept().get(id=result['_source']['conceptid'], include_parentconcepts=True)
# pathlist = concept.get_paths()
# result['in_scheme_name'] = pathlist[0][0]['label']
# newresults.append(result)
# def crawl(conceptid, path=[]):
# query = Query(se, start=0, limit=100)
# bool = Bool()
# bool.must(Match(field='conceptidto', query=conceptid, type='phrase'))
# bool.must(Match(field='relationtype', query='narrower', type='phrase'))
# query.add_query(bool)
# relations = query.search(index='concept_relations')
# for relation in relations['hits']['hits']:
# path.insert(0, relation)
# crawl(relation['_source']['conceptidfrom'], path=path)
# return path
# for result in results['hits']['hits']:
# if result['_source']['conceptid'] not in ids:
# concept_relations = crawl(result['_source']['conceptid'], path=[])
# if len(concept_relations) > 0:
# conceptid = concept_relations[0]['_source']['conceptidfrom']
# if conceptid in cached_scheme_names:
# result['in_scheme_name'] = cached_scheme_names[conceptid]
# else:
# result['in_scheme_name'] = get_preflabel_from_conceptid(conceptid, lang=settings.LANGUAGE_CODE)['value']
# cached_scheme_names[conceptid] = result['in_scheme_name']
# newresults.append(result)
results['hits']['hits'] = newresults
return JSONResponse(results)
def append_dsl(self, search_results_object, permitted_nodegroups,
include_provisional):
search_query = Bool()
querysting_params = self.request.GET.get(details['componentname'], '')
for term in JSONDeserializer().deserialize(querysting_params):
if term['type'] == 'term' or term['type'] == 'string':
string_filter = Bool()
if term['type'] == 'term':
string_filter.must(
Match(field='strings.string',
query=term['value'],
type='phrase'))
elif term['type'] == 'string':
string_filter.should(
Match(field='strings.string',
query=term['value'],
type='phrase_prefix'))
string_filter.should(
Match(field='strings.string.folded',
query=term['value'],
type='phrase_prefix'))
if include_provisional is False:
string_filter.must_not(
Match(field='strings.provisional',
query='true',
type='phrase'))
elif include_provisional == 'only provisional':
string_filter.must_not(
Match(field='strings.provisional',
query='false',
type='phrase'))
string_filter.filter(
Terms(field='strings.nodegroup_id',
terms=permitted_nodegroups))
nested_string_filter = Nested(path='strings',
query=string_filter)
if term['inverted']:
search_query.must_not(nested_string_filter)
else:
search_query.must(nested_string_filter)
# need to set min_score because the query returns results with score 0 and those have to be removed, which I don't think it should be doing
search_results_object['query'].min_score('0.01')
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
conceptid_filter = Bool()
conceptid_filter.filter(
Terms(field='domains.conceptid', terms=concept_ids))
conceptid_filter.filter(
Terms(field='domains.nodegroup_id',
terms=permitted_nodegroups))
if include_provisional is False:
conceptid_filter.must_not(
Match(field='domains.provisional',
query='true',
type='phrase'))
elif include_provisional == 'only provisional':
conceptid_filter.must_not(
Match(field='domains.provisional',
query='false',
type='phrase'))
nested_conceptid_filter = Nested(path='domains',
query=conceptid_filter)
if term['inverted']:
search_query.must_not(nested_conceptid_filter)
else:
search_query.filter(nested_conceptid_filter)
search_results_object['query'].add_query(search_query)
def build_search_results_dsl(request):
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(request.GET.get('spatialFilter', None))
export = request.GET.get('export', None)
page = 1 if request.GET.get('page') == '' else int(request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(request.GET.get('temporalFilter', None))
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit*int(page-1), limit=limit)
boolquery = Bool()
boolfilter = Bool()
if term_filter != '':
for term in JSONDeserializer().deserialize(term_filter):
if term['type'] == 'term':
entitytype = models.EntityTypes.objects.get(conceptid_id=term['context'])
boolfilter_nested = Bool()
boolfilter_nested.must(Terms(field='child_entities.entitytypeid', terms=[entitytype.pk]))
boolfilter_nested.must(Match(field='child_entities.value', query=term['value'], type='phrase'))
nested = Nested(path='child_entities', query=boolfilter_nested)
if term['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
terms = Terms(field='domains.conceptid', terms=concept_ids)
nested = Nested(path='domains', query=terms)
if term['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
elif term['type'] == 'string':
boolfilter_folded = Bool()
boolfilter_folded.should(Match(field='child_entities.value', query=term['value'], type='phrase_prefix'))
boolfilter_folded.should(Match(field='child_entities.value.folded', query=term['value'], type='phrase_prefix'))
nested = Nested(path='child_entities', query=boolfilter_folded)
if term['inverted']:
boolquery.must_not(nested)
else:
boolquery.must(nested)
if 'geometry' in spatial_filter and 'type' in spatial_filter['geometry'] and spatial_filter['geometry']['type'] != '':
geojson = spatial_filter['geometry']
if geojson['type'] == 'bbox':
coordinates = [[geojson['coordinates'][0],geojson['coordinates'][3]], [geojson['coordinates'][2],geojson['coordinates'][1]]]
geoshape = GeoShape(field='geometries.value', type='envelope', coordinates=coordinates )
nested = Nested(path='geometries', query=geoshape)
else:
buffer = spatial_filter['buffer']
geojson = JSONDeserializer().deserialize(_buffer(geojson,buffer['width'],buffer['unit']).json)
geoshape = GeoShape(field='geometries.value', type=geojson['type'], coordinates=geojson['coordinates'] )
nested = Nested(path='geometries', query=geoshape)
if 'inverted' not in spatial_filter:
spatial_filter['inverted'] = False
if spatial_filter['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
if 'year_min_max' in temporal_filter and len(temporal_filter['year_min_max']) == 2:
start = temporal_filter['year_min_max'][0]*10000
end = temporal_filter['year_min_max'][1]*10000
range = Range(field='extendeddates.value', gte=start, lte=end)
nested = Nested(path='extendeddates', query=range)
if 'inverted' not in temporal_filter:
temporal_filter['inverted'] = False
if temporal_filter['inverted']:
boolfilter.must_not(nested)
else:
boolfilter.must(nested)
if 'filters' in temporal_filter:
time_boolfilter = Bool()
for temporal_filter in temporal_filter['filters']:
date_type = ''
date = ''
date_operator = ''
for node in temporal_filter['nodes']:
if node['entitytypeid'] == 'DATE_COMPARISON_OPERATOR.E55':
date_operator = node['value']
elif node['entitytypeid'] == 'date':
date = node['value']
else:
date_type = node['value']
terms = Terms(field='extendeddategroups.conceptid', terms=date_type)
boolfilter.must(terms)
date_value = date_to_int(date)
if date_operator == '1': # equals query
range = Range(field='extendeddategroups.value', gte=date_value, lte=date_value)
elif date_operator == '0': # greater than query
range = Range(field='extendeddategroups.value', lt=date_value)
elif date_operator == '2': # less than query
range = Range(field='extendeddategroups.value', gt=date_value)
if 'inverted' not in temporal_filter:
temporal_filter['inverted'] = False
if temporal_filter['inverted']:
boolfilter.must_not(range)
else:
boolfilter.must(range)
if not boolquery.empty:
query.add_query(boolquery)
if not boolfilter.empty:
query.add_filter(boolfilter)
return query
def build_search_results_dsl(request):
term_filter = request.GET.get('termFilter', '')
spatial_filter = JSONDeserializer().deserialize(
request.GET.get('mapFilter', '{}'))
export = request.GET.get('export', None)
page = 1 if request.GET.get('page') == '' else int(
request.GET.get('page', 1))
temporal_filter = JSONDeserializer().deserialize(
request.GET.get('temporalFilter', '{}'))
se = SearchEngineFactory().create()
if export != None:
limit = settings.SEARCH_EXPORT_ITEMS_PER_PAGE
else:
limit = settings.SEARCH_ITEMS_PER_PAGE
query = Query(se, start=limit * int(page - 1), limit=limit)
query.add_aggregation(
GeoHashGridAgg(field='points',
name='grid',
precision=settings.HEX_BIN_PRECISION))
query.add_aggregation(GeoBoundsAgg(field='points', name='bounds'))
search_query = Bool()
if term_filter != '':
for term in JSONDeserializer().deserialize(term_filter):
if term['type'] == 'term':
term_filter = Match(field='strings',
query=term['value'],
type='phrase')
if term['inverted']:
search_query.must_not(term_filter)
else:
search_query.must(term_filter)
elif term['type'] == 'concept':
concept_ids = _get_child_concepts(term['value'])
conceptid_filter = Terms(field='domains.conceptid',
terms=concept_ids)
if term['inverted']:
search_query.must_not(conceptid_filter)
else:
search_query.must(conceptid_filter)
elif term['type'] == 'string':
string_filter = Bool()
string_filter.should(
Match(field='strings',
query=term['value'],
type='phrase_prefix'))
string_filter.should(
Match(field='strings.folded',
query=term['value'],
type='phrase_prefix'))
if term['inverted']:
search_query.must_not(string_filter)
else:
search_query.must(string_filter)
if 'features' in spatial_filter:
if len(spatial_filter['features']) > 0:
feature_geom = spatial_filter['features'][0]['geometry']
feature_properties = spatial_filter['features'][0]['properties']
buffer = {'width': 0, 'unit': 'ft'}
if 'buffer' in feature_properties:
buffer = feature_properties['buffer']
feature_geom = JSONDeserializer().deserialize(
_buffer(feature_geom, buffer['width'], buffer['unit']).json)
geoshape = GeoShape(field='geometries.features.geometry',
type=feature_geom['type'],
coordinates=feature_geom['coordinates'])
invert_spatial_search = False
if 'inverted' in feature_properties:
invert_spatial_search = feature_properties['inverted']
if invert_spatial_search == True:
search_query.must_not(geoshape)
else:
search_query.must(geoshape)
if 'fromDate' in temporal_filter and 'toDate' in temporal_filter:
now = str(datetime.utcnow())
start_date = None
end_date = None
start_year = 'null'
end_year = 'null'
try:
# start_date = parser.parse(temporal_filter['fromDate'])
# start_date = start_date.isoformat()
sd = FlexiDate.from_str(temporal_filter['fromDate'])
start_date = int((sd.as_float() - 1970) * 31556952 * 1000)
#start_year = parser.parse(start_date).year
start_year = sd.year
except:
pass
try:
# end_date = parser.parse(temporal_filter['toDate'])
# end_date = end_date.isoformat()
ed = FlexiDate.from_str(temporal_filter['toDate'])
end_date = int((ed.as_float() - 1970) * 31556952 * 1000)
#end_year = parser.parse(end_date).year
end_year = ed.year
except:
pass
# add filter for concepts that define min or max dates
sql = None
basesql = """
SELECT value.conceptid
FROM (
SELECT
{select_clause},
v.conceptid
FROM
public."values" v,
public."values" v2
WHERE
v.conceptid = v2.conceptid and
v.valuetype = 'min_year' and
v2.valuetype = 'max_year'
) as value
WHERE overlap = true;
"""
temporal_query = Bool()
if 'inverted' not in temporal_filter:
temporal_filter['inverted'] = False
if temporal_filter['inverted']:
# inverted date searches need to use an OR clause and are generally more complicated to structure (can't use ES must_not)
# eg: less than START_DATE OR greater than END_DATE
select_clause = []
inverted_date_filter = Bool()
field = 'dates'
if 'dateNodeId' in temporal_filter and temporal_filter[
'dateNodeId'] != '':
field = 'tiles.data.%s' % (temporal_filter['dateNodeId'])
if start_date is not None:
inverted_date_filter.should(Range(field=field, lte=start_date))
select_clause.append(
"(numrange(v.value::int, v2.value::int, '[]') && numrange(null,{start_year},'[]'))"
)
if end_date is not None:
inverted_date_filter.should(Range(field=field, gte=end_date))
select_clause.append(
"(numrange(v.value::int, v2.value::int, '[]') && numrange({end_year},null,'[]'))"
)
if 'dateNodeId' in temporal_filter and temporal_filter[
'dateNodeId'] != '':
date_range_query = Nested(path='tiles',
query=inverted_date_filter)
temporal_query.should(date_range_query)
else:
temporal_query.should(inverted_date_filter)
select_clause = " or ".join(select_clause) + " as overlap"
sql = basesql.format(select_clause=select_clause).format(
start_year=start_year, end_year=end_year)
else:
if 'dateNodeId' in temporal_filter and temporal_filter[
'dateNodeId'] != '':
range = Range(field='tiles.data.%s' %
(temporal_filter['dateNodeId']),
gte=start_date,
lte=end_date)
date_range_query = Nested(path='tiles', query=range)
temporal_query.should(date_range_query)
else:
date_range_query = Range(field='dates',
gte=start_date,
lte=end_date)
temporal_query.should(date_range_query)
select_clause = """
numrange(v.value::int, v2.value::int, '[]') && numrange({start_year},{end_year},'[]') as overlap
"""
sql = basesql.format(select_clause=select_clause).format(
start_year=start_year, end_year=end_year)
# is a dateNodeId is not specified
if sql is not None:
cursor = connection.cursor()
cursor.execute(sql)
ret = [str(row[0]) for row in cursor.fetchall()]
if len(ret) > 0:
conceptid_filter = Terms(field='domains.conceptid', terms=ret)
temporal_query.should(conceptid_filter)
search_query.must(temporal_query)
query.add_query(search_query)
return query
