def save(request):
logger = LogManager(__name__, 'SAVE SEARCH')
ds = Datasets().activate_dataset(request.session)
es_m = ds.build_manager(ES_Manager)
es_params = request.POST
es_m.build(es_params)
combined_query = es_m.get_combined_query()
try:
q = combined_query
desc = request.POST['search_description']
s_content = json.dumps([request.POST[x] for x in request.POST.keys() if 'match_txt' in x])
search = Search(author=request.user,search_content=s_content,description=desc,dataset=Dataset.objects.get(pk=int(request.session['dataset'])),query=json.dumps(q))
search.save()
logger.set_context('user_name', request.user.username)
logger.set_context('search_id', search.id)
logger.info('search_saved')
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.set_context('es_params', es_params)
logger.exception('search_saving_failed')
return HttpResponse()
def _get_tags_for_text_index(self, text, alignment, highlight_data):
logger = LogManager(__name__, '_GET_TAGS_FOR_TEXT_INDEX')
data_mapping = {index: datum for index, datum in enumerate(highlight_data)}
data_index_to_spans = [datum['spans'] for datum in highlight_data]
text_index_to_data_index = [[] for i in range(len(text))]
for data_index, spans in enumerate(data_index_to_spans):
for span in spans:
for text_index in range(*span):
try:
text_index_to_data_index[alignment[text_index]].append(data_index)
except Exception as e:
# Throws exception when index out of range
# For example Gets index out of range if in _derive_highlight_data while uses >= instead of >
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.set_context('text', text)
logger.exception('_get_tags_for_text_index try catch execption')
text_index_to_data_index = [frozenset(data_indices) for data_indices in text_index_to_data_index]
spans_to_tags = [(spans, self._get_tag_from_highlight_data([data_mapping[data_index] for data_index in data_indices]))
for spans, data_indices in self._get_spans_to_data_indices(text_index_to_data_index)]
return spans_to_tags
def remove_facts_from_document(self, rm_facts_dict, bs=7500):
'''remove a certain fact from all documents given a [str]key and [str]val'''
logger = LogManager(__name__, 'FACT MANAGER REMOVE FACTS')
try:
# Clears readonly block just in case the index has been set to read only
self.es_m.clear_readonly_block()
query = self._fact_deletion_query(rm_facts_dict)
self.es_m.load_combined_query(query)
response = self.es_m.scroll(size=bs, field_scroll=self.field)
scroll_id = response['_scroll_id']
total_docs = response['hits']['total']
docs_left = total_docs # DEBUG
print('Starting.. Total docs - ', total_docs) # DEBUG
batch = 0
while total_docs > 0:
print('Docs left:', docs_left) # DEBUG
data = ''
for document in response['hits']['hits']:
new_field = [] # The new facts field
for fact in document['_source'][self.field]:
# If the fact name is in rm_facts_dict keys
if fact["fact"] in rm_facts_dict:
# If the fact value is not in the delete key values
if fact['str_val'] not in rm_facts_dict.getlist(
fact["fact"]):
new_field.append(fact)
else:
new_field.append(fact)
# Update dataset
data += json.dumps({
"update": {
"_id": document['_id'],
"_type": document['_type'],
"_index": document['_index']
}
}) + '\n'
document = {'doc': {self.field: new_field}}
data += json.dumps(document) + '\n'
response = self.es_m.scroll(scroll_id=scroll_id,
size=bs,
field_scroll=self.field)
total_docs = len(response['hits']['hits'])
docs_left -= bs # DEBUG
scroll_id = response['_scroll_id']
self.es_m.plain_post_bulk(self.es_m.es_url, data)
print('DONE') # DEBUG
logger.set_context('docs_left', total_docs)
logger.set_context('batch', batch)
logger.info('remove_facts_from_document')
except:
print(traceback.format_exc())
logger.set_context('es_params', self.es_params)
logger.exception('remove_facts_from_document_failed')
def delete(request):
logger = LogManager(__name__, 'DELETE SEARCH')
search_id = request.GET['pk']
logger.set_context('user_name', request.user.username)
logger.set_context('search_id', search_id)
try:
Search.objects.get(pk=search_id).delete()
logger.info('search_deleted')
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.exception('search_deletion_failed')
return HttpResponse(search_id)
def delete(request):
post_data = json.loads(request.POST['data'])
logger = LogManager(__name__, 'DELETE SEARCH')
search_ids = post_data['pks']
logger.set_context('user_name', request.user.username)
logger.set_context('search_ids', search_ids)
try:
for search_id in search_ids:
Search.objects.get(pk=search_id).delete()
logger.info('search_deleted:' + search_id)
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.exception('search_deletion_failed')
return HttpResponse()
def delete(request):
post_data = json.loads(request.POST['data'])
logger = LogManager(__name__, 'DELETE SEARCH')
search_ids = post_data['pks']
logger.set_context('user_name', request.user.username)
logger.set_context('search_ids', search_ids)
try:
for search_id in search_ids:
Search.objects.get(pk=search_id).delete()
logger.info('search_deleted:' + search_id)
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.exception('search_deletion_failed')
return HttpResponse()
def save(request):
logger = LogManager(__name__, 'SAVE SEARCH')
ds = Datasets().activate_datasets(request.session)
es_m = ds.build_manager(ES_Manager)
es_params = request.POST
es_m.build(es_params)
combined_query = es_m.get_combined_query()
try:
q = combined_query
desc = request.POST['search_description']
s_content = {}
# make json
for x in request.POST.keys():
if 'match_txt' in x:
# get the ID of the field, eg match_txt_1 returns 1 match_txt_1533 returns 1533
field_id = x.rsplit("_", 1)[-1]
match_field = request.POST['match_field_' + field_id]
if match_field in s_content.keys():
s_content[match_field].append(request.POST[x])
else:
s_content[match_field] = [request.POST[x]]
search = Search(author=request.user,
search_content=json.dumps(s_content),
description=desc,
query=json.dumps(q))
logger.info('Saving search for datasets: {}'.format(
request.session['dataset']))
search.save()
for dataset_id in request.session['dataset']:
dataset = Dataset.objects.get(pk=int(dataset_id))
search.datasets.add(dataset)
search.save()
logger.set_context('user_name', request.user.username)
logger.set_context('search_id', search.id)
logger.info('search_saved')
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.set_context('es_params', es_params)
logger.exception('search_saving_failed')
return HttpResponse()
def save(request):
logger = LogManager(__name__, 'SAVE SEARCH')
ds = Datasets().activate_datasets(request.session)
es_m = ds.build_manager(ES_Manager)
es_params = request.POST
es_m.build(es_params)
combined_query = es_m.get_combined_query()
try:
q = combined_query
desc = request.POST['search_description']
s_content = {}
# make json
for x in request.POST.keys():
if 'match_txt' in x:
# get the ID of the field, eg match_txt_1 returns 1 match_txt_1533 returns 1533
field_id = x.rsplit("_", 1)[-1]
match_field = request.POST['match_field_' + field_id]
if match_field in s_content.keys():
s_content[match_field].append(request.POST[x])
else:
s_content[match_field] = [request.POST[x]]
search = Search(author=request.user, search_content=json.dumps(s_content), description=desc,
query=json.dumps(q))
logger.info('Saving search for datasets: {}'.format(request.session['dataset']))
search.save()
for dataset_id in request.session['dataset']:
dataset = Dataset.objects.get(pk=int(dataset_id))
search.datasets.add(dataset)
search.save()
logger.set_context('user_name', request.user.username)
logger.set_context('search_id', search.id)
logger.info('search_saved')
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.set_context('es_params', es_params)
logger.exception('search_saving_failed')
return HttpResponse()
def facts_agg(es_params, request):
logger = LogManager(__name__, 'FACTS AGGREGATION')
distinct_values = []
query_results = []
lexicon = []
aggregation_data = es_params['aggregate_over']
aggregation_data = json.loads(aggregation_data)
original_aggregation_field = aggregation_data['path']
aggregation_field = 'texta_link.facts'
try:
aggregation_size = 50
aggregations = {"strings": {es_params['sort_by']: {"field": aggregation_field, 'size': 0}},
"distinct_values": {"cardinality": {"field": aggregation_field}}}
# Define selected mapping
ds = Datasets().activate_dataset(request.session)
dataset = ds.get_index()
mapping = ds.get_mapping()
date_range = ds.get_date_range()
es_m = ES_Manager(dataset, mapping, date_range)
for item in es_params:
if 'saved_search' in item:
s = Search.objects.get(pk=es_params[item])
name = s.description
saved_query = json.loads(s.query)
es_m.load_combined_query(saved_query)
es_m.set_query_parameter('aggs', aggregations)
response = es_m.search()
# Filter response
bucket_filter = '{0}.'.format(original_aggregation_field.lower())
final_bucket = []
for b in response['aggregations']['strings']['buckets']:
if bucket_filter in b['key']:
fact_name = b['key'].split('.')[-1]
b['key'] = fact_name
final_bucket.append(b)
final_bucket = final_bucket[:aggregation_size]
response['aggregations']['distinct_values']['value'] = len(final_bucket)
response['aggregations']['strings']['buckets'] = final_bucket
normalised_counts,labels = normalise_agg(response, es_m, es_params, 'strings')
lexicon = list(set(lexicon+labels))
query_results.append({'name':name,'data':normalised_counts,'labels':labels})
distinct_values.append({'name':name,'data':response['aggregations']['distinct_values']['value']})
es_m.build(es_params)
# FIXME
# this is confusing for the user
if not es_m.is_combined_query_empty():
es_m.set_query_parameter('aggs', aggregations)
response = es_m.search()
# Filter response
bucket_filter = '{0}.'.format(original_aggregation_field.lower())
final_bucket = []
for b in response['aggregations']['strings']['buckets']:
if bucket_filter in b['key']:
fact_name = b['key'].split('.')[-1]
b['key'] = fact_name
final_bucket.append(b)
final_bucket = final_bucket[:aggregation_size]
response['aggregations']['distinct_values']['value'] = len(final_bucket)
response['aggregations']['strings']['buckets'] = final_bucket
normalised_counts,labels = normalise_agg(response, es_m, es_params, 'strings')
lexicon = list(set(lexicon+labels))
query_results.append({'name':'Query','data':normalised_counts,'labels':labels})
distinct_values.append({'name':'Query','data':response['aggregations']['distinct_values']['value']})
data = [a+zero_list(len(query_results)) for a in map(list, zip(*[lexicon]))]
data = [['Word']+[query_result['name'] for query_result in query_results]]+data
for i,word in enumerate(lexicon):
for j,query_result in enumerate(query_results):
for k,label in enumerate(query_result['labels']):
if word == label:
data[i+1][j+1] = query_result['data'][k]
logger.set_context('user_name', request.user.username)
logger.info('facts_aggregation_queried')
except Exception as e:
print('-- Exception[{0}] {1}'.format(__name__, e))
logger.set_context('user_name', request.user.username)
logger.exception('facts_aggregation_query_failed')
table_height = len(data)*15
table_height = table_height if table_height > 500 else 500
return {'data':[data[0]]+sorted(data[1:], key=lambda x: sum(x[1:]), reverse=True),'height':table_height,'type':'bar','distinct_values':json.dumps(distinct_values)}
