def get_related_videos(video):
related_videos = []
conn = ES(['127.0.0.1:9200'])
conn.default_indices = VIDEO_INDEX
conn.refresh(VIDEO_INDEX)
q = {
"query": {
"bool": {
"should": [
{"term" : { "uid" : video.uid } },
{"terms" : { "category" : [video.category]}},
{"terms" : { "topic" : [video.topic]}},
{"terms" : { "language" : [video.language]}}
],
"minimum_should_match" : 1
}
}
}
try:
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % VIDEO_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result['hits']['hits']:
related_videos.append(res['_source'])
except Exception:
pass
return related_videos
def init():
conn = ES('127.0.0.1:9200')
try:
conn.delete_index("zhihu")
except:
pass
conn.create_index("zhihu")
mapping = {
u'id': {
'store': 'yes',
'type': u'integer'
},
u'link': {
'store': 'yes',
'type': u'string'
},
u'title': {
'boost': 1.0,
'index': 'analyzed',
'store': 'yes',
'type': u'string'
},
}
conn.put_mapping("answer", {'properties': mapping}, ["zhihu"])
for item in Data().getData():
conn.index(item, "zhihu", "answer", item['id'])
conn.refresh(["zhihu"])
return redirect('/list')
def get_related_collections(collection, featured):
related_collections = []
conn = ES(["127.0.0.1:9200"])
conn.default_indices = FACET_INDEX
conn.refresh(FACET_INDEX)
q = {
"query": {
"bool": {
"must_not": {"term": {"uid": collection.uid}},
"should": [{"terms": {"subject": [collection.subject]}}, {"terms": {"topic": [collection.topic]}}],
"minimum_should_match": 1,
}
}
}
if featured:
q = {
"query": {
"bool": {
"must_not": {"term": {"uid": collection.uid}},
"should": [{"term": {"featured": True}}],
"minimum_should_match": 1,
}
}
}
try:
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % FACET_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result["hits"]["hits"]:
related_collections.append(res["_source"])
except Exception:
pass
return related_collections
def get_related_collections(collection):
related_collections = []
conn = ES(['127.0.0.1:9200'])
conn.default_indices = FACET_INDEX
conn.refresh(FACET_INDEX)
q ={"query": {
"bool" : {
"must_not" : {"term" : { "uid" : collection.uid }},
"should" : [
{"terms" : { "subject" : [collection.subject] }},
{"terms" : { "topic" : [collection.topic] }},
],
"minimum_should_match" : 1,
}
}
}
try :
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % FACET_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result['hits']['hits']:
related_collections.append(res['_source'])
except Exception:
pass
return related_collections
def get_related_videos(video):
related_videos = []
conn = ES(['127.0.0.1:9200'])
conn.default_indices = VIDEO_INDEX
conn.refresh(VIDEO_INDEX)
q = {
"query": {
"bool": {
"should": [
{"term" : { "uid" : video.uid } },
{"terms" : { "category" : [video.category]}},
{"terms" : { "topic" : [video.topic]}},
{"terms" : { "language" : [video.language]}}
],
"minimum_should_match" : 1
}
}
}
try:
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % VIDEO_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result['hits']['hits']:
related_videos.append(res['_source'])
except Exception:
pass
return related_videos
def searchCompletions(request):
searchString = request.GET.get('searchString')
maxCount = int(request.GET.get('maxCount'))
conn = ES(['127.0.0.1:9200'])
conn.default_indices = COMPLETION_INDEX
conn.refresh(COMPLETION_INDEX)
q = {
"query": {
"query_string": {
"fields": ["searchTerm.partial"],
"query": searchString
}
},
"facets": {
"facet": {
"terms": {
"fields": ["searchTerm"],
"size": MAX_RESULT_SIZE
}
}
},
"size": maxCount
}
try:
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % COMPLETION_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
result_list = []
done_list = []
for res in result['hits']['hits']:
if res['_source']['type'] != "Collections":
result_list.append(res['_source'])
res['_source']['count'] = 0
elif res['_source']['searchTerm'] not in done_list:
val = str(res['_source']['searchTerm']).lower()
for term in result['facets']['facet']['terms']:
if val == term['term']:
res['_source']['count'] = term['count']
done_list.append(res['_source']['searchTerm'])
result_list.append(res['_source'])
if len(result_list) == 0:
result_list.append(
{"searchTerm": "No Results"}
) # for now just displaying no results when nothing is found in completion
resp = json.dumps({
"responseCode": "OK",
"requestParameters": {
"searchString": searchString,
"maxCount": unicode(maxCount)
},
"completions": result_list,
"totalCount": unicode(maxCount)
})
return HttpResponse(resp)
except Exception, ex:
return HttpResponse('0')
def searchCompletions(request):
searchString = request.GET.get('searchString')
maxCount = int(request.GET.get('maxCount'))
conn = ES(['127.0.0.1:9200'])
conn.default_indices = COMPLETION_INDEX
conn.refresh(COMPLETION_INDEX)
q = {"query" : {
"query_string" :{
"fields" : ["searchTerm.partial"],
"query" : searchString
}
},
"facets" : {
"facet" :{
"terms": {
"fields" : [ "searchTerm"],
"size" : MAX_RESULT_SIZE
}
}
},
"size" : maxCount
}
try:
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % COMPLETION_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
result_list = []
done_list = []
for res in result['hits']['hits']:
if res['_source']['type'] != "Collections":
result_list.append(res['_source'])
res['_source']['count'] = 0
elif res['_source']['searchTerm'] not in done_list:
val = str(res['_source']['searchTerm']).lower()
for term in result['facets']['facet']['terms']:
if val == term['term'] :
res['_source']['count'] = term['count']
done_list.append(res['_source']['searchTerm'])
result_list.append(res['_source'])
if len(result_list) == 0:
result_list.append({"searchTerm" : "No Results"}) # for now just displaying no results when nothing is found in completion
resp = json.dumps({"responseCode":"OK","requestParameters":{"searchString":searchString,"maxCount":unicode(maxCount)},"completions": result_list, "totalCount": unicode(maxCount)})
return HttpResponse(resp)
except Exception, ex:
return HttpResponse('0')
def main(fn, args):
conn = ES(args.host, bulk_size=10*args.bulksize)
if fn.endswith(".gz"):
fp = gzip.open(fn)
else:
fp = open(fn)
count = 0
total = 0
try:
for line in fp:
doc = json.loads(line.strip())
if doc.get("_id"):
_id = doc["_id"]
del doc["_id"]
else:
_id = None
conn.index(doc=doc,
index=args.index,
doc_type=args.doctype,
id=_id,
bulk=True)
count+=1
total+=1
if count % args.bulksize == 0:
flush(conn, count)
count = 0
except:
print "traceback", "".join(traceback.format_exception(*sys.exc_info()))
raise
finally:
fp.close()
try:
flush(conn, count)
conn.refresh(args.index)
except:
pass
print "Indexed %s docs total"%total
def init():
conn = ES('127.0.0.1:9200')
try:
conn.delete_index("zhihu")
except:
pass
conn.create_index("zhihu")
mapping = {
u'id': {'store': 'yes',
'type': u'integer'},
u'link': {'store': 'yes',
'type': u'string'},
u'title': {'boost': 1.0,
'index': 'analyzed',
'store': 'yes',
'type': u'string'},
}
conn.put_mapping("answer", {'properties': mapping}, ["zhihu"])
for item in Data().getData():
conn.index(item, "zhihu", "answer", item['id'])
conn.refresh(["zhihu"])
return redirect('/list')
def get_collections_from_elasticsearch(request):
params = request.GET
language_name = params.get('language__name', None)
# TODO: Change this from 'None'?
searchString = params.get('searchString', 'None')
partner_uid = params.get('uid', None)
featured = params.get('featured', None)
# TODO: Change this from 'None'?
if searchString != 'None':
match_query = {"flt" : {"fields" : ["_all", "subject.partial", "language.partial", "partner.partial", "state.partial", "category.partial", "subcategory.partial" , "topic.partial"],
"like_text" : searchString
}
}
elif partner_uid:
partner_name = Partner.objects.get(uid = partner_uid).name
match_query = {"match" : {"partner" :{ "query" : partner_name}}}
else:
match_query = {"match_all" : {}}
query = []
filter = []
if language_name == 'All Languages':
language_name = None
query = create_query(params, language_name)
if query:
filter = {"and" : query}
order_by = params.get('order_by','-featured')
offset = int(params.get('offset'))
limit = int(params.get('limit'))
order_by = order_by[1:] #removing '-' since it will always be '-'
conn = ES(['127.0.0.1:9200'])
conn.default_indices = FACET_INDEX
conn.refresh(FACET_INDEX)
q ={"query": {
"filtered":{
"query" : match_query,
"filter" : filter
}
},
"facets" : {
"facet" :{
"terms": {
"fields" : ["language", "partner", "state", "category", "subcategory" , "topic", "subject"],
"size" : MAX_RESULT_SIZE
}
}
},
"sort" : {
order_by : {"order" : "desc"}
},
"size" : MAX_RESULT_SIZE
}
result_list = []
try :
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % FACET_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result['hits']['hits']:
result_list.append(res['_source'])
facets = json.dumps(result['facets']['facet']['terms'])
if result_list:
resp = json.dumps({"meta": {"limit": str(limit), "next": "", "offset": str(offset), "previous": "null", "total_count": str(len(result_list))},"objects": result_list[offset:offset+limit], "facets" : facets})
else:
resp = json.dumps({"meta": {"limit": str(limit), "next": "", "offset": str(offset), "previous": "null", "total_count": "1"},"objects": [{'Message': 'No Collections Found', 'error': "1"}], "facets" : facets})
return HttpResponse(resp)
except Exception, ex:
print ex
return HttpResponse(str(ex))
class DocManager():
"""The DocManager class creates a connection to the backend engine and
adds/removes documents, and in the case of rollback, searches for them.
The reason for storing id/doc pairs as opposed to doc's is so that
multiple updates to the same doc reflect the most up to date version as
opposed to multiple, slightly different versions of a doc.
We are using elastic native fields for _id and ns, but we also store
them as fields in the document, due to compatibility issues.
"""
def __init__(self, url, auto_commit=True, unique_key='_id'):
"""Verify Elastic URL and establish a connection.
"""
if verify_url(url) is False:
raise SystemError
self.elastic = ES(server=url)
self.auto_commit = auto_commit
self.doc_type = 'string' # default type is string, change if needed
self.unique_key = unique_key
if auto_commit:
self.run_auto_commit()
def stop(self):
""" Stops the instance
"""
self.auto_commit = False
def upsert(self, doc):
"""Update or insert a document into Elastic
If you'd like to have different types of document in your database,
you can store the doc type as a field in Mongo and set doc_type to
that field. (e.g. doc_type = doc['_type'])
"""
doc_type = self.doc_type
index = doc['ns']
doc[self.unique_key] = str(doc[self.unique_key])
doc_id = doc[self.unique_key]
id_query = TextQuery('_id', doc_id)
elastic_cursor = self.elastic.search(query=id_query, indices=index)
try:
self.elastic.index(bsjson.dumps(doc), index, doc_type, doc_id)
except ValueError:
logging.info("Could not update %s" % (doc,))
self.elastic.refresh()
def remove(self, doc):
"""Removes documents from Elastic
The input is a python dictionary that represents a mongo document.
"""
try:
self.elastic.delete(doc['ns'], 'string', str(doc[self.unique_key]))
except (NotFoundException, TypeMissingException, IndexMissingException):
pass
def _remove(self):
"""For test purposes only. Removes all documents in test.test
"""
try:
self.elastic.delete('test.test', 'string', '')
except (NotFoundException, TypeMissingException, IndexMissingException):
pass
def search(self, start_ts, end_ts):
"""Called to query Elastic for documents in a time range.
"""
res = ESRange('_ts', from_value=start_ts, to_value=end_ts)
results = self.elastic.search(RangeQuery(res))
return results
def _search(self):
"""For test purposes only. Performs search on Elastic with empty query.
Does not have to be implemented.
"""
results = self.elastic.search(MatchAllQuery())
return results
def commit(self):
"""This function is used to force a refresh/commit.
"""
retry_until_ok(self.elastic.refresh)
def run_auto_commit(self):
"""Periodically commits to the Elastic server.
"""
self.elastic.refresh()
if self.auto_commit:
Timer(1, self.run_auto_commit).start()
def get_last_doc(self):
"""Returns the last document stored in the Elastic engine.
"""
result = self.elastic.search(MatchAllQuery(), size=1, sort='_ts:desc')
for item in result:
return item
class ESIndexerBase(object):
ES_HOST = ES_HOST
ES_INDEX_NAME = ES_INDEX_NAME
ES_INDEX_TYPE = 'gene'
def __init__(self):
self.conn = ES(self.ES_HOST, default_indexes=[self.ES_INDEX_NAME],
timeout=10.0)
self.step = 10000
def create_index(self):
try:
print self.conn.open_index(self.ES_INDEX_NAME)
except IndexMissingException:
print self.conn.create_index(self.ES_INDEX_NAME)
def delete_index_type(self, index_type):
'''Delete all indexes for a given index_type.'''
index_name = self.ES_INDEX_NAME
# index_type = self.ES_INDEX_TYPE
#Check if index_type exists
mapping = self.conn.get_mapping(index_type, index_name)
if index_name not in mapping or index_type not in mapping[index_name]:
print 'Error: index type "%s" does not exist in index "%s".' % (index_type, index_name)
return
path = '/%s/%s' % (index_name, index_type)
if ask('Confirm to delete all data under "%s":' % path) == 'Y':
return self.conn.delete_mapping(index_name, index_type)
def index(self, doc, index_type, id=None):
'''add a doc to the index. If id is not None, the existing doc will be
updated.
'''
# index_type = self.ES_INDEX_TYPE
return self.conn.index(doc, self.ES_INDEX_NAME, index_type, id=id)
def delete_index(self, index_type, id):
'''delete a doc from the index based on passed id.'''
# index_type = self.ES_INDEX_TYPE
return self.conn.delete(self.ES_INDEX_NAME, index_type, id)
def optimize(self):
return self.conn.optimize(self.ES_INDEX_NAME, wait_for_merge=True)
def get_field_mapping(self):
import dataload
reload(dataload)
dataload.register_sources()
return dataload.get_mapping()
def build_index(self, doc_d, update_mapping=False, bulk=True):
index_name = self.ES_INDEX_NAME
index_type = self.ES_INDEX_TYPE
#Test if index exists
try:
print "Opening index...", self.conn.open_index(index_name)
except NotFoundException:
print 'Error: index "%s" does not exist. Create it first.' % index_name
return -1
try:
cur_mapping = self.conn.get_mapping(index_type, index_name)
empty_mapping = False
except ElasticSearchException:
#if no existing mapping available for index_type
#force update_mapping to True
empty_mapping = True
update_mapping = True
# empty_mapping = not cur_mapping[index_name].get(index_type, {})
# if empty_mapping:
# #if no existing mapping available for index_type
# #force update_mapping to True
# update_mapping = True
if update_mapping:
print "Updating mapping...",
if not empty_mapping:
print "\n\tRemoving existing mapping...",
print self.conn.delete_mapping(index_name, index_type)
_mapping = self.get_field_mapping()
print self.conn.put_mapping(index_type,
_mapping,
[index_name])
print "Building index..."
t0 = time.time()
for doc_id, doc in doc_d.items():
self.conn.index(doc, index_name, index_type, doc_id, bulk=bulk)
print self.conn.flush()
print self.conn.refresh()
print "Done[%s]" % timesofar(t0)
def query(self, qs, fields='symbol,name', **kwargs):
_q = StringQuery(qs)
res = self.conn.search(_q, fields=fields, **kwargs)
return res
def get_collections_from_elasticsearch(request):
params = request.GET
language_name = params.get('language__name', None)
# TODO: Change this from 'None'?
searchString = params.get('searchString', 'None')
partner_uid = params.get('uid', None)
# TODO: Change this from 'None'?
if searchString != 'None':
match_query = {"flt" : {"fields" : ["_all", "subject.partial", "language.partial", "partner.partial", "state.partial", "category.partial", "subcategory.partial" , "topic.partial"],
"like_text" : searchString
}
}
elif partner_uid:
partner_name = Partner.objects.get(uid = partner_uid).name
match_query = {"match" : {"partner" :{ "query" : partner_name}}}
else:
match_query = {"match_all" : {}}
query = []
filter = []
if language_name == 'All Languages':
language_name = None
query = create_query(params, language_name)
if query:
filter = {"and" : query}
order_by = params.get('order_by','-likes')
offset = int(params.get('offset'))
limit = int(params.get('limit'))
order_by = order_by[1:] #removing '-' since it will always be '-'
conn = ES(['127.0.0.1:9200'])
conn.default_indices = FACET_INDEX
conn.refresh(FACET_INDEX)
q ={"query": {
"filtered":{
"query" : match_query,
"filter" : filter
}
},
"facets" : {
"facet" :{
"terms": {
"fields" : ["language", "partner", "state", "category", "subcategory" , "topic", "subject"],
"size" : MAX_RESULT_SIZE
}
}
},
"sort" : {
order_by : {"order" : "desc"}
},
"size" : MAX_RESULT_SIZE
}
result_list = []
try :
query = json.dumps(q)
url = "http://localhost:9200/%s/_search" % FACET_INDEX
response = urllib2.urlopen(url, query)
result = json.loads(response.read())
for res in result['hits']['hits']:
result_list.append(res['_source'])
facets = json.dumps(result['facets']['facet']['terms'])
resp = json.dumps({"meta": {"limit": str(limit), "next": "", "offset": str(offset), "previous": "null", "total_count": str(len(result_list))},"objects": result_list[offset:offset+limit], "facets" : facets})
return HttpResponse(resp)
except Exception, ex:
return HttpResponse('0')
