def test_query_aggregate_and_suggester(self):
q = ElasticQuery()
q.query(Query.match('field', 'query'))
q.aggregate(Aggregate.max('agg_name', 'field'))
q.suggest(Suggester.term('sugg_name', 'term text', 'term_field'))
assert_equal(
self, q.dict(), {
'query': {
'match': {
'field': {
'query': 'query'
}
}
},
'aggregations': {
'agg_name': {
'max': {
'field': 'field'
}
}
},
'suggest': {
'sugg_name': {
'text': 'term text',
'term': {
'field': 'term_field'
}
}
}
})
def query_ec(self, str_query, q_fields, start_date=0, end_date=0, index='logs-*', doc_type='logs',
hours=24, debug=False):
if start_date > end_date:
raise Exception('The start_date can\'t be greater than the end_date')
if start_date == 0 or end_date == 0:
dt_end_date = datetime.now().timestamp()
dt_start_date = (datetime.now() - timedelta(hours=hours)).timestamp()
start_date = int(dt_start_date) * 1000
end_date = int(dt_end_date) * 1000
# print(str(start_date) + ' -- ' + str(end_date))
elastic_qry = ElasticQuery(es=self.elastic_client, index=index, doc_type=doc_type)
elastic_qry.query(
Query.bool(
must=[Query.query_string(str_query),
Query.range('normalDate', gte=start_date, lte=end_date)]
)
)
elastic_qry.aggregate(
Aggregate.date_histogram('2', 'normalDate', '12h')
)
my_qry = elastic_qry.dict()
my_qry['stored_fields'] = q_fields
search_arr = list()
header_qry = {"index": ["logs-*"], "ignore_unavailable": True}
search_arr.append(header_qry)
search_arr.append(my_qry)
print('Elastic Query: ' + str(search_arr))
print('------------------------------------------------------------------------------------')
print('Lucene Query: ' + str_query)
request = ''
for each in search_arr:
request += '%s \n' % json.dumps(each)
# print(request)
resp = self.elastic_client.msearch(body=request)
if resp is None and len(resp['responses']) <= 0:
return None
else:
response = resp['responses'][0]
hits_data = list()
if response['hits']['total'] > 0:
for hit in response['hits']['hits']:
hits_data.append(hit)
# print(str(hits_data))
return search_arr, hits_data
def test_aggregate(self):
q = ElasticQuery()
q.aggregate(Aggregate.terms('agg_name', 'field'))
assert_equal(
self, q.dict(),
{'aggregations': {
'agg_name': {
'terms': {
'field': 'field'
}
}
}})
def test_nested_aggregate(self):
q = ElasticQuery()
q.aggregate(Aggregate.terms('agg_name', 'field').aggregate(
Aggregate.sum('sub_agg_name', 'sub_field')
))
assert_equal(self, q.dict(), {
'aggregations': {
'agg_name': {
'terms': {
'field': 'field'
},
'aggregations': {
'sub_agg_name': {
'sum': {
'field': 'sub_field'
}
}
}
}
}
})
},
'filter': {
'bool': {
'must': [{
'range': {
'field_name1': {
'gte': 0,
'lt': 100
}
}
}],
'must_not': [],
'should': []
}
},
'sort': []
}
}
# Test queries
query = ElasticQuery()
query.must(Filter.range('field_name1', gte=0, lt=100))
query.aggregate('test_aggregate1', Aggregate.terms('field_name1'))
query.aggregate('test_aggregate2', Aggregate.stats('field_name2'))
test('Full query: range + terms agg + stats agg', query.structure,
QUERIES['RANGE_AGGTERMS_AGGSTATS'])
# If we're still here, we're done!
print '[ElasticQuery] All tests complete!\n'
sys.exit(0)
def return_single_field_search(field,search):
q = ElasticQuery(es=Elasticsearch(),index=all_indexes,doc_type='')
q.aggregate(Aggregate.terms(search,field))
q.query(Query.query_string(search,field,default_operator='OR',analyze_wildcard=True))
q.fields(field)
ElasticQuery.sort(q,"_score",order="desc")
