def test_query_output_multi_float_vec_field(self, vec_fields):
"""
target: test query and output multi float vec fields
method: a.specify multi vec field as output
b.specify output_fields with wildcard %
expected: verify query result
"""
# init collection with two float vector fields
schema = cf.gen_schema_multi_vector_fields(vec_fields)
collection_w = self.init_collection_wrap(
name=cf.gen_unique_str(prefix), schema=schema)
df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields)
collection_w.insert(df)
assert collection_w.num_entities == ct.default_nb
# query with two vec output_fields
output_fields = [
ct.default_int64_field_name, ct.default_float_vec_field_name
]
for vec_field in vec_fields:
output_fields.append(vec_field.name)
res = df.loc[:1, output_fields].to_dict('records')
collection_w.load()
collection_w.query(default_term_expr,
output_fields=output_fields,
check_task=CheckTasks.check_query_results,
check_items={
exp_res: res,
"with_vec": True
})
def init_multi_fields_collection_wrap(self, name=cf.gen_unique_str()):
vec_fields = [cf.gen_float_vec_field(ct.another_float_vec_field_name)]
schema = cf.gen_schema_multi_vector_fields(vec_fields)
collection_w = self.init_collection_wrap(name=name, schema=schema)
df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields)
collection_w.insert(df)
assert collection_w.num_entities == ct.default_nb
return collection_w, df
def test_insert_multi_float_vec_fields(self, vec_fields):
"""
target: test insert into multi float vec fields collection
method: create collection with different schema and insert
expected: verify num entities
"""
schema = cf.gen_schema_multi_vector_fields(vec_fields)
collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix), schema=schema)
df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields)
collection_w.insert(df)
assert collection_w.num_entities == ct.default_nb
