milvus-io
/
milvus
mirror of https://github.com/milvus-io/milvus.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

[test]Add testcase of consistency (#16099) 

Signed-off-by: jingkl <jingjing.jia@zilliz.com>
pull/16110/head
jingkl 2022-03-21 09:03:24 +08:00 committed by GitHub
parent ca45e0bd00
commit 19baa7b282
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 168 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

168
tests/python_client/testcases/test_search_20.py
View File

@ -11,6 +11,7 @@ from common import common_type as ct
from common.common_type import CaseLabel, CheckTasks
from utils.util_pymilvus import *
from common.constants import *
from pymilvus.orm.types import CONSISTENCY_STRONG, CONSISTENCY_BOUNDED, CONSISTENCY_SESSION, CONSISTENCY_EVENTUALLY
prefix = "search_collection"
search_num = 10
@ -2159,6 +2160,173 @@ class TestCollectionSearch(TestcaseBase):
"limit": default_limit,
})
@pytest.mark.tags(CaseLabel.L1)
def test_search_with_consistency_bounded(self, nq, dim, auto_id, _async):
"""
target: test search with different consistency level
method: 1. create a collection
2. insert data
3. search with consistency_level is "bounded"
expected: searched successfully
"""
limit = 1000
nb_old = 500
collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb_old,
auto_id=auto_id,
dim=dim)[0:4]
# 2. search for original data after load
vectors = [[random.random() for _ in range(dim)] for _ in range(nq)]
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old,
"_async": _async,
})
kwargs = {}
consistency_level = kwargs.get("consistency_level", CONSISTENCY_BOUNDED)
kwargs.update({"consistency_level": consistency_level})
nb_new = 400
_, _, _, insert_ids_new, _= cf.insert_data(collection_w, nb_new,
auto_id=auto_id, dim=dim,
insert_offset=nb_old)
insert_ids.extend(insert_ids_new)
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
**kwargs,
)
@pytest.mark.tags(CaseLabel.L1)
def test_search_with_consistency_strong(self, nq, dim, auto_id, _async):
"""
target: test search with different consistency level
method: 1. create a collection
2. insert data
3. search with consistency_level is "Strong"
expected: searched successfully
"""
limit = 1000
nb_old = 500
collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb_old,
auto_id=auto_id,
dim=dim)[0:4]
# 2. search for original data after load
vectors = [[random.random() for _ in range(dim)] for _ in range(nq)]
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old,
"_async": _async})
nb_new = 400
_, _, _, insert_ids_new, _ = cf.insert_data(collection_w, nb_new,
auto_id=auto_id, dim=dim,
insert_offset=nb_old)
insert_ids.extend(insert_ids_new)
kwargs = {}
consistency_level = kwargs.get("consistency_level", CONSISTENCY_STRONG)
kwargs.update({"consistency_level": consistency_level})
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
**kwargs,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old + nb_new,
"_async": _async})
@pytest.mark.tags(CaseLabel.L1)
def test_search_with_consistency_eventually(self, nq, dim, auto_id, _async):
"""
target: test search with different consistency level
method: 1. create a collection
2. insert data
3. search with consistency_level is "eventually"
expected: searched successfully
"""
limit = 1000
nb_old = 500
collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb_old,
auto_id=auto_id,
dim=dim)[0:4]
# 2. search for original data after load
vectors = [[random.random() for _ in range(dim)] for _ in range(nq)]
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old,
"_async": _async})
nb_new = 400
_, _, _, insert_ids_new, _= cf.insert_data(collection_w, nb_new,
auto_id=auto_id, dim=dim,
insert_offset=nb_old)
insert_ids.extend(insert_ids_new)
kwargs = {}
consistency_level = kwargs.get("consistency_level", CONSISTENCY_EVENTUALLY)
kwargs.update({"consistency_level": consistency_level})
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
**kwargs
)
@pytest.mark.tags(CaseLabel.L1)
def test_search_with_consistency_session(self, nq, dim, auto_id, _async):
"""
target: test search with different consistency level
method: 1. create a collection
2. insert data
3. search with consistency_level is "session"
expected: searched successfully
"""
limit = 1000
nb_old = 500
collection_w, _, _, insert_ids = self.init_collection_general(prefix, True, nb_old,
auto_id=auto_id,
dim=dim)[0:4]
# 2. search for original data after load
vectors = [[random.random() for _ in range(dim)] for _ in range(nq)]
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old,
"_async": _async})
kwargs = {}
consistency_level = kwargs.get("consistency_level", CONSISTENCY_SESSION)
kwargs.update({"consistency_level": consistency_level})
nb_new = 400
_, _, _, insert_ids_new, _= cf.insert_data(collection_w, nb_new,
auto_id=auto_id, dim=dim,
insert_offset=nb_old)
insert_ids.extend(insert_ids_new)
collection_w.search(vectors[:nq], default_search_field,
default_search_params, limit,
default_search_exp, _async=_async,
**kwargs,
check_task=CheckTasks.check_search_results,
check_items={"nq": nq,
"ids": insert_ids,
"limit": nb_old + nb_new,
"_async": _async})
class TestSearchBase(TestcaseBase):
@pytest.fixture(