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test: Enable more test cases for auto index (#39939)
Signed-off-by: binbin lv <binbin.lv@zilliz.com>
This commit is contained in:
binbin
GitHub
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0dc21f0aeb
commit
76959244ef
@ -54,9 +54,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.parametrize("name", ["12-s", "12 s", "(mn)", "中文", "%$#"])
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def test_milvus_client_index_invalid_collection_name(self, name):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: create index on invalid collection name
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -78,9 +78,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.parametrize("name", ["a".join("a" for i in range(256))])
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def test_milvus_client_index_collection_name_over_max_length(self, name):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: create index on collection name over max length
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -101,9 +101,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_index_not_exist_collection_name(self):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: create index on not exist collection name
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -127,9 +127,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.parametrize("index", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
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def test_milvus_client_index_invalid_index_type(self, index):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: create index on invalid index type
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -152,9 +152,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.parametrize("metric", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
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def test_milvus_client_index_invalid_metric_type(self, metric):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: create index on invalid metric type
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -175,9 +175,9 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_index_drop_index_before_release(self):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index abnormal case
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method: drop index before release
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expected: raise exception
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -190,37 +190,10 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.skip(reason="pymilvus issue 1886")
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def test_milvus_client_index_multiple_indexes_one_field(self):
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def test_milvus_client_create_multiple_diff_index_without_release(self):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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self.create_collection(client, collection_name, default_dim, consistency_level="Strong")
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# 2. prepare index params
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name="vector", index_type="HNSW", metric_type="IP")
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# 3. create index
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self.create_index(client, collection_name, index_params)
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# 4. prepare index params
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name="vector", index_type="IVF_FLAT", metric_type="L2")
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error = {ct.err_code: 1100, ct.err_msg: f""}
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# 5. create another index
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self.create_index(client, collection_name, index_params,
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check_task=CheckTasks.err_res, check_items=error)
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.skip(reason="pymilvus issue 1886")
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def test_milvus_client_create_diff_index_without_release(self):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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target: test index abnormal case
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method: create different index on one field without release
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expected: raise exception
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"""
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client = self._client()
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@ -229,14 +202,16 @@ class TestMilvusClientIndexInvalid(TestMilvusClientV2Base):
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self.create_collection(client, collection_name, default_dim, consistency_level="Strong")
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# 2. prepare index params
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name="vector", index_type="HNSW", metric_type="L2")
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# 3. create index
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self.create_index(client, collection_name, index_params)
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index_params.add_index(field_name="vector", index_type="IVF_FLAT", metric_type="L2")
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# 3. create another index
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error = {ct.err_code: 65535, ct.err_msg: "CreateIndex failed: at most one distinct index is allowed per field"}
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self.create_index(client, collection_name, index_params,
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check_task=CheckTasks.err_res, check_items=error)
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self.drop_collection(client, collection_name)
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class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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""" Test case of search interface """
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""" Test case of index interface """
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@pytest.fixture(scope="function", params=[False, True])
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def auto_id(self, request):
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@ -246,10 +221,18 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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def metric_type(self, request):
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yield request.param
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@pytest.fixture(scope="function", params=["TRIE", "STL_SORT", "AUTOINDEX"])
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@pytest.fixture(scope="function", params=["TRIE", "STL_SORT", "INVERTED", "AUTOINDEX"])
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def scalar_index(self, request):
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yield request.param
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@pytest.fixture(scope="function", params=["TRIE", "INVERTED", "AUTOINDEX", ""])
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def varchar_index(self, request):
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yield request.param
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@pytest.fixture(scope="function", params=["STL_SORT", "INVERTED", "AUTOINDEX", ""])
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def numeric_index(self, request):
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yield request.param
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"""
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******************************************************************
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# The following are valid base cases
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@ -263,9 +246,9 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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ct.default_all_indexes_params[:7]))
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def test_milvus_client_index_default(self, index, params, metric_type):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index normal case
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method: create connection, collection, create index, insert and search
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expected: index/search/query successfully
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -307,15 +290,14 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.skip(reason="pymilvus issue 1884")
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@pytest.mark.parametrize("index, params",
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zip(ct.all_index_types[:7],
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ct.default_all_indexes_params[:7]))
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def test_milvus_client_index_with_params(self, index, params, metric_type):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index with user defined params
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method: create connection, collection, index, insert and search
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expected: index/search/query successfully
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -355,15 +337,14 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.skip("wait for modification")
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@pytest.mark.parametrize("index, params",
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zip(ct.all_index_types[:7],
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ct.default_all_indexes_params[:7]))
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def test_milvus_client_index_after_insert(self, index, params, metric_type):
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"""
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target: test search (high level api) normal case
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method: create connection, collection, insert and search
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expected: search/query successfully
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target: test index after insert
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method: create connection, collection, insert, index and search
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expected: index/search/query successfully
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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@ -378,7 +359,7 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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self.insert(client, collection_name, rows)
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# 3. prepare index params
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type)
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index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type, params=params)
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# 4. create index
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self.create_index(client, collection_name, index_params)
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# 5. load collection
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@ -400,18 +381,27 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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"primary_field": default_primary_key_field_name})
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.skip("wait for modification")
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def test_milvus_client_index_auto_index(self, scalar_index, metric_type):
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@pytest.mark.tags(CaseLabel.L2)
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def test_milvus_client_index_auto_index(self, numeric_index, varchar_index, metric_type):
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"""
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target: test search (high level api) normal case
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target: test index with autoindex on both scalar and vector field
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method: create connection, collection, insert and search
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expected: search/query successfully
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expected: index/search/query successfully
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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self.create_collection(client, collection_name, default_dim, consistency_level="Strong")
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schema = self.create_schema(client)[0]
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schema.add_field(default_primary_key_field_name, DataType.INT64, is_primary=True)
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schema.add_field(ct.default_int32_field_name, DataType.INT32)
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schema.add_field(ct.default_int16_field_name, DataType.INT16)
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schema.add_field(ct.default_int8_field_name, DataType.INT8)
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schema.add_field(default_string_field_name, DataType.VARCHAR, max_length=64)
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schema.add_field(default_float_field_name, DataType.FLOAT)
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schema.add_field(ct.default_double_field_name, DataType.DOUBLE)
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schema.add_field(ct.default_bool_field_name, DataType.BOOL)
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schema.add_field(default_vector_field_name, DataType.FLOAT_VECTOR, dim=default_dim)
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self.create_collection(client, collection_name, schema=schema, consistency_level="Strong")
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self.release_collection(client, collection_name)
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self.drop_index(client, collection_name, "vector")
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res = self.list_indexes(client, collection_name)[0]
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@ -419,19 +409,36 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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# 2. prepare index params
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index = "AUTOINDEX"
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type)
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index_params.add_index(field_name="id", index_type=scalar_index, metric_type=metric_type)
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index_params.add_index(field_name=default_vector_field_name, index_type=index, metric_type=metric_type)
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index_params.add_index(field_name=ct.default_int32_field_name, index_type=numeric_index, metric_type=metric_type)
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index_params.add_index(field_name=ct.default_int16_field_name, index_type=numeric_index, metric_type=metric_type)
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index_params.add_index(field_name=ct.default_int8_field_name, index_type=numeric_index, metric_type=metric_type)
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index_params.add_index(field_name=default_float_field_name, index_type=numeric_index, metric_type=metric_type)
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index_params.add_index(field_name=ct.default_double_field_name, index_type=numeric_index, metric_type=metric_type)
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index_params.add_index(field_name=ct.default_bool_field_name, index_type="", metric_type=metric_type)
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index_params.add_index(field_name=default_string_field_name, index_type=varchar_index, metric_type=metric_type)
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index_params.add_index(field_name=default_primary_key_field_name, index_type=numeric_index, metric_type=metric_type)
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# 3. create index
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self.create_index(client, collection_name, index_params)
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# 4. drop index
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self.drop_index(client, collection_name, "vector")
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self.drop_index(client, collection_name, "id")
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self.drop_index(client, collection_name, default_vector_field_name)
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self.drop_index(client, collection_name, ct.default_int32_field_name)
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self.drop_index(client, collection_name, ct.default_int16_field_name)
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self.drop_index(client, collection_name, ct.default_int8_field_name)
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self.drop_index(client, collection_name, default_float_field_name)
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self.drop_index(client, collection_name, ct.default_double_field_name)
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self.drop_index(client, collection_name, ct.default_bool_field_name)
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self.drop_index(client, collection_name, default_string_field_name)
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self.drop_index(client, collection_name, default_primary_key_field_name)
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# 5. create index
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self.create_index(client, collection_name, index_params)
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# 6. insert
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rng = np.random.default_rng(seed=19530)
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rows = [{default_primary_key_field_name: i, default_vector_field_name: list(rng.random((1, default_dim))[0]),
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default_float_field_name: i * 1.0, default_string_field_name: str(i)} for i in range(default_nb)]
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ct.default_int32_field_name: np.int32(i), ct.default_int16_field_name: np.int16(i),
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ct.default_int8_field_name: np.int8(i), default_float_field_name: i * 1.0,
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ct.default_double_field_name: np.double(i), ct.default_bool_field_name: np.bool_(i),
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default_string_field_name: str(i)} for i in range(default_nb)]
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self.insert(client, collection_name, rows)
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# 7. load collection
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self.load_collection(client, collection_name)
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@ -452,13 +459,145 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
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"primary_field": default_primary_key_field_name})
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self.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.skip("wait for modification")
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def test_milvus_client_index_multiple_vectors(self, scalar_index, metric_type):
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_scalar_hybrid_index_small_distinct_before_insert(self, metric_type):
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"""
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target: test search (high level api) normal case
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target: test index with autoindex on int/varchar with small distinct value (<=100)
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method: create connection, collection, insert and search
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expected: search/query successfully
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expected: index/search/query successfully (autoindex is bitmap index indeed)
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"""
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client = self._client()
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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int64_field_name = "int"
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schema = self.create_schema(client)[0]
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schema.add_field(default_primary_key_field_name, DataType.INT64, is_primary=True)
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schema.add_field(default_string_field_name, DataType.VARCHAR, max_length=64)
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schema.add_field(int64_field_name, DataType.INT64)
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schema.add_field(default_vector_field_name, DataType.FLOAT_VECTOR, dim=default_dim)
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self.create_collection(client, collection_name, schema=schema, consistency_level="Strong")
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self.release_collection(client, collection_name)
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self.drop_index(client, collection_name, "vector")
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res = self.list_indexes(client, collection_name)[0]
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assert res == []
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# 2. prepare index params
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index = "AUTOINDEX"
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index_params = self.prepare_index_params(client)[0]
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index_params.add_index(field_name=default_vector_field_name, index_type=index, metric_type=metric_type)
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index_params.add_index(field_name=int64_field_name, index_type=index, metric_type=metric_type)
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index_params.add_index(field_name=default_string_field_name, index_type=index, metric_type=metric_type)
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# 3. create index
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self.create_index(client, collection_name, index_params)
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# 4. insert
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rng = np.random.default_rng(seed=19530)
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rows = [{default_primary_key_field_name: i, default_vector_field_name: list(rng.random((1, default_dim))[0]),
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int64_field_name: np.random.randint(0, 99), default_string_field_name: str(np.random.randint(0, 99))}
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for i in range(default_nb)]
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self.insert(client, collection_name, rows)
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# 5. load collection
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self.load_collection(client, collection_name)
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# 6. search
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vectors_to_search = rng.random((1, default_dim))
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insert_ids = [i for i in range(default_nb)]
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self.search(client, collection_name, vectors_to_search,
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check_task=CheckTasks.check_search_results,
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check_items={"enable_milvus_client_api": True,
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"nq": len(vectors_to_search),
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"ids": insert_ids,
|
||||
"limit": default_limit})
|
||||
# 7. query
|
||||
self.query(client, collection_name, filter=default_search_exp,
|
||||
check_task=CheckTasks.check_query_results,
|
||||
check_items={exp_res: rows,
|
||||
"with_vec": True,
|
||||
"primary_field": default_primary_key_field_name})
|
||||
self.drop_collection(client, collection_name)
|
||||
|
||||
@pytest.mark.tags(CaseLabel.L1)
|
||||
def test_milvus_client_scalar_hybrid_index_small_to_large_distinct_after_insert(self, metric_type):
|
||||
"""
|
||||
target: test index with autoindex on int/varchar with small distinct value (<=100) first and
|
||||
insert to large distinct (2000+) later
|
||||
method: create connection, collection, insert and search
|
||||
expected: index/search/query successfully
|
||||
"""
|
||||
client = self._client()
|
||||
collection_name = cf.gen_unique_str(prefix)
|
||||
# 1. create collection
|
||||
int64_field_name = "int"
|
||||
schema = self.create_schema(client)[0]
|
||||
schema.add_field(default_primary_key_field_name, DataType.INT64, is_primary=True)
|
||||
schema.add_field(ct.default_int32_field_name, DataType.INT32)
|
||||
schema.add_field(ct.default_int16_field_name, DataType.INT16)
|
||||
schema.add_field(ct.default_int8_field_name, DataType.INT8)
|
||||
schema.add_field(default_string_field_name, DataType.VARCHAR, max_length=64)
|
||||
schema.add_field(int64_field_name, DataType.INT64)
|
||||
schema.add_field(default_vector_field_name, DataType.FLOAT_VECTOR, dim=default_dim)
|
||||
self.create_collection(client, collection_name, schema=schema, consistency_level="Strong")
|
||||
self.release_collection(client, collection_name)
|
||||
self.drop_index(client, collection_name, "vector")
|
||||
res = self.list_indexes(client, collection_name)[0]
|
||||
assert res == []
|
||||
# 2. insert
|
||||
rng = np.random.default_rng(seed=19530)
|
||||
rows = [{default_primary_key_field_name: i, default_vector_field_name: list(rng.random((1, default_dim))[0]),
|
||||
int64_field_name: np.random.randint(0, 99), ct.default_int32_field_name: np.int32(i),
|
||||
ct.default_int16_field_name: np.int16(i), ct.default_int8_field_name: np.int8(i),
|
||||
default_string_field_name: str(np.random.randint(0, 99))} for i in range(default_nb)]
|
||||
self.insert(client, collection_name, rows)
|
||||
# 3. prepare index params
|
||||
index = "AUTOINDEX"
|
||||
index_params = self.prepare_index_params(client)[0]
|
||||
index_params.add_index(field_name=default_vector_field_name, index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name=int64_field_name, index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name=ct.default_int32_field_name, index_type="", metric_type=metric_type)
|
||||
index_params.add_index(field_name=ct.default_int16_field_name, metric_type=metric_type)
|
||||
index_params.add_index(field_name=ct.default_int8_field_name, index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name=default_string_field_name, index_type=index, metric_type=metric_type)
|
||||
# 4. create index
|
||||
self.create_index(client, collection_name, index_params)
|
||||
# 5. load collection
|
||||
self.load_collection(client, collection_name)
|
||||
# 6. search
|
||||
vectors_to_search = rng.random((1, default_dim))
|
||||
insert_ids = [i for i in range(default_nb)]
|
||||
self.search(client, collection_name, vectors_to_search,
|
||||
check_task=CheckTasks.check_search_results,
|
||||
check_items={"enable_milvus_client_api": True,
|
||||
"nq": len(vectors_to_search),
|
||||
"ids": insert_ids,
|
||||
"limit": default_limit})
|
||||
# 7. query
|
||||
self.query(client, collection_name, filter=default_search_exp,
|
||||
check_task=CheckTasks.check_query_results,
|
||||
check_items={exp_res: rows,
|
||||
"with_vec": True,
|
||||
"primary_field": default_primary_key_field_name})
|
||||
# 8. insert more distinct value to the scalar field to make the autoindex change
|
||||
rng = np.random.default_rng(seed=19530)
|
||||
rows = [{default_primary_key_field_name: i, default_vector_field_name: list(rng.random((1, default_dim))[0]),
|
||||
int64_field_name: np.random.randint(0, 99), ct.default_int32_field_name: np.int32(i),
|
||||
ct.default_int16_field_name: np.int16(i), ct.default_int8_field_name: np.int8(i),
|
||||
default_string_field_name: str(np.random.randint(0, 99))} for i in range(default_nb, 2*default_nb)]
|
||||
self.insert(client, collection_name, rows)
|
||||
self.flush(client, collection_name)
|
||||
# 9. search
|
||||
vectors_to_search = rng.random((1, default_dim))
|
||||
insert_ids = [i for i in range(2*default_nb)]
|
||||
self.search(client, collection_name, vectors_to_search,
|
||||
check_task=CheckTasks.check_search_results,
|
||||
check_items={"enable_milvus_client_api": True,
|
||||
"nq": len(vectors_to_search),
|
||||
"ids": insert_ids,
|
||||
"limit": default_limit})
|
||||
self.drop_collection(client, collection_name)
|
||||
|
||||
@pytest.mark.tags(CaseLabel.L2)
|
||||
def test_milvus_client_index_multiple_vectors(self, numeric_index, metric_type):
|
||||
"""
|
||||
target: test index for multiple vectors
|
||||
method: create connection, collection, index, insert and search
|
||||
expected: index/search/query successfully
|
||||
"""
|
||||
client = self._client()
|
||||
collection_name = cf.gen_unique_str(prefix)
|
||||
@ -472,7 +611,7 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
|
||||
index = "AUTOINDEX"
|
||||
index_params = self.prepare_index_params(client)[0]
|
||||
index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name="id", index_type=scalar_index, metric_type=metric_type)
|
||||
index_params.add_index(field_name="id", index_type=numeric_index, metric_type=metric_type)
|
||||
# 3. create index
|
||||
self.create_index(client, collection_name, index_params)
|
||||
# 4. insert
|
||||
@ -501,15 +640,14 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
|
||||
self.drop_collection(client, collection_name)
|
||||
|
||||
@pytest.mark.tags(CaseLabel.L2)
|
||||
@pytest.mark.skip("wait for modification")
|
||||
@pytest.mark.parametrize("index, params",
|
||||
zip(ct.all_index_types[:7],
|
||||
ct.default_all_indexes_params[:7]))
|
||||
def test_milvus_client_index_drop_create_same_index(self, index, params, metric_type):
|
||||
"""
|
||||
target: test search (high level api) normal case
|
||||
method: create connection, collection, insert and search
|
||||
expected: search/query successfully
|
||||
target: test index after drop and create same index twice
|
||||
method: create connection, collection, create/drop/create index, insert and search
|
||||
expected: index create/drop and search/query successfully
|
||||
"""
|
||||
client = self._client()
|
||||
collection_name = cf.gen_unique_str(prefix)
|
||||
@ -521,7 +659,7 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
|
||||
assert res == []
|
||||
# 2. prepare index params
|
||||
index_params = self.prepare_index_params(client)[0]
|
||||
index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name="vector", index_type=index, params=params, metric_type=metric_type)
|
||||
# 3. create index
|
||||
self.create_index(client, collection_name, index_params)
|
||||
# 4. drop index
|
||||
@ -553,15 +691,14 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
|
||||
self.drop_collection(client, collection_name)
|
||||
|
||||
@pytest.mark.tags(CaseLabel.L2)
|
||||
@pytest.mark.skip("wait for modification")
|
||||
@pytest.mark.parametrize("index, params",
|
||||
zip(ct.all_index_types[:7],
|
||||
ct.default_all_indexes_params[:7]))
|
||||
def test_milvus_client_index_drop_create_different_index(self, index, params, metric_type):
|
||||
"""
|
||||
target: test search (high level api) normal case
|
||||
method: create connection, collection, insert and search
|
||||
expected: search/query successfully
|
||||
target: test index after drop and create different index twice
|
||||
method: create connection, collection, create/drop/create index, insert and search
|
||||
expected: index create/drop and search/query successfully
|
||||
"""
|
||||
client = self._client()
|
||||
collection_name = cf.gen_unique_str(prefix)
|
||||
@ -579,7 +716,7 @@ class TestMilvusClientIndexValid(TestMilvusClientV2Base):
|
||||
# 4. drop index
|
||||
self.drop_index(client, collection_name, "vector")
|
||||
# 4. create different index
|
||||
index_params.add_index(field_name="vector", index_type=index, metric_type=metric_type)
|
||||
index_params.add_index(field_name="vector", index_type=index, params=params, metric_type=metric_type)
|
||||
self.create_index(client, collection_name, index_params)
|
||||
# 5. insert
|
||||
rng = np.random.default_rng(seed=19530)
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user