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https://gitee.com/milvus-io/milvus.git
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ee659d50db
related issue: https://github.com/milvus-io/milvus/issues/40698 --------- Signed-off-by: yanliang567 <yanliang.qiao@zilliz.com>
656 lines
33 KiB
Python
656 lines
33 KiB
Python
import pytest
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from base.client_v2_base import TestMilvusClientV2Base
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from utils.util_log import test_log as log
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from common import common_func as cf
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from common import common_type as ct
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from common.common_type import CaseLabel, CheckTasks
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from utils.util_pymilvus import *
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prefix = "milvus_client_api_query"
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epsilon = ct.epsilon
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default_nb = ct.default_nb
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default_nb_medium = ct.default_nb_medium
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default_nq = ct.default_nq
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default_dim = ct.default_dim
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default_limit = ct.default_limit
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default_search_exp = "id >= 0"
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exp_res = "exp_res"
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default_search_string_exp = "varchar >= \"0\""
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default_search_mix_exp = "int64 >= 0 && varchar >= \"0\""
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default_invaild_string_exp = "varchar >= 0"
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default_json_search_exp = "json_field[\"number\"] >= 0"
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perfix_expr = 'varchar like "0%"'
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default_search_field = ct.default_float_vec_field_name
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default_search_params = ct.default_search_params
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default_primary_key_field_name = "id"
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default_vector_field_name = "vector"
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default_float_field_name = ct.default_float_field_name
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default_bool_field_name = ct.default_bool_field_name
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default_string_field_name = ct.default_string_field_name
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default_int32_array_field_name = ct.default_int32_array_field_name
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default_string_array_field_name = ct.default_string_array_field_name
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class TestMilvusClientQueryInvalid(TestMilvusClientV2Base):
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""" Test case of search 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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yield request.param
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@pytest.fixture(scope="function", params=["COSINE", "L2"])
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def metric_type(self, request):
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yield request.param
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"""
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******************************************************************
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# The following are invalid base cases
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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_query_not_all_required_params(self):
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"""
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target: test query (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_collection_name_by_testcase_name()
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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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collections = self.list_collections(client)[0]
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assert collection_name in collections
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self.describe_collection(client, collection_name,
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check_task=CheckTasks.check_describe_collection_property,
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check_items={"collection_name": collection_name,
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"dim": default_dim,
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"consistency_level": 0})
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# 2. 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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self.insert(client, collection_name, rows)
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# 3. query using ids
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error = {ct.err_code: 65535, ct.err_msg: f"empty expression should be used with limit"}
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self.query(client, collection_name,
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check_task=CheckTasks.err_res, check_items=error)
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class TestMilvusClientQueryValid(TestMilvusClientV2Base):
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""" Test case of search 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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yield request.param
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@pytest.fixture(scope="function", params=["COSINE", "L2"])
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def metric_type(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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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_query_default(self):
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"""
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target: test query (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_collection_name_by_testcase_name()
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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. 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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self.insert(client, collection_name, rows)
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# 3. query using ids
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self.query(client, collection_name, ids=[i for i in range(default_nb)],
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": default_primary_key_field_name})
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# 4. query using filter
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self.query(client, collection_name, filter=default_search_exp,
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": 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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def test_milvus_client_query_output_fields(self):
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"""
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target: test query (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_collection_name_by_testcase_name()
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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. 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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self.insert(client, collection_name, rows)
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# 3. query using ids
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self.query(client, collection_name, ids=[i for i in range(default_nb)],
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": default_primary_key_field_name})
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# 4. query using filter
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res = self.query(client, collection_name, filter=default_search_exp,
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output_fields=[default_primary_key_field_name, default_float_field_name,
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default_string_field_name, default_vector_field_name],
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": default_primary_key_field_name})[0]
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assert set(res[0].keys()) == {default_primary_key_field_name, default_vector_field_name,
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default_float_field_name, default_string_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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def test_milvus_client_query_output_fields_all(self):
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"""
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target: test query (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_collection_name_by_testcase_name()
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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. 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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self.insert(client, collection_name, rows)
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# 3. query using ids
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self.query(client, collection_name, ids=[i for i in range(default_nb)],
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": default_primary_key_field_name})
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# 4. query using filter
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res = self.query(client, collection_name, filter=default_search_exp,
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output_fields=["*"],
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows,
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"with_vec": True,
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"pk_name": default_primary_key_field_name})[0]
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assert set(res[0].keys()) == {default_primary_key_field_name, default_vector_field_name,
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default_float_field_name, default_string_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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def test_milvus_client_query_limit(self):
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"""
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target: test query (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_collection_name_by_testcase_name()
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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. 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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self.insert(client, collection_name, rows)
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# 3. query using ids
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limit = 5
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self.query(client, collection_name, ids=[i for i in range(default_nb)],
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limit=limit,
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows[:limit],
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"with_vec": True,
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"pk_name": default_primary_key_field_name[:limit]})
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# 4. query using filter
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self.query(client, collection_name, filter=default_search_exp,
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limit=limit,
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check_task=CheckTasks.check_query_results,
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check_items={exp_res: rows[:limit],
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"with_vec": True,
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"pk_name": default_primary_key_field_name[:limit]})
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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.parametrize("sample_rate", [0.7, 0.5, 0.01])
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def test_milvus_client_query_random_sample(self, sample_rate):
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"""
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target: test query random sample
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method: create connection, collection, insert and query
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expected: query successfully
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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vectors = cf.gen_vectors(default_nb, default_dim)
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rows = [
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{
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default_primary_key_field_name: i,
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default_vector_field_name: vectors[i],
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default_float_field_name: i * 1.0,
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default_string_field_name: cf.generate_random_sentence("English")
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} for i in range(default_nb)
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]
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self.insert(client, collection_name, rows)
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expr = f"{default_string_field_name} like '%red%'"
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# 3. query without sample rate
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all_res = self.query(client, collection_name, filter=expr)[0]
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exp_num = max(1, int(len(all_res) * sample_rate))
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# 4. query using sample rate
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expr = expr + f" && random_sample({sample_rate})"
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sample_res = self.query(client, collection_name, filter=expr)[0]
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log.info(exp_num)
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assert len(sample_res) == exp_num
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("sample_rate", [1, 0, -9])
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def test_milvus_client_query_invalid_sample_rate(self, sample_rate):
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"""
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target: test query random sample
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method: create connection, collection, insert and query
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expected: query successfully
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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vectors = cf.gen_vectors(1, default_dim)
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rows = [
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{
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default_primary_key_field_name: i,
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default_vector_field_name: vectors[i],
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default_float_field_name: i * 1.0,
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default_string_field_name: cf.generate_random_sentence("English")
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} for i in range(1)
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]
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self.insert(client, collection_name, rows)
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expr = f"{default_string_field_name} like '%red%' && random_sample({sample_rate})"
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# 3. query
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error = {ct.err_code: 999,
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ct.err_msg: "the sample factor should be between 0 and 1 and not too close to 0 or 1"}
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self.query(client, collection_name, filter=expr,
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check_task=CheckTasks.err_res, check_items=error)
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class TestMilvusClientGetInvalid(TestMilvusClientV2Base):
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""" Test case of search interface """
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"""
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******************************************************************
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# The following are invalid base cases
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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name",
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["12-s", "12 s", "(mn)", "中文", "%$#",
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"".join("a" for i in range(ct.max_name_length + 1))])
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def test_milvus_client_get_invalid_collection_name(self, name):
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"""
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target: test get interface invalid cases
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method: invalid collection name
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expected: search/query successfully without deleted data
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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default_nb = 1000
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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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self.insert(client, collection_name, rows)
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pks = [i for i in range(default_nb)]
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# 3. get first primary key
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error = {ct.err_code: 1100, ct.err_msg: f"Invalid collection name"}
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self.get(client, name, ids=pks[0:1],
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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.L2)
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def test_milvus_client_get_not_exist_collection_name(self):
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"""
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target: test get interface invalid cases
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method: invalid collection name
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expected: search/query successfully without deleted data
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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default_nb = 1000
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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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self.insert(client, collection_name, rows)
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pks = [i for i in range(default_nb)]
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# 3. get first primary key
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name = "invalid"
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error = {ct.err_code: 100, ct.err_msg: f"can't find collection[database=default][collection={name}]"}
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self.get(client, name, ids=pks[0:1],
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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.L2)
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@pytest.mark.parametrize("invalid_ids", ["中文", "%$#"])
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def test_milvus_client_get_invalid_ids(self, invalid_ids):
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"""
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target: test get interface invalid cases
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method: invalid collection name
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expected: search/query successfully without deleted data
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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default_nb = 1000
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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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self.insert(client, collection_name, rows)
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# 3. get first primary key
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error = {ct.err_code: 1100, ct.err_msg: f"cannot parse expression"}
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self.get(client, collection_name, ids=invalid_ids,
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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 TestMilvusClientGetValid(TestMilvusClientV2Base):
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""" Test case of search 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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yield request.param
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@pytest.fixture(scope="function", params=["COSINE", "L2"])
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def metric_type(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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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_get_normal(self):
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"""
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target: test get interface
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method: create connection, collection, insert delete, and search
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expected: search/query successfully without deleted data
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"""
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client = self._client()
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collection_name = cf.gen_collection_name_by_testcase_name()
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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. insert
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default_nb = 1000
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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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self.insert(client, collection_name, rows)
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pks = [i for i in range(default_nb)]
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# 3. get first primary key
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first_pk_data = self.get(client, collection_name, ids=pks[0:1])[0]
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assert len(first_pk_data) == len(pks[0:1])
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|
first_pk_data_1 = self.get(client, collection_name, ids=0)[0]
|
|
assert first_pk_data == first_pk_data_1
|
|
self.drop_collection(client, collection_name)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_milvus_client_get_output_fields(self):
|
|
"""
|
|
target: test get interface with output fields
|
|
method: create connection, collection, insert delete, and search
|
|
expected: search/query successfully without deleted data
|
|
"""
|
|
client = self._client()
|
|
collection_name = cf.gen_collection_name_by_testcase_name()
|
|
# 1. create collection
|
|
self.create_collection(client, collection_name, default_dim, consistency_level="Strong")
|
|
# 2. insert
|
|
default_nb = 1000
|
|
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]),
|
|
default_float_field_name: i * 1.0, default_string_field_name: str(i)} for i in range(default_nb)]
|
|
self.insert(client, collection_name, rows)
|
|
pks = [i for i in range(default_nb)]
|
|
# 3. get first primary key
|
|
output_fields_array = [default_primary_key_field_name, default_vector_field_name,
|
|
default_float_field_name, default_string_field_name]
|
|
first_pk_data = self.get(client, collection_name, ids=pks[0:1], output_fields=output_fields_array)[0]
|
|
assert len(first_pk_data) == len(pks[0:1])
|
|
assert len(first_pk_data[0]) == len(output_fields_array)
|
|
first_pk_data_1 = self.get(client, collection_name, ids=0, output_fields=output_fields_array)[0]
|
|
assert first_pk_data == first_pk_data_1
|
|
assert len(first_pk_data_1[0]) == len(output_fields_array)
|
|
self.drop_collection(client, collection_name)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
@pytest.mark.skip(reason="pymilvus issue 2056")
|
|
def test_milvus_client_get_normal_string(self):
|
|
"""
|
|
target: test get interface for string field
|
|
method: create connection, collection, insert delete, and search
|
|
expected: search/query successfully without deleted data
|
|
"""
|
|
client = self._client()
|
|
collection_name = cf.gen_collection_name_by_testcase_name()
|
|
# 1. create collection
|
|
self.create_collection(client, collection_name, default_dim, id_type="string", max_length=ct.default_length)
|
|
# 2. insert
|
|
rng = np.random.default_rng(seed=19530)
|
|
rows = [
|
|
{default_primary_key_field_name: str(i), default_vector_field_name: list(rng.random((1, default_dim))[0]),
|
|
default_float_field_name: i * 1.0, default_string_field_name: str(i)} for i in range(default_nb)]
|
|
self.insert(client, collection_name, rows)
|
|
pks = [str(i) for i in range(default_nb)]
|
|
# 3. get first primary key
|
|
first_pk_data = self.get(client, collection_name, ids=pks[0:1])[0]
|
|
assert len(first_pk_data) == len(pks[0:1])
|
|
first_pk_data_1 = self.get(client, collection_name, ids="0")[0]
|
|
assert first_pk_data == first_pk_data_1
|
|
|
|
self.drop_collection(client, collection_name)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.skip(reason="pymilvus issue 2056")
|
|
def test_milvus_client_get_normal_string_output_fields(self):
|
|
"""
|
|
target: test get interface for string field
|
|
method: create connection, collection, insert delete, and search
|
|
expected: search/query successfully without deleted data
|
|
"""
|
|
client = self._client()
|
|
collection_name = cf.gen_collection_name_by_testcase_name()
|
|
# 1. create collection
|
|
self.create_collection(client, collection_name, default_dim, id_type="string", max_length=ct.default_length)
|
|
# 2. insert
|
|
rng = np.random.default_rng(seed=19530)
|
|
rows = [
|
|
{default_primary_key_field_name: str(i), default_vector_field_name: list(rng.random((1, default_dim))[0]),
|
|
default_float_field_name: i * 1.0, default_string_field_name: str(i)} for i in range(default_nb)]
|
|
self.insert(client, collection_name, rows)
|
|
pks = [str(i) for i in range(default_nb)]
|
|
# 3. get first primary key
|
|
output_fields_array = [default_primary_key_field_name, default_vector_field_name,
|
|
default_float_field_name, default_string_field_name]
|
|
first_pk_data = self.get(client, collection_name, ids=pks[0:1], output_fields=output_fields_array)[0]
|
|
assert len(first_pk_data) == len(pks[0:1])
|
|
assert len(first_pk_data[0]) == len(output_fields_array)
|
|
first_pk_data_1 = self.get(client, collection_name, ids="0", output_fields=output_fields_array)[0]
|
|
assert first_pk_data == first_pk_data_1
|
|
assert len(first_pk_data_1[0]) == len(output_fields_array)
|
|
self.drop_collection(client, collection_name)
|
|
|
|
|
|
class TestMilvusClientQueryJsonPathIndex(TestMilvusClientV2Base):
|
|
""" Test case of search interface """
|
|
|
|
@pytest.fixture(scope="function", params=["INVERTED"])
|
|
def supported_varchar_scalar_index(self, request):
|
|
yield request.param
|
|
|
|
# @pytest.fixture(scope="function", params=["DOUBLE", "VARCHAR", "BOOL", "double", "varchar", "bool"])
|
|
@pytest.fixture(scope="function", params=["DOUBLE"])
|
|
def supported_json_cast_type(self, request):
|
|
yield request.param
|
|
|
|
"""
|
|
******************************************************************
|
|
# The following are valid base cases
|
|
******************************************************************
|
|
"""
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("enable_dynamic_field", [True, False])
|
|
@pytest.mark.parametrize("is_flush", [True, False])
|
|
@pytest.mark.parametrize("is_release", [True, False])
|
|
@pytest.mark.parametrize("single_data_num", [50])
|
|
def test_milvus_client_search_json_path_index_all_expressions(self, enable_dynamic_field, supported_json_cast_type,
|
|
supported_varchar_scalar_index, is_flush, is_release,
|
|
single_data_num):
|
|
"""
|
|
target: test query after json path index with all supported basic expressions
|
|
method: Query after json path index with all supported basic expressions
|
|
step: 1. create collection
|
|
2. insert with different data distribution
|
|
3. flush if specified
|
|
4. query when there is no json path index under all expressions
|
|
5. release if specified
|
|
6. prepare index params with json path index
|
|
7. create json path index
|
|
8. create same json index twice
|
|
9. reload collection if released before to make sure the new index load successfully
|
|
10. sleep for 60s to make sure the new index load successfully without release and reload operations
|
|
11. query after there is json path index under all expressions which should get the same result
|
|
with that without json path index
|
|
expected: query successfully after there is json path index under all expressions which should get the same result
|
|
with that without json path index
|
|
"""
|
|
client = self._client()
|
|
collection_name = cf.gen_collection_name_by_testcase_name()
|
|
# 1. create collection
|
|
json_field_name = "json_field"
|
|
schema = self.create_schema(client, enable_dynamic_field=enable_dynamic_field)[0]
|
|
schema.add_field(default_primary_key_field_name, DataType.INT64, is_primary=True, auto_id=False)
|
|
schema.add_field(default_vector_field_name, DataType.FLOAT_VECTOR, dim=default_dim)
|
|
schema.add_field(default_string_field_name, DataType.VARCHAR, max_length=64)
|
|
if not enable_dynamic_field:
|
|
schema.add_field(json_field_name, DataType.JSON, nullable=True)
|
|
index_params = self.prepare_index_params(client)[0]
|
|
index_params.add_index(default_vector_field_name, metric_type="COSINE")
|
|
self.create_collection(client, collection_name, schema=schema, index_params=index_params)
|
|
# 2. insert with different data distribution
|
|
vectors = cf.gen_vectors(default_nb+60, default_dim)
|
|
inserted_data_distribution = ct.get_all_kind_data_distribution
|
|
nb_single = single_data_num
|
|
for i in range(len(inserted_data_distribution)):
|
|
rows = [{default_primary_key_field_name: j, default_vector_field_name: vectors[j],
|
|
default_string_field_name: f"{j}", json_field_name: inserted_data_distribution[i]} for j in
|
|
range(i * nb_single, (i + 1) * nb_single)]
|
|
assert len(rows) == nb_single
|
|
self.insert(client, collection_name=collection_name, data=rows)
|
|
log.info(f"inserted {nb_single} {inserted_data_distribution[i]}")
|
|
# 3. flush if specified
|
|
if is_flush:
|
|
self.flush(client, collection_name)
|
|
# 4. query when there is no json path index under all expressions
|
|
# skip negative expression for issue 40685
|
|
# "my_json['a'] != 1", "my_json['a'] != 1.0", "my_json['a'] != '1'", "my_json['a'] != 1.1", "my_json['a'] not in [1]"
|
|
express_list = cf.gen_json_field_expressions_all_single_operator()
|
|
compare_dict = {}
|
|
for i in range(len(express_list)):
|
|
json_list = []
|
|
id_list = []
|
|
log.info(f"query with filter {express_list[i]} before json path index is:")
|
|
res = self.query(client, collection_name=collection_name, filter=express_list[i], output_fields=["count(*)"])[0]
|
|
count = res[0]['count(*)']
|
|
log.info(f"The count(*) after query with filter {express_list[i]} before json path index is: {count}")
|
|
res = self.query(client, collection_name=collection_name, filter=express_list[i], output_fields=[f"{json_field_name}"])[0]
|
|
for single in res:
|
|
id_list.append(single[f"{default_primary_key_field_name}"])
|
|
json_list.append(single[f"{json_field_name}"])
|
|
assert count == len(id_list)
|
|
assert count == len(json_list)
|
|
compare_dict.setdefault(f'{i}', {})
|
|
compare_dict[f'{i}']["id_list"] = id_list
|
|
compare_dict[f'{i}']["json_list"] = json_list
|
|
# 5. release if specified
|
|
if is_release:
|
|
self.release_collection(client, collection_name)
|
|
self.drop_index(client, collection_name, default_vector_field_name)
|
|
# 6. prepare index params with json path index
|
|
index_name = "json_index"
|
|
index_params = self.prepare_index_params(client)[0]
|
|
json_path_list = [f"{json_field_name}", f"{json_field_name}[0]", f"{json_field_name}[1]",
|
|
f"{json_field_name}[6]", f"{json_field_name}['a']", f"{json_field_name}['a']['b']",
|
|
f"{json_field_name}['a'][0]", f"{json_field_name}['a'][6]", f"{json_field_name}['a'][0]['b']",
|
|
f"{json_field_name}['a']['b']['c']", f"{json_field_name}['a']['b'][0]['d']",
|
|
f"{json_field_name}[10000]", f"{json_field_name}['a']['c'][0]['d']"]
|
|
index_params.add_index(field_name=default_vector_field_name, index_type="AUTOINDEX", metric_type="COSINE")
|
|
for i in range(len(json_path_list)):
|
|
index_params.add_index(field_name=json_field_name, index_name=index_name + f'{i}',
|
|
index_type=supported_varchar_scalar_index,
|
|
params={"json_cast_type": supported_json_cast_type,
|
|
"json_path": json_path_list[i]})
|
|
# 7. create json path index
|
|
self.create_index(client, collection_name, index_params)
|
|
# 8. create same json index twice
|
|
self.create_index(client, collection_name, index_params)
|
|
# 9. reload collection if released before to make sure the new index load successfully
|
|
if is_release:
|
|
self.load_collection(client, collection_name)
|
|
else:
|
|
# 10. sleep for 60s to make sure the new index load successfully without release and reload operations
|
|
time.sleep(60)
|
|
# 11. query after there is json path index under all expressions which should get the same result
|
|
# with that without json path index
|
|
for i in range(len(express_list)):
|
|
json_list = []
|
|
id_list = []
|
|
log.info(f"query with filter {express_list[i]} after json path index is:")
|
|
count = self.query(client, collection_name=collection_name, filter=express_list[i],
|
|
output_fields=["count(*)"])[0]
|
|
log.info(f"The count(*) after query with filter {express_list[i]} after json path index is: {count}")
|
|
res = self.query(client, collection_name=collection_name, filter=express_list[i],
|
|
output_fields=[f"{json_field_name}"])[0]
|
|
for single in res:
|
|
id_list.append(single[f"{default_primary_key_field_name}"])
|
|
json_list.append(single[f"{json_field_name}"])
|
|
if len(json_list) != len(compare_dict[f'{i}']["json_list"]):
|
|
log.debug(f"json field after json path index under expression {express_list[i]} is:")
|
|
log.debug(json_list)
|
|
log.debug(f"json field before json path index to be compared under expression {express_list[i]} is:")
|
|
log.debug(compare_dict[f'{i}']["json_list"])
|
|
assert json_list == compare_dict[f'{i}']["json_list"]
|
|
if len(id_list) != len(compare_dict[f'{i}']["id_list"]):
|
|
log.debug(f"primary key field after json path index under expression {express_list[i]} is:")
|
|
log.debug(id_list)
|
|
log.debug(f"primary key field before json path index to be compared under expression {express_list[i]} is:")
|
|
log.debug(compare_dict[f'{i}']["id_list"])
|
|
assert id_list == compare_dict[f'{i}']["id_list"]
|
|
log.info(f"PASS with expression {express_list[i]}")
|