mirror of https://github.com/milvus-io/milvus.git
268 lines
12 KiB
Python
268 lines
12 KiB
Python
import multiprocessing
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import numbers
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import random
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import numpy
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import threading
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import pytest
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import pandas as pd
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import decimal
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from decimal import Decimal, getcontext
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from time import sleep
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import heapq
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from base.client_base import TestcaseBase
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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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from common.constants import *
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from pymilvus.orm.types import CONSISTENCY_STRONG, CONSISTENCY_BOUNDED, CONSISTENCY_SESSION, CONSISTENCY_EVENTUALLY
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from base.high_level_api_wrapper import HighLevelApiWrapper
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client_w = HighLevelApiWrapper()
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prefix = "milvus_client_api_delete"
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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 TestMilvusClientDeleteInvalid(TestcaseBase):
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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_delete_with_filters_and_ids(self):
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"""
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target: test delete (high level api) with ids and filters
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method: create connection, collection, insert, delete, and search
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expected: raise exception
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"""
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client = self._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.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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pks = client_w.insert(client, collection_name, rows)[0]
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# 3. delete
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delete_num = 3
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client_w.delete(client, collection_name, ids=[i for i in range(delete_num)], filter=f"id < {delete_num}",
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check_task=CheckTasks.err_res,
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check_items={"err_code": 1,
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"err_msg": "Ambiguous filter parameter, "
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"only one deletion condition can be specified."})
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client_w.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.xfail(reason="pymilvus issue 1869")
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def test_milvus_client_delete_with_invalid_id_type(self):
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"""
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target: test delete (high level api)
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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._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.create_collection(client, collection_name, default_dim, consistency_level="Strong")
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# 2. delete
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client_w.delete(client, collection_name, ids=0,
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check_task=CheckTasks.err_res,
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check_items={"err_code": 1,
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"err_msg": "expr cannot be empty"})
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.xfail(reason="pymilvus issue 1870")
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def test_milvus_client_delete_with_not_all_required_params(self):
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"""
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target: test delete (high level api)
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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._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.create_collection(client, collection_name, default_dim, consistency_level="Strong")
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# 2. delete
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client_w.delete(client, collection_name,
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check_task=CheckTasks.err_res,
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check_items={"err_code": 1,
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"err_msg": "expr cannot be empty"})
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class TestMilvusClientDeleteValid(TestcaseBase):
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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_delete_with_ids(self):
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"""
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target: test delete (high level api)
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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._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.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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pks = client_w.insert(client, collection_name, rows)[0]
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# 3. delete
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delete_num = 3
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client_w.delete(client, collection_name, ids=[i for i in range(delete_num)])
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# 4. 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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for insert_id in range(delete_num):
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if insert_id in insert_ids:
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insert_ids.remove(insert_id)
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limit = default_nb - delete_num
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client_w.search(client, collection_name, vectors_to_search, limit=default_nb,
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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,
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"limit": limit})
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# 5. query
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client_w.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[delete_num:],
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"with_vec": True,
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"primary_field": default_primary_key_field_name})
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client_w.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_delete_with_filters(self):
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"""
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target: test delete (high level api)
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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._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.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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pks = client_w.insert(client, collection_name, rows)[0]
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# 3. delete
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delete_num = 3
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client_w.delete(client, collection_name, filter=f"id < {delete_num}")
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# 4. 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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for insert_id in range(delete_num):
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if insert_id in insert_ids:
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insert_ids.remove(insert_id)
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limit = default_nb - delete_num
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client_w.search(client, collection_name, vectors_to_search, limit=default_nb,
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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,
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"limit": limit})
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# 5. query
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client_w.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[delete_num:],
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"with_vec": True,
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"primary_field": default_primary_key_field_name})
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client_w.drop_collection(client, collection_name)
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@pytest.mark.tags(CaseLabel.L1)
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def test_milvus_client_delete_with_filters_partition(self):
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"""
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target: test delete (high level api)
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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._connect(enable_milvus_client_api=True)
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collection_name = cf.gen_unique_str(prefix)
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# 1. create collection
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client_w.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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pks = client_w.insert(client, collection_name, rows)[0]
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# 3. get partition lists
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partition_names = client_w.list_partitions(client, collection_name)
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# 4. delete
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delete_num = 3
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client_w.delete(client, collection_name, filter=f"id < {delete_num}", partition_names=partition_names)
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# 5. 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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for insert_id in range(delete_num):
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if insert_id in insert_ids:
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insert_ids.remove(insert_id)
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limit = default_nb - delete_num
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client_w.search(client, collection_name, vectors_to_search, limit=default_nb,
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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,
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"limit": limit})
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# 6. query
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client_w.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[delete_num:],
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"with_vec": True,
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"primary_field": default_primary_key_field_name})
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client_w.drop_collection(client, collection_name) |