mirror of https://github.com/milvus-io/milvus.git
203 lines
9.8 KiB
Python
203 lines
9.8 KiB
Python
import pytest
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import random
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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 common.milvus_sys import MilvusSys
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from utils.util_pymilvus import *
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from deploy.base import TestDeployBase
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from deploy import common as dc
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from deploy.common import gen_index_param, gen_search_param
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default_nb = ct.default_nb
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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_field = ct.default_float_vec_field_name
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default_search_params = ct.default_search_params
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default_int64_field_name = ct.default_int64_field_name
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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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binary_field_name = default_binary_vec_field_name
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default_search_exp = "int64 >= 0"
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default_term_expr = f'{ct.default_int64_field_name} in [0, 1]'
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class TestActionBeforeReinstall(TestDeployBase):
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""" Test case of action before reinstall """
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def teardown_method(self, method):
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log.info(("*" * 35) + " teardown " + ("*" * 35))
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log.info("[teardown_method] Start teardown test case %s..." %
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method.__name__)
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log.info("skip drop collection")
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@pytest.mark.skip()
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@pytest.mark.tags(CaseLabel.L3)
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@pytest.mark.parametrize("index_type", dc.all_index_types) # , "BIN_FLAT"
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def test_task_1(self, index_type, data_size):
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"""
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before reinstall: create collection and insert data, load and search
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after reinstall: get collection, search, create index, load, and search
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"""
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name = "task_1_" + index_type
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insert_data = False
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is_binary = True if "BIN" in index_type else False
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is_flush = False
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# init collection
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collection_w = self.init_collection_general(insert_data=insert_data, is_binary=is_binary, nb=data_size,
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is_flush=is_flush, name=name)[0]
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if is_binary:
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_, vectors_to_search = cf.gen_binary_vectors(
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default_nb, default_dim)
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default_search_field = ct.default_binary_vec_field_name
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else:
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vectors_to_search = cf.gen_vectors(default_nb, default_dim)
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default_search_field = ct.default_float_vec_field_name
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search_params = gen_search_param(index_type)[0]
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# search
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collection_w.search(vectors_to_search[:default_nq], default_search_field,
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search_params, default_limit,
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default_search_exp,
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check_task=CheckTasks.check_search_results,
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check_items={"nq": default_nq,
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"limit": default_limit})
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# query
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output_fields = [ct.default_int64_field_name]
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collection_w.query(default_term_expr, output_fields=output_fields,
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check_task=CheckTasks.check_query_not_empty)
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# create index
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default_index = gen_index_param(index_type)
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collection_w.create_index(default_search_field, default_index)
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# release and load after creating index
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collection_w.release()
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collection_w.load()
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# search
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collection_w.search(vectors_to_search[:default_nq], default_search_field,
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search_params, default_limit,
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default_search_exp,
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check_task=CheckTasks.check_search_results,
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check_items={"nq": default_nq,
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"limit": default_limit})
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# query
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output_fields = [ct.default_int64_field_name]
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collection_w.query(default_term_expr, output_fields=output_fields,
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check_task=CheckTasks.check_query_not_empty)
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@pytest.mark.tags(CaseLabel.L3)
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@pytest.mark.parametrize("index_type", dc.all_index_types) # , "BIN_FLAT"
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def test_task_2(self, index_type, data_size):
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"""
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before reinstall: create collection, insert data and create index,load and search
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after reinstall: get collection, search, insert data, create index, load, and search
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"""
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name = "task_2_" + index_type
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is_binary = True if "BIN" in index_type else False
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# init collection
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collection_w = self.init_collection_general(insert_data=False, is_binary=is_binary, nb=data_size,
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is_flush=False, name=name, active_trace=True)[0]
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vectors_to_search = cf.gen_vectors(default_nb, default_dim)
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default_search_field = ct.default_float_vec_field_name
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if is_binary:
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_, vectors_to_search = cf.gen_binary_vectors(
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default_nb, default_dim)
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default_search_field = ct.default_binary_vec_field_name
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search_params = gen_search_param(index_type)[0]
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output_fields = [ct.default_int64_field_name]
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# search
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collection_w.search(vectors_to_search[:default_nq], default_search_field,
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search_params, default_limit,
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default_search_exp,
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output_fields=output_fields,
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check_task=CheckTasks.check_search_results,
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check_items={"nq": default_nq,
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"limit": default_limit})
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# query
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collection_w.query(default_term_expr, output_fields=output_fields,
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check_task=CheckTasks.check_query_not_empty)
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# insert data
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self.init_collection_general(insert_data=True, is_binary=is_binary, nb=data_size,
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is_flush=False, name=name, active_trace=True)
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# create index
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default_index = gen_index_param(index_type)
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collection_w.create_index(default_search_field, default_index)
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# release and load after
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collection_w.release()
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collection_w.load()
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# search
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collection_w.search(vectors_to_search[:default_nq], default_search_field,
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search_params, default_limit,
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default_search_exp,
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output_fields=output_fields,
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check_task=CheckTasks.check_search_results,
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check_items={"nq": default_nq,
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"limit": default_limit})
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# query
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collection_w.query(default_term_expr, output_fields=output_fields,
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check_task=CheckTasks.check_query_not_empty)
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@pytest.mark.tags(CaseLabel.L3)
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@pytest.mark.parametrize("replica_number", [0, 1, 2])
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@pytest.mark.parametrize("is_compacted", [True, False])
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@pytest.mark.parametrize("is_deleted", [True, False])
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@pytest.mark.parametrize("is_string_indexed", [True, False])
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@pytest.mark.parametrize("is_vector_indexed", [True, False]) # , "BIN_FLAT"
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@pytest.mark.parametrize("segment_status", ["only_growing", "sealed", "all"]) # , "BIN_FLAT"
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# @pytest.mark.parametrize("is_empty", [True, False]) # , "BIN_FLAT" (keep one is enough)
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@pytest.mark.parametrize("index_type", random.sample(dc.all_index_types, 3)) # , "BIN_FLAT"
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def test_task_all(self, index_type, is_compacted,
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segment_status, is_vector_indexed, is_string_indexed, replica_number, is_deleted, data_size):
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"""
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before reinstall: create collection and insert data, load and search
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after reinstall: get collection, search, create index, load, and search
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"""
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name = f"index_type_{index_type}_segment_status_{segment_status}_is_vector_indexed_{is_vector_indexed}_is_string_indexed_{is_string_indexed}_is_compacted_{is_compacted}_is_deleted_{is_deleted}_replica_number_{replica_number}_data_size_{data_size}"
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ms = MilvusSys()
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is_binary = True if "BIN" in index_type else False
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# insert with small size data without flush to get growing segment
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collection_w = self.init_collection_general(insert_data=True, is_binary=is_binary, nb=3000,
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is_flush=False, name=name)[0]
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# load for growing segment
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if replica_number > 0:
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collection_w.load(replica_number=replica_number)
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delete_expr = f"{ct.default_int64_field_name} in [0,1,2,3,4,5,6,7,8,9]"
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# delete data for growing segment
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if is_deleted:
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collection_w.delete(expr=delete_expr)
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if segment_status == "only_growing":
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pytest.skip("already get growing segment, skip testcase")
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# insert with flush multiple times to generate multiple sealed segment
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for i in range(5):
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self.init_collection_general(insert_data=True, is_binary=is_binary, nb=data_size,
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is_flush=False, name=name)
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if is_binary:
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default_index_field = ct.default_binary_vec_field_name
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else:
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default_index_field = ct.default_float_vec_field_name
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if is_vector_indexed:
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# create index
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default_index_param = gen_index_param(index_type)
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collection_w.create_index(default_index_field, default_index_param)
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if is_string_indexed:
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# create index
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default_string_index_params = {}
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collection_w.create_index(default_string_field_name, default_string_index_params)
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# delete data for sealed segment
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delete_expr = f"{ct.default_int64_field_name} in [10,11,12,13,14,15,16,17,18,19]"
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if is_deleted:
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collection_w.delete(expr=delete_expr)
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if is_compacted:
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collection_w.compact()
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# reload after flush and create index
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if replica_number > 0:
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collection_w.release()
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collection_w.load(replica_number=replica_number)
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