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