mirror of https://github.com/milvus-io/milvus.git
95 lines
4.0 KiB
Python
95 lines
4.0 KiB
Python
# import datetime
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# import pytest
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#
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# from base.client_base import TestcaseBase
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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
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# from utils.util_log import test_log as log
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# from pymilvus import utility
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#
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#
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# rounds = 100
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# per_nb = 100000
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# default_field_name = ct.default_float_vec_field_name
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# default_index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params": {"nlist": 64}}
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#
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#
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# class TestLoad(TestcaseBase):
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# """ Test case of end to end"""
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# @pytest.mark.tags(CaseLabel.L3)
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# def test_load_default(self):
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# name = 'load_test_collection_1'
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# name2 = 'load_test_collection_2'
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# # create
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# # collection_w = self.init_collection_wrap(name=name)
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# # collection_w2 = self.init_collection_wrap(name=name2)
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# # assert collection_w.name == name
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#
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# for i in range(50):
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# name = f"load_collection2_{i}"
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# self.init_collection_wrap(name=name)
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# log.debug(f"total collections: {len(utility.list_collections())}")
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#
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# # # insert
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# # data = cf.gen_default_list_data(per_nb)
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# # log.debug(f"data len: {len(data[0])}")
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# # for i in range(rounds):
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# # t0 = datetime.datetime.now()
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# # ins_res, res = collection_w.insert(data, timeout=180)
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"round{i} insert: {len(ins_res.primary_keys)} entities in {tt}s")
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# # assert res # and per_nb == len(ins_res.primary_keys)
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# #
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# # t0 = datetime.datetime.now()
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# # ins_res2, res = collection_w2.insert(data, timeout=180)
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"round{i} insert2: {len(ins_res2.primary_keys)} entities in {tt}s")
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# # assert res
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# #
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# # # flush
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# # t0 = datetime.datetime.now()
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# # log.debug(f"current collection num_entities: {collection_w.num_entities}")
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"round{i} flush in {tt}")
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# #
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# # t0 = datetime.datetime.now()
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# # log.debug(f"current collection2 num_entities: {collection_w2.num_entities}")
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"round{i} flush2 in {tt}")
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#
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# # index, res = collection_w.create_index(default_field_name, default_all_indexes_params, timeout=60)
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# # assert res
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#
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# # # search
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# # collection_w.load()
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# # search_vectors = cf.gen_vectors(1, ct.default_dim)
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# # t0 = datetime.datetime.now()
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# # res_1, _ = collection_w.search(data=search_vectors,
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# # anns_field=ct.default_float_vec_field_name,
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# # param={"nprobe": 16}, limit=1)
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"assert search: {tt}")
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# # assert len(res_1) == 1
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# # # collection_w.release()
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# #
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# # # index
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# # collection_w.insert(cf.gen_default_dataframe_data(nb=5000))
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# # assert collection_w.num_entities == len(data[0]) + 5000
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# # _index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params": {"nlist": 64}}
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# # t0 = datetime.datetime.now()
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# # index, _ = collection_w.create_index(field_name=ct.default_float_vec_field_name,
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# # index_params=_index_params,
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# # name=cf.gen_unique_str())
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"assert index: {tt}")
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# # assert len(collection_w.indexes) == 1
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# #
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# # # query
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# # term_expr = f'{ct.default_int64_field_name} in [3001,4001,4999,2999]'
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# # t0 = datetime.datetime.now()
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# # res, _ = collection_w.query(term_expr)
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# # tt = datetime.datetime.now() - t0
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# # log.debug(f"assert query: {tt}")
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# # assert len(res) == 4
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