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120 lines
4.8 KiB
Python
120 lines
4.8 KiB
Python
import pdb
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import random
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import pytest
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from base.collection_wrapper import ApiCollectionWrapper
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from common.common_type import CaseLabel
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from scale.helm_env import HelmEnv
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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 scale import constants
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from pymilvus import Index, connections
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prefix = "search_scale"
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nb = 5000
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nq = 5
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default_schema = cf.gen_default_collection_schema()
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default_search_exp = "int64 >= 0"
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default_index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params": {"nlist": 64}}
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class TestQueryNodeScale:
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@pytest.mark.tags(CaseLabel.L3)
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def test_expand_query_node(self):
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release_name = "scale-query"
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env = HelmEnv(release_name=release_name)
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host = env.helm_install_cluster_milvus()
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# connect
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connections.add_connection(default={"host": host, "port": 19530})
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connections.connect(alias='default')
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# create
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c_name = "query_scale_one"
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collection_w = ApiCollectionWrapper()
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collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema())
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# insert
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data = cf.gen_default_list_data(ct.default_nb)
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mutation_res, _ = collection_w.insert(data)
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assert mutation_res.insert_count == ct.default_nb
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# # create index
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# collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
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# assert collection_w.has_index()[0]
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# assert collection_w.index()[0] == Index(collection_w.collection, ct.default_float_vec_field_name,
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# default_index_params)
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collection_w.load()
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# vectors = [[random.random() for _ in range(ct.default_dim)] for _ in range(5)]
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res1, _ = collection_w.search(data[-1][:5], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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# scale queryNode pod
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env.helm_upgrade_cluster_milvus(queryNode=2)
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c_name_2 = "query_scale_two"
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collection_w2 = ApiCollectionWrapper()
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collection_w2.init_collection(name=c_name_2, schema=cf.gen_default_collection_schema())
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collection_w2.insert(data)
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assert collection_w2.num_entities == ct.default_nb
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collection_w2.load()
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res2, _ = collection_w2.search(data[-1][:5], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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assert res1[0].ids == res2[0].ids
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@pytest.mark.tags(CaseLabel.L3)
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def test_shrink_query_node(self):
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"""
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target: test shrink queryNode from 2 to 1
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method: 1.deploy two queryNode
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2.search two collections in two queryNode
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3.upgrade queryNode from 2 to 1
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4.search second collection
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expected: search result is correct
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"""
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# deploy
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release_name = "scale-query"
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env = HelmEnv(release_name=release_name, queryNode=2)
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host = env.helm_install_cluster_milvus(image_pull_policy=constants.IF_NOT_PRESENT)
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# connect
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connections.add_connection(default={"host": host, "port": 19530})
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connections.connect(alias='default')
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# collection one
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data = cf.gen_default_list_data(nb)
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c_name = "query_scale_one"
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collection_w = ApiCollectionWrapper()
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collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema())
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collection_w.insert(data)
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assert collection_w.num_entities == nb
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collection_w.load()
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res1, _ = collection_w.search(data[-1][:nq], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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assert res1[0].ids[0] == data[0][0]
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# collection two
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c_name_2 = "query_scale_two"
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collection_w2 = ApiCollectionWrapper()
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collection_w2.init_collection(name=c_name_2, schema=cf.gen_default_collection_schema())
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collection_w2.insert(data)
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assert collection_w2.num_entities == nb
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collection_w2.load()
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res2, _ = collection_w2.search(data[-1][:nq], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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assert res2[0].ids[0] == data[0][0]
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# scale queryNode pod
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env.helm_upgrade_cluster_milvus(queryNode=1)
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# search
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res1, _ = collection_w.search(data[-1][:nq], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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assert res1[0].ids[0] == data[0][0]
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res2, _ = collection_w2.search(data[-1][:nq], ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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assert res2[0].ids[0] == data[0][0]
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# env.helm_uninstall_cluster_milvus() |