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[skip ci] Update scale query node test (#12729)
Signed-off-by: ThreadDao <yufen.zong@zilliz.com>
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ThreadDao
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@ -1,15 +1,17 @@
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import pdb
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import random
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import threading
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import time
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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 customize.milvus_operator import MilvusOperator
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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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from utils.util_log import test_log as log
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from utils.util_k8s import wait_pods_ready
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prefix = "search_scale"
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nb = 5000
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@ -22,98 +24,86 @@ default_index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params":
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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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def test_scale_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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query_config = {
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'metadata.namespace': constants.NAMESPACE,
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'metadata.name': release_name,
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'spec.components.image': 'harbor.zilliz.cc/milvus/milvus:master-20211202-ed546d0',
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'spec.components.proxy.serviceType': 'LoadBalancer',
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'spec.components.queryNode.replicas': 1,
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'spec.config.dataCoord.enableCompaction': True,
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'spec.config.dataCoord.enableGarbageCollection': True
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}
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mic = MilvusOperator()
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mic.install(query_config)
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healthy = mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200)
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log.info(f"milvus healthy: {healthy}")
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host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
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# host = "10.98.0.8"
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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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c_name = cf.gen_unique_str("scale_query")
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# c_name = 'scale_query_DymS7kI4'
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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.init_collection(name=c_name, schema=cf.gen_default_collection_schema(), shards_num=2)
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# insert two segments
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for i in range(3):
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df = cf.gen_default_dataframe_data(nb)
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collection_w.insert(df)
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log.debug(collection_w.num_entities)
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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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# load
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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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# scale queryNode to 5
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mic.upgrade(release_name, {'spec.components.queryNode.replicas': 5}, constants.NAMESPACE)
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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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# continuously search
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def do_search():
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while True:
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search_res, _ = collection_w.search(cf.gen_vectors(1, ct.default_dim),
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ct.default_float_vec_field_name,
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ct.default_search_params, ct.default_limit)
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log.debug(search_res[0].ids)
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assert len(search_res[0].ids) == ct.default_limit
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assert res1[0].ids == res2[0].ids
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t_search = threading.Thread(target=do_search, args=(), daemon=True)
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t_search.start()
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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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# wait new QN running, continuously insert
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# time.sleep(10)
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healthy = mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200)
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log.info(f"milvus healthy after scale up: {healthy}")
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# wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
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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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def do_insert():
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while True:
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tmp_df = cf.gen_default_dataframe_data(1000)
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collection_w.insert(tmp_df)
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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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t_insert = threading.Thread(target=do_insert, args=(), daemon=True)
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t_insert.start()
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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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log.debug(collection_w.num_entities)
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time.sleep(20)
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log.debug("Expand querynode test finished")
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# scale queryNode pod
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env.helm_upgrade_cluster_milvus(queryNode=1)
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mic.upgrade(release_name, {'spec.components.queryNode.replicas': 3}, constants.NAMESPACE)
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time.sleep(60)
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wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
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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()
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log.debug(collection_w.num_entities)
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time.sleep(60)
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log.debug("Shrink querynode test finished")
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