mirror of https://github.com/milvus-io/milvus.git
[skip ci] Update scale data node test (#12879)
Signed-off-by: ThreadDao <yufen.zong@zilliz.com>pull/12883/head
ThreadDao
GitHub
parent
d8b2e84135
commit
55e62cc7ff
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@ -1,6 +1,6 @@
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# scale object
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IMAGE_REPOSITORY = "milvusdb/milvus-dev" # repository of milvus image
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IMAGE_TAG = "master-latest" # tag of milvus image
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IMAGE_REPOSITORY = "harbor.zilliz.cc/milvus/milvus" # repository of milvus image
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IMAGE_TAG = "master-20211207-4cd314d" # tag of milvus image
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NAMESPACE = "chaos-testing" # namespace
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IF_NOT_PRESENT = "IfNotPresent" # image pullPolicy IfNotPresent
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ALWAYS = "Always" # image pullPolicy Always
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@ -1,12 +1,16 @@
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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 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, scale_common
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from scale.helm_env import HelmEnv
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from pymilvus import connections, utility
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from customize.milvus_operator import MilvusOperator
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from scale import constants
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from pymilvus import 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 = "data_scale"
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default_schema = cf.gen_default_collection_schema()
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@ -17,89 +21,76 @@ default_index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params":
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class TestDataNodeScale:
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@pytest.mark.tags(CaseLabel.L3)
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def test_expand_data_node(self):
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def test_scale_data_node(self):
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"""
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target: test create and insert api after expand dataNode pod
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method: 1.create collection a and insert df
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2.expand dataNode pod from 1 to 2
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3.verify collection a property and verify create and insert of new collection
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expected: two collection create and insert op are both correctly
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target:
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method:
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expected:
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"""
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release_name = "scale-data"
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milvusOp, host, port = scale_common.deploy_default_milvus(release_name)
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# connect
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connections.add_connection(default={"host": host, "port": port})
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connections.connect(alias='default')
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# create
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c_name = cf.gen_unique_str(prefix)
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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()
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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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# scale dataNode to 2 pods
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milvusOp.upgrade(release_name, {'spec.components.dataNode.replicas': 2}, constants.NAMESPACE)
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milvusOp.wait_for_healthy(release_name, constants.NAMESPACE)
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# after scale, assert data consistent
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assert utility.has_collection(c_name)
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assert collection_w.num_entities == ct.default_nb
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# assert new operations
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new_cname = cf.gen_unique_str(prefix)
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new_collection_w = ApiCollectionWrapper()
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new_collection_w.init_collection(name=new_cname, schema=cf.gen_default_collection_schema())
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new_mutation_res, _ = new_collection_w.insert(data)
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assert new_mutation_res.insert_count == ct.default_nb
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assert new_collection_w.num_entities == ct.default_nb
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# assert old collection ddl
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mutation_res_2, _ = collection_w.insert(data)
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assert mutation_res.insert_count == ct.default_nb
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assert collection_w.num_entities == ct.default_nb*2
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collection_w.drop()
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new_collection_w.drop()
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# milvusOp.uninstall(release_name, namespace=constants.NAMESPACE)
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@pytest.mark.tags(CaseLabel.L3)
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def test_shrink_data_node(self):
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"""
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target: test shrink dataNode from 2 to 1
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method: 1.create collection and insert df 2. shrink dataNode 3.insert df
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expected: verify the property of collection which channel on shrink pod
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"""
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release_name = "scale-data"
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env = HelmEnv(release_name=release_name, dataNode=2)
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host = env.helm_install_cluster_milvus(image_pull_policy=constants.IF_NOT_PRESENT)
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image = f'{constants.IMAGE_REPOSITORY}:{constants.IMAGE_TAG}'
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data_config = {
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'metadata.namespace': constants.NAMESPACE,
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'metadata.name': release_name,
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'spec.components.image': image,
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'spec.components.proxy.serviceType': 'LoadBalancer',
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'spec.components.dataNode.replicas': 2,
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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(data_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 = '10.98.0.4'
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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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c_name = "data_scale_one"
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data = cf.gen_default_list_data(ct.default_nb)
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# create
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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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mutation_res, _ = collection_w.insert(data)
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assert mutation_res.insert_count == ct.default_nb
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assert collection_w.num_entities == ct.default_nb
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collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema(), shards_num=5)
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c_name_2 = "data_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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mutation_res2, _ = collection_w2.insert(data)
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assert mutation_res2.insert_count == ct.default_nb
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assert collection_w2.num_entities == ct.default_nb
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tmp_nb = 10000
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env.helm_upgrade_cluster_milvus(dataNode=1)
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def do_insert():
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while True:
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tmp_df = cf.gen_default_dataframe_data(tmp_nb)
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collection_w.insert(tmp_df)
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log.debug(collection_w.num_entities)
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assert collection_w.num_entities == ct.default_nb
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mutation_res2, _ = collection_w2.insert(data)
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assert collection_w2.num_entities == ct.default_nb*2
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collection_w.drop()
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collection_w2.drop()
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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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# env.helm_uninstall_cluster_milvus()
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# scale dataNode to 5
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mic.upgrade(release_name, {'spec.components.dataNode.replicas': 5}, constants.NAMESPACE)
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time.sleep(300)
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log.debug("Expand dataNode test finished")
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# create new collection and insert
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new_c_name = cf.gen_unique_str("scale_query")
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collection_w_new = ApiCollectionWrapper()
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collection_w_new.init_collection(name=new_c_name, schema=cf.gen_default_collection_schema(), shards_num=2)
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def do_new_insert():
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while True:
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tmp_df = cf.gen_default_dataframe_data(tmp_nb)
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collection_w_new.insert(tmp_df)
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log.debug(collection_w_new.num_entities)
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t_insert_new = threading.Thread(target=do_new_insert, args=(), daemon=True)
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t_insert_new.start()
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# scale dataNode to 3
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mic.upgrade(release_name, {'spec.components.dataNode.replicas': 3}, constants.NAMESPACE)
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wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
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log.debug(collection_w.num_entities)
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time.sleep(300)
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log.debug("Shrink dataNode test finished")
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# mic.uninstall(release_name, namespace=constants.NAMESPACE)
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