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105 lines
4.3 KiB
Python
105 lines
4.3 KiB
Python
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 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 scale.helm_env import HelmEnv
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from pymilvus import connections, utility
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prefix = "data_scale"
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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 TestDataNodeScale:
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@pytest.mark.tags(CaseLabel.L3)
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def test_expand_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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"""
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# deploy all nodes one pod cluster milvus with helm
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release_name = "scale-data"
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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 = 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(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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# scale dataNode to 2 pods
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env.helm_upgrade_cluster_milvus(dataNode=2)
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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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# env.helm_uninstall_cluster_milvus()
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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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# 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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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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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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env.helm_upgrade_cluster_milvus(dataNode=1)
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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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# env.helm_uninstall_cluster_milvus()
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