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126 lines
5.0 KiB
Python
126 lines
5.0 KiB
Python
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 customize.milvus_operator import MilvusOperator
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from scale import constants, scale_common
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from pymilvus import connections, MilvusException
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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, read_pod_log
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from utils.util_pymilvus import get_latest_tag
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from utils.wrapper import counter
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class TestDataNodeScale:
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@pytest.mark.tags(CaseLabel.L3)
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def test_scale_data_node(self):
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"""
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target: test scale dataNode
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method: 1.deploy milvus cluster with 2 dataNode
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2.create collection with shards_num=5
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3.continuously insert new data (daemon thread)
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4.expand dataNode from 2 to 5
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5.create new collection with shards_num=2
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6.continuously insert new collection new data (daemon thread)
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7.shrink dataNode from 5 to 3
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expected: Verify milvus remains healthy, Insert and flush successfully during scale
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Average dataNode memory usage
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"""
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release_name = "scale-data"
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image_tag = get_latest_tag()
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image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
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data_config = {
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'metadata.namespace': constants.NAMESPACE,
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'spec.mode': 'cluster',
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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.common.retentionDuration': 60
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}
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mic = MilvusOperator()
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mic.install(data_config)
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if mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1800):
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host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
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else:
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raise MilvusException(message=f'Milvus healthy timeout 1800s')
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try:
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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("scale_data")
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collection_w = ApiCollectionWrapper()
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collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema(), shards_num=4)
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tmp_nb = 10000
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@counter
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def do_insert():
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""" do insert and flush """
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insert_res, is_succ = collection_w.insert(cf.gen_default_dataframe_data(tmp_nb))
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log.debug(collection_w.num_entities)
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return insert_res, is_succ
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def loop_insert():
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""" loop do insert """
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while True:
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do_insert()
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threading.Thread(target=loop_insert, args=(), daemon=True).start()
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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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mic.wait_for_healthy(release_name, constants.NAMESPACE)
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wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
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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_data")
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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=3)
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@counter
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def do_new_insert():
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""" do new insert """
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insert_res, is_succ = collection_w_new.insert(cf.gen_default_dataframe_data(tmp_nb))
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log.debug(collection_w_new.num_entities)
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return insert_res, is_succ
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def loop_new_insert():
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""" loop new insert """
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while True:
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do_new_insert()
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threading.Thread(target=loop_new_insert, args=(), daemon=True).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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mic.wait_for_healthy(release_name, 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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scale_common.check_succ_rate(do_insert)
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scale_common.check_succ_rate(do_new_insert)
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log.debug("Shrink dataNode test finished")
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except Exception as e:
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log.error(str(e))
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# raise Exception(str(e))
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finally:
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label = f"app.kubernetes.io/instance={release_name}"
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log.info('Start to export milvus pod logs')
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read_pod_log(namespace=constants.NAMESPACE, label_selector=label, release_name=release_name)
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mic.uninstall(release_name, namespace=constants.NAMESPACE)
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