mirror of https://github.com/milvus-io/milvus.git
513 lines
26 KiB
Python
513 lines
26 KiB
Python
import pytest
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import sys
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from typing import Dict, List
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from pymilvus import DefaultConfig
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from base.database_wrapper import ApiDatabaseWrapper
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sys.path.append("..")
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from base.connections_wrapper import ApiConnectionsWrapper
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from base.collection_wrapper import ApiCollectionWrapper
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from base.partition_wrapper import ApiPartitionWrapper
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from base.index_wrapper import ApiIndexWrapper
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from base.utility_wrapper import ApiUtilityWrapper
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from base.schema_wrapper import ApiCollectionSchemaWrapper, ApiFieldSchemaWrapper
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from base.async_milvus_client_wrapper import AsyncMilvusClientWrapper
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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 common.common_params import IndexPrams
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from pymilvus import ResourceGroupInfo, DataType, utility
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import pymilvus
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class Base:
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""" Initialize class object """
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connection_wrap = None
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collection_wrap = None
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partition_wrap = None
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index_wrap = None
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utility_wrap = None
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collection_schema_wrap = None
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field_schema_wrap = None
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database_wrap = None
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tear_down_collection_names = []
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resource_group_list = []
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async_milvus_client_wrap = None
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skip_connection = False
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def setup_class(self):
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log.info("[setup_class] Start setup class...")
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def teardown_class(self):
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log.info("[teardown_class] Start teardown class...")
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def setup_method(self, method):
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log.info(("*" * 35) + " setup " + ("*" * 35))
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log.info(f"pymilvus version: {pymilvus.__version__}")
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log.info("[setup_method] Start setup test case %s." % method.__name__)
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self._setup_objects()
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def _setup_objects(self):
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self.connection_wrap = ApiConnectionsWrapper()
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self.utility_wrap = ApiUtilityWrapper()
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self.collection_wrap = ApiCollectionWrapper()
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self.partition_wrap = ApiPartitionWrapper()
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self.index_wrap = ApiIndexWrapper()
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self.collection_schema_wrap = ApiCollectionSchemaWrapper()
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self.field_schema_wrap = ApiFieldSchemaWrapper()
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self.database_wrap = ApiDatabaseWrapper()
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self.async_milvus_client_wrap = AsyncMilvusClientWrapper()
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def teardown_method(self, method):
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log.info(("*" * 35) + " teardown " + ("*" * 35))
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log.info("[teardown_method] Start teardown test case %s..." % method.__name__)
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self._teardown_objects()
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def _teardown_objects(self):
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try:
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""" Drop collection before disconnect """
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if not self.connection_wrap.has_connection(alias=DefaultConfig.DEFAULT_USING)[0]:
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self.connection_wrap.connect(alias=DefaultConfig.DEFAULT_USING, host=cf.param_info.param_host,
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port=cf.param_info.param_port, user=ct.default_user,
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password=ct.default_password)
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if self.collection_wrap.collection is not None:
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if self.collection_wrap.collection.name.startswith("alias"):
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log.info(f"collection {self.collection_wrap.collection.name} is alias, skip drop operation")
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else:
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self.collection_wrap.drop(check_task=ct.CheckTasks.check_nothing)
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collection_list = self.utility_wrap.list_collections()[0]
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for collection_name in self.tear_down_collection_names:
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if collection_name is not None and collection_name in collection_list:
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self.collection_wrap.init_collection(name=collection_name)[0].drop()
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""" Clean up the rgs before disconnect """
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rgs_list = self.utility_wrap.list_resource_groups()[0]
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for rg_name in self.resource_group_list:
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if rg_name is not None and rg_name in rgs_list:
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rg = self.utility_wrap.describe_resource_group(
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name=rg_name, check_task=ct.CheckTasks.check_nothing)[0]
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if isinstance(rg, ResourceGroupInfo):
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if rg.num_available_node > 0:
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self.utility_wrap.transfer_node(source=rg_name,
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target=ct.default_resource_group_name,
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num_node=rg.num_available_node)
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self.utility_wrap.drop_resource_group(rg_name, check_task=ct.CheckTasks.check_nothing)
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except Exception as e:
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log.debug(str(e))
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try:
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""" Drop roles before disconnect """
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if not self.connection_wrap.has_connection(alias=DefaultConfig.DEFAULT_USING)[0]:
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self.connection_wrap.connect(alias=DefaultConfig.DEFAULT_USING, host=cf.param_info.param_host,
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port=cf.param_info.param_port, user=ct.default_user,
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password=ct.default_password)
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role_list = self.utility_wrap.list_roles(False)[0]
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for role in role_list.groups:
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role_name = role.role_name
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if role_name not in ["admin", "public"]:
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each_role = self.utility_wrap.init_role(name=role_name)[0]
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each_role.drop()
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except Exception as e:
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log.debug(str(e))
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try:
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""" Delete connection and reset configuration"""
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res = self.connection_wrap.list_connections()
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for i in res[0]:
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self.connection_wrap.remove_connection(i[0])
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# because the connection is in singleton mode, it needs to be restored to the original state after teardown
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self.connection_wrap.add_connection(default={"host": DefaultConfig.DEFAULT_HOST,
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"port": DefaultConfig.DEFAULT_PORT})
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except Exception as e:
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log.debug(str(e))
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class TestcaseBase(Base):
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"""
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Additional methods;
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Public methods that can be used for test cases.
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"""
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def _connect(self, enable_milvus_client_api=False):
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""" Add a connection and create the connect """
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if self.skip_connection:
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return None
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if enable_milvus_client_api:
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if cf.param_info.param_uri:
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uri = cf.param_info.param_uri
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else:
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uri = "http://" + cf.param_info.param_host + ":" + str(cf.param_info.param_port)
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self.connection_wrap.connect(alias=DefaultConfig.DEFAULT_USING,uri=uri,token=cf.param_info.param_token)
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res, is_succ = self.connection_wrap.MilvusClient(uri=uri,
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token=cf.param_info.param_token)
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else:
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if cf.param_info.param_user and cf.param_info.param_password:
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res, is_succ = self.connection_wrap.connect(alias=DefaultConfig.DEFAULT_USING,
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host=cf.param_info.param_host,
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port=cf.param_info.param_port,
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user=cf.param_info.param_user,
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password=cf.param_info.param_password,
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secure=cf.param_info.param_secure)
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else:
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res, is_succ = self.connection_wrap.connect(alias=DefaultConfig.DEFAULT_USING,
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host=cf.param_info.param_host,
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port=cf.param_info.param_port)
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server_version = utility.get_server_version()
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log.info(f"server version: {server_version}")
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return res
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# def init_async_milvus_client(self):
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# uri = cf.param_info.param_uri or f"http://{cf.param_info.param_host}:{cf.param_info.param_port}"
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# kwargs = {
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# "uri": uri,
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# "user": cf.param_info.param_user,
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# "password": cf.param_info.param_password,
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# "token": cf.param_info.param_token,
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# }
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# self.async_milvus_client_wrap.init_async_client(**kwargs)
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def init_collection_wrap(self, name=None, schema=None, check_task=None, check_items=None,
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enable_dynamic_field=False, with_json=True, **kwargs):
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name = cf.gen_unique_str('coll_') if name is None else name
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schema = cf.gen_default_collection_schema(enable_dynamic_field=enable_dynamic_field, with_json=with_json) \
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if schema is None else schema
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if not self.connection_wrap.has_connection(alias=DefaultConfig.DEFAULT_USING)[0]:
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self._connect()
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collection_w = ApiCollectionWrapper()
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collection_w.init_collection(name=name, schema=schema, check_task=check_task,
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check_items=check_items, **kwargs)
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self.tear_down_collection_names.append(name)
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return collection_w
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def init_multi_fields_collection_wrap(self, name=cf.gen_unique_str()):
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vec_fields = [cf.gen_float_vec_field(ct.another_float_vec_field_name)]
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schema = cf.gen_schema_multi_vector_fields(vec_fields)
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collection_w = self.init_collection_wrap(name=name, schema=schema)
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df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields)
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collection_w.insert(df)
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assert collection_w.num_entities == ct.default_nb
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return collection_w, df
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def init_partition_wrap(self, collection_wrap=None, name=None, description=None,
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check_task=None, check_items=None, **kwargs):
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name = cf.gen_unique_str("partition_") if name is None else name
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description = cf.gen_unique_str("partition_des_") if description is None else description
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collection_wrap = self.init_collection_wrap() if collection_wrap is None else collection_wrap
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partition_wrap = ApiPartitionWrapper()
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partition_wrap.init_partition(collection_wrap.collection, name, description,
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check_task=check_task, check_items=check_items,
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**kwargs)
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return partition_wrap
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def insert_data_general(self, prefix="test", insert_data=False, nb=ct.default_nb,
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partition_num=0, is_binary=False, is_all_data_type=False,
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auto_id=False, dim=ct.default_dim,
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primary_field=ct.default_int64_field_name, is_flush=True, name=None,
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enable_dynamic_field=False, with_json=True, **kwargs):
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"""
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"""
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self._connect()
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collection_name = cf.gen_unique_str(prefix)
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if name is not None:
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collection_name = name
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vectors = []
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binary_raw_vectors = []
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insert_ids = []
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time_stamp = 0
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# 1 create collection
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default_schema = cf.gen_default_collection_schema(auto_id=auto_id, dim=dim, primary_field=primary_field,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json)
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if is_binary:
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default_schema = cf.gen_default_binary_collection_schema(auto_id=auto_id, dim=dim,
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primary_field=primary_field)
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if is_all_data_type:
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default_schema = cf.gen_collection_schema_all_datatype(auto_id=auto_id, dim=dim,
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primary_field=primary_field,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json)
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log.info("insert_data_general: collection creation")
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collection_w = self.init_collection_wrap(name=collection_name, schema=default_schema, **kwargs)
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pre_entities = collection_w.num_entities
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if insert_data:
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collection_w, vectors, binary_raw_vectors, insert_ids, time_stamp = \
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cf.insert_data(collection_w, nb, is_binary, is_all_data_type, auto_id=auto_id, dim=dim,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json)
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if is_flush:
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collection_w.flush()
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assert collection_w.num_entities == nb + pre_entities
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return collection_w, vectors, binary_raw_vectors, insert_ids, time_stamp
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def init_collection_general(self, prefix="test", insert_data=False, nb=ct.default_nb,
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partition_num=0, is_binary=False, is_all_data_type=False,
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auto_id=False, dim=ct.default_dim, is_index=True,
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primary_field=ct.default_int64_field_name, is_flush=True, name=None,
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enable_dynamic_field=False, with_json=True, random_primary_key=False,
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multiple_dim_array=[], is_partition_key=None, vector_data_type="FLOAT_VECTOR",
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nullable_fields={}, default_value_fields={}, language=None, **kwargs):
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"""
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target: create specified collections
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method: 1. create collections (binary/non-binary, default/all data type, auto_id or not)
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2. create partitions if specified
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3. insert specified (binary/non-binary, default/all data type) data
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into each partition if any
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4. not load if specifying is_index as True
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5. enable insert null data: nullable_fields = {"nullable_fields_name": null data percent}
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6. enable insert default value: default_value_fields = {"default_fields_name": default value}
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expected: return collection and raw data, insert ids
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"""
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log.info("Test case of search interface: initialize before test case")
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if not self.connection_wrap.has_connection(alias=DefaultConfig.DEFAULT_USING)[0]:
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self._connect()
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collection_name = cf.gen_unique_str(prefix)
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if name is not None:
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collection_name = name
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if not isinstance(nullable_fields, dict):
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log.error("nullable_fields should a dict like {'nullable_fields_name': null data percent}")
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assert False
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if not isinstance(default_value_fields, dict):
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log.error("default_value_fields should a dict like {'default_fields_name': default value}")
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assert False
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vectors = []
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binary_raw_vectors = []
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insert_ids = []
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time_stamp = 0
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# 1 create collection
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default_schema = cf.gen_default_collection_schema(auto_id=auto_id, dim=dim, primary_field=primary_field,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json, multiple_dim_array=multiple_dim_array,
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is_partition_key=is_partition_key,
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vector_data_type=vector_data_type,
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nullable_fields=nullable_fields,
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default_value_fields=default_value_fields)
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if is_binary:
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default_schema = cf.gen_default_binary_collection_schema(auto_id=auto_id, dim=dim,
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primary_field=primary_field,
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nullable_fields=nullable_fields,
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default_value_fields=default_value_fields)
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if vector_data_type == ct.sparse_vector:
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default_schema = cf.gen_default_sparse_schema(auto_id=auto_id, primary_field=primary_field,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json,
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multiple_dim_array=multiple_dim_array,
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nullable_fields=nullable_fields,
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default_value_fields=default_value_fields)
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if is_all_data_type:
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default_schema = cf.gen_collection_schema_all_datatype(auto_id=auto_id, dim=dim,
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primary_field=primary_field,
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enable_dynamic_field=enable_dynamic_field,
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with_json=with_json,
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multiple_dim_array=multiple_dim_array,
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nullable_fields=nullable_fields,
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default_value_fields=default_value_fields)
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log.info("init_collection_general: collection creation")
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collection_w = self.init_collection_wrap(name=collection_name, schema=default_schema, **kwargs)
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vector_name_list = cf.extract_vector_field_name_list(collection_w)
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# 2 add extra partitions if specified (default is 1 partition named "_default")
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if partition_num > 0:
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cf.gen_partitions(collection_w, partition_num)
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# 3 insert data if specified
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if insert_data:
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collection_w, vectors, binary_raw_vectors, insert_ids, time_stamp = \
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cf.insert_data(collection_w, nb, is_binary, is_all_data_type, auto_id=auto_id,
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dim=dim, enable_dynamic_field=enable_dynamic_field, with_json=with_json,
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random_primary_key=random_primary_key, multiple_dim_array=multiple_dim_array,
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primary_field=primary_field, vector_data_type=vector_data_type,
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nullable_fields=nullable_fields, language=language)
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if is_flush:
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assert collection_w.is_empty is False
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assert collection_w.num_entities == nb
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# 4 create default index if specified
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if is_index:
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# This condition will be removed after auto index feature
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if is_binary:
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collection_w.create_index(ct.default_binary_vec_field_name, ct.default_bin_flat_index)
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elif vector_data_type == ct.sparse_vector:
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for vector_name in vector_name_list:
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collection_w.create_index(vector_name, ct.default_sparse_inverted_index)
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else:
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if len(multiple_dim_array) == 0 or is_all_data_type is False:
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vector_name_list.append(ct.default_float_vec_field_name)
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for vector_name in vector_name_list:
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# Unlike dense vectors, sparse vectors cannot create flat index.
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if ct.sparse_vector in vector_name:
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collection_w.create_index(vector_name, ct.default_sparse_inverted_index)
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else:
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collection_w.create_index(vector_name, ct.default_flat_index)
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collection_w.load()
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return collection_w, vectors, binary_raw_vectors, insert_ids, time_stamp
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def insert_entities_into_two_partitions_in_half(self, half, prefix='query'):
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"""
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insert default entities into two partitions(partition_w and _default) in half(int64 and float fields values)
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:param half: half of nb
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:return: collection wrap and partition wrap
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"""
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self._connect()
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collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix))
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partition_w = self.init_partition_wrap(collection_wrap=collection_w)
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# insert [0, half) into partition_w
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df_partition = cf.gen_default_dataframe_data(nb=half, start=0)
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partition_w.insert(df_partition)
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# insert [half, nb) into _default
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df_default = cf.gen_default_dataframe_data(nb=half, start=half)
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collection_w.insert(df_default)
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# flush
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collection_w.num_entities
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collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
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collection_w.load(partition_names=[partition_w.name, "_default"])
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return collection_w, partition_w, df_partition, df_default
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def collection_insert_multi_segments_one_shard(self, collection_prefix, num_of_segment=2, nb_of_segment=1,
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is_dup=True):
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"""
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init collection with one shard, insert data into two segments on one shard (they can be merged)
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:param collection_prefix: collection name prefix
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:param num_of_segment: number of segments
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:param nb_of_segment: number of entities per segment
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:param is_dup: whether the primary keys of each segment is duplicated
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:return: collection wrap and partition wrap
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"""
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collection_w = self.init_collection_wrap(name=cf.gen_unique_str(collection_prefix), shards_num=1)
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for i in range(num_of_segment):
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start = 0 if is_dup else i * nb_of_segment
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df = cf.gen_default_dataframe_data(nb_of_segment, start=start)
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collection_w.insert(df)
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assert collection_w.num_entities == nb_of_segment * (i + 1)
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return collection_w
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def init_resource_group(self, name, using="default", timeout=None, check_task=None, check_items=None, **kwargs):
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if not self.connection_wrap.has_connection(alias=DefaultConfig.DEFAULT_USING)[0]:
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self._connect()
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utility_w = ApiUtilityWrapper()
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res, check_result = utility_w.create_resource_group(name=name, using=using, timeout=timeout,
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check_task=check_task,
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check_items=check_items, **kwargs)
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if res is None and check_result:
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self.resource_group_list.append(name)
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return res, check_result
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def init_user_with_privilege(self, privilege_object, object_name, privilege, db_name="default"):
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"""
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init a user and role, grant privilege to the role with the db, then bind the role to the user
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:param privilege_object: privilege object: Global, Collection, User
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:type privilege_object: str
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|
:param object_name: privilege object name
|
|
:type object_name: str
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|
:param privilege: privilege
|
|
:type privilege: str
|
|
:param db_name: database name
|
|
:type db_name: str
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|
:return: user name, user pwd, role name
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|
:rtype: str, str, str
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|
"""
|
|
tmp_user = cf.gen_unique_str("user")
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|
tmp_pwd = cf.gen_unique_str("pwd")
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|
tmp_role = cf.gen_unique_str("role")
|
|
|
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# create user
|
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self.utility_wrap.create_user(tmp_user, tmp_pwd)
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|
|
|
# create role
|
|
self.utility_wrap.init_role(tmp_role)
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|
self.utility_wrap.create_role()
|
|
|
|
# grant privilege to the role
|
|
self.utility_wrap.role_grant(object=privilege_object, object_name=object_name, privilege=privilege,
|
|
db_name=db_name)
|
|
|
|
# bind the role to the user
|
|
self.utility_wrap.role_add_user(tmp_user)
|
|
|
|
return tmp_user, tmp_pwd, tmp_role
|
|
|
|
def build_multi_index(self, index_params: Dict[str, IndexPrams], collection_obj: ApiCollectionWrapper = None):
|
|
collection_obj = collection_obj or self.collection_wrap
|
|
for k, v in index_params.items():
|
|
collection_obj.create_index(field_name=k, index_params=v.to_dict, index_name=k)
|
|
log.info(f"[TestcaseBase] Build all indexes done: {list(index_params.keys())}")
|
|
return collection_obj
|
|
|
|
def drop_multi_index(self, index_names: List[str], collection_obj: ApiCollectionWrapper = None,
|
|
check_task=None, check_items=None):
|
|
collection_obj = collection_obj or self.collection_wrap
|
|
for n in index_names:
|
|
collection_obj.drop_index(index_name=n, check_task=check_task, check_items=check_items)
|
|
log.info(f"[TestcaseBase] Drop all indexes done: {index_names}")
|
|
return collection_obj
|
|
|
|
def show_indexes(self, collection_obj: ApiCollectionWrapper = None):
|
|
collection_obj = collection_obj or self.collection_wrap
|
|
indexes = {n.field_name: n.params for n in self.collection_wrap.indexes}
|
|
log.info("[TestcaseBase] Collection: `{0}` index: {1}".format(collection_obj.name, indexes))
|
|
return indexes
|
|
|
|
""" Property """
|
|
|
|
@property
|
|
def all_scalar_fields(self):
|
|
dtypes = [DataType.INT8, DataType.INT16, DataType.INT32, DataType.INT64, DataType.VARCHAR, DataType.BOOL,
|
|
DataType.FLOAT, DataType.DOUBLE]
|
|
dtype_names = [f"{n.name}" for n in dtypes] + [f"ARRAY_{n.name}" for n in dtypes] + [DataType.JSON.name]
|
|
return dtype_names
|
|
|
|
@property
|
|
def all_index_scalar_fields(self):
|
|
return list(set(self.all_scalar_fields) - {DataType.JSON.name})
|
|
|
|
@property
|
|
def inverted_support_dtype_names(self):
|
|
return self.all_index_scalar_fields
|
|
|
|
@property
|
|
def inverted_not_support_dtype_names(self):
|
|
return [DataType.JSON.name]
|
|
|
|
@property
|
|
def bitmap_support_dtype_names(self):
|
|
dtypes = [DataType.INT8, DataType.INT16, DataType.INT32, DataType.INT64, DataType.BOOL, DataType.VARCHAR]
|
|
dtype_names = [f"{n.name}" for n in dtypes] + [f"ARRAY_{n.name}" for n in dtypes]
|
|
return dtype_names
|
|
|
|
@property
|
|
def bitmap_not_support_dtype_names(self):
|
|
return list(set(self.all_scalar_fields) - set(self.bitmap_support_dtype_names))
|
|
|
|
|
|
class TestCaseClassBase(TestcaseBase):
|
|
"""
|
|
Setup objects on class
|
|
"""
|
|
|
|
def setup_class(self):
|
|
log.info("[setup_class] " + " Start setup class ".center(100, "~"))
|
|
self._setup_objects(self)
|
|
|
|
def teardown_class(self):
|
|
log.info("[teardown_class]" + " Start teardown class ".center(100, "~"))
|
|
self._teardown_objects(self)
|
|
|
|
def setup_method(self, method):
|
|
log.info(" setup ".center(80, "*"))
|
|
log.info("[setup_method] Start setup test case %s." % method.__name__)
|
|
|
|
def teardown_method(self, method):
|
|
log.info(" teardown ".center(80, "*"))
|
|
log.info("[teardown_method] Start teardown test case %s..." % method.__name__)
|