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ba862ef91d
1. modify test case: test_search_repeatedly_ivf_index_different_limit 2. update pymilvus version from 2.4.0rc19 to 2.4.0rc24 3. Before, insert will return a pk list. In the latest milvus client, insert will return a number that is inserted successfully 4. In the latest milvus client, flush and num_entities have been removed 5. Before, the default consistency level of a new collection is strong. In the latest milvus client, it becomes bounded. So related cases have been modified correspondingly, or immediate search after insert will return no results. 6. In the latest pymilvus, new data type FLOAT16_VECTOR and BFLOAT16_VECTOR have been added. Signed-off-by: nico <cheng.yuan@zilliz.com>
4497 lines
209 KiB
Python
4497 lines
209 KiB
Python
import random
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import numpy
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import pandas as pd
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import pytest
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from pymilvus import DataType
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from base.client_base import TestcaseBase
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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_type import CaseLabel, CheckTasks
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from utils.util_pymilvus import *
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from utils.util_log import test_log as log
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prefix = "collection"
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exp_name = "name"
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exp_schema = "schema"
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exp_num = "num_entities"
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exp_primary = "primary"
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exp_shards_num = "shards_num"
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default_term_expr = f'{ct.default_int64_field_name} in [0, 1]'
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default_schema = cf.gen_default_collection_schema()
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default_binary_schema = cf.gen_default_binary_collection_schema()
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default_shards_num = 1
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uid_count = "collection_count"
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tag = "collection_count_tag"
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uid_stats = "get_collection_stats"
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uid_create = "create_collection"
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uid_describe = "describe_collection"
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uid_drop = "drop_collection"
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uid_has = "has_collection"
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uid_list = "list_collections"
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uid_load = "load_collection"
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partition1 = 'partition1'
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partition2 = 'partition2'
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field_name = default_float_vec_field_name
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default_single_query = {
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"data": gen_vectors(1, default_dim),
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"anns_field": default_float_vec_field_name,
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"param": {"metric_type": "L2", "params": {"nprobe": 10}},
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"limit": default_top_k,
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}
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default_index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params": {"nlist": 64}}
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default_binary_index_params = {"index_type": "BIN_IVF_FLAT", "metric_type": "JACCARD", "params": {"nlist": 64}}
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default_nq = ct.default_nq
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default_search_exp = "int64 >= 0"
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default_limit = ct.default_limit
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vectors = [[random.random() for _ in range(default_dim)] for _ in range(default_nq)]
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default_search_field = ct.default_float_vec_field_name
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default_search_params = ct.default_search_params
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max_vector_field_num = ct.max_vector_field_num
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class TestCollectionParams(TestcaseBase):
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""" Test case of collection interface """
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@pytest.fixture(scope="function", params=ct.get_invalid_strs)
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def get_none_removed_invalid_strings(self, request):
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if request.param is None:
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pytest.skip("None schema is valid")
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yield request.param
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@pytest.fixture(scope="function", params=ct.get_invalid_type_fields)
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def get_invalid_type_fields(self, request):
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if isinstance(request.param, list):
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pytest.skip("list is valid fields")
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yield request.param
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@pytest.fixture(scope="function", params=cf.gen_all_type_fields())
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def get_unsupported_primary_field(self, request):
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if request.param.dtype == DataType.INT64 or request.param.dtype == DataType.VARCHAR:
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pytest.skip("int64 type is valid primary key")
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yield request.param
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@pytest.fixture(scope="function", params=ct.get_invalid_strs)
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def get_invalid_dim(self, request):
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if request.param == 1:
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pytest.skip("1 is valid dim")
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yield request.param
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@pytest.mark.tags(CaseLabel.L0)
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def test_collection(self):
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"""
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target: test collection with default schema
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method: create collection with default schema
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expected: assert collection property
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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self.collection_wrap.init_collection(c_name, schema=default_schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema, exp_num: 0,
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exp_primary: ct.default_int64_field_name})
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assert c_name in self.utility_wrap.list_collections()[0]
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_empty_name(self):
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"""
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target: test collection with empty name
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method: create collection with an empty name
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expected: raise exception
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"""
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self._connect()
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c_name = ""
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error = {ct.err_code: 1, ct.err_msg: f'`collection_name` value is illegal'}
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self.collection_wrap.init_collection(c_name, schema=default_schema, check_task=CheckTasks.err_res,
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check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name", [[], 1, [1, "2", 3], (1,), {1: 1}, "qw$_o90", "1ns_", None])
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def test_collection_illegal_name(self, name):
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"""
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target: test collection with illegal name
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method: create collection with illegal name
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expected: raise exception
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"""
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self._connect()
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error1 = {ct.err_code: 1, ct.err_msg: "`collection_name` value {} is illegal".format(name)}
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error2 = {ct.err_code: 1100, ct.err_msg: "Invalid collection name: 1ns_. the first character of a"
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" collection name must be an underscore or letter: invalid"
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" parameter".format(name)}
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error = error1 if name not in ["1ns_", "qw$_o90"] else error2
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self.collection_wrap.init_collection(name, schema=default_schema, check_task=CheckTasks.err_res,
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check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name", ["_co11ection", "co11_ection"])
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def test_collection_naming_rules(self, name):
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"""
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target: test collection with valid name
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method: 1. connect milvus
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2. Create a field with a name which uses all the supported elements in the naming rules
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3. Create a collection with a name which uses all the supported elements in the naming rules
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expected: Collection created successfully
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"""
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self._connect()
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fields = [cf.gen_int64_field(), cf.gen_int64_field("_1nt"), cf.gen_float_vec_field("f10at_")]
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schema = cf.gen_collection_schema(fields=fields, primary_field=ct.default_int64_field_name)
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self.collection_wrap.init_collection(name, schema=schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: name, exp_schema: schema})
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name", ["12-s", "12 s", "(mn)", "中文", "%$#", "".join("a" for i in range(ct.max_name_length + 1))])
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def test_collection_invalid_name(self, name):
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"""
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target: test collection with invalid name
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method: create collection with invalid name
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expected: raise exception
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"""
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self._connect()
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error = {ct.err_code: 1, ct.err_msg: "Invalid collection name: {}".format(name)}
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self.collection_wrap.init_collection(name, schema=default_schema, check_task=CheckTasks.err_res,
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check_items=error)
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@pytest.mark.tags(CaseLabel.L0)
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def test_collection_dup_name(self):
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"""
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target: test collection with dup name
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method: create collection with dup name and none schema and data
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expected: collection properties consistent
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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self.collection_wrap.init_collection(collection_w.name)
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assert collection_w.name == self.collection_wrap.name
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assert collection_w.schema == self.collection_wrap.schema
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assert collection_w.num_entities == self.collection_wrap.num_entities
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assert collection_w.name in self.utility_wrap.list_collections()[0]
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_dup_name_with_desc(self):
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"""
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target: test collection with dup name
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method: 1. default schema with desc 2. dup name collection
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expected: desc consistent
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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schema = cf.gen_default_collection_schema(description=ct.collection_desc)
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collection_w = self.init_collection_wrap(name=c_name, schema=schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})
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self.collection_wrap.init_collection(c_name,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})
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assert collection_w.description == self.collection_wrap.description
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@pytest.mark.tags(CaseLabel.L1)
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def test_collection_dup_name_new_schema(self):
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"""
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target: test collection with dup name and new schema
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method: 1.create collection with default schema
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2. collection with dup name and new schema
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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fields = [cf.gen_int64_field(is_primary=True)]
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schema = cf.gen_collection_schema(fields=fields)
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error = {ct.err_code: 0, ct.err_msg: "The collection already exist, but the schema is not the same as the "
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"schema passed in."}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_dup_name_new_primary(self):
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"""
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target: test collection with dup name and new primary_field schema
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method: 1.collection with default schema
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2. collection with same fields and new primary_field schema
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_field_one = cf.gen_int64_field()
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int_field_two = cf.gen_int64_field(name="int2")
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fields = [int_field_one, int_field_two, cf.gen_float_vec_field()]
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schema = cf.gen_collection_schema(fields, primary_field=int_field_one.name)
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collection_w = self.init_collection_wrap(name=c_name, schema=schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema,
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exp_primary: int_field_one.name})
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new_schema = cf.gen_collection_schema(fields, primary_field=int_field_two.name)
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error = {ct.err_code: 0, ct.err_msg: "The collection already exist, but the schema is not the same as the "
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"schema passed in."}
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self.collection_wrap.init_collection(c_name, schema=new_schema, check_task=CheckTasks.err_res,
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check_items=error)
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assert collection_w.primary_field.name == int_field_one.name
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@pytest.mark.tags(CaseLabel.L1)
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def test_collection_dup_name_new_dim(self):
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"""
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target: test collection with dup name and new dim schema
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method: 1. default schema 2. schema with new dim
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expected: raise exception
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"""
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self._connect()
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new_dim = 120
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c_name = cf.gen_unique_str(prefix)
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collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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schema = cf.gen_default_collection_schema()
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new_fields = cf.gen_float_vec_field(dim=new_dim)
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schema.fields[-1] = new_fields
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error = {ct.err_code: 0, ct.err_msg: "The collection already exist, but the schema is not the same as the "
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"schema passed in."}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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dim = collection_w.schema.fields[-1].params['dim']
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assert dim == ct.default_dim
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_dup_name_invalid_schema_type(self, get_none_removed_invalid_strings):
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"""
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target: test collection with dup name and invalid schema
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method: 1. default schema 2. invalid schema
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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error = {ct.err_code: 0, ct.err_msg: "Schema type must be schema.CollectionSchema"}
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schema = get_none_removed_invalid_strings
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self.collection_wrap.init_collection(collection_w.name, schema=schema,
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check_task=CheckTasks.err_res, check_items=error)
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assert collection_w.name == c_name
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@pytest.mark.tags(CaseLabel.L1)
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def test_collection_dup_name_same_schema(self):
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"""
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target: test collection with dup name and same schema
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method: dup name and same schema
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expected: two collection object is available
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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collection_w = self.init_collection_wrap(name=c_name, schema=default_schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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self.collection_wrap.init_collection(name=c_name, schema=default_schema,
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check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: default_schema})
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assert collection_w.name == self.collection_wrap.name
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_none_schema(self):
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"""
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target: test collection with none schema
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method: create collection with none schema
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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error = {ct.err_code: 1, ct.err_msg: "Collection '%s' not exist, or you can pass in schema to create one."}
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self.collection_wrap.init_collection(c_name, schema=None, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_invalid_type_schema(self, get_none_removed_invalid_strings):
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"""
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target: test collection with invalid schema
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method: create collection with non-CollectionSchema type schema
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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error = {ct.err_code: 0, ct.err_msg: "Schema type must be schema.CollectionSchema"}
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self.collection_wrap.init_collection(c_name, schema=get_none_removed_invalid_strings,
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check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_invalid_type_fields(self, get_invalid_type_fields):
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"""
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target: test collection with invalid fields type, non-list
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method: create collection schema with non-list invalid fields
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expected: exception
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"""
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self._connect()
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fields = get_invalid_type_fields
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error = {ct.err_code: 1, ct.err_msg: "The fields of schema must be type list."}
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self.collection_schema_wrap.init_collection_schema(fields=fields,
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check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_with_unknown_type(self):
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"""
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target: test collection with unknown type
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method: create with DataType.UNKNOWN
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expected: raise exception
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"""
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self._connect()
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error = {ct.err_code: 1, ct.err_msg: "Field dtype must be of DataType"}
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self.field_schema_wrap.init_field_schema(name="unknown", dtype=DataType.UNKNOWN,
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check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name", [[], 1, (1,), {1: 1}, "12-s"])
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def test_collection_invalid_type_field(self, name):
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"""
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target: test collection with invalid field name
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method: invalid string name
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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field, _ = self.field_schema_wrap.init_field_schema(name=name, dtype=5, is_primary=True)
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vec_field = cf.gen_float_vec_field()
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schema = cf.gen_collection_schema(fields=[field, vec_field])
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error = {ct.err_code: 1701, ct.err_msg: f"bad argument type for built-in"}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("name", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
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def test_collection_invalid_field_name(self, name):
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"""
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target: test collection with invalid field name
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method: invalid string name
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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field, _ = self.field_schema_wrap.init_field_schema(name=name, dtype=DataType.INT64, is_primary=True)
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vec_field = cf.gen_float_vec_field()
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schema = cf.gen_collection_schema(fields=[field, vec_field])
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error = {ct.err_code: 1, ct.err_msg: "Invalid field name"}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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def test_collection_none_field_name(self):
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"""
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target: test field schema with None name
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method: None field name
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expected: raise exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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field, _ = self.field_schema_wrap.init_field_schema(name=None, dtype=DataType.INT64, is_primary=True)
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schema = cf.gen_collection_schema(fields=[field, cf.gen_float_vec_field()])
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error = {ct.err_code: 1701, ct.err_msg: "field name should not be empty"}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("dtype", [6, [[]], {}, (), "", "a"])
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def test_collection_invalid_field_type(self, dtype):
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"""
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target: test collection with invalid field type
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method: invalid DataType
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expected: raise exception
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"""
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self._connect()
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error = {ct.err_code: 0, ct.err_msg: "Field dtype must be of DataType"}
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self.field_schema_wrap.init_field_schema(name="test", dtype=dtype, is_primary=True,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.xfail(reason="issue #19334")
|
|
def test_collection_field_dtype_float_value(self):
|
|
"""
|
|
target: test collection with float type
|
|
method: create field with float type
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
field, _ = self.field_schema_wrap.init_field_schema(name=ct.default_int64_field_name, dtype=5.0,
|
|
is_primary=True)
|
|
schema = cf.gen_collection_schema(fields=[field, cf.gen_float_vec_field()])
|
|
error = {ct.err_code: 0, ct.err_msg: "Field type must be of DataType!"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_empty_fields(self):
|
|
"""
|
|
target: test collection with empty fields
|
|
method: create collection with fields = []
|
|
expected: exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_schema_wrap.init_collection_schema(fields=[], primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_dup_field(self):
|
|
"""
|
|
target: test collection with dup field name
|
|
method: Two FieldSchema have same name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
field_one = cf.gen_int64_field(is_primary=True)
|
|
field_two = cf.gen_int64_field()
|
|
schema = cf.gen_collection_schema(fields=[field_one, field_two, cf.gen_float_vec_field()])
|
|
error = {ct.err_code: 1, ct.err_msg: "duplicated field name"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
assert not self.utility_wrap.has_collection(c_name)[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
@pytest.mark.parametrize("field", [cf.gen_float_vec_field(), cf.gen_binary_vec_field()])
|
|
def test_collection_only_vector_field(self, field):
|
|
"""
|
|
target: test collection just with vec field
|
|
method: create with float-vec fields
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_schema_wrap.init_collection_schema([field], check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_multi_float_vectors(self):
|
|
"""
|
|
target: test collection with multi float vectors
|
|
method: create collection with two float-vec fields
|
|
expected: Collection created successfully
|
|
"""
|
|
# 1. connect
|
|
self._connect()
|
|
# 2. create collection with multiple vectors
|
|
c_name = cf.gen_unique_str(prefix)
|
|
fields = [cf.gen_int64_field(is_primary=True), cf.gen_float_field(),
|
|
cf.gen_float_vec_field(dim=default_dim), cf.gen_float_vec_field(name="tmp", dim=default_dim)]
|
|
schema = cf.gen_collection_schema(fields=fields)
|
|
self.collection_wrap.init_collection(c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_mix_vectors(self):
|
|
"""
|
|
target: test collection with mix vectors
|
|
method: create with float and binary vec
|
|
expected: Collection created successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
fields = [cf.gen_int64_field(is_primary=True), cf.gen_float_vec_field(), cf.gen_binary_vec_field()]
|
|
schema = cf.gen_collection_schema(fields=fields, auto_id=True)
|
|
self.collection_wrap.init_collection(c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_without_vectors(self):
|
|
"""
|
|
target: test collection without vectors
|
|
method: create collection only with int field
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_collection_schema([cf.gen_int64_field(is_primary=True)])
|
|
error = {ct.err_code: 0, ct.err_msg: "No vector field is found."}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_without_primary_field(self):
|
|
"""
|
|
target: test collection without primary field
|
|
method: no primary field specified in collection schema and fields
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
int_fields, _ = self.field_schema_wrap.init_field_schema(name=ct.default_int64_field_name, dtype=DataType.INT64)
|
|
vec_fields, _ = self.field_schema_wrap.init_field_schema(name=ct.default_float_vec_field_name,
|
|
dtype=DataType.FLOAT_VECTOR, dim=ct.default_dim)
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_schema_wrap.init_collection_schema([int_fields, vec_fields],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_is_primary_false(self):
|
|
"""
|
|
target: test collection with all is_primary false
|
|
method: set all fields if_primary false
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
fields = [cf.gen_int64_field(is_primary=False), cf.gen_float_field(is_primary=False),
|
|
cf.gen_float_vec_field(is_primary=False)]
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_schema_wrap.init_collection_schema(fields, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("is_primary", ct.get_invalid_strs)
|
|
def test_collection_invalid_is_primary(self, is_primary):
|
|
"""
|
|
target: test collection with invalid primary
|
|
method: define field with is_primary=non-bool
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
name = cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 0, ct.err_msg: "Param is_primary must be bool type"}
|
|
self.field_schema_wrap.init_field_schema(name=name, dtype=DataType.INT64, is_primary=is_primary,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_field", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
|
|
def test_collection_invalid_primary_field(self, primary_field):
|
|
"""
|
|
target: test collection with invalid primary_field
|
|
method: specify invalid string primary_field in collection schema
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
fields = [cf.gen_int64_field(), cf.gen_float_vec_field()]
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_schema_wrap.init_collection_schema(fields=fields, primary_field=primary_field,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_field", [[], 1, [1, "2", 3], (1,), {1: 1}, None])
|
|
def test_collection_non_string_primary_field(self, primary_field):
|
|
"""
|
|
target: test collection with non-string primary_field
|
|
method: primary_field type is not string
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
fields = [cf.gen_int64_field(), cf.gen_float_vec_field()]
|
|
error = {ct.err_code: 1, ct.err_msg: "Param primary_field must be str type."}
|
|
self.collection_schema_wrap.init_collection_schema(fields, primary_field=primary_field,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_not_existed_primary_field(self):
|
|
"""
|
|
target: test collection with not exist primary field
|
|
method: specify not existed field as primary_field
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
fake_field = cf.gen_unique_str()
|
|
fields = [cf.gen_int64_field(), cf.gen_float_vec_field()]
|
|
error = {ct.err_code: 1, ct.err_msg: "Schema must have a primary key field."}
|
|
|
|
self.collection_schema_wrap.init_collection_schema(fields, primary_field=fake_field,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_primary_in_schema(self):
|
|
"""
|
|
target: test collection with primary field
|
|
method: specify primary field in CollectionSchema
|
|
expected: collection.primary_field
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_default_collection_schema(primary_field=ct.default_int64_field_name)
|
|
self.collection_wrap.init_collection(c_name, schema=schema)
|
|
assert self.collection_wrap.primary_field.name == ct.default_int64_field_name
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_primary_in_field(self):
|
|
"""
|
|
target: test collection with primary field
|
|
method: specify primary field in FieldSchema
|
|
expected: collection.primary_field
|
|
"""
|
|
self._connect()
|
|
fields = [cf.gen_int64_field(is_primary=True), cf.gen_float_field(), cf.gen_float_vec_field()]
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema(fields)
|
|
self.collection_wrap.init_collection(cf.gen_unique_str(prefix), schema=schema)
|
|
assert self.collection_wrap.primary_field.name == ct.default_int64_field_name
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_unsupported_primary_field(self, get_unsupported_primary_field):
|
|
"""
|
|
target: test collection with unsupported primary field type
|
|
method: specify non-int64 as primary field
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
field = get_unsupported_primary_field
|
|
vec_field = cf.gen_float_vec_field(name="vec")
|
|
error = {ct.err_code: 1, ct.err_msg: "Primary key type must be DataType.INT64 or DataType.VARCHAR."}
|
|
self.collection_schema_wrap.init_collection_schema(fields=[field, vec_field], primary_field=field.name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_multi_primary_fields(self):
|
|
"""
|
|
target: test collection with multi primary
|
|
method: collection with two primary fields
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
int_field_one = cf.gen_int64_field(is_primary=True)
|
|
int_field_two = cf.gen_int64_field(name="int2", is_primary=True)
|
|
error = {ct.err_code: 0, ct.err_msg: "Expected only one primary key field"}
|
|
self.collection_schema_wrap.init_collection_schema(
|
|
fields=[int_field_one, int_field_two, cf.gen_float_vec_field()],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_primary_inconsistent(self):
|
|
"""
|
|
target: test collection with different primary field setting
|
|
method: 1. set A field is_primary 2. set primary_field is B
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
int_field_one = cf.gen_int64_field(is_primary=True)
|
|
int_field_two = cf.gen_int64_field(name="int2")
|
|
fields = [int_field_one, int_field_two, cf.gen_float_vec_field()]
|
|
error = {ct.err_code: 1, ct.err_msg: "Expected only one primary key field"}
|
|
self.collection_schema_wrap.init_collection_schema(fields, primary_field=int_field_two.name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_primary_consistent(self):
|
|
"""
|
|
target: test collection with both collection schema and field schema
|
|
method: 1. set A field is_primary 2.set primary_field is A
|
|
expected: verify primary field
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field_one = cf.gen_int64_field(is_primary=True)
|
|
schema = cf.gen_collection_schema(fields=[int_field_one, cf.gen_float_vec_field()],
|
|
primary_field=int_field_one.name)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
@pytest.mark.parametrize("auto_id", [True, False])
|
|
def test_collection_auto_id_in_field_schema(self, auto_id):
|
|
"""
|
|
target: test collection with auto_id in field schema
|
|
method: specify auto_id True in field schema
|
|
expected: verify schema's auto_id
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field = cf.gen_int64_field(is_primary=True, auto_id=auto_id)
|
|
vec_field = cf.gen_float_vec_field(name='vec')
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema([int_field, vec_field])
|
|
assert schema.auto_id == auto_id
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
@pytest.mark.parametrize("auto_id", [True, False])
|
|
def test_collection_auto_id_in_collection_schema(self, auto_id):
|
|
"""
|
|
target: test collection with auto_id in collection schema
|
|
method: specify auto_id True in collection schema
|
|
expected: verify schema auto_id and collection schema
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field(name='vec')
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema([int_field, vec_field], auto_id=auto_id)
|
|
assert schema.auto_id == auto_id
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_auto_id_non_primary_field(self):
|
|
"""
|
|
target: test collection set auto_id in non-primary field
|
|
method: set auto_id=True in non-primary field
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 0, ct.err_msg: "auto_id can only be specified on the primary key field"}
|
|
self.field_schema_wrap.init_field_schema(name=ct.default_int64_field_name, dtype=DataType.INT64, auto_id=True,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_auto_id_false_non_primary(self):
|
|
"""
|
|
target: test collection set auto_id in non-primary field
|
|
method: set auto_id=True in non-primary field
|
|
expected: verify schema auto_id is False
|
|
"""
|
|
self._connect()
|
|
int_field_one = cf.gen_int64_field(is_primary=True)
|
|
int_field_two = cf.gen_int64_field(name='int2', auto_id=False)
|
|
fields = [int_field_one, int_field_two, cf.gen_float_vec_field()]
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema(fields)
|
|
assert not schema.auto_id
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.xfail(reason="issue 24578")
|
|
def test_collection_auto_id_inconsistent(self):
|
|
"""
|
|
target: test collection auto_id with both collection schema and field schema
|
|
method: 1.set primary field auto_id=True in field schema 2.set auto_id=False in collection schema
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
int_field = cf.gen_int64_field(is_primary=True, auto_id=True)
|
|
vec_field = cf.gen_float_vec_field(name='vec')
|
|
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema([int_field, vec_field], auto_id=False)
|
|
assert schema.auto_id
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("auto_id", [True, False])
|
|
def test_collection_auto_id_consistent(self, auto_id):
|
|
"""
|
|
target: test collection auto_id with both collection schema and field schema
|
|
method: set auto_id=True/False both field and schema
|
|
expected: verify auto_id
|
|
"""
|
|
self._connect()
|
|
int_field = cf.gen_int64_field(is_primary=True, auto_id=auto_id)
|
|
vec_field = cf.gen_float_vec_field(name='vec')
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema([int_field, vec_field], auto_id=auto_id)
|
|
assert schema.auto_id == auto_id
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_auto_id_none_in_field(self):
|
|
"""
|
|
target: test collection with auto_id is None
|
|
method: set auto_id=None
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 0, ct.err_msg: "Param auto_id must be bool type"}
|
|
self.field_schema_wrap.init_field_schema(name=ct.default_int64_field_name, dtype=DataType.INT64,
|
|
is_primary=True,
|
|
auto_id=None, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.xfail(reason="issue 24578")
|
|
@pytest.mark.parametrize("auto_id", ct.get_invalid_strs)
|
|
def test_collection_invalid_auto_id(self, auto_id):
|
|
"""
|
|
target: test collection with invalid auto_id
|
|
method: define field with auto_id=non-bool
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field(name='vec')
|
|
error = {ct.err_code: 0, ct.err_msg: "Param auto_id must be bool type"}
|
|
self.collection_schema_wrap.init_collection_schema([int_field, vec_field], auto_id=auto_id,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_multi_fields_auto_id(self):
|
|
"""
|
|
target: test collection auto_id with multi fields
|
|
method: specify auto_id=True for multi int64 fields
|
|
expected: todo raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 0, ct.err_msg: "auto_id can only be specified on the primary key field"}
|
|
cf.gen_int64_field(is_primary=True, auto_id=True)
|
|
self.field_schema_wrap.init_field_schema(name="int", dtype=DataType.INT64, auto_id=True,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("dtype", [DataType.FLOAT_VECTOR, DataType.BINARY_VECTOR])
|
|
def test_collection_vector_without_dim(self, dtype):
|
|
"""
|
|
target: test collection without dimension
|
|
method: define vector field without dim
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
float_vec_field, _ = self.field_schema_wrap.init_field_schema(name="vec", dtype=dtype)
|
|
schema = cf.gen_collection_schema(fields=[cf.gen_int64_field(is_primary=True), float_vec_field])
|
|
error = {ct.err_code: 1, ct.err_msg: "dimension is not defined in field type params"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.xfail(reason="issue #29796")
|
|
def test_collection_vector_invalid_dim(self, get_invalid_dim):
|
|
"""
|
|
target: test collection with invalid dimension
|
|
method: define float-vec field with invalid dimension
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
float_vec_field = cf.gen_float_vec_field(dim=get_invalid_dim)
|
|
schema = cf.gen_collection_schema(fields=[cf.gen_int64_field(is_primary=True), float_vec_field])
|
|
error = {ct.err_code: 65535, ct.err_msg: "strconv.ParseInt: parsing \"[]\": invalid syntax"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("dim", [-1, 0, 32769])
|
|
def test_collection_vector_out_bounds_dim(self, dim):
|
|
"""
|
|
target: test collection with out of bounds dim
|
|
method: invalid dim -1 and 32759
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
float_vec_field = cf.gen_float_vec_field(dim=dim)
|
|
schema = cf.gen_collection_schema(fields=[cf.gen_int64_field(is_primary=True), float_vec_field])
|
|
error = {ct.err_code: 1, ct.err_msg: "invalid dimension: {}. should be in range 1 ~ 32768".format(dim)}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_non_vector_field_dim(self):
|
|
"""
|
|
target: test collection with dim for non-vector field
|
|
method: define int64 field with dim
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field, _ = self.field_schema_wrap.init_field_schema(name=ct.default_int64_field_name, dtype=DataType.INT64,
|
|
dim=ct.default_dim)
|
|
float_vec_field = cf.gen_float_vec_field()
|
|
schema = cf.gen_collection_schema(fields=[int_field, float_vec_field],
|
|
primary_field=ct.default_int64_field_name)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_desc(self):
|
|
"""
|
|
target: test collection with description
|
|
method: create with description
|
|
expected: assert default description
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_default_collection_schema(description=ct.collection_desc)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_none_desc(self):
|
|
"""
|
|
target: test collection with none description
|
|
method: create with none description
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_default_collection_schema(description=None)
|
|
error = {ct.err_code: 1, ct.err_msg: "None has type NoneType, but expected one of: bytes, unicode"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_long_desc(self):
|
|
"""
|
|
target: test collection with long desc
|
|
method: create with long desc
|
|
expected:
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
desc = "a".join("a" for _ in range(256))
|
|
schema = cf.gen_default_collection_schema(description=desc)
|
|
self.collection_wrap.init_collection(c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_binary(self):
|
|
"""
|
|
target: test collection with binary-vec
|
|
method: create collection with binary field
|
|
expected: assert binary field
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.collection_wrap.init_collection(c_name, schema=default_binary_schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_binary_schema})
|
|
assert c_name in self.utility_wrap.list_collections()[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_shards_num_with_default_value(self):
|
|
"""
|
|
target:test collection with shards_num
|
|
method:create collection with shards_num
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema, shards_num=default_shards_num,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_shards_num: default_shards_num})
|
|
assert c_name in self.utility_wrap.list_collections()[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
@pytest.mark.parametrize("shards_num", [-256, 0, ct.max_shards_num // 2, ct.max_shards_num])
|
|
def test_collection_shards_num_with_not_default_value(self, shards_num):
|
|
"""
|
|
target:test collection with shards_num
|
|
method:create collection with not default shards_num
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema, shards_num=shards_num,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_shards_num: shards_num})
|
|
assert c_name in self.utility_wrap.list_collections()[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("shards_num", [ct.max_shards_num + 1, 257])
|
|
def test_collection_shards_num_invalid(self, shards_num):
|
|
"""
|
|
target:test collection with invalid shards_num
|
|
method:create collection with shards_num out of [1, 16]
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 1, ct.err_msg: f"maximum shards's number should be limited to {ct.max_shards_num}"}
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema, shards_num=shards_num,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("error_type_shards_num", [1.0, "2"])
|
|
def test_collection_shards_num_with_error_type(self, error_type_shards_num):
|
|
"""
|
|
target:test collection with error type shards_num
|
|
method:create collection with error type shards_num
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 1, ct.err_msg: f"expected one of: int, long"}
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema, shards_num=error_type_shards_num,
|
|
check_task=CheckTasks.err_res,
|
|
check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_create_collection_maximum_fields(self):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
limit_num = ct.max_field_num - 2
|
|
for i in range(limit_num):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_float_vec_field())
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_create_collection_maximum_vector_fields(self):
|
|
"""
|
|
target: Test create collection with the maximum vector fields (default is 4)
|
|
method: create collection with the maximum vector field number
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
limit_num = max_vector_field_num
|
|
for i in range(limit_num):
|
|
vector_field_name = cf.gen_unique_str("vector_field_name")
|
|
field = cf.gen_float_vec_field(name=vector_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_key", [cf.gen_int64_field(is_primary=True), cf.gen_string_field(is_primary=True)])
|
|
def test_create_collection_multiple_vector_and_maximum_fields(self, primary_key):
|
|
"""
|
|
target: test create collection with multiple vector fields and maximum fields
|
|
method: create collection with multiple vector fields and maximum fields
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
vector_limit_num = max_vector_field_num - 2
|
|
limit_num = ct.max_field_num - 2
|
|
# add maximum vector fields
|
|
for i in range(vector_limit_num):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
# add other vector fields to maximum fields num
|
|
for i in range(limit_num - 2):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_float_vec_field())
|
|
int_fields.append(primary_key)
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_key", [cf.gen_int64_field(is_primary=True), cf.gen_string_field(is_primary=True)])
|
|
def test_create_collection_maximum_vector_and_all_fields(self, primary_key):
|
|
"""
|
|
target: test create collection with maximum vector fields and maximum fields
|
|
method: create collection with maximum vector fields and maximum fields
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
vector_limit_num = max_vector_field_num
|
|
limit_num = ct.max_field_num - 2
|
|
# add maximum vector fields
|
|
for i in range(vector_limit_num):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
# add other vector fields to maximum fields num
|
|
for i in range(limit_num - 4):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_float_vec_field())
|
|
int_fields.append(primary_key)
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_create_collection_over_maximum_fields(self):
|
|
"""
|
|
target: Test create collection with more than the maximum fields
|
|
method: create collection with more than the maximum field number
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
limit_num = ct.max_field_num
|
|
for i in range(limit_num):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_float_vec_field())
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
error = {ct.err_code: 1, ct.err_msg: "maximum field's number should be limited to 64"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_create_collection_over_maximum_vector_fields(self):
|
|
"""
|
|
target: Test create collection with more than the maximum vector fields (default is 4)
|
|
method: create collection with more than the maximum vector field number
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
limit_num = max_vector_field_num
|
|
for i in range(limit_num + 1):
|
|
vector_field_name = cf.gen_unique_str("vector_field_name")
|
|
field = cf.gen_float_vec_field(name=vector_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
error = {ct.err_code: 65535, ct.err_msg: "maximum vector field's number should be limited to 4"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_create_collection_multiple_vector_and_over_maximum_all_fields(self):
|
|
"""
|
|
target: test create collection with multiple vector fields and over maximum fields
|
|
method: create collection with multiple vector fields and over maximum fields
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
vector_limit_num = max_vector_field_num - 2
|
|
limit_num = ct.max_field_num
|
|
# add multiple vector fields
|
|
for i in range(vector_limit_num):
|
|
vector_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_float_vec_field(name=vector_field_name)
|
|
int_fields.append(field)
|
|
# add other vector fields to maximum fields num
|
|
for i in range(limit_num):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
log.debug(len(int_fields))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
error = {ct.err_code: 65535, ct.err_msg: "maximum field's number should be limited to 64"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_create_collection_over_maximum_vector_and_all_fields(self):
|
|
"""
|
|
target: test create collection with over maximum vector fields and maximum fields
|
|
method: create collection with over maximum vector fields and maximum fields
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_fields = []
|
|
vector_limit_num = max_vector_field_num
|
|
limit_num = ct.max_field_num - 2
|
|
# add maximum vector fields
|
|
for i in range(vector_limit_num + 1):
|
|
vector_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_float_vec_field(name=vector_field_name)
|
|
int_fields.append(field)
|
|
# add other vector fields to maximum fields num
|
|
for i in range(limit_num - 4):
|
|
int_field_name = cf.gen_unique_str("field_name")
|
|
field = cf.gen_int64_field(name=int_field_name)
|
|
int_fields.append(field)
|
|
int_fields.append(cf.gen_float_vec_field())
|
|
int_fields.append(cf.gen_int64_field(is_primary=True))
|
|
schema = cf.gen_collection_schema(fields=int_fields)
|
|
error = {ct.err_code: 65535, ct.err_msg: "maximum field's number should be limited to 64"}
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
|
|
class TestCollectionOperation(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test collection interface operations
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_without_connection(self):
|
|
"""
|
|
target: test collection without connection
|
|
method: 1.create collection after connection removed
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
assert self.collection_wrap.collection is None
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_multi_create_drop(self):
|
|
"""
|
|
target: test cycle creation and deletion of multiple collections
|
|
method: in a loop, collections are created and deleted sequentially
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_num = 20
|
|
for _ in range(c_num):
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.collection_wrap.init_collection(c_name, schema=default_schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
self.collection_wrap.drop()
|
|
assert c_name not in self.utility_wrap.list_collections()[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_dup_name_drop(self):
|
|
"""
|
|
target: test collection with dup name, and drop
|
|
method: 1. two dup name collection object
|
|
2. one object drop collection
|
|
expected: collection dropped
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
self.collection_wrap.init_collection(c_name, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
self.collection_wrap.drop()
|
|
assert not self.utility_wrap.has_collection(c_name)[0]
|
|
error = {ct.err_code: 4, ct.err_msg: 'collection not found'}
|
|
collection_w.has_partition("p", check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_after_drop(self):
|
|
"""
|
|
target: test create collection after create and drop
|
|
method: 1. create a 2. drop a 3, re-create a
|
|
expected: no exception
|
|
"""
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
collection_w.drop()
|
|
assert not self.utility_wrap.has_collection(collection_w.name)[0]
|
|
self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
assert self.utility_wrap.has_collection(c_name)[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_all_datatype_fields(self):
|
|
"""
|
|
target: test create collection with all dataType fields
|
|
method: create collection with all dataType schema
|
|
expected: create successfully
|
|
"""
|
|
self._connect()
|
|
fields = []
|
|
for k, v in DataType.__members__.items():
|
|
if v and v != DataType.UNKNOWN and v != DataType.STRING \
|
|
and v != DataType.VARCHAR and v != DataType.FLOAT_VECTOR \
|
|
and v != DataType.BINARY_VECTOR and v != DataType.ARRAY \
|
|
and v != DataType.FLOAT16_VECTOR and v != DataType.BFLOAT16_VECTOR:
|
|
field, _ = self.field_schema_wrap.init_field_schema(name=k.lower(), dtype=v)
|
|
fields.append(field)
|
|
fields.append(cf.gen_float_vec_field())
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema(fields,
|
|
primary_field=ct.default_int64_field_name)
|
|
log.info(schema)
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_partition(self):
|
|
"""
|
|
target: test release the partition after load collection
|
|
method: load collection and load the partition
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_w1 = self.init_partition_wrap(collection_w)
|
|
partition_w1.insert(cf.gen_default_list_data())
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
partition_w1.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_release_partition(self):
|
|
"""
|
|
target: test release the partition after load collection
|
|
method: load collection and release the partition
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_w1 = self.init_partition_wrap(collection_w)
|
|
partition_w1.insert(cf.gen_default_list_data())
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_release_collection(self):
|
|
"""
|
|
target: test release the collection after load collection
|
|
method: load collection and release the collection
|
|
expected: no exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
collection_w.insert(cf.gen_default_list_data())
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
|
|
|
|
class TestCollectionDataframe(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test construct_from_dataframe
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.fixture(scope="function", params=ct.get_invalid_strs)
|
|
def get_non_df(self, request):
|
|
if request.param is None:
|
|
pytest.skip("skip None")
|
|
yield request.param
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_construct_from_dataframe(self):
|
|
"""
|
|
target: test collection with dataframe data
|
|
method: create collection and insert with dataframe
|
|
expected: collection num entities equal to nb
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
# flush
|
|
assert self.collection_wrap.num_entities == ct.default_nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_construct_from_binary_dataframe(self):
|
|
"""
|
|
target: test binary collection with dataframe
|
|
method: create binary collection with dataframe
|
|
expected: collection num entities equal to nb
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df, _ = cf.gen_default_binary_dataframe_data(nb=ct.default_nb)
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_binary_schema})
|
|
assert self.collection_wrap.num_entities == ct.default_nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_none_dataframe(self):
|
|
"""
|
|
target: test create collection by empty dataframe
|
|
method: invalid dataframe type create collection
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 1, ct.err_msg: "Dataframe can not be None."}
|
|
self.collection_wrap.construct_from_dataframe(c_name, None, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_dataframe_only_column(self):
|
|
"""
|
|
target: test collection with dataframe only columns
|
|
method: dataframe only has columns
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = pd.DataFrame(columns=[ct.default_int64_field_name, ct.default_float_vec_field_name])
|
|
error = {ct.err_code: 0, ct.err_msg: "Cannot infer schema from empty dataframe"}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_inconsistent_dataframe(self):
|
|
"""
|
|
target: test collection with data inconsistent
|
|
method: create and insert with inconsistent data
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
# one field different type df
|
|
mix_data = [(1, 2., [0.1, 0.2]), (2, 3., 4)]
|
|
df = pd.DataFrame(data=mix_data, columns=list("ABC"))
|
|
error = {ct.err_code: 0, ct.err_msg: "The data in the same column must be of the same type"}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field='A', check_task=CheckTasks.err_res,
|
|
check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_non_dataframe(self, get_non_df):
|
|
"""
|
|
target: test create collection by invalid dataframe
|
|
method: non-dataframe type create collection
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 0, ct.err_msg: "Data type must be pandas.DataFrame."}
|
|
df = get_non_df
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_data_type_dataframe(self):
|
|
"""
|
|
target: test collection with invalid dataframe
|
|
method: create with invalid dataframe
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = pd.DataFrame({"date": pd.date_range('20210101', periods=3), ct.default_int64_field_name: [1, 2, 3]})
|
|
error = {ct.err_code: 0, ct.err_msg: "Cannot infer schema from empty dataframe."}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_from_invalid_field_name(self):
|
|
"""
|
|
target: test collection with invalid field name
|
|
method: create with invalid field name dataframe
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = pd.DataFrame({'%$#': cf.gen_vectors(3, 2), ct.default_int64_field_name: [1, 2, 3]})
|
|
error = {ct.err_code: 1, ct.err_msg: "Invalid field name"}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_none_primary_field(self):
|
|
"""
|
|
target: test collection with none primary field
|
|
method: primary_field is none
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
error = {ct.err_code: 0, ct.err_msg: "Schema must have a primary key field."}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=None,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_not_existed_primary_field(self):
|
|
"""
|
|
target: test collection with not existed primary field
|
|
method: primary field not existed
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
error = {ct.err_code: 0, ct.err_msg: "Primary field must in dataframe."}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=c_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_with_none_auto_id(self):
|
|
"""
|
|
target: test construct with non-int64 as primary field
|
|
method: non-int64 as primary field
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
error = {ct.err_code: 0, ct.err_msg: "Param auto_id must be bool type"}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
auto_id=None, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_auto_id_true_insert(self):
|
|
"""
|
|
target: test construct with true auto_id
|
|
method: auto_id=True and insert values
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(nb=100)
|
|
error = {ct.err_code: 0, ct.err_msg: "Auto_id is True, primary field should not have data."}
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
auto_id=True, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_auto_id_true_no_insert(self):
|
|
"""
|
|
target: test construct with true auto_id
|
|
method: auto_id=True and not insert ids(primary fields all values are None)
|
|
expected: verify num entities
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data()
|
|
# df.drop(ct.default_int64_field_name, axis=1, inplace=True)
|
|
df[ct.default_int64_field_name] = None
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
auto_id=True)
|
|
assert self.collection_wrap.num_entities == ct.default_nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_none_value_auto_id_true(self):
|
|
"""
|
|
target: test construct with none value, auto_id
|
|
method: df primary field with none value, auto_id=true
|
|
expected: todo
|
|
"""
|
|
self._connect()
|
|
nb = 100
|
|
df = cf.gen_default_dataframe_data(nb)
|
|
df.iloc[:, 0] = numpy.NaN
|
|
res, _ = self.collection_wrap.construct_from_dataframe(cf.gen_unique_str(prefix), df,
|
|
primary_field=ct.default_int64_field_name, auto_id=True)
|
|
mutation_res = res[1]
|
|
assert cf._check_primary_keys(mutation_res.primary_keys, 100)
|
|
assert self.collection_wrap.num_entities == nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_auto_id_false(self):
|
|
"""
|
|
target: test construct with false auto_id
|
|
method: auto_id=False, primary_field correct
|
|
expected: verify auto_id
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
auto_id=False)
|
|
assert not self.collection_wrap.schema.auto_id
|
|
assert self.collection_wrap.num_entities == ct.default_nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_construct_none_value_auto_id_false(self):
|
|
"""
|
|
target: test construct with none value, auto_id
|
|
method: df primary field with none value, auto_id=false
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
nb = 100
|
|
df = cf.gen_default_dataframe_data(nb)
|
|
df.iloc[:, 0] = numpy.NaN
|
|
error = {ct.err_code: 0, ct.err_msg: "Primary key type must be DataType.INT64"}
|
|
self.collection_wrap.construct_from_dataframe(cf.gen_unique_str(prefix), df,
|
|
primary_field=ct.default_int64_field_name, auto_id=False,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_auto_id_false_same_values(self):
|
|
"""
|
|
target: test construct with false auto_id and same value
|
|
method: auto_id=False, primary field same values
|
|
expected: verify num entities
|
|
"""
|
|
self._connect()
|
|
nb = 100
|
|
df = cf.gen_default_dataframe_data(nb)
|
|
df.iloc[1:, 0] = 1
|
|
res, _ = self.collection_wrap.construct_from_dataframe(cf.gen_unique_str(prefix), df,
|
|
primary_field=ct.default_int64_field_name, auto_id=False)
|
|
collection_w = res[0]
|
|
collection_w.flush()
|
|
assert collection_w.num_entities == nb
|
|
mutation_res = res[1]
|
|
assert mutation_res.primary_keys == df[ct.default_int64_field_name].values.tolist()
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_auto_id_false_negative_values(self):
|
|
"""
|
|
target: test construct with negative values
|
|
method: auto_id=False, primary field values is negative
|
|
expected: verify num entities
|
|
"""
|
|
self._connect()
|
|
nb = 100
|
|
df = cf.gen_default_dataframe_data(nb)
|
|
new_values = pd.Series(data=[i for i in range(0, -nb, -1)])
|
|
df[ct.default_int64_field_name] = new_values
|
|
self.collection_wrap.construct_from_dataframe(cf.gen_unique_str(prefix), df,
|
|
primary_field=ct.default_int64_field_name, auto_id=False)
|
|
assert self.collection_wrap.num_entities == nb
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_construct_from_dataframe_dup_name(self):
|
|
"""
|
|
target: test collection with dup name and insert dataframe
|
|
method: create collection with dup name, none schema, dataframe
|
|
expected: two collection object is correct
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
df = cf.gen_default_dataframe_data(ct.default_nb)
|
|
self.collection_wrap.construct_from_dataframe(c_name, df, primary_field=ct.default_int64_field_name,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: default_schema})
|
|
# flush
|
|
assert collection_w.num_entities == ct.default_nb
|
|
assert collection_w.num_entities == self.collection_wrap.num_entities
|
|
|
|
|
|
class TestCollectionCount(TestcaseBase):
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_count_no_vectors(self):
|
|
"""
|
|
target: test collection rows_count is correct or not, if collection is empty
|
|
method: create collection and no vectors in it,
|
|
assert the value returned by num_entities attribute is equal to 0
|
|
expected: the count is equal to 0
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
assert collection_w.num_entities == 0
|
|
|
|
|
|
class TestCollectionCountIP(TestcaseBase):
|
|
"""
|
|
params means different nb, the nb value may trigger merge, or not
|
|
"""
|
|
|
|
@pytest.fixture(
|
|
scope="function",
|
|
params=[
|
|
1,
|
|
1000,
|
|
2001
|
|
],
|
|
)
|
|
def insert_count(self, request):
|
|
yield request.param
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_count_after_index_created(self, insert_count):
|
|
"""
|
|
target: test count_entities, after index have been created
|
|
method: add vectors in db, and create index, then calling num_entities with correct params
|
|
expected: count_entities raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
|
|
data = cf.gen_default_list_data(insert_count, ct.default_dim)
|
|
collection_w.insert(data)
|
|
|
|
collection_w.create_index(ct.default_float_vec_field_name, default_index_params,
|
|
index_name=ct.default_index_name)
|
|
assert collection_w.num_entities == insert_count
|
|
|
|
|
|
class TestCollectionCountBinary(TestcaseBase):
|
|
"""
|
|
params means different nb, the nb value may trigger merge, or not
|
|
"""
|
|
|
|
@pytest.fixture(
|
|
scope="function",
|
|
params=[
|
|
1,
|
|
1000,
|
|
2001
|
|
],
|
|
)
|
|
def insert_count(self, request):
|
|
yield request.param
|
|
|
|
# TODO: need to update and enable
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_count_after_index_created_binary(self, insert_count):
|
|
"""
|
|
target: test num_entities, after index have been created
|
|
method: add vectors in db, and create binary index, then calling num_entities with correct params
|
|
expected: num_entities equals entities count just inserted
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, schema=default_binary_schema)
|
|
df, _ = cf.gen_default_binary_dataframe_data(insert_count)
|
|
mutation_res, _ = collection_w.insert(data=df)
|
|
collection_w.create_index(ct.default_binary_vec_field_name, default_binary_index_params)
|
|
assert collection_w.num_entities == insert_count
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
@pytest.mark.parametrize("auto_id", [True, False])
|
|
def test_binary_collection_with_min_dim(self, auto_id):
|
|
"""
|
|
target: test binary collection when dim=1
|
|
method: creat collection and set dim=1
|
|
expected: check error message successfully
|
|
"""
|
|
self._connect()
|
|
dim = 1
|
|
c_schema = cf.gen_default_binary_collection_schema(auto_id=auto_id, dim=dim)
|
|
collection_w = self.init_collection_wrap(schema=c_schema,
|
|
check_task=CheckTasks.err_res,
|
|
check_items={"err_code": 1,
|
|
"err_msg": f"invalid dimension: {dim}. should be multiple of 8."})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_count_no_entities(self):
|
|
"""
|
|
target: test collection num_entities is correct or not, if collection is empty
|
|
method: create collection and no vectors in it,
|
|
assert the value returned by num_entities method is equal to 0
|
|
expected: the count is equal to 0
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, schema=default_binary_schema)
|
|
assert collection_w.num_entities == 0
|
|
|
|
|
|
class TestCollectionMultiCollections(TestcaseBase):
|
|
"""
|
|
params means different nb, the nb value may trigger merge, or not
|
|
"""
|
|
|
|
@pytest.fixture(
|
|
scope="function",
|
|
params=[
|
|
1,
|
|
1000,
|
|
2001
|
|
],
|
|
)
|
|
def insert_count(self, request):
|
|
yield request.param
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_collection_count_multi_collections_l2(self, insert_count):
|
|
"""
|
|
target: test collection rows_count is correct or not with multiple collections of L2
|
|
method: create collection and add entities in it,
|
|
assert the value returned by num_entities is equal to length of entities
|
|
expected: the count is equal to the length of entities
|
|
"""
|
|
self._connect()
|
|
data = cf.gen_default_list_data(insert_count)
|
|
collection_list = []
|
|
collection_num = 10
|
|
for i in range(collection_num):
|
|
collection_name = gen_unique_str(uid_count)
|
|
collection_w = self.init_collection_wrap(name=collection_name)
|
|
collection_w.insert(data)
|
|
collection_list.append(collection_name)
|
|
for i in range(collection_num):
|
|
res, _ = self.collection_wrap.init_collection(collection_list[i])
|
|
assert self.collection_wrap.num_entities == insert_count
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_count_multi_collections_binary(self, insert_count):
|
|
"""
|
|
target: test collection rows_count is correct or not with multiple collections of JACCARD
|
|
method: create collection and add entities in it,
|
|
assert the value returned by count_entities method is equal to length of entities
|
|
expected: the count is equal to the length of entities
|
|
"""
|
|
self._connect()
|
|
df, _ = cf.gen_default_binary_dataframe_data(insert_count)
|
|
collection_list = []
|
|
collection_num = 20
|
|
for i in range(collection_num):
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, schema=default_binary_schema)
|
|
mutation_res, _ = collection_w.insert(data=df)
|
|
collection_list.append(c_name)
|
|
for i in range(collection_num):
|
|
res, _ = self.collection_wrap.init_collection(collection_list[i])
|
|
assert self.collection_wrap.num_entities == insert_count
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_count_multi_collections_mix(self):
|
|
"""
|
|
target: test collection rows_count is correct or not with multiple collections of
|
|
method: create collection and add entities in it,
|
|
assert the value returned by count_entities method is equal to length of entities
|
|
expected: the count is equal to the length of entities
|
|
"""
|
|
self._connect()
|
|
collection_list = []
|
|
collection_num = 20
|
|
data = cf.gen_default_list_data()
|
|
df, _ = cf.gen_default_binary_dataframe_data(ct.default_nb)
|
|
for i in range(0, int(collection_num / 2)):
|
|
collection_name = gen_unique_str(uid_count)
|
|
collection_w = self.init_collection_wrap(name=collection_name)
|
|
collection_w.insert(data)
|
|
collection_list.append(collection_name)
|
|
for i in range(int(collection_num / 2), collection_num):
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, schema=default_binary_schema)
|
|
mutation_res, _ = collection_w.insert(data=df)
|
|
collection_list.append(c_name)
|
|
for i in range(collection_num):
|
|
res, _ = self.collection_wrap.init_collection(collection_list[i])
|
|
assert self.collection_wrap.num_entities == ct.default_nb
|
|
|
|
|
|
class TestCreateCollection(TestcaseBase):
|
|
|
|
@pytest.fixture(scope="function", params=[False, True])
|
|
def auto_id(self, request):
|
|
yield request.param
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_create_collection_multithread(self):
|
|
"""
|
|
target: test create collection with multi-thread
|
|
method: create collection using multi-thread,
|
|
expected: collections are created
|
|
"""
|
|
self._connect()
|
|
threads_num = 8
|
|
threads = []
|
|
collection_names = []
|
|
|
|
def create():
|
|
collection_name = gen_unique_str(uid_create)
|
|
collection_names.append(collection_name)
|
|
self.init_collection_wrap(name=collection_name)
|
|
|
|
for i in range(threads_num):
|
|
t = MyThread(target=create, args=())
|
|
threads.append(t)
|
|
t.start()
|
|
time.sleep(0.2)
|
|
for t in threads:
|
|
t.join()
|
|
|
|
for item in collection_names:
|
|
assert item in self.utility_wrap.list_collections()[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
@pytest.mark.skip("not support default_value now")
|
|
def test_create_collection_using_default_value(self, auto_id):
|
|
"""
|
|
target: test create collection with default_value
|
|
method: create a schema with all fields using default value
|
|
expected: collections are created
|
|
"""
|
|
fields = [
|
|
cf.gen_int64_field(name='pk', is_primary=True),
|
|
cf.gen_float_vec_field(),
|
|
cf.gen_int8_field(default_value=numpy.int8(8)),
|
|
cf.gen_int16_field(default_value=numpy.int16(16)),
|
|
cf.gen_int32_field(default_value=numpy.int32(32)),
|
|
cf.gen_int64_field(default_value=numpy.int64(64)),
|
|
cf.gen_float_field(default_value=numpy.float32(3.14)),
|
|
cf.gen_double_field(default_value=numpy.double(3.1415)),
|
|
cf.gen_bool_field(default_value=False),
|
|
cf.gen_string_field(default_value="abc")
|
|
]
|
|
schema = cf.gen_collection_schema(fields, auto_id=auto_id)
|
|
self.init_collection_wrap(schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={"schema": schema})
|
|
|
|
|
|
class TestCreateCollectionInvalid(TestcaseBase):
|
|
"""
|
|
Test creating collections with invalid params
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_create_collection_limit_fields(self):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
limit_num = ct.max_field_num
|
|
field_schema_list = []
|
|
field_pr = cf.gen_int64_field(ct.default_int64_field_name, is_primary=True)
|
|
field_v = cf.gen_float_vec_field(ct.default_float_vec_field_name)
|
|
field_schema_list.append(field_pr)
|
|
field_schema_list.append(field_v)
|
|
|
|
for i in range(limit_num):
|
|
field_name_tmp = gen_unique_str("field_name")
|
|
field_schema_temp = cf.gen_int64_field(field_name_tmp)
|
|
field_schema_list.append(field_schema_temp)
|
|
error = {ct.err_code: 65535, ct.err_msg: "maximum field's number should be limited to 64"}
|
|
schema, _ = self.collection_schema_wrap.init_collection_schema(fields=field_schema_list)
|
|
self.init_collection_wrap(name=c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("invalid_name", ["中文", "español", "عربي", "हिंदी", "Русский"])
|
|
def test_create_schema_with_different_language(self, invalid_name):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
fields = [cf.gen_int64_field(is_primary=True), cf.gen_float_vec_field(),
|
|
cf.gen_string_field(name=invalid_name)]
|
|
schema = cf.gen_collection_schema(fields)
|
|
self.init_collection_wrap(schema=schema,
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1701,
|
|
ct.err_msg: "Invalid field name: %s" % invalid_name})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("invalid_name", ["中文", "español", "عربي", "हिंदी", "Русский"])
|
|
def test_create_collection_with_different_language(self, invalid_name):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
schema = cf.gen_default_collection_schema()
|
|
self.init_collection_wrap(name=invalid_name, schema=schema,
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1100,
|
|
ct.err_msg: "Invalid collection name: %s" % invalid_name})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("default_value", ["abc"])
|
|
@pytest.mark.skip(reason="issue #24634")
|
|
def test_create_collection_with_invalid_default_value_string(self, default_value):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
fields = [
|
|
cf.gen_int64_field(name='pk', is_primary=True),
|
|
cf.gen_float_vec_field(),
|
|
cf.gen_string_field(max_length=2, default_value=default_value)
|
|
]
|
|
schema = cf.gen_collection_schema(fields)
|
|
self.init_collection_wrap(schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={"schema": schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.skip("not support default_value now")
|
|
@pytest.mark.parametrize("default_value", ["abc", 9.09, 1, False])
|
|
def test_create_collection_with_invalid_default_value_float(self, default_value):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
fields = [
|
|
cf.gen_int64_field(name='pk', is_primary=True),
|
|
cf.gen_float_vec_field(),
|
|
cf.gen_float_field(default_value=default_value)
|
|
]
|
|
schema = cf.gen_collection_schema(fields)
|
|
self.init_collection_wrap(schema=schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "default value type mismatches field schema type"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.skip("not support default_value now")
|
|
@pytest.mark.parametrize("default_value", ["abc", 9.09, 1, False])
|
|
def test_create_collection_with_invalid_default_value_int8(self, default_value):
|
|
"""
|
|
target: test create collection with maximum fields
|
|
method: create collection with maximum field number
|
|
expected: raise exception
|
|
"""
|
|
fields = [
|
|
cf.gen_int64_field(name='pk', is_primary=True),
|
|
cf.gen_float_vec_field(),
|
|
cf.gen_int8_field(default_value=default_value)
|
|
]
|
|
schema = cf.gen_collection_schema(fields)
|
|
self.init_collection_wrap(schema=schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "default value type mismatches field schema type"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.skip("not support default_value now")
|
|
def test_create_collection_with_pk_field_using_default_value(self):
|
|
"""
|
|
target: test create collection with pk field using default value
|
|
method: create a pk field and set default value
|
|
expected: report error
|
|
"""
|
|
# 1. pk int64
|
|
fields = [
|
|
cf.gen_int64_field(name='pk', is_primary=True, default_value=np.int64(1)),
|
|
cf.gen_float_vec_field(), cf.gen_string_field(max_length=2)
|
|
]
|
|
schema = cf.gen_collection_schema(fields)
|
|
collection_w = self.init_collection_wrap(schema=schema)
|
|
collection_w.insert([[], [vectors[0]], ["a"]],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "pk field schema can not set default value"})
|
|
# 2. pk string
|
|
fields = [
|
|
cf.gen_string_field(name='pk', is_primary=True, default_value="a"),
|
|
cf.gen_float_vec_field(), cf.gen_string_field(max_length=2)
|
|
]
|
|
schema = cf.gen_collection_schema(fields)
|
|
collection_w = self.init_collection_wrap(schema=schema)
|
|
collection_w.insert([[], [vectors[0]], ["a"]],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "pk field schema can not set default value"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.skip("not support default_value now")
|
|
def test_create_collection_with_json_field_using_default_value(self):
|
|
"""
|
|
target: test create collection with json field using default value
|
|
method: create a json field and set default value
|
|
expected: report error
|
|
"""
|
|
json_default_value = {"number": 1, "float": 2.0, "string": "abc", "bool": True,
|
|
"list": [i for i in range(5)]}
|
|
cf.gen_json_field(default_value=json_default_value,
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "Default value unsupported data type: 999"})
|
|
|
|
|
|
class TestDropCollection(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `drop_collection` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_drop_collection_A(self):
|
|
"""
|
|
target: test delete collection created with correct params
|
|
method: create collection and then delete,
|
|
assert the value returned by delete method
|
|
expected: status ok, and no collection in collections
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.drop()
|
|
assert not self.utility_wrap.has_collection(c_name)[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_drop_collection_without_connection(self):
|
|
"""
|
|
target: test describe collection, without connection
|
|
method: drop collection with correct params, with a disconnected instance
|
|
expected: drop raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_wr = self.init_collection_wrap(c_name)
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
collection_wr.drop(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_drop_collection_not_existed(self):
|
|
"""
|
|
target: test if collection not created
|
|
method: random a collection name, which not existed in db,
|
|
assert the exception raised returned by drp_collection method
|
|
expected: False
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
self.init_collection_wrap(name=c_name)
|
|
c_name_2 = cf.gen_unique_str()
|
|
# error = {ct.err_code: 0, ct.err_msg: 'DescribeCollection failed: collection not found: %s' % c_name_2}
|
|
# self.utility_wrap.drop_collection(c_name_2, check_task=CheckTasks.err_res, check_items=error)
|
|
# @longjiquan: dropping collection should be idempotent.
|
|
self.utility_wrap.drop_collection(c_name_2)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_create_drop_collection_multithread(self):
|
|
"""
|
|
target: test create and drop collection with multi-thread
|
|
method: create and drop collection using multi-thread,
|
|
expected: collections are created, and dropped
|
|
"""
|
|
self._connect()
|
|
threads_num = 8
|
|
threads = []
|
|
collection_names = []
|
|
|
|
def create():
|
|
c_name = cf.gen_unique_str()
|
|
collection_names.append(c_name)
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.drop()
|
|
|
|
for i in range(threads_num):
|
|
t = MyThread(target=create, args=())
|
|
threads.append(t)
|
|
t.start()
|
|
time.sleep(0.2)
|
|
for t in threads:
|
|
t.join()
|
|
|
|
for item in collection_names:
|
|
assert not self.utility_wrap.has_collection(item)[0]
|
|
|
|
|
|
class TestDropCollectionInvalid(TestcaseBase):
|
|
"""
|
|
Test drop collection with invalid params
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("name", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
|
|
def test_drop_collection_with_invalid_collection_name(self, name):
|
|
"""
|
|
target: test drop invalid collection
|
|
method: drop collection with invalid collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 1, ct.err_msg: "Invalid collection name: {}".format(name)}
|
|
self.utility_wrap.drop_collection(name, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_drop_collection_with_empty_or_None_collection_name(self):
|
|
"""
|
|
target: test drop invalid collection
|
|
method: drop collection with empty or None collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: -1, ct.err_msg: '`collection_name` value is illegal'}
|
|
self.utility_wrap.drop_collection('', check_task=CheckTasks.err_res, check_items=error)
|
|
error_none = {ct.err_code: -1, ct.err_msg: '`collection_name` value None is illegal'}
|
|
self.utility_wrap.drop_collection(None, check_task=CheckTasks.err_res, check_items=error_none)
|
|
|
|
|
|
class TestHasCollection(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `has_collection` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_has_collection_without_connection(self):
|
|
"""
|
|
target: test has collection, without connection
|
|
method: calling has collection with correct params, with a disconnected instance
|
|
expected: has collection raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
self.init_collection_wrap(c_name)
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
self.utility_wrap.has_collection(c_name, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_has_collection_not_existed(self):
|
|
"""
|
|
target: test if collection not created
|
|
method: random a collection name, create this collection then drop it,
|
|
assert the value returned by has_collection method
|
|
expected: False
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.drop()
|
|
assert not self.utility_wrap.has_collection(c_name)[0]
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_has_collection_multithread(self):
|
|
"""
|
|
target: test create collection with multi-thread
|
|
method: create collection using multi-thread,
|
|
expected: collections are created
|
|
"""
|
|
self._connect()
|
|
threads_num = 4
|
|
threads = []
|
|
c_name = cf.gen_unique_str()
|
|
self.init_collection_wrap(name=c_name)
|
|
|
|
def has():
|
|
assert self.utility_wrap.has_collection(c_name)
|
|
# assert not assert_collection(connect, collection_name)
|
|
|
|
for i in range(threads_num):
|
|
t = MyThread(target=has, args=())
|
|
threads.append(t)
|
|
t.start()
|
|
time.sleep(0.2)
|
|
for t in threads:
|
|
t.join()
|
|
|
|
|
|
class TestHasCollectionInvalid(TestcaseBase):
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("name", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
|
|
def test_has_collection_with_invalid_collection_name(self, name):
|
|
"""
|
|
target: test list collections with invalid scenario
|
|
method: show collection with invalid collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: 1, ct.err_msg: "Invalid collection name: {}".format(name)}
|
|
self.utility_wrap.has_collection(name, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_has_collection_with_empty_collection_name(self):
|
|
"""
|
|
target: test list collections with invalid scenario
|
|
method: show collection with empty collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: -1, ct.err_msg: '`collection_name` value is illegal'}
|
|
self.utility_wrap.has_collection('', check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_has_collection_with_none_collection_name(self):
|
|
"""
|
|
target: test list collections with invalid scenario
|
|
method: show collection with no collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
error = {ct.err_code: -1, ct.err_msg: '`collection_name` value None is illegal'}
|
|
self.utility_wrap.has_collection(None, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
|
|
class TestListCollections(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `utility.list_collections()` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_list_collections_multi_collections(self):
|
|
"""
|
|
target: test list collections
|
|
method: create collection, assert the value returned by list_collections method
|
|
expected: True
|
|
"""
|
|
self._connect()
|
|
collection_num = 50
|
|
collection_names = []
|
|
for i in range(collection_num):
|
|
collection_name = cf.gen_unique_str()
|
|
collection_names.append(collection_name)
|
|
self.init_collection_wrap(name=collection_name)
|
|
for i in range(collection_num):
|
|
assert collection_names[i] in self.utility_wrap.list_collections()[0]
|
|
self.utility_wrap.drop_collection(collection_names[i])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_list_collections_without_connection(self):
|
|
"""
|
|
target: test list collections, without connection
|
|
method: calling list collections with correct params, with a disconnected instance
|
|
expected: list collections raise exception
|
|
"""
|
|
self._connect()
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
self.utility_wrap.list_collections(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_list_collections_multithread(self):
|
|
"""
|
|
target: test list collection with multi-threads
|
|
method: list collection using multi-threads
|
|
expected: list collections correctly
|
|
"""
|
|
self._connect()
|
|
threads_num = 10
|
|
threads = []
|
|
collection_name = cf.gen_unique_str()
|
|
self.init_collection_wrap(name=collection_name)
|
|
|
|
def _list():
|
|
assert collection_name in self.utility_wrap.list_collections()[0]
|
|
|
|
for i in range(threads_num):
|
|
t = MyThread(target=_list)
|
|
threads.append(t)
|
|
t.start()
|
|
time.sleep(0.2)
|
|
for t in threads:
|
|
t.join()
|
|
|
|
|
|
class TestLoadCollection(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `collection.load()` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_load_collection_after_index(self):
|
|
"""
|
|
target: test load collection, after index created
|
|
method: insert and create index, load collection with correct params
|
|
expected: no error raised
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
data = cf.gen_default_list_data()
|
|
collection_w.insert(data)
|
|
collection_w.create_index(ct.default_float_vec_field_name, default_index_params,
|
|
index_name=ct.default_index_name)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_load_collection_after_index_binary(self):
|
|
"""
|
|
target: test load binary_collection, after index created
|
|
method: insert and create index, load binary_collection with correct params
|
|
expected: no error raised
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name, schema=default_binary_schema)
|
|
df, _ = cf.gen_default_binary_dataframe_data(ct.default_nb)
|
|
mutation_res, _ = collection_w.insert(data=df)
|
|
collection_w.create_index(ct.default_binary_vec_field_name, default_binary_index_params)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_empty_collection(self):
|
|
"""
|
|
target: test load an empty collection with no data inserted
|
|
method: no entities in collection, load and release the collection
|
|
expected: load and release successfully
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_dis_connect(self):
|
|
"""
|
|
target: test load collection, without connection
|
|
method: load collection with correct params, with a disconnected instance
|
|
expected: load raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_wr = self.init_collection_wrap(c_name)
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
collection_wr.load(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_collection_dis_connect(self):
|
|
"""
|
|
target: test release collection, without connection
|
|
method: release collection with correct params, with a disconnected instance
|
|
expected: release raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_wr = self.init_collection_wrap(c_name)
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first'}
|
|
collection_wr.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_not_existed(self):
|
|
"""
|
|
target: test load invalid collection
|
|
method: load not existed collection
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.drop()
|
|
error = {ct.err_code: 100,
|
|
ct.err_msg: "collection= : collection not found"}
|
|
collection_wr.load(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_collection_not_existed(self):
|
|
"""
|
|
target: test release a not existed collection
|
|
method: release with a not existed collection name
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.drop()
|
|
error = {ct.err_code: 100,
|
|
ct.err_msg: "collection= : collection not found"}
|
|
collection_wr.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_collection_not_load(self):
|
|
"""
|
|
target: test release collection without load
|
|
method: release collection without load
|
|
expected: release successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_load_collection_after_load_release(self):
|
|
"""
|
|
target: test load collection after load and release
|
|
method: 1.load and release collection after entities flushed
|
|
2.re-load collection
|
|
expected: No exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
insert_data = cf.gen_default_list_data()
|
|
collection_w.insert(data=insert_data)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_repeatedly(self):
|
|
"""
|
|
target: test load collection repeatedly
|
|
method: load collection twice
|
|
expected: No exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
insert_data = cf.gen_default_list_data()
|
|
collection_w.insert(data=insert_data)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load()
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_load_partitions_after_load_collection(self):
|
|
"""
|
|
target: test load partitions after load collection
|
|
method: 1. load collection
|
|
2. load partitions
|
|
3. search on one partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
self.init_partition_wrap(collection_w, partition1)
|
|
self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
collection_w.load(partition_names=[partition1, partition2])
|
|
res = collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_load_release_collection(self):
|
|
"""
|
|
target: test load partitions after load release collection
|
|
method: 1. load collection
|
|
2. release collection
|
|
3. load partitions
|
|
4. search on one partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
self.init_partition_wrap(collection_w, partition1)
|
|
self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
collection_w.load(partition_names=[partition1, partition2])
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_release_collection_partition(self):
|
|
"""
|
|
target: test load collection after release collection and partition
|
|
method: 1. load collection
|
|
2. release collection
|
|
3. release one partition
|
|
4. load collection
|
|
5. search on the partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w = self.init_partition_wrap(collection_w, partition1)
|
|
self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
partition_w.release()
|
|
collection_w.load()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_release_collection_partition(self):
|
|
"""
|
|
target: test load partitions after release collection and partition
|
|
method: 1. load collection
|
|
2. release collection
|
|
3. release partition
|
|
4. search on the partition and report error
|
|
5. load partitions
|
|
6. search on the partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
collection_w.release()
|
|
partition_w1.release()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "not loaded"})
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_release_partition(self):
|
|
"""
|
|
target: test load collection after load collection and release partition
|
|
method: 1. load collection
|
|
2. release one partition
|
|
3. search on the released partition and report error
|
|
4. search on the non-released partition and raise no exception
|
|
3. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "not loaded"})
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition2])
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_release_partition(self):
|
|
"""
|
|
target: test load collection after release partition and load partitions
|
|
method: 1. load collection
|
|
2. release partition
|
|
3. search on the released partition and report error
|
|
4. load partitions
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 1,
|
|
ct.err_msg: "not loaded"})
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_release_partition_collection(self):
|
|
"""
|
|
target: test load collection after release partition and collection
|
|
method: 1. load collection
|
|
2. release partition
|
|
3. query on the released partition and report error
|
|
3. release collection
|
|
4. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w = self.init_partition_wrap(collection_w, partition1)
|
|
self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w.release()
|
|
error = {ct.err_code: 65538, ct.err_msg: 'partition not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
collection_w.release()
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_release_partition_collection(self):
|
|
"""
|
|
target: test load partitions after release partition and collection
|
|
method: 1. load collection
|
|
2. release partition
|
|
3. release collection
|
|
4. load one partition
|
|
5. query on the other partition and raise error
|
|
6. load the other partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
collection_w.release()
|
|
partition_w1.load()
|
|
error = {ct.err_code: 65538, ct.err_msg: 'partition not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition2],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w2.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_release_partitions(self):
|
|
"""
|
|
target: test load collection after release partitions
|
|
method: 1. load collection
|
|
2. release partitions
|
|
3. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w2.release()
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_release_partitions(self):
|
|
"""
|
|
target: test load partitions after release partitions
|
|
method: 1. load collection
|
|
2. release partitions
|
|
3. load partitions
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w2.release()
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_drop_partition_and_release_another(self):
|
|
"""
|
|
target: test load collection after drop a partition and release another
|
|
method: 1. load collection
|
|
2. drop a partition
|
|
3. release left partition
|
|
4. query on the left partition
|
|
5. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.release()
|
|
error = {ct.err_code: 65538, ct.err_msg: 'partition not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition2],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partition_after_drop_partition_and_release_another(self):
|
|
"""
|
|
target: test load partition after drop a partition and release another
|
|
method: 1. load collection
|
|
2. drop a partition
|
|
3. release left partition
|
|
4. load partition
|
|
5. query on the partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.release()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_another_partition_after_drop_one_partition(self):
|
|
"""
|
|
target: test load another partition after drop a partition
|
|
method: 1. load collection
|
|
2. drop a partition
|
|
3. load another partition
|
|
4. query on the partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_drop_one_partition(self):
|
|
"""
|
|
target: test load collection after drop a partition
|
|
method: 1. load collection
|
|
2. drop a partition
|
|
3. load collection
|
|
4. query on the partition
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
collection_w.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_release_collection(self):
|
|
"""
|
|
target: test load, release non-exist collection
|
|
method: 1. load, release and drop collection
|
|
2. load and release dropped collection
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_wr.load()
|
|
collection_wr.release()
|
|
collection_wr.drop()
|
|
error = {ct.err_code: 100, ct.err_msg: "collection not found"}
|
|
collection_wr.load(check_task=CheckTasks.err_res, check_items=error)
|
|
collection_wr.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_collection_after_drop(self):
|
|
"""
|
|
target: test release collection after drop
|
|
method: insert and flush, then release collection after load and drop
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_wr.load()
|
|
collection_wr.drop()
|
|
error = {ct.err_code: 100, ct.err_msg: "collection not found"}
|
|
collection_wr.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_load_partition_names_empty(self):
|
|
"""
|
|
target: test query another partition
|
|
method: 1. insert entities into two partitions
|
|
2.query on one partition and query result empty
|
|
expected: query result is empty
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix))
|
|
partition_w = self.init_partition_wrap(collection_wrap=collection_w)
|
|
|
|
# insert [0, half) into partition_w
|
|
half = ct.default_nb // 2
|
|
df_partition = cf.gen_default_dataframe_data(nb=half)
|
|
partition_w.insert(df_partition)
|
|
# insert [half, nb) into _default
|
|
df_default = cf.gen_default_dataframe_data(nb=half, start=half)
|
|
collection_w.insert(df_default)
|
|
# flush
|
|
collection_w.num_entities
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
# load
|
|
error = {ct.err_code: 0, ct.err_msg: "due to no partition specified"}
|
|
collection_w.load(partition_names=[], check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.fixture(scope="function", params=ct.get_invalid_strs)
|
|
def get_non_number_replicas(self, request):
|
|
if request.param == 1:
|
|
pytest.skip("1 is valid replica number")
|
|
if request.param is None:
|
|
pytest.skip("None is valid replica number")
|
|
yield request.param
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.xfail(reason="issue #21618")
|
|
def test_load_replica_non_number(self, get_non_number_replicas):
|
|
"""
|
|
target: test load collection with non-number replicas
|
|
method: load with non-number replicas
|
|
expected: raise exceptions
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
# load with non-number replicas
|
|
error = {ct.err_code: 0, ct.err_msg: f"but expected one of: int, long"}
|
|
collection_w.load(replica_number=get_non_number_replicas, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("replicas", [-1, 0])
|
|
def test_load_replica_invalid_number(self, replicas):
|
|
"""
|
|
target: test load partition with invalid replica number
|
|
method: load with invalid replica number
|
|
expected: load successfully as replica = 1
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
collection_w.load(replica_number=replicas)
|
|
replicas = collection_w.get_replicas()[0]
|
|
groups = replicas.groups
|
|
assert len(groups) == 1
|
|
assert len(groups[0].shards) == 1
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("replicas", [None])
|
|
def test_load_replica_number_none(self, replicas):
|
|
"""
|
|
target: test load partition with replica number none
|
|
method: load with replica number=None
|
|
expected: raise exceptions
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
collection_w.load(replica_number=replicas,
|
|
check_task=CheckTasks.err_res,
|
|
check_items={"err_code": 1,
|
|
"err_msg": "`replica_number` value None is illegal"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_replica_greater_than_querynodes(self):
|
|
"""
|
|
target: test load with replicas that greater than querynodes
|
|
method: load with 3 replicas (2 querynode)
|
|
expected: Raise exception
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
error = {ct.err_code: 65535,
|
|
ct.err_msg: "failed to load collection: failed to spawn replica for collection: nodes not enough"}
|
|
collection_w.load(replica_number=3, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.ClusterOnly)
|
|
def test_load_replica_change(self):
|
|
"""
|
|
target: test load replica change
|
|
method: 1.load with replica 1
|
|
2.load with a new replica number
|
|
3.release collection
|
|
4.load with a new replica
|
|
5.create index is a must because get_query_segment_info could
|
|
only return indexed and loaded segment
|
|
expected: The second time successfully loaded with a new replica number
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, ct.default_index)
|
|
collection_w.load(replica_number=1)
|
|
for seg in self.utility_wrap.get_query_segment_info(collection_w.name)[0]:
|
|
assert len(seg.nodeIds) == 1
|
|
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0]")
|
|
loading_progress, _ = self.utility_wrap.loading_progress(collection_w.name)
|
|
assert loading_progress == {'loading_progress': '100%'}
|
|
|
|
# verify load different replicas thrown an exception
|
|
error = {ct.err_code: 1100, ct.err_msg: "failed to load collection: can't change the replica number for "
|
|
"loaded collection: expected=1, actual=2: invalid parameter"}
|
|
collection_w.load(replica_number=2, check_task=CheckTasks.err_res, check_items=error)
|
|
one_replica, _ = collection_w.get_replicas()
|
|
assert len(one_replica.groups) == 1
|
|
|
|
collection_w.release()
|
|
collection_w.load(replica_number=2)
|
|
# replicas is not yet reflected in loading progress
|
|
loading_progress, _ = self.utility_wrap.loading_progress(collection_w.name)
|
|
assert loading_progress == {'loading_progress': '100%'}
|
|
two_replicas, _ = collection_w.get_replicas()
|
|
assert len(two_replicas.groups) == 2
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0]", check_task=CheckTasks.check_query_results,
|
|
check_items={'exp_res': [{'int64': 0}]})
|
|
|
|
# verify loaded segments included 2 replicas and twice num entities
|
|
seg_info = self.utility_wrap.get_query_segment_info(collection_w.name)[0]
|
|
num_entities = 0
|
|
for seg in seg_info:
|
|
assert len(seg.nodeIds) == 2
|
|
num_entities += seg.num_rows
|
|
assert num_entities == ct.default_nb
|
|
|
|
@pytest.mark.tags(CaseLabel.ClusterOnly)
|
|
def test_load_replica_multi(self):
|
|
"""
|
|
target: test load with multiple replicas
|
|
method: 1.create collection with one shards
|
|
2.insert multiple segments
|
|
3.load with multiple replicas
|
|
4.query and search
|
|
expected: Query and search successfully
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix), shards_num=1)
|
|
tmp_nb = 1000
|
|
replica_number = 2
|
|
for i in range(replica_number):
|
|
df = cf.gen_default_dataframe_data(nb=tmp_nb, start=i * tmp_nb)
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == (i + 1) * tmp_nb
|
|
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load(replica_number=replica_number)
|
|
replicas = collection_w.get_replicas()[0]
|
|
assert len(replicas.groups) == replica_number
|
|
|
|
for seg in self.utility_wrap.get_query_segment_info(collection_w.name)[0]:
|
|
assert len(seg.nodeIds) == replica_number
|
|
|
|
query_res, _ = collection_w.query(expr=f"{ct.default_int64_field_name} in [0, {tmp_nb}]")
|
|
assert len(query_res) == 2
|
|
search_res, _ = collection_w.search(vectors, default_search_field, default_search_params, default_limit)
|
|
assert len(search_res[0]) == ct.default_limit
|
|
|
|
@pytest.mark.tags(CaseLabel.ClusterOnly)
|
|
def test_load_replica_partitions(self):
|
|
"""
|
|
target: test load replica with partitions
|
|
method: 1.Create collection and one partition
|
|
2.Insert data into collection and partition
|
|
3.Load multi replicas with partition
|
|
4.Query
|
|
expected: Verify query result
|
|
"""
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df_1 = cf.gen_default_dataframe_data(nb=ct.default_nb)
|
|
df_2 = cf.gen_default_dataframe_data(nb=ct.default_nb, start=ct.default_nb)
|
|
|
|
collection_w.insert(df_1)
|
|
partition_w = self.init_partition_wrap(collection_w, ct.default_tag)
|
|
partition_w.insert(df_2)
|
|
assert collection_w.num_entities == ct.default_nb * 2
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
collection_w.load([partition_w.name], replica_number=2)
|
|
for seg in self.utility_wrap.get_query_segment_info(collection_w.name)[0]:
|
|
assert len(seg.nodeIds) == 2
|
|
# default tag query 0 empty
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0]", partition_names=[ct.default_tag],
|
|
check_tasks=CheckTasks.check_query_empty)
|
|
# default query 0 empty
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [2000]",
|
|
check_task=CheckTasks.check_query_results,
|
|
check_items={'exp_res': df_2.iloc[:1, :1].to_dict('records')})
|
|
|
|
error = {ct.err_code: 65538, ct.err_msg: "partition not loaded"}
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0]",
|
|
partition_names=[ct.default_partition_name, ct.default_tag],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L3)
|
|
def test_load_replica_non_shard_leader(self):
|
|
"""
|
|
target: test replica groups which one of QN is not shard leader
|
|
method: 1.deploy cluster with 5 QNs
|
|
2.create collection with 2 shards
|
|
3.insert and flush
|
|
4.load with 2 replica number
|
|
5.insert growing data
|
|
6.search and query
|
|
expected: Verify search and query results
|
|
"""
|
|
# create and insert entities
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix), shards_num=2)
|
|
df = cf.gen_default_dataframe_data()
|
|
collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
# load with multi replica and insert growing data
|
|
collection_w.load(replica_number=2)
|
|
df_growing = cf.gen_default_dataframe_data(100, start=ct.default_nb)
|
|
collection_w.insert(df_growing)
|
|
|
|
replicas = collection_w.get_replicas()[0]
|
|
# verify there are 2 groups (2 replicas)
|
|
assert len(replicas.groups) == 2
|
|
log.debug(replicas)
|
|
all_group_nodes = []
|
|
for group in replicas.groups:
|
|
# verify each group have 3 shards
|
|
assert len(group.shards) == 2
|
|
all_group_nodes.extend(group.group_nodes)
|
|
# verify all groups has 5 querynodes
|
|
assert len(all_group_nodes) == 5
|
|
|
|
# Verify 2 replicas segments loaded
|
|
seg_info, _ = self.utility_wrap.get_query_segment_info(collection_w.name)
|
|
for seg in seg_info:
|
|
assert len(seg.nodeIds) == 2
|
|
|
|
# verify search successfully
|
|
res, _ = collection_w.search(vectors, default_search_field, default_search_params, default_limit)
|
|
assert len(res[0]) == ct.default_limit
|
|
|
|
# verify query sealed and growing data successfully
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0, {ct.default_nb}]",
|
|
check_task=CheckTasks.check_query_results,
|
|
check_items={'exp_res': [{'int64': 0}, {'int64': 3000}]})
|
|
|
|
@pytest.mark.tags(CaseLabel.L3)
|
|
def test_load_replica_multiple_shard_leader(self):
|
|
"""
|
|
target: test replica groups which one of QN is shard leader of multiple shards
|
|
method: 1.deploy cluster with 5 QNs
|
|
2.create collection with 3 shards
|
|
3.insert and flush
|
|
4.load with 2 replica number
|
|
5.insert growng data
|
|
6.search and query
|
|
expected: Verify search and query results
|
|
"""
|
|
# craete and insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix), shards_num=3)
|
|
df = cf.gen_default_dataframe_data()
|
|
collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
# load with multi replicas and insert growing data
|
|
collection_w.load(replica_number=2)
|
|
df_growing = cf.gen_default_dataframe_data(100, start=ct.default_nb)
|
|
collection_w.insert(df_growing)
|
|
|
|
# verify replica infos
|
|
replicas, _ = collection_w.get_replicas()
|
|
log.debug(replicas)
|
|
assert len(replicas.groups) == 2
|
|
all_group_nodes = []
|
|
for group in replicas.groups:
|
|
# verify each group have 3 shards
|
|
assert len(group.shards) == 3
|
|
all_group_nodes.extend(group.group_nodes)
|
|
# verify all groups has 5 querynodes
|
|
assert len(all_group_nodes) == 5
|
|
|
|
# Verify 2 replicas segments loaded
|
|
seg_info, _ = self.utility_wrap.get_query_segment_info(collection_w.name)
|
|
for seg in seg_info:
|
|
assert len(seg.nodeIds) == 2
|
|
|
|
# Verify search successfully
|
|
res, _ = collection_w.search(vectors, default_search_field, default_search_params, default_limit)
|
|
assert len(res[0]) == ct.default_limit
|
|
|
|
# Verify query sealed and growing entities successfully
|
|
collection_w.query(expr=f"{ct.default_int64_field_name} in [0, {ct.default_nb}]",
|
|
check_task=CheckTasks.check_query_results,
|
|
check_items={'exp_res': [{'int64': 0}, {'int64': 3000}]})
|
|
|
|
@pytest.mark.tags(CaseLabel.L3)
|
|
def test_load_replica_sq_count_balance(self):
|
|
"""
|
|
target: test load with multi replicas, and sq request load balance cross replicas
|
|
method: 1.Deploy milvus with multi querynodes
|
|
2.Insert entities and load with replicas
|
|
3.Do query req many times
|
|
4.Verify the querynode sq_req_count metrics
|
|
expected: Infer whether the query request is load balanced.
|
|
"""
|
|
from utils.util_k8s import get_metrics_querynode_sq_req_count
|
|
collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data(nb=5000)
|
|
mutation_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == 5000
|
|
total_sq_count = 20
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
|
|
collection_w.load(replica_number=3)
|
|
for i in range(total_sq_count):
|
|
ids = [random.randint(0, 100) for _ in range(5)]
|
|
collection_w.query(f"{ct.default_int64_field_name} in {ids}")
|
|
|
|
replicas, _ = collection_w.get_replicas()
|
|
log.debug(replicas)
|
|
sq_req_count = get_metrics_querynode_sq_req_count()
|
|
for group in replicas.groups:
|
|
group_nodes = group.group_nodes
|
|
group_sq_req_count = 0
|
|
for node in group_nodes:
|
|
group_sq_req_count += sq_req_count[node]
|
|
log.debug(f"Group nodes {group_nodes} with total sq_req_count {group_sq_req_count}")
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_get_collection_replicas_not_loaded(self):
|
|
"""
|
|
target: test get replicas of not loaded collection
|
|
method: not loaded collection and get replicas
|
|
expected: raise an exception
|
|
"""
|
|
# create, insert
|
|
collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
insert_res, _ = collection_w.insert(df)
|
|
assert collection_w.num_entities == ct.default_nb
|
|
|
|
collection_w.get_replicas(check_task=CheckTasks.err_res,
|
|
check_items={"err_code": 400,
|
|
"err_msg": "failed to get replicas by collection: "
|
|
"replica not found"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L3)
|
|
def test_count_multi_replicas(self):
|
|
"""
|
|
target: test count multi replicas
|
|
method: 1. load data with multi replicas
|
|
2. count
|
|
expected: verify count
|
|
"""
|
|
# create -> insert -> flush
|
|
collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix))
|
|
df = cf.gen_default_dataframe_data()
|
|
collection_w.insert(df)
|
|
collection_w.flush()
|
|
|
|
# index -> load replicas
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_w.load(replica_number=2)
|
|
|
|
# count
|
|
collection_w.query(expr=f'{ct.default_int64_field_name} >= 0', output_fields=[ct.default_count_output],
|
|
check_task=CheckTasks.check_query_results,
|
|
check_items={'exp_res': [{"count(*)": ct.default_nb}]})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_load_collection_without_creating_index(self):
|
|
"""
|
|
target: test drop index after load without release
|
|
method: create a collection without index, then load
|
|
expected: raise exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix, True, is_index=False)[0]
|
|
collection_w.load(check_task=CheckTasks.err_res,
|
|
check_items={"err_code": 1,
|
|
"err_msg": "index not found"})
|
|
|
|
|
|
class TestDescribeCollection(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `collection.describe` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_describe(self):
|
|
"""
|
|
target: test describe collection
|
|
method: create a collection and check its information when describe
|
|
expected: return correct information
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
collection_w = self.init_collection_wrap(name=c_name)
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
description = \
|
|
{'collection_name': c_name, 'auto_id': False, 'num_shards': ct.default_shards_num, 'description': '',
|
|
'fields': [{'field_id': 100, 'name': 'int64', 'description': '', 'type': 5, 'params': {},
|
|
'is_primary': True, 'element_type': 0},
|
|
{'field_id': 101, 'name': 'float', 'description': '', 'type': 10, 'params': {},
|
|
'element_type': 0},
|
|
{'field_id': 102, 'name': 'varchar', 'description': '', 'type': 21,
|
|
'params': {'max_length': 65535}, 'element_type': 0},
|
|
{'field_id': 103, 'name': 'json_field', 'description': '', 'type': 23, 'params': {},
|
|
'element_type': 0},
|
|
{'field_id': 104, 'name': 'float_vector', 'description': '', 'type': 101,
|
|
'params': {'dim': 128}, 'element_type': 0}],
|
|
'aliases': [], 'consistency_level': 0, 'properties': {}, 'num_partitions': 1}
|
|
res = collection_w.describe()[0]
|
|
del res['collection_id']
|
|
log.info(res)
|
|
assert description == res
|
|
|
|
|
|
class TestReleaseAdvanced(TestcaseBase):
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_release_collection_during_searching(self):
|
|
"""
|
|
target: test release collection during searching
|
|
method: insert entities into collection, flush and load collection, release collection during searching
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
data = cf.gen_default_list_data()
|
|
c_name = cf.gen_unique_str()
|
|
collection_wr = self.init_collection_wrap(name=c_name)
|
|
collection_wr.insert(data=data)
|
|
assert collection_wr.num_entities == ct.default_nb
|
|
collection_wr.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
collection_wr.load()
|
|
search_res, _ = collection_wr.search(vectors, default_search_field, default_search_params,
|
|
default_limit, _async=True)
|
|
collection_wr.release()
|
|
error = {ct.err_code: 65535, ct.err_msg: "collection not loaded"}
|
|
collection_wr.search(vectors, default_search_field, default_search_params, default_limit,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_partition_during_searching(self):
|
|
"""
|
|
target: test release partition during searching
|
|
method: insert entities into partition, flush and load partition, release partition during searching
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
partition_num = 1
|
|
collection_w = self.init_collection_general(prefix, True, 10, partition_num, is_index=False)[0]
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
par = collection_w.partitions
|
|
par_name = par[partition_num].name
|
|
par[partition_num].load()
|
|
limit = 10
|
|
collection_w.search(vectors, default_search_field,
|
|
default_search_params, limit, default_search_exp,
|
|
[par_name])
|
|
par[partition_num].release()
|
|
collection_w.search(vectors, default_search_field,
|
|
default_search_params, limit, default_search_exp,
|
|
[par_name],
|
|
check_task=CheckTasks.err_res,
|
|
check_items={"err_code": 65535,
|
|
"err_msg": "collection not loaded"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_release_indexed_collection_during_searching(self):
|
|
"""
|
|
target: test release indexed collection during searching
|
|
method: insert entities into partition, flush and load partition, release collection during searching
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
partition_num = 1
|
|
collection_w = self.init_collection_general(prefix, True, 10, partition_num, is_index=False)[0]
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
par = collection_w.partitions
|
|
par_name = par[partition_num].name
|
|
par[partition_num].load()
|
|
limit = 10
|
|
collection_w.search(vectors, default_search_field,
|
|
default_search_params, limit, default_search_exp,
|
|
[par_name], _async=True)
|
|
collection_w.release()
|
|
error = {ct.err_code: 65535, ct.err_msg: "collection not loaded"}
|
|
collection_w.search(vectors, default_search_field,
|
|
default_search_params, limit, default_search_exp,
|
|
[par_name],
|
|
check_task=CheckTasks.err_res,
|
|
check_items=error)
|
|
|
|
|
|
class TestLoadPartition(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test `load_collection` function
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.fixture(
|
|
scope="function",
|
|
params=gen_simple_index()
|
|
)
|
|
def get_simple_index(self, request, connect):
|
|
return request.param
|
|
|
|
@pytest.fixture(
|
|
scope="function",
|
|
params=gen_binary_index()
|
|
)
|
|
def get_binary_index(self, request):
|
|
log.info(request.param)
|
|
if request.param["index_type"] in ct.binary_support:
|
|
return request.param
|
|
else:
|
|
pytest.skip("Skip index Temporary")
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
@pytest.mark.parametrize('binary_index', gen_binary_index())
|
|
@pytest.mark.parametrize('metric_type', ct.binary_metrics)
|
|
def test_load_partition_after_index_binary(self, binary_index, metric_type):
|
|
"""
|
|
target: test load binary_collection, after index created
|
|
method: insert and create index, load binary_collection with correct params
|
|
expected: no error raised
|
|
"""
|
|
self._connect()
|
|
partition_num = 1
|
|
collection_w = self.init_collection_general(prefix, True, ct.default_nb, partition_num,
|
|
is_binary=True, is_index=False)[0]
|
|
|
|
# for metric_type in ct.binary_metrics:
|
|
binary_index["metric_type"] = metric_type
|
|
if binary_index["index_type"] == "BIN_IVF_FLAT" and metric_type in ct.structure_metrics:
|
|
error = {ct.err_code: 65535,
|
|
ct.err_msg: "metric type not found or not supported, supported: [HAMMING JACCARD]"}
|
|
collection_w.create_index(ct.default_binary_vec_field_name, binary_index,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
collection_w.create_index(ct.default_binary_vec_field_name, ct.default_bin_flat_index)
|
|
else:
|
|
collection_w.create_index(ct.default_binary_vec_field_name, binary_index)
|
|
par = collection_w.partitions
|
|
par[partition_num].load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partition_dis_connect(self):
|
|
"""
|
|
target: test load partition, without connection
|
|
method: load partition with correct params, with a disconnected instance
|
|
expected: load raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0}
|
|
)
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
partition_w.load()
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first.'}
|
|
partition_w.load(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_partition_dis_connect(self):
|
|
"""
|
|
target: test release collection, without connection
|
|
method: release collection with correct params, with a disconnected instance
|
|
expected: release raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0}
|
|
)
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
partition_w.load()
|
|
self.connection_wrap.remove_connection(ct.default_alias)
|
|
res_list, _ = self.connection_wrap.list_connections()
|
|
assert ct.default_alias not in res_list
|
|
error = {ct.err_code: 0, ct.err_msg: 'should create connect first.'}
|
|
partition_w.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partition_not_existed(self):
|
|
"""
|
|
target: test load partition for invalid scenario
|
|
method: load not existed partition
|
|
expected: raise exception and report the error
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0})
|
|
collection_w.create_index(ct.default_float_vec_field_name, index_params=ct.default_flat_index)
|
|
partition_w.drop()
|
|
error = {ct.err_code: 200, ct.err_msg: 'partition not found[partition=%s]' % partition_name}
|
|
partition_w.load(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_release_partition_not_load(self):
|
|
"""
|
|
target: test release partition without load
|
|
method: release partition without load
|
|
expected: release success
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0})
|
|
partition_w.release()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_release_after_drop(self):
|
|
"""
|
|
target: test load and release partition after drop
|
|
method: drop partition and then load and release it
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0})
|
|
partition_w.drop()
|
|
collection_w.create_index(ct.default_float_vec_field_name)
|
|
error = {ct.err_code: 200, ct.err_msg: 'partition not found[partition=%s]' % partition_name}
|
|
partition_w.load(check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_release_partition_after_drop(self):
|
|
"""
|
|
target: test release collection after drop
|
|
method: insert and flush, then release collection after load and drop
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0})
|
|
partition_w.drop()
|
|
error = {ct.err_code: 200, ct.err_msg: 'partition not found[partition=%s]' % partition_name}
|
|
partition_w.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_load_release_after_collection_drop(self):
|
|
"""
|
|
target: test release collection after drop
|
|
method: insert and flush, then release collection after load and drop
|
|
expected: raise exception
|
|
"""
|
|
self._connect()
|
|
collection_w = self.init_collection_wrap()
|
|
name = collection_w.name
|
|
partition_name = cf.gen_unique_str(prefix)
|
|
description = cf.gen_unique_str("desc_")
|
|
partition_w = self.init_partition_wrap(collection_w, partition_name,
|
|
description=description,
|
|
check_task=CheckTasks.check_partition_property,
|
|
check_items={"name": partition_name, "description": description,
|
|
"is_empty": True, "num_entities": 0})
|
|
collection_w.drop()
|
|
error = {ct.err_code: 0, ct.err_msg: "collection not found"}
|
|
partition_w.load(check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w.release(check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_loaded_partition(self):
|
|
"""
|
|
target: test load partition after load partition
|
|
method: 1. load partition
|
|
2. load the partition again
|
|
3. query on the non-loaded partition
|
|
4. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.load()
|
|
error = {ct.err_code: 65538,
|
|
ct.err_msg: 'partition not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition2],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_unloaded_partition(self):
|
|
"""
|
|
target: test load partition after load an unloaded partition
|
|
method: 1. load partition
|
|
2. load another partition
|
|
3. query on the collection
|
|
4. load collection
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr)
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_one_partition(self):
|
|
"""
|
|
target: test load partition after load partition
|
|
method: 1. load partition
|
|
2. load collection
|
|
3. query on the partitions
|
|
expected: No exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition1, partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
def test_load_partitions_release_collection(self):
|
|
"""
|
|
target: test release collection after load partitions
|
|
method: 1. load partition
|
|
2. release collection
|
|
3. query on the partition
|
|
4. load partitions
|
|
5. query on the collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
collection_w.release()
|
|
error = {ct.err_code: 65535, ct.err_msg: "collection not loaded"}
|
|
collection_w.query(default_term_expr, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_release_collection(self):
|
|
"""
|
|
target: test load collection after load partitions
|
|
method: 1. load partition
|
|
2. release collection
|
|
3. load collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
collection_w.release()
|
|
collection_w.load()
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_load_release_partition(self):
|
|
"""
|
|
target: test load partitions after load and release partition
|
|
method: 1. load partition
|
|
2. release partition
|
|
3. query on the partition
|
|
4. load partitions(include released partition and non-released partition)
|
|
5. query on the collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
error = {ct.err_code: 65535,
|
|
ct.err_msg: 'collection not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_release_partition(self):
|
|
"""
|
|
target: test load collection after load and release partition
|
|
method: 1. load partition
|
|
2. release partition
|
|
3. load collection
|
|
4. search on the collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
collection_w.load()
|
|
collection_w.search(vectors, default_search_field, default_search_params,
|
|
default_limit, partition_names=[partition1, partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partitions_after_load_partition_release_partitions(self):
|
|
"""
|
|
target: test load partitions after load partition and release partitions
|
|
method: 1. load partition
|
|
2. release partitions
|
|
3. load partitions
|
|
4. query on the partitions
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w2.release()
|
|
partition_w1.load()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition1, partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_partition_release_partitions(self):
|
|
"""
|
|
target: test load collection after load partition and release partitions
|
|
method: 1. load partition
|
|
2. release partitions
|
|
3. query on the partitions
|
|
4. load collection
|
|
5. query on the partitions
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w2.release()
|
|
error = {ct.err_code: 65535,
|
|
ct.err_msg: 'collection not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition1, partition2],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition1, partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_partition_after_load_drop_partition(self):
|
|
"""
|
|
target: test load partition after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the loaded partition
|
|
3. load the left partition
|
|
4. query on the partition
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_collection_after_load_drop_partition(self):
|
|
"""
|
|
target: test load collection after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the loaded partition
|
|
3. query on the partition
|
|
4. drop another partition
|
|
5. load collection
|
|
6. query on the collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
error = {ct.err_code: 65535, ct.err_msg: f'partition name {partition1} not found'}
|
|
collection_w.query(default_term_expr, partition_names=[partition1, partition2],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w2.drop()
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_load_partition_after_load_drop_partition(self):
|
|
"""
|
|
target: test release load partition after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the loaded partition
|
|
3. release another partition
|
|
4. load the partition
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.release()
|
|
partition_w2.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition2])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_load_collection_after_load_drop_partition(self):
|
|
"""
|
|
target: test release load partition after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the loaded partition
|
|
3. release another partition
|
|
4. load collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w1.release()
|
|
partition_w1.drop()
|
|
partition_w2.release()
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_load_another_partition_after_load_drop_partition(self):
|
|
"""
|
|
target: test load another collection after load and drop one partition
|
|
method: 1. load partition
|
|
2. drop the unloaded partition
|
|
3. load the partition again
|
|
4. query on the partition
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w2.drop()
|
|
partition_w1.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_load_partition_after_load_partition_drop_another(self):
|
|
"""
|
|
target: test release load partition after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the unloaded partition
|
|
3. release the loaded partition
|
|
4. query on the released partition
|
|
5. reload the partition
|
|
6. query on the partition
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w2.drop()
|
|
partition_w1.release()
|
|
error = {ct.err_code: 65535,
|
|
ct.err_msg: 'collection not loaded'}
|
|
collection_w.query(default_term_expr, partition_names=[partition1],
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
partition_w1.load()
|
|
collection_w.query(default_term_expr, partition_names=[partition1])
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_load_collection_after_load_partition_drop_another(self):
|
|
"""
|
|
target: test release load partition after load and drop partition
|
|
method: 1. load partition
|
|
2. drop the unloaded partition
|
|
3. release the loaded partition
|
|
4. load collection
|
|
5. query on the collection
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w2.drop()
|
|
partition_w1.release()
|
|
collection_w.load()
|
|
collection_w.query(default_term_expr)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_release_unloaded_partition(self):
|
|
"""
|
|
target: test load collection after load and drop partition
|
|
method: 1. load partition
|
|
2. release the other partition
|
|
3. query on the first partition
|
|
expected: no exception
|
|
"""
|
|
collection_w = self.init_collection_general(prefix)[0]
|
|
partition_w1 = self.init_partition_wrap(collection_w, partition1)
|
|
partition_w2 = self.init_partition_wrap(collection_w, partition2)
|
|
partition_w1.load()
|
|
partition_w2.release()
|
|
collection_w.query(default_term_expr, partition_names=[partition1])
|
|
|
|
|
|
class TestCollectionString(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test about string
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_string_field_is_primary(self):
|
|
"""
|
|
target: test create collection with string field
|
|
method: 1. create collection with string field and vector field
|
|
2. set string fields is_primary=True
|
|
expected: Create collection successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_string_pk_default_collection_schema()
|
|
self.collection_wrap.init_collection(name=c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_with_muti_string_fields(self):
|
|
"""
|
|
target: test create collection with muti string fields
|
|
method: 1. create collection with primary string field and not primary string field
|
|
2. string fields is_primary=True
|
|
expected: Create collection successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field = cf.gen_int64_field()
|
|
vec_field = cf.gen_float_vec_field()
|
|
string_field_1 = cf.gen_string_field(is_primary=True)
|
|
string_field_2 = cf.gen_string_field(name=c_name)
|
|
schema = cf.gen_collection_schema(fields=[int_field, string_field_1, string_field_2, vec_field])
|
|
self.collection_wrap.init_collection(name=c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_only_string_field(self):
|
|
"""
|
|
target: test create collection with one string field
|
|
method: create collection with only string field
|
|
expected: Raise exception
|
|
"""
|
|
self._connect()
|
|
string_field = cf.gen_string_field(is_primary=True)
|
|
schema = cf.gen_collection_schema([string_field])
|
|
error = {ct.err_code: 0, ct.err_msg: "No vector field is found"}
|
|
self.collection_wrap.init_collection(name=cf.gen_unique_str(prefix), schema=schema,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_string_field_with_exceed_max_len(self):
|
|
"""
|
|
target: test create collection with string field
|
|
method: 1. create collection with string field
|
|
2. String field max_length exceeds maximum
|
|
expected: Raise exception
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
max_length = 100000
|
|
string_field = cf.gen_string_field(max_length=max_length)
|
|
schema = cf.gen_collection_schema([int_field, string_field, vec_field])
|
|
error = {ct.err_code: 65535, ct.err_msg: "the maximum length specified for a VarChar should be in (0, 65535]"}
|
|
self.collection_wrap.init_collection(name=c_name, schema=schema,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_invalid_string_field_dtype(self):
|
|
"""
|
|
target: test create collection with string field
|
|
method: create collection with string field, the string field datatype is invaild
|
|
expected: Raise exception
|
|
"""
|
|
self._connect()
|
|
string_field = self.field_schema_wrap.init_field_schema(name="string", dtype=DataType.STRING)[0]
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
schema = cf.gen_collection_schema(fields=[int_field, string_field, vec_field])
|
|
error = {ct.err_code: 0, ct.err_msg: "string data type not supported yet, please use VarChar type instead"}
|
|
self.collection_wrap.init_collection(name=cf.gen_unique_str(prefix), schema=schema,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
def test_collection_string_field_is_primary_and_auto_id(self):
|
|
"""
|
|
target: test create collection with string field
|
|
method: create collection with string field, the string field primary and auto id are true
|
|
expected: Create collection successfully
|
|
"""
|
|
self._connect()
|
|
int_field = cf.gen_int64_field()
|
|
vec_field = cf.gen_float_vec_field()
|
|
string_field = cf.gen_string_field(is_primary=True, auto_id=True)
|
|
fields = [int_field, string_field, vec_field]
|
|
schema = self.collection_schema_wrap.init_collection_schema(fields=fields)[0]
|
|
self.init_collection_wrap(schema=schema, check_task=CheckTasks.check_collection_property,
|
|
check_items={"schema": schema, "primary": ct.default_string_field_name})
|
|
|
|
|
|
class TestCollectionJSON(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test about json
|
|
******************************************************************
|
|
"""
|
|
@pytest.mark.tags(CaseLabel.L1)
|
|
@pytest.mark.parametrize("auto_id", [True, False])
|
|
def test_collection_json_field_as_primary_key(self, auto_id):
|
|
"""
|
|
target: test create collection with JSON field as primary key
|
|
method: 1. create collection with one JSON field, and vector field
|
|
2. set json field is_primary=true
|
|
3. set auto_id as true
|
|
expected: Raise exception (not supported)
|
|
"""
|
|
self._connect()
|
|
int_field = cf.gen_int64_field()
|
|
vec_field = cf.gen_float_vec_field()
|
|
string_field = cf.gen_string_field()
|
|
# 1. create json field as primary key through field schema api
|
|
error = {ct.err_code: 1, ct.err_msg: "Primary key type must be DataType.INT64 or DataType.VARCHAR"}
|
|
json_field = cf.gen_json_field(is_primary=True, auto_id=auto_id)
|
|
fields = [int_field, string_field, json_field, vec_field]
|
|
self.collection_schema_wrap.init_collection_schema(fields=fields,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
# 2. create json field as primary key through collection schema api
|
|
json_field = cf.gen_json_field()
|
|
fields = [int_field, string_field, json_field, vec_field]
|
|
self.collection_schema_wrap.init_collection_schema(fields=fields, primary_field=ct.default_json_field_name,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_field", [ct.default_float_field_name, ct.default_json_field_name])
|
|
def test_collection_json_field_partition_key(self, primary_field):
|
|
"""
|
|
target: test create collection with multiple JSON fields
|
|
method: 1. create collection with multiple JSON fields, primary key field and vector field
|
|
2. set json field is_primary=false
|
|
expected: Raise exception
|
|
"""
|
|
self._connect()
|
|
cf.gen_unique_str(prefix)
|
|
error = {ct.err_code: 1, ct.err_msg: "Partition key field type must be DataType.INT64 or DataType.VARCHAR."}
|
|
cf.gen_json_default_collection_schema(primary_field=primary_field, is_partition_key=True,
|
|
check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L0)
|
|
@pytest.mark.parametrize("primary_field", [ct.default_int64_field_name, ct.default_string_field_name])
|
|
def test_collection_json_field_supported_primary_key(self, primary_field):
|
|
"""
|
|
target: test create collection with one JSON field
|
|
method: 1. create collection with one JSON field, primary key field and vector field
|
|
2. set json field is_primary=false
|
|
expected: Create collection successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_json_default_collection_schema(primary_field=primary_field)
|
|
self.collection_wrap.init_collection(name=c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("primary_field", [ct.default_int64_field_name, ct.default_string_field_name])
|
|
def test_collection_multiple_json_fields_supported_primary_key(self, primary_field):
|
|
"""
|
|
target: test create collection with multiple JSON fields
|
|
method: 1. create collection with multiple JSON fields, primary key field and vector field
|
|
2. set json field is_primary=false
|
|
expected: Create collection successfully
|
|
"""
|
|
self._connect()
|
|
c_name = cf.gen_unique_str(prefix)
|
|
schema = cf.gen_multiple_json_default_collection_schema(primary_field=primary_field)
|
|
self.collection_wrap.init_collection(name=c_name, schema=schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_name: c_name, exp_schema: schema})
|
|
|
|
|
|
class TestCollectionARRAY(TestcaseBase):
|
|
"""
|
|
******************************************************************
|
|
The following cases are used to test about array
|
|
******************************************************************
|
|
"""
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_array_field_element_type_not_exist(self):
|
|
"""
|
|
target: test create collection with ARRAY field without element type
|
|
method: create collection with one array field without element type
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(element_type=None)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 65535, ct.err_msg: "element data type None is not valid"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
# @pytest.mark.skip("issue #27522")
|
|
@pytest.mark.parametrize("element_type", [1001, 'a', [], (), {1}, DataType.BINARY_VECTOR,
|
|
DataType.FLOAT_VECTOR, DataType.JSON, DataType.ARRAY])
|
|
def test_collection_array_field_element_type_invalid(self, element_type):
|
|
"""
|
|
target: Create a field with invalid element_type
|
|
method: Create a field with invalid element_type
|
|
1. Type not in DataType: 1, 'a', ...
|
|
2. Type in DataType: binary_vector, float_vector, json_field, array_field
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(element_type=element_type)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
error = {ct.err_code: 65535, ct.err_msg: "element data type None is not valid"}
|
|
if element_type in ['a', {1}]:
|
|
error = {ct.err_code: 1, ct.err_msg: "Unexpected error"}
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res, check_items=error)
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_array_field_no_capacity(self):
|
|
"""
|
|
target: Create a field without giving max_capacity
|
|
method: Create a field without giving max_capacity
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(max_capacity=None)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 65535,
|
|
ct.err_msg: "the value of max_capacity must be an integer"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("max_capacity", [[], 'a', (), -1, 4097])
|
|
def test_collection_array_field_invalid_capacity(self, max_capacity):
|
|
"""
|
|
target: Create a field with invalid max_capacity
|
|
method: Create a field with invalid max_capacity
|
|
1. Type invalid: [], 'a', ()
|
|
2. Value invalid: <0, >max_capacity(4096)
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(max_capacity=max_capacity)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 65535,
|
|
ct.err_msg: "the maximum capacity specified for a "
|
|
"Array should be in (0, 4096]"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_string_array_without_max_length(self):
|
|
"""
|
|
target: Create string array without giving max length
|
|
method: Create string array without giving max length
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(element_type=DataType.VARCHAR)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 65535,
|
|
ct.err_msg: "type param(max_length) should be specified for "
|
|
"varChar field of collection"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
@pytest.mark.parametrize("max_length", [[], 'a', (), -1, 65536])
|
|
def test_collection_string_array_max_length_invalid(self, max_length):
|
|
"""
|
|
target: Create string array with invalid max length
|
|
method: Create string array with invalid max length
|
|
1. Type invalid: [], 'a', ()
|
|
2. Value invalid: <0, >max_length(65535)
|
|
expected: Raise exception
|
|
"""
|
|
int_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
array_field = cf.gen_array_field(element_type=DataType.VARCHAR, max_length=max_length)
|
|
array_schema = cf.gen_collection_schema([int_field, vec_field, array_field])
|
|
self.init_collection_wrap(schema=array_schema, check_task=CheckTasks.err_res,
|
|
check_items={ct.err_code: 65535,
|
|
ct.err_msg: "the maximum length specified for a VarChar "
|
|
"should be in (0, 65535]"})
|
|
|
|
@pytest.mark.tags(CaseLabel.L2)
|
|
def test_collection_array_field_all_datatype(self):
|
|
"""
|
|
target: test create collection with ARRAY field all data type
|
|
method: 1. Create field respectively: int8, int16, int32, int64, varchar, bool, float, double
|
|
2. Insert data respectively: int8, int16, int32, int64, varchar, bool, float, double
|
|
expected: Raise exception
|
|
"""
|
|
# Create field respectively
|
|
nb = ct.default_nb
|
|
pk_field = cf.gen_int64_field(is_primary=True)
|
|
vec_field = cf.gen_float_vec_field()
|
|
int8_array = cf.gen_array_field(name="int8_array", element_type=DataType.INT8, max_capacity=nb)
|
|
int16_array = cf.gen_array_field(name="int16_array", element_type=DataType.INT16, max_capacity=nb)
|
|
int32_array = cf.gen_array_field(name="int32_array", element_type=DataType.INT32, max_capacity=nb)
|
|
int64_array = cf.gen_array_field(name="int64_array", element_type=DataType.INT64, max_capacity=nb)
|
|
bool_array = cf.gen_array_field(name="bool_array", element_type=DataType.BOOL, max_capacity=nb)
|
|
float_array = cf.gen_array_field(name="float_array", element_type=DataType.FLOAT, max_capacity=nb)
|
|
double_array = cf.gen_array_field(name="double_array", element_type=DataType.DOUBLE, max_capacity=nb)
|
|
string_array = cf.gen_array_field(name="string_array", element_type=DataType.VARCHAR, max_capacity=nb,
|
|
max_length=100)
|
|
array_schema = cf.gen_collection_schema([pk_field, vec_field, int8_array, int16_array, int32_array,
|
|
int64_array, bool_array, float_array, double_array, string_array])
|
|
collection_w = self.init_collection_wrap(schema=array_schema,
|
|
check_task=CheckTasks.check_collection_property,
|
|
check_items={exp_schema: array_schema})
|
|
|
|
# check array in collection.describe()
|
|
res = collection_w.describe()[0]
|
|
log.info(res)
|
|
fields = [
|
|
{"field_id": 100, "name": "int64", "description": "", "type": 5, "params": {},
|
|
"element_type": 0, "is_primary": True},
|
|
{"field_id": 101, "name": "float_vector", "description": "", "type": 101,
|
|
"params": {"dim": ct.default_dim}, "element_type": 0},
|
|
{"field_id": 102, "name": "int8_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 2},
|
|
{"field_id": 103, "name": "int16_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 3},
|
|
{"field_id": 104, "name": "int32_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 4},
|
|
{"field_id": 105, "name": "int64_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 5},
|
|
{"field_id": 106, "name": "bool_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 1},
|
|
{"field_id": 107, "name": "float_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 10},
|
|
{"field_id": 108, "name": "double_array", "description": "", "type": 22,
|
|
"params": {"max_capacity": "2000"}, "element_type": 11},
|
|
{"field_id": 109, "name": "string_array", "description": "", "type": 22,
|
|
"params": {"max_length": "100", "max_capacity": "2000"}, "element_type": 21}
|
|
]
|
|
assert res["fields"] == fields
|
|
|
|
# Insert data respectively
|
|
nb = 10
|
|
pk_values = [i for i in range(nb)]
|
|
float_vec = cf.gen_vectors(nb, ct.default_dim)
|
|
int8_values = [[numpy.int8(j) for j in range(nb)] for i in range(nb)]
|
|
int16_values = [[numpy.int16(j) for j in range(nb)] for i in range(nb)]
|
|
int32_values = [[numpy.int32(j) for j in range(nb)] for i in range(nb)]
|
|
int64_values = [[numpy.int64(j) for j in range(nb)] for i in range(nb)]
|
|
bool_values = [[numpy.bool_(j) for j in range(nb)] for i in range(nb)]
|
|
float_values = [[numpy.float32(j) for j in range(nb)] for i in range(nb)]
|
|
double_values = [[numpy.double(j) for j in range(nb)] for i in range(nb)]
|
|
string_values = [[str(j) for j in range(nb)] for i in range(nb)]
|
|
data = [pk_values, float_vec, int8_values, int16_values, int32_values, int64_values,
|
|
bool_values, float_values, double_values, string_values]
|
|
collection_w.insert(data)
|
|
|
|
# check insert successfully
|
|
collection_w.flush()
|
|
collection_w.num_entities == nb
|
|
|
|
|
|
class TestCollectionMultipleVectorValid(TestcaseBase):
|
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"""
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******************************************************************
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# The followings are valid cases
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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.parametrize("primary_key", [cf.gen_int64_field(is_primary=True), cf.gen_string_field(is_primary=True)])
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@pytest.mark.parametrize("auto_id", [True, False])
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@pytest.mark.parametrize("shards_num", [1, 3])
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def test_create_collection_multiple_vectors_all_supported_field_type(self, primary_key, auto_id, shards_num):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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vector_limit_num = max_vector_field_num - 2
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# add multiple vector fields
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for i in range(vector_limit_num):
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vector_field_name = cf.gen_unique_str("field_name")
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field = cf.gen_float_vec_field(name=vector_field_name)
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int_fields.append(field)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int8_field())
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int_fields.append(cf.gen_int16_field())
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int_fields.append(cf.gen_int32_field())
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int_fields.append(cf.gen_float_field())
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int_fields.append(cf.gen_double_field())
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int_fields.append(cf.gen_string_field(cf.gen_unique_str("vchar_field_name")))
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int_fields.append(cf.gen_json_field())
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int_fields.append(cf.gen_bool_field())
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int_fields.append(cf.gen_array_field())
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int_fields.append(cf.gen_binary_vec_field())
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int_fields.append(primary_key)
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schema = cf.gen_collection_schema(fields=int_fields, auto_id=auto_id, shards_num=shards_num)
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("primary_key", [ct.default_int64_field_name, ct.default_string_field_name])
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@pytest.mark.parametrize("auto_id", [True, False])
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@pytest.mark.parametrize("enable_dynamic_field", [True, False])
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def test_create_collection_multiple_vectors_different_dim(self, primary_key, auto_id, enable_dynamic_field):
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"""
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target: test create collection with multiple vector fields (different dim)
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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another_dim = 1
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schema = cf.gen_default_collection_schema(primary_field=primary_key, auto_id=auto_id, dim=ct.max_dim,
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enable_dynamic_field=enable_dynamic_field,
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multiple_dim_array=[another_dim])
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("primary_key", [ct.default_int64_field_name, ct.default_string_field_name])
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def test_create_collection_multiple_vectors_maximum_dim(self, primary_key):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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schema = cf.gen_default_collection_schema(primary_field=primary_key, dim=ct.max_dim,
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multiple_dim_array=[ct.max_dim])
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})
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@pytest.mark.tags(CaseLabel.L2)
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@pytest.mark.parametrize("primary_key", [cf.gen_int64_field(is_primary=True), cf.gen_string_field(is_primary=True)])
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@pytest.mark.parametrize("auto_id", [True, False])
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@pytest.mark.parametrize("par_key_field", [ct.default_int64_field_name, ct.default_string_field_name])
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def test_create_collection_multiple_vectors_partition_key(self, primary_key, auto_id, par_key_field):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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vector_limit_num = max_vector_field_num - 2
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# add multiple vector fields
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for i in range(vector_limit_num):
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vector_field_name = cf.gen_unique_str("field_name")
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field = cf.gen_float_vec_field(name=vector_field_name)
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int_fields.append(field)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int8_field())
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int_fields.append(cf.gen_int16_field())
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int_fields.append(cf.gen_int32_field())
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int_fields.append(cf.gen_int64_field(cf.gen_unique_str("int_field_name"),
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is_partition_key=(par_key_field == ct.default_int64_field_name)))
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int_fields.append(cf.gen_float_field())
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int_fields.append(cf.gen_double_field())
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int_fields.append(cf.gen_string_field(cf.gen_unique_str("vchar_field_name"),
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is_partition_key=(par_key_field == ct.default_string_field_name)))
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int_fields.append(cf.gen_json_field())
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int_fields.append(cf.gen_bool_field())
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int_fields.append(cf.gen_array_field())
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int_fields.append(cf.gen_binary_vec_field())
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int_fields.append(primary_key)
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schema = cf.gen_collection_schema(fields=int_fields, auto_id=auto_id)
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collection_w = \
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.check_collection_property,
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check_items={exp_name: c_name, exp_schema: schema})[0]
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assert len(collection_w.partitions) == ct.default_partition_num
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class TestCollectionMultipleVectorInvalid(TestcaseBase):
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""" Test case of search interface """
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@pytest.fixture(scope="function", params=ct.get_invalid_strs)
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def get_invalid_dim(self, request):
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if request.param == 1:
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pytest.skip("1 is valid dim")
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yield request.param
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"""
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******************************************************************
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# The followings are invalid cases
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******************************************************************
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"""
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.parametrize("primary_key", [cf.gen_int64_field(is_primary=True), cf.gen_string_field(is_primary=True)])
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def test_create_collection_multiple_vectors_same_vector_field_name(self, primary_key):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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vector_limit_num = max_vector_field_num - 2
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# add multiple vector fields
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for i in range(vector_limit_num):
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field = cf.gen_float_vec_field()
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int_fields.append(field)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int8_field())
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int_fields.append(cf.gen_int16_field())
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int_fields.append(cf.gen_int32_field())
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int_fields.append(cf.gen_float_field())
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int_fields.append(cf.gen_double_field())
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int_fields.append(cf.gen_string_field(cf.gen_unique_str("vchar_field_name")))
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int_fields.append(cf.gen_json_field())
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int_fields.append(cf.gen_bool_field())
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int_fields.append(cf.gen_array_field())
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int_fields.append(cf.gen_binary_vec_field())
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int_fields.append(primary_key)
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schema = cf.gen_collection_schema(fields=int_fields)
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error = {ct.err_code: 65535, ct.err_msg: "duplicated field name"}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.parametrize("invalid_vector_name", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
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def test_create_collection_multiple_vectors_invalid_part_vector_field_name(self, invalid_vector_name):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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# add multiple vector fields
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vector_field_1 = cf.gen_float_vec_field(name=invalid_vector_name)
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int_fields.append(vector_field_1)
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vector_field_2 = cf.gen_float_vec_field(name="valid_field_name")
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int_fields.append(vector_field_2)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int64_field(is_primary=True))
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schema = cf.gen_collection_schema(fields=int_fields)
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error = {ct.err_code: 1701, ct.err_msg: "Invalid field name: %s" % invalid_vector_name}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.parametrize("invalid_vector_name", ["12-s", "12 s", "(mn)", "中文", "%$#", "a".join("a" for i in range(256))])
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def test_create_collection_multiple_vectors_invalid_all_vector_field_name(self, invalid_vector_name):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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# add multiple vector fields
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vector_field_1 = cf.gen_float_vec_field(name=invalid_vector_name)
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int_fields.append(vector_field_1)
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vector_field_2 = cf.gen_float_vec_field(name=invalid_vector_name + " ")
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int_fields.append(vector_field_2)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int64_field(is_primary=True))
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schema = cf.gen_collection_schema(fields=int_fields)
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error = {ct.err_code: 1701, ct.err_msg: "Invalid field name: %s" % invalid_vector_name}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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@pytest.mark.tags(CaseLabel.L1)
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@pytest.mark.xfail(reason="issue #29796")
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def test_create_collection_multiple_vectors_invalid_dim(self, get_invalid_dim):
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"""
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target: test create collection with multiple vector fields
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method: create collection with multiple vector fields
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expected: no exception
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"""
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self._connect()
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c_name = cf.gen_unique_str(prefix)
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int_fields = []
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# add multiple vector fields
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vector_field_1 = cf.gen_float_vec_field(dim=get_invalid_dim)
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int_fields.append(vector_field_1)
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vector_field_2 = cf.gen_float_vec_field(name="float_vec_field")
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int_fields.append(vector_field_2)
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# add other vector fields to maximum fields num
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int_fields.append(cf.gen_int64_field(is_primary=True))
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schema = cf.gen_collection_schema(fields=int_fields)
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error = {ct.err_code: 65535, ct.err_msg: "Invalid dim"}
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self.collection_wrap.init_collection(c_name, schema=schema, check_task=CheckTasks.err_res, check_items=error)
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