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Add test for numpy files in diff folders (#17175)
Signed-off-by: yanliang567 <yanliang.qiao@zilliz.com>
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@ -847,11 +847,10 @@ class TestBulkLoad(TestcaseBase):
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"limit": 1})
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@pytest.mark.tags(CaseLabel.L3)
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@pytest.mark.parametrize("auto_id", [True])
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@pytest.mark.parametrize("auto_id", [True, False])
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@pytest.mark.parametrize("dim", [6])
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@pytest.mark.parametrize("entities", [10])
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@pytest.mark.parametrize("file_nums", [2]) # 32, max task nums 32? need improve
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@pytest.mark.xfail(reason="only one numpy file imported successfully, issue #16992")
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@pytest.mark.parametrize("entities", [1000])
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@pytest.mark.parametrize("file_nums", [10])
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def test_multi_numpy_files_from_diff_folders(self, auto_id, dim, entities, file_nums):
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"""
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collection schema 1: [pk, float_vector]
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@ -859,18 +858,10 @@ class TestBulkLoad(TestcaseBase):
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Steps:
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1. create collection
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2. import data
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3. if row_based: verify import failed
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4. if column_based:
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4.1 verify the data entities equal the import data
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4.2 verify search and query successfully
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3. verify that import numpy files in a loop
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"""
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row_based = False # numpy files supports only column based
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data_fields = [df.vec_field]
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if not auto_id:
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data_fields.append(df.pk_field)
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files = prepare_bulk_load_numpy_files(rows=entities, dim=dim,
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data_fields=data_fields,
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file_nums=file_nums, force=True)
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self._connect()
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c_name = cf.gen_unique_str()
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fields = [cf.gen_int64_field(name=df.pk_field, is_primary=True),
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@ -882,16 +873,22 @@ class TestBulkLoad(TestcaseBase):
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self.collection_wrap.create_index(field_name=df.vec_field, index_params=index_params)
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# load collection
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self.collection_wrap.load()
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t0 = time.time()
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task_ids, _ = self.utility_wrap.bulk_load(collection_name=c_name,
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row_based=row_based,
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files=files)
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data_fields = [df.vec_field]
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if not auto_id:
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data_fields.append(df.pk_field)
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for i in range(file_nums):
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files = prepare_bulk_load_numpy_files(rows=entities, dim=dim,
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data_fields=data_fields,
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file_nums=1, force=True)
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task_ids, _ = self.utility_wrap.bulk_load(collection_name=c_name,
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row_based=row_based,
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files=files)
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success, states = self.utility_wrap.\
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wait_for_bulk_load_tasks_completed(task_ids=task_ids,
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target_state=BulkLoadStates.BulkLoadPersisted,
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timeout=30)
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tt = time.time() - t0
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log.info(f"bulk load state:{success} in {tt}")
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log.info(f"bulk load state:{success}")
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assert success
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log.info(f" collection entities: {self.collection_wrap.num_entities}")
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@ -1734,6 +1731,51 @@ class TestBulkLoadInvalidParams(TestcaseBase):
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# res, _ = self.collection_wrap.query(expr=f"{float_field} in [1.0]", output_fields=[float_field])
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# assert res[0].get(float_field, 0) == 1.0
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@pytest.mark.tags(CaseLabel.L3)
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@pytest.mark.parametrize("auto_id", [True, False])
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@pytest.mark.parametrize("dim", [6])
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@pytest.mark.parametrize("entities", [10])
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@pytest.mark.parametrize("file_nums", [2])
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def test_multi_numpy_files_from_diff_folders_in_one_request(self, auto_id, dim, entities, file_nums):
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"""
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collection schema 1: [pk, float_vector]
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data file: .npy files in different folders
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Steps:
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1. create collection
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2. import data
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3. fail to import data with errors
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"""
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row_based = False # numpy files supports only column based
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data_fields = [df.vec_field]
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if not auto_id:
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data_fields.append(df.pk_field)
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files = prepare_bulk_load_numpy_files(rows=entities, dim=dim,
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data_fields=data_fields,
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file_nums=file_nums, force=True)
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self._connect()
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c_name = cf.gen_unique_str()
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fields = [cf.gen_int64_field(name=df.pk_field, is_primary=True),
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cf.gen_float_vec_field(name=df.vec_field, dim=dim)]
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schema = cf.gen_collection_schema(fields=fields, auto_id=auto_id)
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self.collection_wrap.init_collection(c_name, schema=schema)
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t0 = time.time()
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task_ids, _ = self.utility_wrap.bulk_load(collection_name=c_name,
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row_based=row_based,
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files=files)
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success, states = self.utility_wrap. \
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wait_for_bulk_load_tasks_completed(task_ids=task_ids,
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target_state=BulkLoadStates.BulkLoadPersisted,
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timeout=30)
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tt = time.time() - t0
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log.info(f"bulk load state:{success} in {tt}")
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assert not success
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failed_reason = "duplicate file"
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for state in states.values():
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assert state.state_name == "BulkLoadFailed"
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assert failed_reason in state.infos.get("failed_reason", "")
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assert self.collection_wrap.num_entities == 0
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# TODO: string data on float field
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@ -1810,6 +1852,4 @@ class TestBulkLoadAdvanced(TestcaseBase):
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"limit": 1})
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# self.collection_wrap.query(expr=f"id in {ids}")
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"""Validate data consistency and availability during import"""
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"""Validate data consistency and availability during import"""
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