run test for milvus faile with error pymilvus.exceptions.DataTypeNotSupportException

[zhuwenxing]

commit

commit 804b2974ae14d4c9815414a302fcdcbba624ca30 (HEAD -> add_mongodb)
Author: zhuwenxing <[email protected]>
Date:   Thu Jan 9 15:33:10 2025 +0800

    Revert "enhance: Refine the coding style and enable lint-action"
    
    This reverts commit 032515f9f066398a8fc6c31c0e8c33ed43a0f446.

commit 032515f9f066398a8fc6c31c0e8c33ed43a0f446 (upstream/main)
Author: yangxuan <[email protected]>
Date:   Wed Jan 8 18:39:35 2025 +0800

    enhance: Refine the coding style and enable lint-action
    
    Signed-off-by: yangxuan <[email protected]>

commit cc30d03010faaae5a589aad51644e19f3c3d6736
Author: Luka958Pixion <[email protected]>
Date:   Wed Jan 8 19:00:17 2025 +0100

    fixed ef_runtime

commit 88f5a1a1796097463e5bfbdbcb539366ce08d5dd
Author: Luka958Pixion <[email protected]>
Date:   Wed Jan 8 17:41:37 2025 +0000

    fixed query

log

❯ init_bench
2025-01-09 15:33:58,486 | INFO: all configs: [('ALIYUN_OSS_URL', 'assets.zilliz.com.cn/benchmark/'), ('AWS_S3_URL', 'assets.zilliz.com/benchmark/'), ('CONCURRENCY_DURATION', 30), ('CONFIG_LOCAL_DIR', PosixPath('/Users/zilliz/workspace/VectorDBBench/vectordb_bench/config-files')), ('CUSTOM_CONFIG_DIR', PosixPath('/Users/zilliz/workspace/VectorDBBench/vectordb_bench/custom/custom_case.json')), ('DATASET_LOCAL_DIR', PosixPath('/tmp/vectordb_bench/dataset')), ('DEFAULT_DATASET_URL', 'assets.zilliz.com/benchmark/'), ('DROP_OLD', True), ('K_DEFAULT', 100), ('LOG_LEVEL', 'INFO'), ('NUM_CONCURRENCY', [1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]), ('NUM_PER_BATCH', 100), ('RESULTS_LOCAL_DIR', PosixPath('/Users/zilliz/workspace/VectorDBBench/vectordb_bench/results')), ('USE_SHUFFLED_DATA', True)] (__main__.py:11) (97354)

  You can now view your Streamlit app in your browser.

  Local URL: http://localhost:8501
  Network URL: http://172.16.20.20:8501

  For better performance, install the Watchdog module:

  $ xcode-select --install
  $ pip install watchdog
            
2025-01-09 15:34:49,953 | INFO: generated uuid for the tasks: 44829e46e3d8418ba589343d0f41a273 (interface.py:66) (97367)
2025-01-09 15:34:50,552 | INFO | DB             | CaseType     Dataset               Filter | task_label (task_runner.py:339)
2025-01-09 15:34:50,553 | INFO | -----------    | ------------ -------------------- ------- | -------    (task_runner.py:339)
2025-01-09 15:34:50,553 | INFO | Milvus         | Performance  OpenAI-SMALL-50K        None | 2025010915 (task_runner.py:339)
2025-01-09 15:34:50,553 | INFO: task submitted: id=44829e46e3d8418ba589343d0f41a273, 2025010915, case number: 1 (interface.py:231) (97367)
2025-01-09 15:34:54,298 | INFO: [1/1] start case: {'label': <CaseLabel.Performance: 2>, 'dataset': {'data': {'name': 'OpenAI', 'size': 50000, 'dim': 1536, 'metric_type': <MetricType.COSINE: 'COSINE'>}}, 'db': 'Milvus'}, drop_old=True (interface.py:164) (98016)
2025-01-09 15:34:54,298 | INFO: Starting run (task_runner.py:100) (98016)
2025-01-09 15:34:54,581 | INFO: Milvus create collection: VectorDBBenchCollection (milvus.py:55) (98016)
2025-01-09 15:34:54,581 | WARNING: pre run case error: <DataTypeNotSupportException: (code=1, message=Field dtype must be of DataType)> (task_runner.py:96) (98016)
2025-01-09 15:34:54,582 | WARNING: [1/1] case {'label': <CaseLabel.Performance: 2>, 'dataset': {'data': {'name': 'OpenAI', 'size': 50000, 'dim': 1536, 'metric_type': <MetricType.COSINE: 'COSINE'>}}, 'db': 'Milvus'} failed to run, reason=<DataTypeNotSupportException: (code=1, message=Field dtype must be of DataType)> (interface.py:184) (98016)
Traceback (most recent call last):
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/interface.py", line 165, in _async_task_v2
    case_res.metrics = runner.run(drop_old)
                       ^^^^^^^^^^^^^^^^^^^^
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/backend/task_runner.py", line 102, in run
    self._pre_run(drop_old)
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/backend/task_runner.py", line 97, in _pre_run
    raise e from None
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/backend/task_runner.py", line 88, in _pre_run
    self.init_db(drop_old)
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/backend/task_runner.py", line 78, in init_db
    self.db = db_cls(
              ^^^^^^^
  File "/Users/zilliz/workspace/VectorDBBench/vectordb_bench/backend/clients/milvus/milvus.py", line 60, in __init__
    schema=CollectionSchema(fields),
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/zilliz/workspace/pymilvus/pymilvus/orm/schema.py", line 118, in __init__
    self._fields = [copy.deepcopy(field) for field in fields]
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/zilliz/workspace/pymilvus/pymilvus/orm/schema.py", line 118, in <listcomp>
    self._fields = [copy.deepcopy(field) for field in fields]
                    ^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/Cellar/[email protected]/3.11.9_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/copy.py", line 153, in deepcopy
    y = copier(memo)
        ^^^^^^^^^^^^
  File "/Users/zilliz/workspace/pymilvus/pymilvus/orm/schema.py", line 426, in __deepcopy__
    return self.construct_from_dict(self.to_dict())
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/zilliz/workspace/pymilvus/pymilvus/orm/schema.py", line 477, in construct_from_dict
    fs = FieldSchema(raw["name"], raw["type"], raw.get("description", ""), **kwargs)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/zilliz/workspace/pymilvus/pymilvus/orm/schema.py", line 381, in __init__
    raise DataTypeNotSupportException(message=ExceptionsMessage.FieldDtype) from None
pymilvus.exceptions.DataTypeNotSupportException: <DataTypeNotSupportException: (code=1, message=Field dtype must be of DataType)>
2025-01-09 15:34:54,589 | INFO |Task summary: run_id=44829, task_label=2025010915 (models.py:364)
2025-01-09 15:34:54,589 | INFO |DB     | db_label case                label      | load_dur    qps        latency(p99)    recall        max_load_count | label (models.py:364)
2025-01-09 15:34:54,589 | INFO |------ | -------- ------------------- ---------- | ----------- ---------- --------------- ------------- -------------- | ----- (models.py:364)
2025-01-09 15:34:54,589 | INFO |Milvus |          Performance1536D50K 2025010915 | 0.0         0.0        0.0             0.0           0              | x     (models.py:364)
2025-01-09 15:34:54,590 | WARNING: Replacing existing result with the same file_name: /Users/zilliz/workspace/VectorDBBench/vectordb_bench/results/Milvus/result_20250109_2025010915_milvus.json (models.py:218) (98016)
2025-01-09 15:34:54,590 | INFO: write results to disk /Users/zilliz/workspace/VectorDBBench/vectordb_bench/results/Milvus/result_20250109_2025010915_milvus.json (models.py:222) (98016)
2025-01-09 15:34:54,593 | INFO: Success to finish task: label=2025010915, run_id=44829e46e3d8418ba589343d0f41a273 (interface.py:203) (98016)
^C  Stopping...
2025-01-09 15:36:30,482 | INFO: exit streamlit... (__main__.py:33) (97354)

[zhuwenxing]

milvus version: master-20241206-f16232f8-amd64
python version: 3.10 and 3.12

[XuanYang-cn]

Tried with Milvus master latest and pymilvus==2.5.3, works fine.