get_bulk_insert_state()

This operation returns the state of a specified bulk-insert task.

Request syntax

get_bulk_insert_state(
    task_id: int,
    timeout: float | None,
    using: str = "default",
    **kwargs,
)

from pymilvus import connections, utility
connections.connect()

task_id = utility.do_bulk_insert(
    collection_name="string",
    files=["string.npy", "string.npy"],
)

# Get bulk-insert task state
res = utility.get_bulk_insert_state(task_id=task_id)

PARAMETERS:

• task_id (int) - [REQUIRED]

  A task ID returned by the do_bulk_insert() function.

• using (str) -

  The alias of the employed connection.

  The default value is default, indicating that this operation employs the default connection.

• timeout (float | None)

  The timeout duration for this operation. Setting this to None indicates that this operation timeouts when any response arrives or any error occurs.

RETURN TYPE:

BulkInsertState

RETURNS: A BulkInsertState that contains information about the state of the specified bulk-insert task.

├── BulkInsertState
│   ├── task_id 
│   ├── state 
│   ├── state_name   
│   ├── row_count
│   ├── progress
│   └── infos
│       ├── files
│       ├── collection
│       ├── partition
│       ├── failed_reason
│       ├── progress_percent
│       └── persist_cost
│   ├── ids
│   ├── id_ranges
│   ├── files
│   ├── create_timestamp
│   ├── create_time_str
│   └── collection_name

A BulkInsertState object has the following fields

• task_id (int)

  A task ID returned by the do_bulk_insert() function.

• state (int)

  The state of the specified bulk_insert task in integers. Possible values are the following integers:

  • 0: Indicates that the task is in a pending state

  • 1: Indicates that the task failed.

  • 2: Indicates that the task has already started.

  • 5: Indicates that the data has been persisted.

  • 6: Indicates that the task has been completed.

  • 7: Indicates that the task failed and the data has been cleaned up.

  • 100: Indicates that the task is in an unknown state.

• state_name (str)

  The state of the specified bulk_insert task in integers. Possible values are the following integers:

  • Pending: Indicates that the task is in a pending state

  • Failed: Indicates that the task failed.

  • Started: Indicates that the task has already started.

  • Persisted: Indicates that the data has been persisted.

  • Completed: Indicates that the task has been completed.

  • FailedAndCleaned: Indicates that the task failed and the data has been cleaned up.

  • Unknown: Indicates that the task is in an unknown state.

• row_count (int)

  The number of entities inserted in the current bulk-insert task.

• progress (int)

  The progress of the current bulk-insert task.

• infos (dict)

  A dictionary containing information about the current bulk-insert task. Possible keys are as follows:

  • files (str)

    The names of the files involved in the current bulk-insert task in a comma-separated string.

  • collection (str)

    The name of the target collection.

  • partition (str)

    The name of the target partition.

  • failed_reason (str)

    The reason for any bulk-insert failures. If the task succeeds, this is an empty string.

  • progress_percent (str)

    The progress of the current bulk-insert task in percentage.

  • persist_cost (str)

    The persistence cost of the current bulk-insert task.

• ids (list)

  The IDs of the inserted entities in a list.

• id_ranges (_google._upb.message.RepeatedScalarContainer)

• The ID of the inserted entities in a range.

• files (str)

  The names of the files involved in the current bulk-insert task in a comma-separated string.

• create_timestamp (int)

  The timestamp at which the current bulk-insert task has been created.

• create_time_str (str)

  The timestamp at which the current bulk-insert task has been created, in a human-readable string.

• collection_name (str)

  The name of the target collection.

EXCEPTIONS:

• MilvusException

  This exception will be raised when any error occurs during this operation.

Examples

from pymilvus import connections, utility

# Connect to localhost:19530
connections.connect()

# Bulk-insert data
task_id = utility.do_bulk_insert(
    collection_name="test_collection",
    files=["data/id.npy", "data/vector.npy"],
) # 446781855410077319

# Get bulk-insert task state
res = utility.get_bulk_insert_state(task_id=task_id)

# <Bulk insert state:
#     - taskID          : 446781855410077319,
#     - state           : Completed,
#     - row_count       : 10000,
#     - infos           : {'files': 'data/id.npy,data/vector.npy', 'collection': 'test_collection_2', 'partition': '_default', 'failed_reason': '', 'progress_percent': '100', 'persist_cost': '0.34'},
#     - id_ranges       : [],
#     - create_ts       : 2024-01-06 22:24:07
# >