do_bulk_insert()
This method inserts entities from files. You have to organize your data in a row-based JSON file and upload the JSON file to a MINIO or S3 bucket. For details, see Prepare a JSON file.
Invocation
do_bulk_insert(collection_name, partition_name=None, files, timeout=None, using='default', kwargs)
Parameters
| Parameter | Description | Type | Required |
|---|---|---|---|
collection_name | Name of a colletion | String | True |
partition_name | Name of a partition | String | False |
files | List of file paths. The path must be a MINIO or S3 bucket path | List[String] | True |
timetout | An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs. | Integer | False |
using | Alias of the Milvus connection to be attached to | String | False |
Raises
BaseException: Thrown ifcollection_namedoes not exist.BaseException: Thrown if the list of files is invalid.
Example
from pymilvus import connections, Collection, FieldSchema, CollectionSchema, DataType, utility
connections.connect()
schema = CollectionSchema([
FieldSchema("film_id", DataType.INT64, is_primary=True),
FieldSchema("films", dtype=DataType.FLOAT_VECTOR, dim=2)
])
collection = Collection("test_collection_bulk_insert", schema)
task_id = utility.do_bulk_insert(collection_name=collection.name, files=['data.json'])
print(task_id)