bulk_import()
This operation imports the prepared data files to Milvus. To learn how to prepare your data files, read Prepare Source Data.
Request syntax
bulk_import(
url: str,
collection_name: str,
files: list
)
PARAMETERS:
url (string) -
[REQUIRED]
The URI of your Milvus instance.
collection_name (string) -
[REQUIRED]
The name of a collection in the target cluster of this operation.
files (list) -
[REQUIRED]
The list of string lists, each string list contains a singular row-based file path or multiple column-based file paths.
RETURN TYPE:
dict
RETURNS:
Response syntax
# { # "code": 200, # "data": { # "jobId": "string" # } # }Response structure
jobId (string) -
If present, indicates that a bulk-import job has been created successfully and is currently running.
EXCEPTIONS:
None
Examples
from pymilvus.bulk_writer import bulk_import
url = f"http://localhost:19530"
# Bulk-insert data from a set of JSON files already uploaded to the MinIO server
resp = bulk_import(
url=url,
collection_name="quick_setup",
files=[['a1e18323-a658-4d1b-95a7-9907a4391bcf/1.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/2.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/3.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/4.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/5.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/6.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/7.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/8.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/9.parquet'],
['a1e18323-a658-4d1b-95a7-9907a4391bcf/10.parquet']],
)
job_id = resp.json()['data']['jobId']
print(job_id)
# {
# "code": 200,
# "data": {
# "jobId": "453240863839750922"
# }
# }