Bulk Importing Vectors

Bulk import loads vectors from cloud storage (Amazon S3, Google Cloud Storage, or Azure Blob Storage) into a Pinecone index. The import runs server-side, so it handles millions of vectors without keeping a long-lived client connection open.

The source must be a directory of Parquet files formatted to the Pinecone-required schema <https://docs.pinecone.io/guides/data/understanding-imports>_.

Start an import

{meth}~pinecone.Index.start_import initiates the operation and returns immediately with an operation ID:

from pinecone import Pinecone

pc = Pinecone(api_key="your-api-key")
index = pc.index("product-search")

response = index.start_import(uri="s3://my-bucket/embeddings/")
import_id = response.id
print(import_id)  # e.g. "1"

uri points to a directory prefix, not an individual file.

Handle errors during import

By default, error_mode is "continue" — the server skips records that fail to parse and continues importing the rest. Pass error_mode="abort" to stop the entire import on the first error:

response = index.start_import(
    uri="s3://my-bucket/embeddings/",
    error_mode="abort",
)

You can also use the {class}~pinecone.models.ImportErrorMode enum:

from pinecone.models.imports.error_mode import ImportErrorMode

response = index.start_import(
    uri="s3://my-bucket/embeddings/",
    error_mode=ImportErrorMode.ABORT,
)

Check import status

{meth}~pinecone.Index.describe_import returns an {class}~pinecone.models.ImportModel with the current state:

import_op = index.describe_import(import_id)
print(import_op.status)           # e.g. "InProgress"
print(import_op.percent_complete) # e.g. 42.0
print(import_op.records_imported) # e.g. 150000

status is one of: "Pending", "InProgress", "Completed", "Failed", "Cancelled".

Poll until complete

import time

import_op = index.describe_import(import_id)
while import_op.status not in ("Completed", "Failed", "Cancelled"):
    time.sleep(10)
    import_op = index.describe_import(import_id)

if import_op.status == "Completed":
    print(f"Imported {import_op.records_imported} records")
else:
    print(f"Import ended with status: {import_op.status}")
    if import_op.error:
        print(import_op.error)

List imports

{meth}~pinecone.Index.list_imports yields {class}~pinecone.models.ImportModel objects for all imports on the index, following pagination automatically:

for imp in index.list_imports():
    print(imp.id, imp.status, imp.percent_complete)

Pass limit to control the page size (max 100):

for imp in index.list_imports(limit=20):
    print(imp.id, imp.status)

Cancel an import

{meth}~pinecone.Index.cancel_import stops an in-progress import. Already-imported records are not rolled back.

index.cancel_import(import_id)

See also

• {doc}/how-to/vectors/upsert-and-query — upsert vectors directly in batches
• {class}~pinecone.Index — full data plane client reference
• {class}~pinecone.models.ImportModel — import operation model