index_building_progress()
This operation returns the progress of the index-building process.
Request Syntax
index_building_progress(
collection_name: str,
index_name: str = "",
using: str = "default",
timeout: float | None,
)
PARAMETERS:
-
collection_name (str) -
[REQUIRED]
The name of an existing collection.
Setting this to a non-existing collection leads to a CollectionNotExistException.
-
index_name (str) -
The name of the target index of this operation.
If left unspecified, the default index applies. If the collection has multiple indexes, this parameter is mandatory.
Setting this to a non-existing index leads to an IndexNotExistException.
-
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 times out when any response arrives or any error occurs.
RETURN TYPE:
dict
RETURNS: A dictionary that contains the number of indexed entities as well as that of total entities in the specified collection. The dictionary has the following keys:
-
total_rows (int)
The total number of entities in the specified collection.
-
indexed_rows (int)
The number of indexed entities in the specified collection.
-
pending_index_rows (int)
The number of entities that are pending to be indexed.
EXCEPTIONS:
-
CollectionNotExistException
This exception will be raised if the specified collection does not exist.
-
IndexNotExistException
This exception will be raised if the specified index does not exist.
-
AmbiguousIndexName
This exception will be raised if multiple indexes exist but the index name is left unspecified.
Examples
from pymilvus import (
connections,
Collection,
CollectionSchema,
FieldSchema,
DataType,
utility,
)
# Connection to localhost:19530
connections.connect()
# Create a collection
collection = Collection(
name="test_collection",
schema=CollectionSchema([
FieldSchema("id", DataType.INT64, is_primary=True),
FieldSchema("vector", DataType.FLOAT_VECTOR, dim=5)
])
)
# Create an index on a scalar field
collection.create_index(
field_name="id"
)
# Set the index parameters
index_params = {
"index_type": "AUTOINDEX",
"metric_type": "COSINE",
"params": {
"nprobe": 10
}
}
# Create an index on the vector field
collection.create_index(
field_name="vector",
index_params=index_params,
timeout=None
)
# List all indexes
utility.list_indexes(
collection_name="test_collection"
) # ['_default_idx_101', '_default_idx_100']
# Get the building progress of a specific index
utility.index_building_progress(
collection_name="test_collection",
index_name="_default_idx_101"
)
Related operations
The following operations are related to index_building_progress()