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": "IVF_FLAT",
"metric_type": "COSINE",
"params": {
"nlist": 128
}
}
# 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()