add_index()
This operation adds index parameters for a specific field in a collection.
Request syntax
IndexParams.add_index(
field_name: str,
index_type: str,
index_name: str,
metric_type: str,
params: dict
) -> None
PARAMETERS:
field_name (str) -
The name of the target file to apply this object applies.
index_name (str) -
The name of the index file generated after this object has been applied.
index_type (str) -
The name of the algorithm used to arrange data in the specific field. For applicable algorithms, refer to In-memory Index and On-disk Index.
metric_type (str) -
The algorithm that is used to measure similarity between vectors. Possible values:
IP,L2,COSINE,HAMMING,JACCARD,BM25(used only for full text search). For more information, refer to Metric Types.This is available only when the specified field is a vector field.
params (dict) -
The fine-tuning parameters for the specified index type. For details on possible keys and value ranges, refer to In-memory Index.
RETURN TYPE:
NoneType
RETURNS:
None
EXCEPTIONS:
MilvusException
This exception will be raised when any error occurs during this operation.
Examples
from pymilvus import MilvusClient, DataType
# 1. Create schema
schema = MilvusClient.create_schema(
auto_id=False,
enable_dynamic_field=False,
)
# 2. Add fields to schema
schema.add_field(field_name="my_id", datatype=DataType.INT64, is_primary=True)
# {
# 'auto_id': False,
# 'description': '',
# 'fields': [
# {
# 'name': 'my_id',
# 'description': '',
# 'type': <DataType.INT64: 5>,
# 'is_primary': True,
# 'auto_id': False
# }
# ]
# }
schema.add_field(field_name="my_vector", datatype=DataType.FLOAT_VECTOR, dim=5)
# {
# 'auto_id': False,
# 'description': '',
# 'fields': [
# {
# 'name': 'my_id',
# 'description': '',
# 'type': <DataType.INT64: 5>,
# 'is_primary': True,
# 'auto_id': False
# },
# {
# 'name': 'my_vector',
# 'description': '',
# 'type': <DataType.FLOAT_VECTOR: 101>,
# 'params': {
# 'dim': 5
# }
# }
# ]
# }
# 3. Create index parameters
index_params = client.prepare_index_params()
# 4. Add indexes
# - For a scalar field
index_params.add_index(
field_name="my_id",
index_type="STL_SORT"
)
# - For a vector field
index_params.add_index(
field_name="my_vector",
index_type="IVF_FLAT",
metric_type="L2",
params={"nlist": 1024}
)