​
OceanBaseStorage

class OceanBaseStorage(BaseVectorStorage):

An implementation of the BaseVectorStorage for interacting with OceanBase Vector Database.

Parameters:

  • vector_dim (int): The dimension of storing vectors.
  • table_name (str): Name for the table in OceanBase.
  • uri (str): Connection URI for OceanBase (host:port). (default: :obj:"127.0.0.1:2881")
  • user (str): Username for connecting to OceanBase. (default: :obj:"root@test")
  • password (str): Password for the user. (default: :obj:"") (default: "")
  • db_name (str): Database name in OceanBase. (default: :obj:"test")
  • distance (Literal["l2", "cosine"], optional): The distance metric for vector comparison. Options: “l2”, “cosine”. (default: :obj:"l2")
  • delete_table_on_del (bool, optional): Flag to determine if the table should be deleted upon object destruction. (default: :obj:False) **kwargs (Any): Additional keyword arguments for initializing ObVecClient.

​
init

def __init__(
    self,
    vector_dim: int,
    table_name: str,
    uri: str = '127.0.0.1:2881',
    user: str = 'root@test',
    password: str = '',
    db_name: str = 'test',
    distance: Literal['l2', 'cosine'] = 'l2',
    delete_table_on_del: bool = False,
    **kwargs: Any
):

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del

def __del__(self):

Deletes the table if :obj:delete_table_on_del is set to :obj:True.

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add

def add(
    self,
    records: List[VectorRecord],
    batch_size: int = 100,
    **kwargs: Any
):

Saves a list of vector records to the storage.

Parameters:

  • records (List[VectorRecord]): List of vector records to be saved.
  • batch_size (int): Number of records to insert each batch. Larger batches are more efficient but use more memory. (default: :obj:100) **kwargs (Any): Additional keyword arguments.

​
delete

def delete(self, ids: List[str], **kwargs: Any):

Deletes a list of vectors identified by their IDs from the storage.

Parameters:

  • ids (List[str]): List of unique identifiers for the vectors to be deleted. **kwargs (Any): Additional keyword arguments.

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status

def status(self):

Returns:

VectorDBStatus: The vector database status.

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query

def query(self, query: VectorDBQuery, **kwargs: Any):

Searches for similar vectors in the storage based on the provided query.

Parameters:

  • query (VectorDBQuery): The query object containing the search vector and the number of top similar vectors to retrieve. **kwargs (Any): Additional keyword arguments.

Returns:

List[VectorDBQueryResult]: A list of vectors retrieved from the storage based on similarity to the query vector.

​
_convert_distance_to_similarity

def _convert_distance_to_similarity(self, distance: float):

Converts distance to similarity score based on distance metric.

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clear

def clear(self):

Remove all vectors from the storage.

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load

def load(self):

Load the collection hosted on cloud service.

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client

def client(self):

Provides access to underlying OceanBase vector database client.