Create Non-Linear Algorithm Index

Creating non-linear algorithm indexes allows you to optimize query execution based on spatial or high-dimensional data structures.

The NonLinearAlgorithm enum currently supports algorithms like KDTree (K-dimensional tree), which is useful for nearest-neighbor searches and multidimensional range queries.

Non Linear Algorithm Indexes improve query performance by pre-structuring the data, but depending on the algorithm, there may be tradeoffs between query time and memory consumption.

In the Ahnlich client, you can create a non-linear algorithm index by calling the create_non_linear_algorithm_index RPC via the DbServiceStub.

Define a Client and Call the API

The following example shows how to initialize a client, request index creation, and inspect the server’s response.

Click to expand code

import asyncio
from grpclib.client import Channel
from ahnlich_client_py.grpc.services.db_service import DbServiceStub
from ahnlich_client_py.grpc.db import query as db_query
from ahnlich_client_py.grpc.algorithm.nonlinear import NonLinearAlgorithm


async def create_non_linear_algo_index():
  async with Channel(host="127.0.0.1", port=1369) as channel:
      client = DbServiceStub(channel)
      
      response = await client.create_non_linear_algorithm_index(
          db_query.CreateNonLinearAlgorithmIndex(
              store="test store 003",
              non_linear_indices=[NonLinearAlgorithm.KDTree]
          )
      )
      # response.created_indexes shows how many indexes were created
  print(response)


if __name__ == "__main__":
  asyncio.run(create_non_linear_algo_index())

Define a Client and Call the API​

Define a Client and Call the API