Drop Non-Linear Algorithm Index

Schema

This request accepts an optional schema field. When it is omitted, the server uses the public schema. Set schema to target a store in another schema.

Removes an existing non-linear algorithm index from a store. This operation is useful when an index is no longer needed, when switching to a different indexing strategy, or during cleanup of store resources. Dropping the index reverts the store back to standard linear search behavior unless another index exists.

Source Code Example

Click to expand

Rust

use ahnlich_types::db::query::DropNonLinearAlgorithmIndex;
use ahnlich_types::algorithm::nonlinear::NonLinearAlgorithm;
use ahnlich_types::db::server::Del;
use ahnlich_client_rs::db::DbClient;


#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let addr = "http://127.0.0.1:1369".to_string();
    let db_client = DbClient::new(addr).await?;


    let params = DropNonLinearAlgorithmIndex {
        store: "Main".to_string(),
        schema: Some("analytics".to_string()),
        non_linear_indices: vec![NonLinearAlgorithm::Hnsw as i32],
        error_if_not_exists: false,
    };


    match db_client
        .drop_non_linear_algorithm_index(params, None)
        .await
    {
        Ok(Del { deleted_count }) => {
            println!("Successfully dropped {} non-linear index(es).", deleted_count);
        }
        Err(e) => {
            eprintln!("Error dropping non-linear index: {:?}", e);
        }
    }


    Ok(())
}

Parameters

• params: DropNonLinearAlgorithmIndex — Specifies the target store and index to be dropped.

• tracing_id: Option<String> — Optional trace identifier for observability.

Returns

• Del — Confirmation that the index has been dropped.

• AhnlichError — If the operation fails due to invalid parameters or missing index.

Behavior

• Builds a request with the given params.

• Adds tracing information when provided.

• Sends the request to the DB service to drop the index.

• Returns confirmation once the index has been removed.

• Cleaning up unused indexes.

• Switching from non-linear search back to linear search.

• Replacing an old index with a newly configured one.