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//! Async operations for VecStore
//!
//! This module provides async/await interfaces for batch operations,
//! enabling efficient parallel processing with tokio.
//!
//! ## Features
//!
//! - Async batch insertions with parallel processing
//! - Async batch queries
//! - Stream-based results
//! - Configurable concurrency limits
//!
//! ## Example
//!
//! ```no_run
//! use vecstore::VecStore;
//! use vecstore::async_ops::AsyncVecStore;
//!
//! #[tokio::main]
//! async fn main() -> anyhow::Result<()> {
//! let store = VecStore::open("vectors.db")?;
//! let async_store = AsyncVecStore::new(store);
//!
//! // Batch insert with parallelism
//! let items = vec![
//! ("doc1".to_string(), vec![0.1, 0.2, 0.3]),
//! ("doc2".to_string(), vec![0.4, 0.5, 0.6]),
//! ];
//! async_store.batch_upsert(items).await?;
//!
//! Ok(())
//! }
//! ```
#[cfg(feature = "async")]
use crate::store::{Metadata, Neighbor, VecStore};
#[cfg(feature = "async")]
use anyhow::Result;
#[cfg(feature = "async")]
use std::sync::{Arc, Mutex};
#[cfg(feature = "async")]
use tokio::task;
/// Async wrapper for VecStore providing parallel batch operations
#[cfg(feature = "async")]
#[derive(Clone)]
pub struct AsyncVecStore {
store: Arc<Mutex<VecStore>>,
}
#[cfg(feature = "async")]
impl AsyncVecStore {
/// Create a new async wrapper around a VecStore
pub fn new(store: VecStore) -> Self {
Self {
store: Arc::new(Mutex::new(store)),
}
}
/// Async batch upsert with parallel processing
///
/// Inserts multiple vectors in parallel using tokio tasks.
/// This is significantly faster than sequential insertions for large batches.
///
/// # Arguments
/// * `items` - Vector of (id, vector, metadata) tuples
/// * `chunk_size` - Number of items to process per task (default: 100)
///
/// # Example
/// ```no_run
/// # use vecstore::VecStore;
/// # use vecstore::async_ops::AsyncVecStore;
/// # #[tokio::main]
/// # async fn main() -> anyhow::Result<()> {
/// let store = VecStore::open("vectors.db")?;
/// let async_store = AsyncVecStore::new(store);
///
/// let items: Vec<_> = (0..1000)
/// .map(|i| {
/// let id = format!("doc{}", i);
/// let vector = vec![i as f32, (i + 1) as f32, (i + 2) as f32];
/// let metadata = serde_json::json!({"index": i});
/// (id, vector, metadata)
/// })
/// .collect();
///
/// async_store.batch_upsert_with_metadata(items, 100).await?;
/// # Ok(())
/// # }
/// ```
pub async fn batch_upsert_with_metadata(
&self,
items: Vec<(String, Vec<f32>, serde_json::Value)>,
chunk_size: usize,
) -> Result<()> {
// Split into chunks for parallel processing
let chunks: Vec<_> = items.chunks(chunk_size).map(|c| c.to_vec()).collect();
let mut handles = Vec::new();
for chunk in chunks {
let store_clone = self.store.clone();
let handle = task::spawn_blocking(move || {
let mut store = store_clone.lock().unwrap();
for (id, vector, metadata) in chunk {
let metadata: Metadata = serde_json::from_value(metadata)?;
store.upsert(id, vector, metadata)?;
}
Ok::<(), anyhow::Error>(())
});
handles.push(handle);
}
// Wait for all tasks to complete
for handle in handles {
handle.await??;
}
Ok(())
}
/// Async batch upsert without metadata
pub async fn batch_upsert(&self, items: Vec<(String, Vec<f32>)>) -> Result<()> {
let items_with_metadata: Vec<_> = items
.into_iter()
.map(|(id, vec)| (id, vec, serde_json::json!({})))
.collect();
self.batch_upsert_with_metadata(items_with_metadata, 100)
.await
}
/// Async batch query - query multiple vectors in parallel
///
/// # Arguments
/// * `queries` - Vector of query vectors
/// * `k` - Number of results per query
///
/// # Returns
/// Vector of result sets, one per query
pub async fn batch_query(
&self,
queries: Vec<Vec<f32>>,
k: usize,
) -> Result<Vec<Vec<Neighbor>>> {
use crate::store::Query;
let mut handles = Vec::new();
for query_vec in queries {
let store_clone = self.store.clone();
let handle = task::spawn_blocking(move || {
let store = store_clone.lock().unwrap();
let query = Query::new(query_vec).with_limit(k);
store.query(query)
});
handles.push(handle);
}
// Collect results
let mut results = Vec::new();
for handle in handles {
results.push(handle.await??);
}
Ok(results)
}
/// Async batch delete
pub async fn batch_delete(&self, ids: Vec<String>) -> Result<()> {
let mut handles = Vec::new();
for id in ids {
let store_clone = self.store.clone();
let handle = task::spawn_blocking(move || {
let mut store = store_clone.lock().unwrap();
store.delete(&id)
});
handles.push(handle);
}
// Wait for all deletes to complete
for handle in handles {
handle.await??;
}
Ok(())
}
/// Get the underlying VecStore (blocking)
pub fn get_store(&self) -> Arc<Mutex<VecStore>> {
self.store.clone()
}
}
#[cfg(all(test, feature = "async"))]
mod tests {
use super::*;
use tempfile::tempdir;
#[tokio::test]
async fn test_async_batch_upsert() {
let dir = tempdir().unwrap();
let store = VecStore::open(dir.path().join("test.db")).unwrap();
let async_store = AsyncVecStore::new(store);
let items: Vec<_> = (0..100)
.map(|i| {
(
format!("doc{}", i),
vec![i as f32, (i + 1) as f32, (i + 2) as f32],
)
})
.collect();
async_store.batch_upsert(items).await.unwrap();
let store_guard = async_store.store.lock().unwrap();
assert_eq!(store_guard.len(), 100);
}
#[tokio::test]
async fn test_async_batch_query() {
let dir = tempdir().unwrap();
let store = VecStore::open(dir.path().join("test.db")).unwrap();
let async_store = AsyncVecStore::new(store);
// Insert test data
let items: Vec<_> = (0..50)
.map(|i| {
(
format!("doc{}", i),
vec![i as f32, (i + 1) as f32, (i + 2) as f32],
)
})
.collect();
async_store.batch_upsert(items).await.unwrap();
// Batch query
let queries = vec![
vec![0.0, 1.0, 2.0],
vec![10.0, 11.0, 12.0],
vec![20.0, 21.0, 22.0],
];
let results = async_store.batch_query(queries, 5).await.unwrap();
assert_eq!(results.len(), 3);
for result_set in results {
assert_eq!(result_set.len(), 5);
}
}
}