Files
wifi-densepose/vendor/ruvector/examples/rust/batch_operations.rs

79 lines
2.3 KiB
Rust

//! Batch operations example
//!
//! Demonstrates efficient batch processing for high throughput
use ruvector_core::{VectorDB, VectorEntry, SearchQuery, DbOptions, Result};
use rand::Rng;
use std::time::Instant;
fn main() -> Result<()> {
println!("🚀 Ruvector Batch Operations Example\n");
// Setup
let mut options = DbOptions::default();
options.dimensions = 128;
options.storage_path = "./examples_batch.db".to_string();
let db = VectorDB::new(options)?;
// Generate test data
println!("1. Generating 10,000 random vectors...");
let mut rng = rand::thread_rng();
let entries: Vec<VectorEntry> = (0..10_000)
.map(|i| {
let vector: Vec<f32> = (0..128)
.map(|_| rng.gen::<f32>())
.collect();
VectorEntry {
id: Some(format!("vec_{:05}", i)),
vector,
metadata: None,
}
})
.collect();
println!(" ✓ Generated 10,000 vectors\n");
// Batch insert
println!("2. Batch inserting 10,000 vectors...");
let start = Instant::now();
let ids = db.insert_batch(entries)?;
let duration = start.elapsed();
println!(" ✓ Inserted {} vectors", ids.len());
println!(" ✓ Time: {:?}", duration);
println!(" ✓ Throughput: {:.0} vectors/sec\n",
ids.len() as f64 / duration.as_secs_f64()
);
// Benchmark search
println!("3. Benchmarking search operations...");
let num_queries = 1000;
let query_vector: Vec<f32> = (0..128).map(|_| rng.gen::<f32>()).collect();
let start = Instant::now();
for _ in 0..num_queries {
let query = SearchQuery {
vector: query_vector.clone(),
k: 10,
filter: None,
include_vectors: false,
};
db.search(&query)?;
}
let duration = start.elapsed();
println!(" ✓ Executed {} queries", num_queries);
println!(" ✓ Total time: {:?}", duration);
println!(" ✓ Average latency: {:.2}ms",
duration.as_secs_f64() * 1000.0 / num_queries as f64
);
println!(" ✓ Throughput: {:.0} queries/sec\n",
num_queries as f64 / duration.as_secs_f64()
);
println!("✅ Batch operations completed!");
Ok(())
}