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mirror of https://github.com/osmarks/meme-search-engine.git synced 2026-06-08 22:02:11 +00:00
Files
meme-search-engine/src/query_disk_index.rs
2025-11-07 16:59:25 +00:00

743 lines
30 KiB
Rust

use anyhow::{Context, Result};
use lazy_static::lazy_static;
use monoio::{blocking::DefaultThreadPool, fs};
use std::path::PathBuf;
use base64::Engine;
use argh::FromArgs;
use itertools::Itertools;
use foldhash::{HashSet, HashSetExt};
use half::f16;
use diskann::{NeighbourBuffer, vector::{fast_dot_noprefetch, QueryLUT, scale_dot_result, scale_dot_result_f64, SCALE_F64}};
use simsimd::SpatialSimilarity;
use memmap2::{Mmap, MmapOptions};
use std::rc::Rc;
use monoio::net::{TcpListener, TcpStream};
use monoio::io::IntoPollIo;
use hyper::{body::{Body, Bytes, Incoming, Frame}, server::conn::http1, Method, Request, Response, StatusCode};
use http_body_util::{BodyExt, Empty, Full};
use prometheus::{register_int_counter, register_int_counter_vec, register_int_gauge, Encoder, IntCounter, IntGauge, IntCounterVec};
use std::pin::Pin;
use std::future::Future;
use serde::{Serialize, Deserialize};
use std::str::FromStr;
use std::collections::HashMap;
use std::io::Write;
use std::sync::Arc;
mod common;
use common::{resize_for_embed_sync, QueryTerm, FrontendInit, IndexHeader, InferenceServerConfig, PackedIndexEntry, QueryRequest, QueryResult};
#[derive(FromArgs, Clone)]
#[argh(description="Query disk index")]
struct CLIArguments {
#[argh(positional)]
index_path: String,
#[argh(option, short='q', description="query vector in base64")]
query_vector_base64: Option<String>,
#[argh(option, short='f', description="file of FP16 query vectors")]
query_vector_file: Option<String>,
#[argh(switch, short='v', description="verbose")]
verbose: bool,
#[argh(option, short='n', description="stop at n queries")]
n: Option<usize>,
#[argh(option, short='L', description="search list size")]
search_list_size: Option<usize>,
#[argh(switch, description="always use full-precision vectors (slow)")]
disable_pq: bool,
#[argh(option, short='c', description="server config file")]
config_path: Option<String>,
#[argh(switch, short='l', description="lock memory")]
lock_memory: bool,
#[argh(option, short='T', description="number of threads to use")]
threads: Option<usize>
}
#[derive(Deserialize, Clone)]
struct ServerConfig {
listen_address: String,
clip_server: String,
descriptor_names: Vec<String>,
telemetry_file: String,
search_list: usize,
beam_width: usize
}
lazy_static! {
static ref QUERIES_COUNTER: IntCounter = register_int_counter!("mse_queries", "queries executed").unwrap();
static ref TERMS_COUNTER: IntCounterVec = register_int_counter_vec!("mse_terms", "terms used in queries, by type", &["type"]).unwrap();
static ref NODE_READS: IntCounter = register_int_counter!("mse_node_reads", "graph nodes read").unwrap();
static ref PQ_COMPARISONS: IntCounter = register_int_counter!("mse_pq_comparisons", "product quantization comparisons").unwrap();
}
async fn read_node<'a>(id: u32, index: Rc<Index>) -> Result<PackedIndexEntry> {
let offset = id as usize * index.header.record_pad_size;
let buf = vec![0; index.header.record_pad_size as usize];
let (res, buf) = index.data_file.read_exact_at(buf, offset as u64).await;
res?;
NODE_READS.inc();
let len = u16::from_le_bytes(buf[0..2].try_into().unwrap()) as usize;
Ok(bitcode::decode(&buf[2..len+2])?)
}
fn next_several_unvisited(s: &mut NeighbourBuffer, n: usize) -> Option<Vec<u32>> {
let mut result = Vec::new();
for _ in 0..n {
if let Some(neighbour) = s.next_unvisited() {
result.push(neighbour);
} else {
break;
}
}
if result.len() > 0 {
Some(result)
} else {
None
}
}
const DUPLICATES_THRESHOLD: f32 = 0.95;
fn read_pq_codes(id: u32, index: Rc<Index>, buf: &mut Vec<u8>) {
let loc = (id as usize) * index.pq_code_size;
buf.extend(&index.memory_maps.pq_codes[loc..loc+index.pq_code_size])
}
struct VisitedNode {
image_url: String,
scores: Vec<f32>,
shards: Vec<u32>,
id: u32,
score: i64,
timestamp: u64,
dimensions: (u32, u32)
}
struct Scratch {
visited_adjacent: HashSet<u32>,
visited: HashSet<u32>,
neighbour_buffer: NeighbourBuffer,
neighbour_pre_buffer: Vec<u32>,
visited_list: Vec<VisitedNode>,
visited_embeddings: Vec<f32>
}
struct Index {
data_file: fs::File,
header: Rc<IndexHeader>,
pq_code_size: usize,
n_descriptors: usize,
memory_maps: Arc<MemoryMaps>
}
struct DescriptorScales(Vec<f32>);
fn descriptor_product(index: Rc<Index>, scales: &DescriptorScales, neighbour: u32) -> i64 {
let mut result = 0;
// effectively an extra part of the vector to dot product
for (j, d) in scales.0.iter().enumerate() {
result += scale_dot_result(d * index.memory_maps.descriptors[neighbour as usize * index.n_descriptors + j] as f32);
}
result
}
async fn greedy_search<'a>(scratch: &mut Scratch, start: u32, query: &[f16], query_preprocessed: &QueryLUT, descriptor_scales: &DescriptorScales, index: Rc<Index>, disable_pq: bool, beamwidth: usize) -> Result<(usize, usize)> {
scratch.visited_adjacent.clear();
scratch.neighbour_buffer.clear();
scratch.visited_list.clear();
scratch.visited.clear();
let mut cmps = 0;
let mut pq_cmps = 0;
scratch.neighbour_buffer.insert(start, 0);
scratch.visited_adjacent.insert(start);
while let Some(pts) = next_several_unvisited(&mut scratch.neighbour_buffer, beamwidth) {
scratch.neighbour_pre_buffer.clear();
let mut join_handles = Vec::with_capacity(pts.len());
for &pt in pts.iter() {
join_handles.push(monoio::spawn(read_node(pt, index.clone())));
}
for handle in join_handles {
let index = index.clone();
let node = handle.await?;
let vector = bytemuck::cast_slice(&node.vector);
let mut score = fast_dot_noprefetch(query, &vector);
score += descriptor_product(index.clone(), &descriptor_scales, node.id);
cmps += 1;
if scratch.visited.insert(node.id) && node.url.len() > 0 {
scratch.visited_list.push(VisitedNode {
image_url: node.url,
scores: node.scores,
shards: node.shards,
id: node.id,
score,
timestamp: node.timestamp,
dimensions: node.dimensions
});
scratch.visited_embeddings.extend(bytemuck::cast_slice(&node.vector).iter().map(|x: &f16| x.to_f32()));
};
for &neighbour in node.vertices.iter() {
if scratch.visited_adjacent.insert(neighbour) {
scratch.neighbour_pre_buffer.push(neighbour);
}
}
let mut pq_codes = Vec::with_capacity(index.pq_code_size * scratch.neighbour_pre_buffer.len());
for &neighbour in scratch.neighbour_pre_buffer.iter() {
read_pq_codes(neighbour, index.clone(), &mut pq_codes);
}
let mut approx_scores = index.header.quantizer.asymmetric_dot_product(&query_preprocessed, &pq_codes);
for (i, &neighbour) in scratch.neighbour_pre_buffer.iter().enumerate() {
if disable_pq {
let node = read_node(neighbour, index.clone()).await?;
let vector = bytemuck::cast_slice(&node.vector);
let mut score = fast_dot_noprefetch(query, &vector);
score += descriptor_product(index.clone(), &descriptor_scales, neighbour);
scratch.neighbour_buffer.insert(neighbour, score);
} else {
approx_scores[i] += descriptor_product(index.clone(), &descriptor_scales, neighbour);
scratch.neighbour_buffer.insert(neighbour, approx_scores[i]);
pq_cmps += 1;
PQ_COMPARISONS.inc();
}
}
}
}
Ok((cmps, pq_cmps))
}
fn summary_stats(ranks: &mut [usize]) {
let sum = ranks.iter().sum::<usize>();
let mean = sum as f64 / ranks.len() as f64 + 1.0;
ranks.sort_unstable();
let median = ranks[ranks.len() / 2] + 1;
let harmonic_mean = ranks.iter().map(|x| 1.0 / ((x+1) as f64)).sum::<f64>() / ranks.len() as f64;
println!("median {} mean {:.2} max {} min {} harmonic mean {:.2}", median, mean, ranks[ranks.len() - 1] + 1, ranks[0] + 1, 1.0 / harmonic_mean);
}
const K: usize = 20;
#[monoio::main(threads=1)]
async fn evaluate(args: Arc<CLIArguments>, memory_maps: Arc<MemoryMaps>) -> Result<()> {
let index = initialize_index(args.clone(), memory_maps).await?;
let mut top_k_ranks_best_shard = vec![];
let mut top_rank_best_shard = vec![];
let mut pq_cmps = vec![];
let mut cmps = vec![];
let mut recall_total = 0;
let mut queries = vec![];
if let Some(query_vector_base64) = &args.query_vector_base64 {
let query_vector: Vec<f16> = common::chunk_fp16_buffer(&base64::engine::general_purpose::URL_SAFE_NO_PAD.decode(query_vector_base64.as_bytes()).context("invalid base64")?);
queries.push(query_vector);
}
if let Some(query_vector_file) = &args.query_vector_file {
let query_vectors = fs::read(query_vector_file).await?;
queries.extend(common::chunk_fp16_buffer(&query_vectors).chunks(1152).map(|x| x.to_vec()).collect::<Vec<_>>());
}
if let Some(n) = args.n {
queries.truncate(n);
}
for query_vector in queries.iter() {
let query_vector_fp32 = query_vector.iter().map(|x| x.to_f32()).collect::<Vec<f32>>();
let query_preprocessed = index.header.quantizer.preprocess_query(&query_vector_fp32);
// TODO slightly dubious
let selected_shard = index.header.shards.iter().position_max_by_key(|x| {
scale_dot_result_f64(SpatialSimilarity::dot(&x.0, &query_vector_fp32).unwrap())
}).unwrap();
if args.verbose {
println!("selected shard is {}", selected_shard);
}
let mut matches = vec![];
// brute force scan
for i in 0..index.header.count {
let node = read_node(i, index.clone()).await?;
//println!("{} {}", i, node.url);
let vector = bytemuck::cast_slice(&node.vector);
matches.push((i, fast_dot_noprefetch(&query_vector, &vector), node.url, node.shards));
}
matches.sort_unstable_by_key(|x| -x.1);
let mut matches = matches.into_iter().enumerate().map(|(i, (id, distance, url, shards))| (id, i)).collect::<Vec<_>>();
matches.sort_unstable();
/*for (id, distance, url, shards) in matches.iter().take(20) {
println!("brute force: {} {} {} {:?}", id, distance, url, shards);
}*/
let mut top_ranks = vec![usize::MAX; K];
for shard in 0..index.header.shards.len() {
let selected_start = index.header.shards[shard].1;
let beamwidth = 3;
let mut scratch = Scratch {
visited: HashSet::new(),
neighbour_buffer: NeighbourBuffer::new(args.search_list_size.unwrap_or(1000)),
neighbour_pre_buffer: Vec::new(),
visited_list: Vec::new(),
visited_adjacent: HashSet::new(),
visited_embeddings: Vec::new()
};
let descriptor_scales = DescriptorScales(vec![0.0, 0.0, 0.0, 0.0]);
let cmps_result = greedy_search(&mut scratch, selected_start, &query_vector, &query_preprocessed, &descriptor_scales, index.clone(), args.disable_pq, beamwidth).await?;
// slightly dubious because this is across shards
pq_cmps.push(cmps_result.1);
cmps.push(cmps_result.0);
if args.verbose {
println!("index scan {}: {:?} cmps", shard, cmps_result);
}
scratch.visited_list.sort_by_key(|x| -x.score);
for (i, node) in scratch.visited_list.iter().take(20).enumerate() {
let found_id = match matches.binary_search(&(node.id, 0)) {
Ok(pos) => pos,
Err(pos) => pos
};
if args.verbose {
println!("index scan: {} {} {} {:?} {:?}; rank {}", node.id, node.score, node.image_url, node.shards, node.scores, matches[found_id].1 + 1);
};
top_ranks[i] = std::cmp::min(top_ranks[i], matches[found_id].1);
}
if args.verbose { println!("") }
}
// results list is always correctly sorted
for &rank in top_ranks.iter() {
if rank < K {
recall_total += 1;
}
}
top_rank_best_shard.push(top_ranks[0]);
top_k_ranks_best_shard.extend(top_ranks);
}
println!("ranks of top 20:");
summary_stats(&mut top_k_ranks_best_shard);
println!("ranks of top 1:");
summary_stats(&mut top_rank_best_shard);
println!("pq comparisons:");
summary_stats(&mut pq_cmps);
println!("comparisons:");
summary_stats(&mut cmps);
println!("recall@{}: {}", K, recall_total as f64 / (K * queries.len()) as f64);
Ok(())
}
pub async fn query_clip_server<I, O>(base_url: &str, path: &str, data: Option<I>) -> Result<O> where I: Serialize, O: serde::de::DeserializeOwned {
// TODO connection pool or something
// also this won't work over TLS
let url = hyper::Uri::from_str(base_url)?;
let stream = TcpStream::connect(format!("{}:{}", url.host().unwrap(), url.port_u16().unwrap_or(80))).await?;
let io = monoio_compat::hyper::MonoioIo::new(stream.into_poll_io()?);
let (mut sender, conn) = hyper::client::conn::http1::handshake(io).await?;
monoio::spawn(async move {
if let Err(err) = conn.await {
tracing::error!("connection failed: {:?}", err);
}
});
let authority = url.authority().unwrap().clone();
let req = Request::builder()
.uri(path)
.header(hyper::header::HOST, authority.as_str())
.header(hyper::header::CONTENT_TYPE, "application/msgpack");
let res = match data {
Some(data) => sender.send_request(req.method(Method::POST).body(Full::new(Bytes::from(rmp_serde::to_vec_named(&data)?)))?).await?,
None => sender.send_request(req.method(Method::GET).body(Full::new(Bytes::from("")))?).await?
};
if res.status() != StatusCode::OK {
return Err(anyhow::anyhow!("unexpected status code: {}", res.status()));
}
let data = res.collect().await?.to_bytes();
let result: O = rmp_serde::from_slice(&data)?;
Ok(result)
}
#[derive(Serialize, Deserialize)]
struct TelemetryMessage {
#[serde(rename="correlationId")]
correlation_id: String,
data: serde_json::Value,
event: String,
#[serde(rename="instanceId")]
instance_id: String,
page: Option<String>
}
#[derive(Clone)]
struct Service {
index: Rc<Index>,
inference_server_config: Rc<InferenceServerConfig>,
config: Rc<ServerConfig>,
telemetry_channel: std::sync::mpsc::Sender<TelemetryMessage>
}
impl hyper::service::Service<Request<Incoming>> for Service {
type Response = Response<Full<Bytes>>;
type Error = anyhow::Error;
type Future = Pin<Box<dyn Future<Output = Result<Self::Response, Self::Error>>>>;
fn call(&self, req: Request<Incoming>) -> Self::Future {
let index = self.index.clone();
let config = self.config.clone();
let inference_server_config = self.inference_server_config.clone();
let channel = self.telemetry_channel.clone();
Box::pin(async move {
let mut body = match (req.method(), req.uri().path()) {
(&Method::GET, "/") => Response::new(Full::new(Bytes::from(serde_json::to_vec(&FrontendInit {
n_total: (index.header.count - index.header.dead_count) as u64,
d_emb: index.header.quantizer.n_dims,
predefined_embedding_names: config.descriptor_names.clone()
})?))),
(&Method::POST, "/") => {
let upper = req.body().size_hint().upper().unwrap_or(u64::MAX);
if upper > 1<<23 {
let mut resp = Response::new(Full::new(Bytes::from("Body too big")));
*resp.status_mut() = hyper::StatusCode::PAYLOAD_TOO_LARGE;
return Ok(resp);
}
let whole_body = req.collect().await?.to_bytes();
let body: QueryRequest = serde_json::from_slice(&whole_body)?;
let query = common::get_total_embedding(
&body.terms,
&*inference_server_config,
|batch, _config| {
query_clip_server(config.clip_server.as_str(), "/", Some(batch))
},
|image, config| async move {
let image = image::load_from_memory(&image)?;
Ok(serde_bytes::ByteBuf::from(resize_for_embed_sync(&*config, image)?))
},
&std::collections::HashMap::new(),
inference_server_config.clone(),
()
).await?;
let selected_shard = index.header.shards.iter().position_max_by_key(|x| {
scale_dot_result_f64(SpatialSimilarity::dot(&x.0, &query).unwrap())
}).unwrap();
let selected_start = index.header.shards[selected_shard].1;
let beamwidth = config.beam_width;
let mut scratch = Scratch {
visited: HashSet::new(),
neighbour_buffer: NeighbourBuffer::new(config.search_list),
neighbour_pre_buffer: Vec::new(),
visited_list: Vec::new(),
visited_adjacent: HashSet::new(),
visited_embeddings: Vec::new()
};
let mut desc = vec![0.0, 0.0, 0.0, 0.0];
for term in &body.terms {
if let Some(name) = &term.predefined_embedding {
if let Some(index) = config.descriptor_names.iter().position(|x| x == name) {
desc[index] = term.weight.unwrap_or(1.0) * 1.0/512.0;
}
}
}
let descriptor_scales = DescriptorScales(desc);
let query_preprocessed = index.header.quantizer.preprocess_query(&query);
let query = query.iter().map(|x| half::f16::from_f32(*x)).collect::<Vec<f16>>();
let cmps_result = greedy_search(&mut scratch, selected_start, &query, &query_preprocessed, &descriptor_scales, index.clone(), false, beamwidth).await?;
QUERIES_COUNTER.inc();
let n_visited = scratch.visited_list.len();
let n_dims = index.header.quantizer.n_dims;
let visited_embeddings = std::mem::replace(&mut scratch.visited_embeddings, vec![]);
let similarities_against_self = monoio::spawn_blocking(move || {
let mut similarities_against_self = vec![0.0f32; n_visited * n_visited];
// runtime deduplication of results list
unsafe {
// vecs @ vecs.T
matrixmultiply::sgemm(
n_visited,
n_dims,
n_visited,
1.0,
visited_embeddings.as_ptr(),
n_dims as isize,
1,
visited_embeddings.as_ptr(),
1,
n_dims as isize,
0.0,
similarities_against_self.as_mut_ptr(),
n_visited as isize,
1
);
}
similarities_against_self
}).await.map_err(|e| anyhow::anyhow!("threadpool error: {:?}", e))?;
// discard anything similar to something already in list
let mut i = 0;
let mut included = bitvec::bitvec![0; n_visited];
scratch.visited_list.retain(|_node| {
let row = &similarities_against_self[(i * n_visited)..((i + 1) * n_visited)];
let old_i = i;
i += 1;
for (other_i, similarity) in row.iter().enumerate() {
if similarity > &DUPLICATES_THRESHOLD && included[other_i] {
return false;
}
}
included.set(old_i, true);
true
});
scratch.visited_list.sort_unstable_by_key(|x| -x.score);
let matches = scratch.visited_list
.drain(..)
.map(|node| {
let debug = if body.debug_enabled {
Some((node.scores, node.shards, node.timestamp))
} else {
None
};
((node.score as f64 / SCALE_F64) as f32, node.image_url, String::new(), 0, Some(node.dimensions), debug)
})
.collect::<Vec<_>>();
let result = QueryResult {
formats: vec![],
extensions: HashMap::new(),
matches
};
let result = serde_json::to_vec(&result)?;
Response::new(Full::new(Bytes::from(result)))
},
(&Method::GET, "/metrics") => {
let mut buffer = Vec::new();
let encoder = prometheus::TextEncoder::new();
let metric_families = prometheus::gather();
encoder.encode(&metric_families, &mut buffer).unwrap();
Response::builder()
.header(hyper::header::CONTENT_TYPE, "text/plain; version=0.0.4")
.body(Full::new(Bytes::from(buffer))).unwrap()
},
(&Method::POST, "/telemetry") => {
// TODO refactor
let upper = req.body().size_hint().upper().unwrap_or(u64::MAX);
if upper > 1000 {
let mut resp = Response::new(Full::new(Bytes::from("Body too big")));
*resp.status_mut() = hyper::StatusCode::PAYLOAD_TOO_LARGE;
return Ok(resp);
}
let whole_body = req.collect().await?.to_bytes();
let message = serde_json::from_slice::<TelemetryMessage>(&whole_body)?;
channel.send(message)?;
Response::builder()
.status(StatusCode::NO_CONTENT)
.body(Full::new(Bytes::from(""))).unwrap()
}
(&Method::OPTIONS, "/") => {
Response::builder()
.status(StatusCode::NO_CONTENT)
.body(Full::new(Bytes::from(""))).unwrap()
},
_ => Response::builder()
.status(StatusCode::NOT_FOUND)
.body(Full::new(Bytes::from("Not Found")))
.unwrap()
};
body.headers_mut().entry(hyper::header::CONTENT_TYPE).or_insert(hyper::header::HeaderValue::from_static("application/json"));
body.headers_mut().entry(hyper::header::ACCESS_CONTROL_ALLOW_ORIGIN).or_insert(hyper::header::HeaderValue::from_static("*"));
body.headers_mut().entry(hyper::header::ACCESS_CONTROL_ALLOW_METHODS).or_insert(hyper::header::HeaderValue::from_static("GET, POST, OPTIONS"));
body.headers_mut().entry(hyper::header::ACCESS_CONTROL_ALLOW_HEADERS).or_insert(hyper::header::HeaderValue::from_static("Content-Type"));
Result::<_, anyhow::Error>::Ok(body)
})
}
}
async fn get_backend_config(clip_server: &String) -> Result<InferenceServerConfig> {
loop {
match query_clip_server(clip_server, "/config", Option::<()>::None).await {
Ok(config) => return Ok(config),
Err(err) => {
tracing::warn!("waiting for clip server: {}", err);
monoio::time::sleep(std::time::Duration::from_secs(1)).await;
}
};
}
}
// can't run this as an async task because monoio File API is positional writes only
fn telemetry_handler(rx: std::sync::mpsc::Receiver<TelemetryMessage>, config: ServerConfig) -> Result<()> {
let mut telemetry_file = std::fs::OpenOptions::new().create(true).create(true).append(true).open(&config.telemetry_file)?;
while let Ok(message) = rx.recv() {
telemetry_file.write_all(rmp_serde::to_vec(&message)?.as_slice())?;
}
Ok(())
}
async fn serve(args: Arc<CLIArguments>, index: Rc<Index>) -> Result<()> {
let config: ServerConfig = serde_json::from_slice(&std::fs::read(args.config_path.as_ref().unwrap())?)?;
let (telemetry_channel, telemetry_receiver) = std::sync::mpsc::channel();
let config_ = config.clone();
std::thread::spawn(move || telemetry_handler(telemetry_receiver, config_));
let service = Service {
index,
inference_server_config: Rc::new(get_backend_config(&config.clip_server).await?),
config: Rc::new(config.clone()),
telemetry_channel
};
let listener = TcpListener::bind(config.listen_address)?;
println!("Listening");
loop {
let (stream, _) = listener.accept().await?;
let stream_poll = monoio_compat::hyper::MonoioIo::new(stream.into_poll_io()?);
let service = service.clone();
monoio::spawn(async move {
// Handle the connection from the client using HTTP1 and pass any
// HTTP requests received on that connection to the `hello` function
if let Err(err) = http1::Builder::new()
.timer(monoio_compat::hyper::MonoioTimer)
.serve_connection(stream_poll, service)
.await
{
println!("Error serving connection: {:?}", err);
}
});
}
}
struct MemoryMaps {
pq_codes: memmap2::Mmap,
descriptors: memmap2::Mmap,
guards: Vec<region::LockGuard>
}
async fn initialize_index(args: Arc<CLIArguments>, memory_maps: Arc<MemoryMaps>) -> Result<Rc<Index>> {
let index_path = PathBuf::from(&args.index_path);
let header: IndexHeader = rmp_serde::from_slice(&fs::read(index_path.join("index.msgpack")).await?)?;
let header = Rc::new(header);
// contains graph structure, full-precision vectors, and bulk metadata
let data_file = fs::File::open(index_path.join("index.bin")).await?;
// contains product quantization codes
println!("{} items {} dead {} shards", header.count, header.dead_count, header.shards.len());
let index = Rc::new(Index {
data_file,
header: header.clone(),
pq_code_size: header.quantizer.n_dims / header.quantizer.n_dims_per_code,
n_descriptors: header.descriptor_cdfs.len(),
memory_maps
});
Ok(index)
}
fn initialize_memory_maps(args: &CLIArguments) -> Result<MemoryMaps> {
let index_path = PathBuf::from(&args.index_path);
let pq_codes_file = std::fs::File::open(index_path.join("index.pq-codes.bin"))?;
let pq_codes = unsafe {
// This is unsafe because other processes could in principle edit the mmap'd file.
// It would be annoying to do anything about this possibility, so ignore it.
MmapOptions::new().populate().map_copy_read_only(&pq_codes_file)?
};
// contains metadata descriptors
let descriptors_file = std::fs::File::open(index_path.join("index.descriptor-codes.bin"))?;
let descriptors = unsafe {
MmapOptions::new().populate().map_copy_read_only(&descriptors_file)?
};
let guards = if args.lock_memory {
let g1 = region::lock(descriptors.as_ptr(), descriptors.len())?;
let g2 = region::lock(pq_codes.as_ptr(), pq_codes.len())?;
vec![g1, g2]
} else {
vec![]
};
Ok(MemoryMaps { pq_codes, descriptors, guards })
}
fn main() -> Result<()> {
let args: CLIArguments = argh::from_env();
let maps = Arc::new(initialize_memory_maps(&args)?);
let args = Arc::new(args);
if args.config_path.is_some() {
let mut join_handles = vec![];
for _ in 0..args.threads.unwrap_or(num_cpus::get()) {
let args_ = args.clone();
let maps_ = maps.clone();
let handle = std::thread::spawn(move || {
let pool = DefaultThreadPool::new(num_cpus::get());
let mut rt = monoio::RuntimeBuilder::<monoio::IoUringDriver>::new()
.attach_thread_pool(Box::new(pool))
.enable_timer()
.build().unwrap();
let index = rt.block_on(initialize_index(args_.clone(), maps_))?;
rt.block_on(serve(args_, index))
});
join_handles.push(handle);
}
for handle in join_handles {
handle.join().unwrap()?;
}
} else {
evaluate(args, maps)?;
}
Ok(())
}