Files
qdrant/lib/segment/tests/integration/gpu_hnsw_test.rs
qdrant-cloud-bot 7e15d343c2 Introduce EdgeShardConfig for edge shard (#8322)
* Introduce EdgeShardConfig for edge shard

- Add EdgeShardConfig and EdgeOptimizersConfig in lib/edge/src/config.rs
  - Segment config (vector_data, sparse_vector_data, payload_storage_type)
  - Global hnsw_config and per-vector HNSW in segment config
  - Optimizer params: deleted_threshold, vacuum_min_vector_number,
    default_segment_number, max_segment_size, indexing_threshold,
    prevent_unoptimized (excludes memmap_threshold, flush_interval_sec,
    max_optimization_threads)
- Persist/load as edge_config.json in shard path
- EdgeShard uses RwLock<EdgeShardConfig>; load() accepts Option<EdgeShardConfig>,
  falls back to file or infer from segments; compatibility checked on load
- load_with_segment_config() for backward compatibility (SegmentConfig -> EdgeShardConfig)
- optimize() uses EdgeShardConfig for hnsw and optimizer thresholds
- Public methods: set_hnsw_config(), set_vector_hnsw_config(), set_optimizers_config()
  (update and persist)
- Python and examples use load_with_segment_config with existing config API

Made-with: Cursor

* Refactor EdgeShardConfig: user-facing params only, config module

- Replace SegmentConfig inside EdgeShardConfig with user-facing fields:
  - on_disk_payload (bool) instead of payload_storage_type
  - vectors: HashMap<VectorNameBuf, EdgeVectorParams> with on_disk per vector,
    no per-vector quantization; global quantization_config only
  - sparse_vectors: HashMap<VectorNameBuf, EdgeSparseVectorParams> with on_disk
- EdgeVectorParams / EdgeSparseVectorParams use on_disk (bool) instead of
  storage_type; conversion to VectorDataConfig/SparseVectorDataConfig in
  to_segment_config()
- Add config module: mod.rs, optimizers.rs, vectors.rs, shard.rs
- from_segment_config(&SegmentConfig) fills all inferrable params
- to_segment_config() builds SegmentConfig for segments and optimize()
- load_with_segment_config takes Option<SegmentConfig>, uses from_segment_config

Made-with: Cursor

* Move optimizer threshold helpers to shard crate

- Add get_number_segments, get_indexing_threshold_kb, get_max_segment_size_kb,
  get_deferred_points_threshold_bytes in shard::optimizers::config
- Collection OptimizersConfig and edge EdgeOptimizersConfig delegate to these
- Single place for threshold logic; collection and edge use shard helpers

Made-with: Cursor

* Use destructuring in config conversions to avoid missing new fields

- EdgeVectorParams: destructure VectorDataConfig in from_*, destructure self in to_vector_data_config
- EdgeSparseVectorParams: destructure SparseVectorDataConfig and SparseIndexConfig in from_*, destructure self in to_sparse_vector_data_config
- EdgeShardConfig: destructure SegmentConfig in from_segment_config, destructure self in to_segment_config
Adding new fields to source structs will now cause compile errors until conversions are updated.

Made-with: Cursor

* refactor: centralize on_disk_payload→payload_storage_type, on_disk→storage_type, and appendable quantization logic

- PayloadStorageType::from_on_disk_payload(bool) in segment (Mmap/InRamMmap)
- VectorStorageType::from_on_disk(bool) in segment (ChunkedMmap/InRamChunkedMmap)
- QuantizationConfig::for_appendable_segment(Option<&Self>) in segment (feature flag + supports_appendable)
- collection: use from_on_disk_payload in non-rocksdb branch
- edge shard/vectors: use new helpers; remove duplicated conditionals
- shard optimizers: use from_on_disk and for_appendable_segment

Made-with: Cursor

* refactor(edge): use EdgeShardConfig directly, drop segment_config

- Add plain_segment_config() for create_appendable_segment (no HNSW)
- Add segment_optimizer_config() built from EdgeShardConfig for blocking optimizers
- Add vector_data_config(name) for query/MMR
- build_blocking_optimizers: use segment_optimizer_config() instead of SegmentConfig
- create_appendable_segment: use plain_segment_config()
- search/query: use config().vectors and vector_data_config() instead of segment_config()
- Remove segment_config() from EdgeShardConfig and EdgeShard
- Add to_plain_vector_data_config on EdgeVectorParams

Made-with: Cursor

* [manual] review changes

* refactor(edge-py): wrap EdgeShardConfig, add EdgeVectorParams/EdgeSparseVectorParams

- PyEdgeConfig now wraps EdgeShardConfig (vectors, sparse_vectors, on_disk_payload, etc.)
- PyEdgeVectorParams / PyEdgeSparseVectorParams wrap edge config types
- PyEdgeOptimizersConfig for optional optimizer settings
- EdgeShard.load() uses EdgeShardConfig; edge::config made pub for Python crate
- cargo fmt + clippy (remove map_identity)

Made-with: Cursor

* refactor(edge-py): simplify config API, remove unused Py* types, add EdgeConfig

- Remove unused PyPayloadStorageType, PyVectorDataConfig, PyVectorStorageType,
  PySparseVectorDataConfig, PySparseVectorStorageType from Python bindings
- Move PyEdgeOptimizersConfig to lib/edge/python/src/config/optimizers.rs
- Update qdrant_edge.pyi: EdgeConfig with vectors/sparse_vectors,
  EdgeVectorParams, EdgeSparseVectorParams, EdgeOptimizersConfig
- Update examples (common.py, repr.py) to use new config API
- Run cargo fmt

Made-with: Cursor

* [manual] review changes

* [manual] review changes

* [manual] fix test

* Address CodeRabbit review comments for PR 8322 (#8324)

* Address CodeRabbit review comments for PR 8322

- Python examples: explicit imports (repr.py, common.py) and new EdgeConfig API
- HnswIndexConfig: add max_indexing_threads param and property in .pyi and Rust bindings
- EdgeConfig: make vectors optional for sparse-only configs; validate at least one of vectors/sparse_vectors
- EdgeShardConfig::load: use try_exists(), propagate I/O errors
- from_segment_config: infer hnsw_config from per-vector HNSW when all agree
- EdgeShard setters: atomic clone-mutate-save-then-replace; persist config save errors
- Segment compat: prefix vector name in error messages; resolve None datatype to Float32
- max_indexing_threads: preserve 0 (auto) sentinel in trait default; remove per-optimizer overrides
- SegmentOptimizerConfig:🆕 build plain and optimizer maps in single pass
- config_mismatch_optimizer tests: use VectorNameBuf::from() instead of .into()
- vectors.rs: doc updates for per-vector quantization

Made-with: Cursor

* Address @generall review: SaveOnDisk for config, resolve num_rayon_threads in optimizer

- Use SaveOnDisk<EdgeShardConfig> for EdgeShard config (generall: 'We have SaveOnDisk struct for this')
  - Create via SaveOnDisk::new() after resolving config; setters use .write() for atomic persist
  - set_vector_hnsw_config: clone then mutate then write (fallible setter)
- max_indexing_threads: resolve 0 (auto) via num_rayon_threads inside impl (generall: 'proper solution would be to resolve num_rayon_threads inside the optimizer impl')
  - max_indexing_threads_sentinel_aware() now returns Some(num_rayon_threads(raw)) so callers get actual thread count

Made-with: Cursor

* [manual] reorganize num_rayon_threads -> get_num_indexing_threads to better account per-vector configuration

---------

Co-authored-by: Cursor Agent <agent@cursor.com>
Co-authored-by: generall <andrey@vasnetsov.com>

* update docstring and pyi

* fmt

* fmt

* clipy

---------

Co-authored-by: Cursor Agent <agent@cursor.com>
Co-authored-by: generall <andrey@vasnetsov.com>
2026-03-10 00:10:04 +01:00

234 lines
7.5 KiB
Rust

use std::sync::Arc;
use std::sync::atomic::AtomicBool;
use common::budget::ResourcePermit;
use common::counter::hardware_counter::HardwareCounterCell;
use common::flags::FeatureFlags;
use common::progress_tracker::ProgressTracker;
use common::types::TelemetryDetail;
use ordered_float::OrderedFloat;
use parking_lot::Mutex;
use rand::prelude::StdRng;
use rand::{RngExt, SeedableRng};
use segment::data_types::vectors::{DEFAULT_VECTOR_NAME, only_default_vector};
use segment::entry::entry_point::SegmentEntry;
use segment::fixtures::payload_fixtures::{random_int_payload, random_vector};
use segment::index::hnsw_index::get_num_indexing_threads;
use segment::index::hnsw_index::gpu::gpu_devices_manager::LockedGpuDevice;
use segment::index::hnsw_index::hnsw::{HNSWIndex, HnswIndexOpenArgs};
use segment::index::{PayloadIndex, VectorIndex};
use segment::json_path::JsonPath;
use segment::payload_json;
use segment::segment_constructor::VectorIndexBuildArgs;
use segment::segment_constructor::simple_segment_constructor::build_simple_segment;
use segment::types::{
Condition, Distance, FieldCondition, Filter, HnswConfig, HnswGlobalConfig, PayloadSchemaType,
Range, SearchParams, SeqNumberType,
};
use tempfile::Builder;
/// Captured logs from env_logger. It's used to check that indexing was performed using GPU correctly.
/// We cannot just check `Ok` because it's possible that GPU fails and index will be built on CPU without errors.
pub struct CapturedLogs {
strings: Arc<Mutex<Vec<String>>>,
}
impl std::io::Write for CapturedLogs {
fn write(&mut self, buf: &[u8]) -> std::io::Result<usize> {
if let Ok(buf_str) = std::str::from_utf8(buf) {
let mut strings = self.strings.lock();
strings.push(buf_str.to_string());
}
Ok(buf.len())
}
fn flush(&mut self) -> std::io::Result<()> {
Ok(())
}
}
#[test]
fn test_gpu_filterable_hnsw() {
let captured_logs = Arc::new(Mutex::new(Vec::new()));
let _env_logger = env_logger::builder()
.is_test(true)
.target(env_logger::Target::Pipe(Box::new(CapturedLogs {
strings: captured_logs.clone(),
})))
.filter_level(log::LevelFilter::Trace)
.try_init();
let stopped = AtomicBool::new(false);
let max_failures = 7;
let dim = 8;
let m = 8;
let num_vectors: u64 = 10_000;
let ef = 32;
let ef_construct = 16;
let distance = Distance::Cosine;
let full_scan_threshold = 32; // KB
let num_payload_values = 2;
let mut rng = StdRng::seed_from_u64(42);
let dir = Builder::new().prefix("segment_dir").tempdir().unwrap();
let hnsw_dir = Builder::new().prefix("hnsw_dir").tempdir().unwrap();
let int_key = "int";
let hw_counter = HardwareCounterCell::new();
let mut segment = build_simple_segment(dir.path(), dim, distance).unwrap();
for n in 0..num_vectors {
let idx = n.into();
let vector = random_vector(&mut rng, dim);
let int_payload = random_int_payload(&mut rng, num_payload_values..=num_payload_values);
let payload = payload_json! {int_key: int_payload};
segment
.upsert_point(
n as SeqNumberType,
idx,
only_default_vector(&vector),
&hw_counter,
)
.unwrap();
segment
.set_full_payload(n as SeqNumberType, idx, &payload, &hw_counter)
.unwrap();
}
let payload_index_ptr = segment.payload_index.clone();
let hnsw_config = HnswConfig {
m,
ef_construct,
full_scan_threshold,
max_indexing_threads: 2,
on_disk: Some(false),
payload_m: None,
inline_storage: None,
};
let vector_storage = &segment.vector_data[DEFAULT_VECTOR_NAME].vector_storage;
let quantized_vectors = &segment.vector_data[DEFAULT_VECTOR_NAME].quantized_vectors;
payload_index_ptr
.borrow_mut()
.set_indexed(
&JsonPath::new(int_key),
PayloadSchemaType::Integer,
&hw_counter,
)
.unwrap();
let permit_cpu_count = get_num_indexing_threads(hnsw_config.max_indexing_threads);
let permit = Arc::new(ResourcePermit::dummy(permit_cpu_count as u32));
let instance = gpu::GPU_TEST_INSTANCE.clone();
let device =
Mutex::new(gpu::Device::new(instance.clone(), &instance.physical_devices()[0]).unwrap());
let locked_device = LockedGpuDevice::new(device.lock());
let hnsw_index = HNSWIndex::build(
HnswIndexOpenArgs {
path: hnsw_dir.path(),
id_tracker: segment.id_tracker.clone(),
vector_storage: vector_storage.clone(),
quantized_vectors: quantized_vectors.clone(),
payload_index: payload_index_ptr.clone(),
hnsw_config,
},
VectorIndexBuildArgs {
permit,
old_indices: &[],
gpu_device: Some(&locked_device), // enable GPU
rng: &mut rng,
stopped: &stopped,
hnsw_global_config: &HnswGlobalConfig::default(),
feature_flags: FeatureFlags::default(),
progress: ProgressTracker::new_for_test(),
},
)
.unwrap();
let top = 3;
let mut hits = 0;
let attempts = 100;
for i in 0..attempts {
let query = random_vector(&mut rng, dim).into();
let range_size = 40;
let left_range = rng.random_range(0..400);
let right_range = left_range + range_size;
let filter = Filter::new_must(Condition::Field(FieldCondition::new_range(
JsonPath::new(int_key),
Range {
lt: None,
gt: None,
gte: Some(OrderedFloat::from(f64::from(left_range))),
lte: Some(OrderedFloat::from(f64::from(right_range))),
},
)));
let filter_query = Some(&filter);
let index_result = hnsw_index
.search(
&[&query],
filter_query,
top,
Some(&SearchParams {
hnsw_ef: Some(ef),
..Default::default()
}),
&Default::default(),
)
.unwrap();
// check that search was performed using HNSW index
assert_eq!(
hnsw_index
.get_telemetry_data(TelemetryDetail::default())
.filtered_large_cardinality
.count,
i + 1
);
let plain_result = segment.vector_data[DEFAULT_VECTOR_NAME]
.vector_index
.borrow()
.search(&[&query], filter_query, top, None, &Default::default())
.unwrap();
if plain_result == index_result {
hits += 1;
}
}
assert!(
attempts - hits <= max_failures,
"hits: {hits} of {attempts}"
); // Not more than X% failures
eprintln!("hits = {hits:#?} out of {attempts}");
// Check from logs that GPU was used correctly.
let logs = captured_logs.lock().clone();
const UPLOAD_VECTORS_PATTERN: &str = "Upload vector data";
const UPLOAD_LINKS_PATTERN: &str = "Upload links on level 0";
// Check that vectors was uploaded to GPU only one time.
assert_eq!(
logs.iter()
.filter(|s| s.contains(UPLOAD_VECTORS_PATTERN))
.count(),
1
);
// Check that indexing was called more than one time.
let gpu_indexes_count = logs
.iter()
.filter(|s| s.contains(UPLOAD_LINKS_PATTERN))
.count();
assert!(gpu_indexes_count > 1);
}