1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
//! Raw bulk CRUD operations for Collection (`upsert_bulk_from_raw`).
//!
//! Extracted from `crud_bulk.rs` to keep each file under 500 NLOC.
//! These methods accept flat contiguous slices (zero-copy from numpy / FFI)
//! instead of `Point` structs, avoiding per-row `Vec<f32>` allocation.
use crate::collection::types::Collection;
use crate::error::{Error, Result};
use crate::storage::{PayloadStorage, VectorStorage};
use crate::validation::validate_dimension_match;
use std::collections::{HashMap, HashSet};
impl Collection {
/// Bulk insert from contiguous flat slices (zero-copy from numpy / FFI).
///
/// Accepts a flat `f32` slice of shape `(n, dimension)` in row-major order
/// plus a matching `u64` ID slice of length `n`. This avoids per-row
/// `Vec<f32>` allocation that `upsert_bulk` requires through `Point`.
///
/// # Performance
///
/// Eliminates `n * dimension * 4` bytes of intermediate copies compared
/// to the `Point`-based `upsert_bulk` path. For 100K vectors at 768D
/// this saves ~293 MB of heap allocations.
///
/// # Errors
///
/// - Returns [`crate::error::Error::InvalidVector`] if `vectors.len() != ids.len() * dimension`.
/// - Returns [`crate::error::Error::DimensionMismatch`] if `dimension` does not match the collection.
pub fn upsert_bulk_from_raw(
&self,
vectors: &[f32],
ids: &[u64],
dimension: usize,
payloads: Option<&[Option<serde_json::Value>]>,
) -> Result<usize> {
// LOCK ORDER: config(1, read) → payload_storage(3, read) →
// store_vectors_and_payload_entries (vector_storage(2) ‖ payload_storage(3)) →
// secondary_indexes(6, read) → label_index(7, write) → HNSW index (internal) →
// config(1, write).
let n = ids.len();
if n == 0 {
return Ok(0);
}
// Validate inputs and enforce the runtime ingest limits (parity item E)
// BEFORE any state mutation, so the caps are not bypassable on this
// zero-copy path (the dominant Python/REST bulk upsert surface).
self.validate_raw_inputs(vectors, ids, dimension, payloads)?;
// Build (id, &[f32]) pairs by slicing the flat buffer -- zero copy.
let vector_refs: Vec<(u64, &[f32])> = ids
.iter()
.enumerate()
.map(|(i, &id)| (id, &vectors[i * dimension..(i + 1) * dimension]))
.collect();
// Collect pre-batch payloads BEFORE overwriting -- for histogram decrements.
// Bug #46: deduplicate by ID -- only the first occurrence retrieves the
// pre-batch value; duplicates get None so the old value is decremented
// exactly once.
let old_payloads: Vec<Option<serde_json::Value>> = if payloads.is_some() {
let storage = self.payload_storage.read();
let mut seen = HashSet::new();
ids.iter()
.map(|&id| {
if seen.insert(id) {
storage.retrieve(id).ok().flatten()
} else {
None
}
})
.collect()
} else {
Vec::new()
};
// Payload entries for batch WAL write (only ids that have payloads).
let payload_entries: Vec<(u64, &serde_json::Value)> = payloads
.into_iter()
.flat_map(|ps| {
ps.iter()
.enumerate()
.filter_map(|(i, opt)| opt.as_ref().map(|val| (ids[i], val)))
})
.collect();
self.store_vectors_and_payload_entries(&vector_refs, &payload_entries)?;
self.update_text_index_from_raw(ids, payloads)?;
self.update_label_index_from_raw(ids, payloads);
self.update_secondary_indexes_from_raw(ids, payloads, &old_payloads);
let inserted = self.bulk_index_or_defer(&vector_refs);
self.config.write().point_count = self.vector_storage.read().len();
self.maintain_histograms_for_raw(ids, payloads, &old_payloads);
self.invalidate_caches_and_bump_generation();
Ok(inserted)
}
/// Incremental histogram maintenance for a raw-slices bulk upsert.
///
/// Decrements old values and increments new values in a single atomic
/// read/modify/write cycle (Bug #49). Bug #47: only the last occurrence
/// per ID is counted for new payloads to match last-writer-wins storage
/// semantics.
///
/// Extracted from `upsert_bulk_from_raw` to keep its CC under the
/// Codacy limit after adding the BM25 WAL propagation (#389).
fn maintain_histograms_for_raw(
&self,
ids: &[u64],
payloads: Option<&[Option<serde_json::Value>]>,
old_payloads: &[Option<serde_json::Value>],
) {
let Some(ps) = payloads else { return };
let mut dedup_map: HashMap<u64, usize> = HashMap::with_capacity(ids.len());
for (i, &id) in ids.iter().enumerate() {
dedup_map.insert(id, i);
}
let owned: Vec<Option<serde_json::Value>> = ps
.iter()
.enumerate()
.map(|(i, opt)| {
if dedup_map.get(&ids[i]) == Some(&i) {
opt.clone()
} else {
None
}
})
.collect();
self.update_histograms_replace(old_payloads, &owned);
}
/// Enforces the runtime ingest limits (parity item E) for the raw bulk
/// path, reusing the shared `Collection` gates so the slice-based and
/// `Point`-based ingest paths apply identical caps.
///
/// # Errors
///
/// Returns [`crate::error::Error::GuardRail`] when the batch would push the
/// collection past `max_vectors_per_collection`, or when any payload
/// exceeds `max_payload_size`.
fn enforce_raw_upsert_limits(
&self,
ids: &[u64],
payloads: Option<&[Option<serde_json::Value>]>,
) -> Result<()> {
let limits = self.runtime_limits();
self.enforce_vector_count(ids.len(), limits.max_vectors_per_collection)?;
if let Some(ps) = payloads {
for (i, opt) in ps.iter().enumerate() {
if let Some(payload) = opt {
Self::enforce_payload_value_size(ids[i], payload, limits.max_payload_size)?;
}
}
}
Ok(())
}
/// Validates raw bulk-insert inputs before any state mutation.
fn validate_raw_inputs(
&self,
vectors: &[f32],
ids: &[u64],
dimension: usize,
payloads: Option<&[Option<serde_json::Value>]>,
) -> Result<()> {
let n = ids.len();
let expected_len = n.checked_mul(dimension).ok_or_else(|| {
Error::InvalidVector(format!(
"overflow computing {n} * {dimension} for flat vector length"
))
})?;
if vectors.len() != expected_len {
return Err(Error::InvalidVector(format!(
"flat vectors length {} != ids.len() ({n}) * dimension ({dimension}) = {expected_len}",
vectors.len()
)));
}
if let Some(ps) = payloads {
if ps.len() != n {
return Err(Error::InvalidVector(format!(
"payloads length ({}) must match ids length ({n})",
ps.len()
)));
}
}
let collection_dim = self.config.read().dimension;
validate_dimension_match(collection_dim, dimension)?;
self.enforce_raw_upsert_limits(ids, payloads)?;
Ok(())
}
/// Stores pre-built payload entries via batch WAL write + flush.
///
/// Extracted from `bulk_store_payloads` to accept `(u64, &Value)` pairs
/// directly, avoiding the need to reconstruct `Point` structs.
fn bulk_store_payload_entries(&self, entries: &[(u64, &serde_json::Value)]) -> Result<()> {
self.bulk_store_payload_entries_inner(entries, true)
}
/// Stores payload entries with configurable fsync behavior.
fn bulk_store_payload_entries_inner(
&self,
entries: &[(u64, &serde_json::Value)],
fsync: bool,
) -> Result<()> {
if entries.is_empty() {
return Ok(());
}
if fsync {
self.payload_storage.write().store_batch(entries)?;
} else {
self.payload_storage.write().store_batch_deferred(entries)?;
}
Ok(())
}
/// Writes vectors and raw payload entries to storage (parallel when available).
fn store_vectors_and_payload_entries(
&self,
vector_refs: &[(u64, &[f32])],
payload_entries: &[(u64, &serde_json::Value)],
) -> Result<()> {
// LOCK ORDER: vector_storage(2, write, parallel) ‖ payload_storage(3, write, parallel).
// Each rayon closure acquires only one lock — no ordering dependency between them.
#[cfg(feature = "persistence")]
{
let (vec_result, pay_result) = rayon::join(
|| self.bulk_store_vectors(vector_refs),
|| self.bulk_store_payload_entries(payload_entries),
);
vec_result?;
pay_result?;
}
#[cfg(not(feature = "persistence"))]
{
self.bulk_store_vectors(vector_refs)?;
self.bulk_store_payload_entries(payload_entries)?;
}
Ok(())
}
/// Batch-updates secondary indexes from raw payload slices.
///
/// For each point with a payload, **removes the prior indexed value and
/// inserts the new one** (via [`update_secondary_indexes_on_upsert`]) so an
/// overwrite of an already-indexed point does not leave a stale entry in the
/// old key's bucket. Without the removal the same id would sit in both its
/// old and new key buckets, inflating `Σ buckets` above `point_count` so the
/// ordered-index coverage check declines the fast path — and a restart that
/// rebuilds from the final stored payload (backfill) would then diverge from
/// the live tree (EPIC-081 phase 3d restore equivalence). `old_payloads[i]`
/// is the pre-batch payload for `ids[i]` (already collected by the caller),
/// deduplicated so a duplicate id within the same batch carries `None`.
///
/// Skips entirely when no secondary indexes exist (fast path for bulk
/// loading before `create_index`).
///
/// [`update_secondary_indexes_on_upsert`]: Self::update_secondary_indexes_on_upsert
fn update_secondary_indexes_from_raw(
&self,
ids: &[u64],
payloads: Option<&[Option<serde_json::Value>]>,
old_payloads: &[Option<serde_json::Value>],
) {
let Some(ps) = payloads else { return };
if self.secondary_indexes.read().is_empty() {
return;
}
for (i, opt) in ps.iter().enumerate() {
if opt.is_none() {
continue;
}
let old = old_payloads.get(i).and_then(Option::as_ref);
self.update_secondary_indexes_on_upsert(ids[i], old, opt.as_ref());
}
}
/// Updates BM25 text index from raw payload slices (WAL-then-apply).
///
/// Points with `Some(payload)` get their text indexed; points with
/// `None` payload get their stale BM25 entry removed. Mirrors the
/// contract of `update_text_index` in `crud.rs`.
///
/// Issue #389: each mutation is appended to the BM25 WAL BEFORE it
/// is applied in-memory so that a crash between the two replays
/// the mutation on next open. WAL append errors propagate and the
/// in-memory mutation is skipped, so in-memory and WAL state never
/// diverge.
fn update_text_index_from_raw(
&self,
ids: &[u64],
payloads: Option<&[Option<serde_json::Value>]>,
) -> Result<()> {
let Some(ps) = payloads else { return Ok(()) };
for (i, opt) in ps.iter().enumerate() {
if let Some(payload) = opt {
let text = Self::extract_text_from_payload(payload);
if !text.is_empty() {
#[cfg(feature = "persistence")]
self.append_bm25_wal_add(ids[i], &text)?;
self.text_index.add_document(ids[i], &text);
}
} else {
#[cfg(feature = "persistence")]
self.append_bm25_wal_remove(ids[i])?;
self.text_index.remove_document(ids[i]);
}
}
Ok(())
}
/// Batch-updates the label index from raw payload slices.
///
/// Mirrors `update_text_index_from_raw` but for the label index.
/// Only indexes payloads that contain `_labels` arrays.
///
/// LOCK ORDER: label_index(7) -- after payload_storage(3).
fn update_label_index_from_raw(
&self,
ids: &[u64],
payloads: Option<&[Option<serde_json::Value>]>,
) {
let Some(ps) = payloads else { return };
let has_labels = ps
.iter()
.any(|opt| opt.as_ref().is_some_and(|v| v.get("_labels").is_some()));
if !has_labels {
return;
}
let mut label_idx = self.label_index.write();
for (i, opt) in ps.iter().enumerate() {
if let Some(payload) = opt {
label_idx.index_from_payload(ids[i], payload);
}
}
}
}