wedb_embed 0.1.4

Embedded database engine providing Redis-like APIs, built on fjall / 嵌入式数据库引擎,提供类似 Redis 的接口,底层基于 fjall 开发
Documentation
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
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
use std::str;

use simsimd::SpatialSimilarity;
use sonic_rs::{JsonContainerTrait, JsonValueTrait};

use crate::{
  error::{Error, Result},
  key_composer::{decode_oppv_u64, encode_oppv_u64, oppv_len_u64},
  meta::{decode_hex_u64, u64_to_hex_16},
  search::meta::{
    DistanceMetric, IndexFieldType, IndexOnDataType, VectorAlgorithm, VectorFieldMetadata,
    VectorType,
  },
};

/// Domain operation (aligned with Apache Kvrocks SearchSubkeyType).
/// 检索子键类型枚举(对标 Apache Kvrocks SearchSubkeyType)
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
#[repr(u8)]
pub enum SearchSubkeyType {
  IndexMeta = 0,
  Prefixes = 1,
  FieldMeta = 2,
  Field = 3,
  FieldAlias = 4,
}

impl SearchSubkeyType {
  #[inline]
  pub const fn from_u8(val: u8) -> Option<Self> {
    match val {
      0 => Some(Self::IndexMeta),
      1 => Some(Self::Prefixes),
      2 => Some(Self::FieldMeta),
      3 => Some(Self::Field),
      4 => Some(Self::FieldAlias),
      _ => None,
    }
  }
}

/// Domain operation (aligned with Apache Kvrocks HnswLevelType).
/// HNSW 图层级数据类型(对标 Apache Kvrocks HnswLevelType)
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
#[repr(u8)]
pub enum HnswLevelType {
  Node = 1,
  Edge = 2,
}

impl HnswLevelType {
  #[inline]
  pub const fn from_u8(val: u8) -> Option<Self> {
    match val {
      1 => Some(Self::Node),
      2 => Some(Self::Edge),
      _ => None,
    }
  }
}

/// Composes storage key or prefix.
/// 检索键构造器(对标 Apache Kvrocks SearchKey,全面采用 OPPV 与数值命名空间)
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct SearchKey<'a> {
  pub ns_id: u64,
  pub index: &'a str,
  pub field: Option<&'a str>,
}

impl<'a> SearchKey<'a> {
  #[inline]
  pub const fn new(ns_id: u64, index: &'a str) -> Self {
    Self {
      ns_id,
      index,
      field: None,
    }
  }

  #[inline]
  pub const fn with_field(ns_id: u64, index: &'a str, field: &'a str) -> Self {
    Self {
      ns_id,
      index,
      field: Some(field),
    }
  }

  #[inline]
  pub fn put_namespace(dst: &mut Vec<u8>, ns_id: u64) {
    dst.push(0);
    encode_oppv_u64(ns_id, dst);
  }

  #[inline]
  pub fn put_type(dst: &mut Vec<u8>, subkey_type: SearchSubkeyType) {
    dst.push(subkey_type as u8);
  }

  #[inline]
  pub fn put_sized_string(dst: &mut Vec<u8>, s: &str) {
    encode_oppv_u64(s.len() as u64, dst);
    dst.extend_from_slice(s.as_bytes());
  }

  #[inline]
  pub fn get_sized_string<'b>(input: &mut &'b [u8]) -> Option<&'b str> {
    let (len, consumed) = decode_oppv_u64(input)?;
    let len = len as usize;
    *input = &input[consumed..];
    if input.len() < len {
      return None;
    }
    let str_bytes = &input[..len];
    *input = &input[len..];
    str::from_utf8(str_bytes).ok()
  }

  #[inline]
  pub fn put_hnsw_level_prefix(
    dst: &mut Vec<u8>,
    ns_id: u64,
    index: &str,
    field: &str,
    level: u16,
  ) {
    Self::put_namespace(dst, ns_id);
    Self::put_type(dst, SearchSubkeyType::Field);
    Self::put_sized_string(dst, index);
    Self::put_sized_string(dst, field);
    dst.extend_from_slice(&level.to_be_bytes());
  }

  #[inline]
  pub fn put_hnsw_level_node_prefix(
    dst: &mut Vec<u8>,
    ns_id: u64,
    index: &str,
    field: &str,
    level: u16,
  ) {
    Self::put_hnsw_level_prefix(dst, ns_id, index, field, level);
    dst.push(HnswLevelType::Node as u8);
  }

  #[inline]
  pub fn put_hnsw_level_edge_prefix(
    dst: &mut Vec<u8>,
    ns_id: u64,
    index: &str,
    field: &str,
    level: u16,
  ) {
    Self::put_hnsw_level_prefix(dst, ns_id, index, field, level);
    dst.push(HnswLevelType::Edge as u8);
  }

  #[inline]
  pub fn construct_index_meta(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len());
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::IndexMeta);
    Self::put_sized_string(&mut dst, self.index);
    dst
  }

  #[inline]
  pub fn construct_index_prefixes(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len());
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::Prefixes);
    Self::put_sized_string(&mut dst, self.index);
    dst
  }

  #[inline]
  pub fn construct_field_meta(&self) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 9 + field_name.len(),
    );
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::FieldMeta);
    Self::put_sized_string(&mut dst, self.index);
    Self::put_sized_string(&mut dst, field_name);
    dst
  }

  #[inline]
  pub fn construct_all_field_meta_begin(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 1);
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::FieldMeta);
    Self::put_sized_string(&mut dst, self.index);
    dst.push(0);
    dst
  }

  #[inline]
  pub fn construct_all_field_meta_end(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 1);
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::FieldMeta);
    Self::put_sized_string(&mut dst, self.index);
    dst.push(0xFF);
    dst
  }

  #[inline]
  pub fn construct_all_field_data_begin(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 1);
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::Field);
    Self::put_sized_string(&mut dst, self.index);
    dst.push(0);
    dst
  }

  #[inline]
  pub fn construct_all_field_data_end(&self) -> Vec<u8> {
    let mut dst = Vec::with_capacity(1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 1);
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::Field);
    Self::put_sized_string(&mut dst, self.index);
    dst.push(0xFF);
    dst
  }

  #[inline]
  pub fn construct_tag_field_data(&self, tag: &str, key: &str) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id)
        + 1
        + 9
        + self.index.len()
        + 9
        + field_name.len()
        + 9
        + tag.len()
        + 9
        + key.len(),
    );
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::Field);
    Self::put_sized_string(&mut dst, self.index);
    Self::put_sized_string(&mut dst, field_name);
    Self::put_sized_string(&mut dst, tag);
    Self::put_sized_string(&mut dst, key);
    dst
  }

  #[inline]
  pub fn construct_numeric_field_data(&self, num: f64, key: &str) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id)
        + 1
        + 9
        + self.index.len()
        + 9
        + field_name.len()
        + 8
        + 9
        + key.len(),
    );
    Self::put_namespace(&mut dst, self.ns_id);
    Self::put_type(&mut dst, SearchSubkeyType::Field);
    Self::put_sized_string(&mut dst, self.index);
    Self::put_sized_string(&mut dst, field_name);
    dst.extend_from_slice(&encode_sortable_f64_u64(num).to_be_bytes());
    Self::put_sized_string(&mut dst, key);
    dst
  }

  #[inline]
  pub fn construct_hnsw_level_node_prefix(&self, level: u16) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id) + 1 + 9 + self.index.len() + 9 + field_name.len() + 2 + 1,
    );
    Self::put_hnsw_level_node_prefix(&mut dst, self.ns_id, self.index, field_name, level);
    dst
  }

  #[inline]
  pub fn construct_hnsw_node(&self, level: u16, key: &str) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id)
        + 1
        + 9
        + self.index.len()
        + 9
        + field_name.len()
        + 2
        + 1
        + 9
        + key.len(),
    );
    Self::put_hnsw_level_node_prefix(&mut dst, self.ns_id, self.index, field_name, level);
    Self::put_sized_string(&mut dst, key);
    dst
  }

  #[inline]
  pub fn construct_hnsw_edge_with_single_end(&self, level: u16, key: &str) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id)
        + 1
        + 9
        + self.index.len()
        + 9
        + field_name.len()
        + 2
        + 1
        + 9
        + key.len(),
    );
    Self::put_hnsw_level_edge_prefix(&mut dst, self.ns_id, self.index, field_name, level);
    Self::put_sized_string(&mut dst, key);
    dst
  }

  #[inline]
  pub fn construct_hnsw_edge(&self, level: u16, key1: &str, key2: &str) -> Vec<u8> {
    let field_name = self.field.unwrap_or("");
    let mut dst = Vec::with_capacity(
      1 + oppv_len_u64(self.ns_id)
        + 1
        + 9
        + self.index.len()
        + 9
        + field_name.len()
        + 2
        + 1
        + 9
        + key1.len()
        + 9
        + key2.len(),
    );
    Self::put_hnsw_level_edge_prefix(&mut dst, self.ns_id, self.index, field_name, level);
    Self::put_sized_string(&mut dst, key1);
    Self::put_sized_string(&mut dst, key2);
    dst
  }
}

/// Encodes data into binary format.
/// 索引元数据二进制编码(对标 Apache Kvrocks IndexMetadata::Encode)
#[inline]
pub fn encode_index_meta(on_data_type: IndexOnDataType) -> Vec<u8> {
  vec![0u8, on_data_type as u8]
}

/// Decodes data from binary format.
/// 索引元数据二进制解码(对标 Apache Kvrocks IndexMetadata::Decode)
#[inline]
pub fn decode_index_meta(slice: &[u8]) -> Result<IndexOnDataType> {
  if slice.len() < 2 {
    return Err(Error::invalid_data(
      "insufficient length while decoding metadata",
    ));
  }
  match slice[1] {
    2 => Ok(IndexOnDataType::Hash),
    10 => Ok(IndexOnDataType::Json),
    other => Err(Error::invalid_data(format!(
      "unknown on_data_type: {other}"
    ))),
  }
}

/// Encodes data into binary format with prefix-free OPPV string length encoding.
/// 索引前缀列表二进制编码(OPPV 变长保序编码)
pub fn encode_index_prefixes(prefixes: &[&str]) -> Vec<u8> {
  let mut dst = Vec::new();
  for prefix in prefixes {
    encode_oppv_u64(prefix.len() as u64, &mut dst);
    dst.extend_from_slice(prefix.as_bytes());
  }
  dst
}

/// Decodes data from binary format with prefix-free OPPV string length decoding.
/// 索引前缀列表二进制解码(OPPV 变长保序解码)
pub fn decode_index_prefixes(mut slice: &[u8]) -> Result<Vec<String>> {
  let mut prefixes = Vec::new();
  while !slice.is_empty() {
    let (len, consumed) = decode_oppv_u64(slice)
      .ok_or_else(|| Error::invalid_data("insufficient length while decoding index prefixes"))?;
    let len = len as usize;
    slice = &slice[consumed..];
    if slice.len() < len {
      return Err(Error::invalid_data(
        "insufficient length while decoding index prefixes",
      ));
    }
    let prefix_str = str::from_utf8(&slice[..len])
      .map_err(|_| Error::invalid_data("invalid utf-8 string in index prefixes"))?;
    prefixes.push(prefix_str.to_string());
    slice = &slice[len..];
  }
  Ok(prefixes)
}

/// Encodes data into binary format.
/// 标签字段元数据二进制编码(对标 Apache Kvrocks TagFieldMetadata::Encode)
#[inline]
pub fn encode_tag_field_meta(separator: char, case_sensitive: bool, noindex: bool) -> Vec<u8> {
  let flag = (noindex as u8) | ((IndexFieldType::Tag as u8) << 1);
  vec![flag, separator as u8, case_sensitive as u8]
}

/// Decodes data from binary format.
/// 标签字段元数据二进制解码(对标 Apache Kvrocks TagFieldMetadata::Decode)
#[inline]
pub fn decode_tag_field_meta(slice: &[u8]) -> Result<(char, bool, bool)> {
  if slice.len() < 3 {
    return Err(Error::invalid_data(
      "insufficient length while decoding tag field metadata",
    ));
  }
  let flag = slice[0];
  let noindex = (flag & 1) != 0;
  let separator = slice[1] as char;
  let case_sensitive = slice[2] != 0;
  Ok((separator, case_sensitive, noindex))
}

/// Encodes data into binary format.
/// 数值字段元数据二进制编码(对标 Apache Kvrocks NumericFieldMetadata::Encode)
#[inline]
pub fn encode_numeric_field_meta(noindex: bool) -> Vec<u8> {
  let flag = (noindex as u8) | ((IndexFieldType::Numeric as u8) << 1);
  vec![flag]
}

/// Decodes data from binary format.
/// 数值字段元数据二进制解码(对标 Apache Kvrocks NumericFieldMetadata::Decode)
#[inline]
pub fn decode_numeric_field_meta(slice: &[u8]) -> Result<bool> {
  if slice.is_empty() {
    return Err(Error::invalid_data(
      "insufficient length while decoding numeric field metadata",
    ));
  }
  let flag = slice[0];
  let noindex = (flag & 1) != 0;
  Ok(noindex)
}

/// Encodes data into binary format.
/// HNSW 向量字段元数据编码字节长度 (1 flag + 1 type + 2 dim + 1 metric + 4 cap + 2 m + 4 ef_c + 4 ef_r + 8 epsilon + 2 num_levels)
pub use super::r#const::HNSW_VECTOR_FIELD_META_LEN;

/// Encodes data into binary format.
/// HNSW 向量字段元数据二进制编码(对标 Apache Kvrocks HnswVectorFieldMetadata::Encode)
pub fn encode_hnsw_vector_field_meta(meta: &VectorFieldMetadata, noindex: bool) -> Vec<u8> {
  let flag = (noindex as u8) | ((IndexFieldType::Vector as u8) << 1);
  let mut dst = Vec::with_capacity(HNSW_VECTOR_FIELD_META_LEN);
  dst.push(flag);
  dst.push(meta.vector_type as u8);
  dst.extend_from_slice(&(meta.dim as u16).to_be_bytes());
  dst.push(meta.distance_metric as u8);
  dst.extend_from_slice(&(meta.initial_cap as u32).to_be_bytes());
  dst.extend_from_slice(&(meta.m as u16).to_be_bytes());
  dst.extend_from_slice(&(meta.ef_construction as u32).to_be_bytes());
  dst.extend_from_slice(&(meta.ef_runtime as u32).to_be_bytes());
  dst.extend_from_slice(&encode_sortable_f64_u64(meta.epsilon).to_be_bytes());
  dst.extend_from_slice(&meta.num_levels.to_be_bytes());
  dst
}

/// Decodes data from binary format.
/// HNSW 向量字段元数据二进制解码(对标 Apache Kvrocks HnswVectorFieldMetadata::Decode)
pub fn decode_hnsw_vector_field_meta(slice: &[u8]) -> Result<(VectorFieldMetadata, bool)> {
  if slice.len() < HNSW_VECTOR_FIELD_META_LEN {
    return Err(Error::invalid_data(
      "insufficient length while decoding hnsw vector field metadata",
    ));
  }
  let flag = slice[0];
  let noindex = (flag & 1) != 0;

  let vector_type = match slice[1] {
    1 => VectorType::Float64,
    2 => VectorType::Float32,
    _ => VectorType::Float64,
  };
  let dim = u16::from_be_bytes([slice[2], slice[3]]) as usize;
  let distance_metric = match slice[4] {
    0 => DistanceMetric::L2,
    1 => DistanceMetric::IP,
    2 => DistanceMetric::Cosine,
    _ => DistanceMetric::Cosine,
  };
  let initial_cap = u32::from_be_bytes([slice[5], slice[6], slice[7], slice[8]]) as usize;
  let m = u16::from_be_bytes([slice[9], slice[10]]) as usize;
  let ef_construction = u32::from_be_bytes([slice[11], slice[12], slice[13], slice[14]]) as usize;
  let ef_runtime = u32::from_be_bytes([slice[15], slice[16], slice[17], slice[18]]) as usize;
  let epsilon_u64 = u64::from_be_bytes([
    slice[19], slice[20], slice[21], slice[22], slice[23], slice[24], slice[25], slice[26],
  ]);
  let epsilon = decode_sortable_f64_u64(epsilon_u64);
  let num_levels = u16::from_be_bytes([slice[27], slice[28]]);

  let meta = VectorFieldMetadata {
    vector_type,
    dim,
    distance_metric,
    algorithm: VectorAlgorithm::Hnsw,
    initial_cap,
    m,
    ef_construction,
    ef_runtime,
    epsilon,
    num_levels,
  };
  Ok((meta, noindex))
}

/// Encodes data into binary format.
/// HNSW 节点元数据二进制编码(对标 Apache Kvrocks HnswNodeFieldMetadata::Encode)
pub fn encode_hnsw_node_meta(num_neighbours: u16, vector: &[f64]) -> Vec<u8> {
  let mut dst = Vec::with_capacity(4 + vector.len() * 8);
  dst.extend_from_slice(&num_neighbours.to_be_bytes());
  dst.extend_from_slice(&(vector.len() as u16).to_be_bytes());
  for &element in vector {
    dst.extend_from_slice(&encode_sortable_f64_u64(element).to_be_bytes());
  }
  dst
}

/// Decodes data from binary format.
/// HNSW 节点元数据二进制解码(对标 Apache Kvrocks HnswNodeFieldMetadata::Decode)
pub fn decode_hnsw_node_meta(slice: &[u8]) -> Result<(u16, Vec<f64>)> {
  if slice.len() < 4 {
    return Err(Error::invalid_data(
      "insufficient length while decoding hnsw node metadata",
    ));
  }
  let num_neighbours = u16::from_be_bytes([slice[0], slice[1]]);
  let dim = u16::from_be_bytes([slice[2], slice[3]]) as usize;
  if slice.len() != 4 + dim * 8 {
    return Err(Error::invalid_data(
      "length is too short or too long to be parsed as a vector",
    ));
  }
  let mut vec = Vec::with_capacity(dim);
  for chunk in slice[4..].as_chunks::<8>().0 {
    let u = u64::from_be_bytes(*chunk);
    vec.push(decode_sortable_f64_u64(u));
  }
  Ok((num_neighbours, vec))
}

/// Operation definition.
/// 浮点数可排序 64 位整数转换(按位变换保证前缀扫描有序,IEEE 754 标准映射)
pub use crate::meta::{decode_sortable_f64_u64, encode_sortable_f64_u64};

/// Encodes data into binary format.
/// 浮点数可排序十六进制字符串编码
#[inline]
pub fn encode_sortable_f64(val: f64) -> String {
  let encoded = encode_sortable_f64_u64(val);
  let bytes = u64_to_hex_16(encoded);
  unsafe { str::from_utf8_unchecked(&bytes) }.to_string()
}

/// Decodes data from binary format.
/// 浮点数可排序十六进制字符串解码
#[inline]
pub fn decode_sortable_f64(hex_str: &str) -> Option<f64> {
  let sortable = decode_hex_u64(hex_str.as_bytes())?;
  Some(decode_sortable_f64_u64(sortable))
}

/// Encodes data into binary format.
/// 有符号 64 位整数可排序十六进制编码
#[inline]
pub fn encode_sortable_i64(val: i64) -> String {
  let unsigned = (val as u64) ^ (1 << 63);
  let bytes = u64_to_hex_16(unsigned);
  unsafe { str::from_utf8_unchecked(&bytes) }.to_string()
}

/// Decodes data from binary format.
/// 有符号 64 位整数可排序十六进制解码
#[inline]
pub fn decode_sortable_i64(hex_str: &str) -> Option<i64> {
  let unsigned = decode_hex_u64(hex_str.as_bytes())?;
  Some((unsigned ^ (1 << 63)) as i64)
}

/// Returns or computes calculated value.
/// SQ8 标量量化向量距离计算(调用 simsimd AVX-512 / NEON 硬件级 Int8 SIMD 算子,4x~8x 吞吐加速)
#[inline]
pub fn compute_sq8_distance(q: &[i8], v: &[i8], metric: DistanceMetric) -> Result<f64> {
  if q.len() != v.len() {
    let len1 = q.len();
    let len2 = v.len();
    return Err(Error::invalid_data(format!(
      "sq8 vector dimension mismatch: {len1} vs {len2}"
    )));
  }
  if q.is_empty() {
    return Err(Error::invalid_data("empty vector is invalid"));
  }

  match metric {
    DistanceMetric::L2 => {
      if let Some(sq) = <i8 as SpatialSimilarity>::sqeuclidean(q, v) {
        Ok(sq.max(0.0).sqrt())
      } else {
        let mut sum = 0u64;
        for (&a, &b) in q.iter().zip(v.iter()) {
          let diff = (a as i32) - (b as i32);
          sum += (diff * diff) as u64;
        }
        Ok((sum as f64).sqrt())
      }
    }
    DistanceMetric::IP => {
      if let Some(dot) = <i8 as SpatialSimilarity>::dot(q, v) {
        Ok(-dot)
      } else {
        let mut dot = 0i64;
        for (&a, &b) in q.iter().zip(v.iter()) {
          dot += (a as i64) * (b as i64);
        }
        Ok(-(dot as f64))
      }
    }
    DistanceMetric::Cosine => {
      if let Some(cos) = <i8 as SpatialSimilarity>::cosine(q, v) {
        Ok(cos)
      } else {
        let mut dot = 0i64;
        let mut sum_sq1 = 0i64;
        let mut sum_sq2 = 0i64;
        for (&a, &b) in q.iter().zip(v.iter()) {
          let a = a as i64;
          let b = b as i64;
          dot += a * b;
          sum_sq1 += a * a;
          sum_sq2 += b * b;
        }
        let denom = ((sum_sq1 * sum_sq2) as f64).sqrt();
        if denom == 0.0 || !denom.is_finite() {
          return Ok(1.0);
        }
        let cos = ((dot as f64) / denom).clamp(-1.0, 1.0);
        Ok(1.0 - cos)
      }
    }
  }
}

/// Returns or computes calculated value.
/// 向量距离与相似度度量计算(优先调用 simsimd 硬件加速内核,带 8 路循环展开 fallback)
#[inline]
pub fn compute_vector_distance(v1: &[f64], v2: &[f64], metric: DistanceMetric) -> Result<f64> {
  if v1.len() != v2.len() {
    let len1 = v1.len();
    let len2 = v2.len();
    return Err(Error::invalid_data(format!(
      "vector dimension mismatch: {len1} vs {len2}"
    )));
  }
  if v1.is_empty() {
    return Err(Error::invalid_data("empty vector is invalid"));
  }

  match metric {
    DistanceMetric::L2 => {
      if let Some(sq) = <f64 as SpatialSimilarity>::sqeuclidean(v1, v2) {
        Ok(sq.max(0.0).sqrt())
      } else {
        let (c1, r1) = v1.as_chunks::<8>();
        let (c2, r2) = v2.as_chunks::<8>();
        let mut acc0 = 0.0;
        let mut acc1 = 0.0;
        let mut acc2 = 0.0;
        let mut acc3 = 0.0;
        let mut acc4 = 0.0;
        let mut acc5 = 0.0;
        let mut acc6 = 0.0;
        let mut acc7 = 0.0;
        for (a, b) in c1.iter().zip(c2.iter()) {
          let d0 = a[0] - b[0];
          let d1 = a[1] - b[1];
          let d2 = a[2] - b[2];
          let d3 = a[3] - b[3];
          let d4 = a[4] - b[4];
          let d5 = a[5] - b[5];
          let d6 = a[6] - b[6];
          let d7 = a[7] - b[7];
          acc0 += d0 * d0;
          acc1 += d1 * d1;
          acc2 += d2 * d2;
          acc3 += d3 * d3;
          acc4 += d4 * d4;
          acc5 += d5 * d5;
          acc6 += d6 * d6;
          acc7 += d7 * d7;
        }
        let mut sum = ((acc0 + acc1) + (acc2 + acc3)) + ((acc4 + acc5) + (acc6 + acc7));
        for (&a, &b) in r1.iter().zip(r2.iter()) {
          let diff = a - b;
          sum += diff * diff;
        }
        Ok(sum.sqrt())
      }
    }
    DistanceMetric::IP => {
      if let Some(dot) = <f64 as SpatialSimilarity>::dot(v1, v2) {
        Ok(-dot)
      } else {
        let (c1, r1) = v1.as_chunks::<8>();
        let (c2, r2) = v2.as_chunks::<8>();
        let mut dot0 = 0.0;
        let mut dot1 = 0.0;
        let mut dot2 = 0.0;
        let mut dot3 = 0.0;
        let mut dot4 = 0.0;
        let mut dot5 = 0.0;
        let mut dot6 = 0.0;
        let mut dot7 = 0.0;
        for (a, b) in c1.iter().zip(c2.iter()) {
          dot0 += a[0] * b[0];
          dot1 += a[1] * b[1];
          dot2 += a[2] * b[2];
          dot3 += a[3] * b[3];
          dot4 += a[4] * b[4];
          dot5 += a[5] * b[5];
          dot6 += a[6] * b[6];
          dot7 += a[7] * b[7];
        }
        let mut dot = ((dot0 + dot1) + (dot2 + dot3)) + ((dot4 + dot5) + (dot6 + dot7));
        for (&a, &b) in r1.iter().zip(r2.iter()) {
          dot += a * b;
        }
        Ok(-dot)
      }
    }
    DistanceMetric::Cosine => {
      if let Some(cos) = <f64 as SpatialSimilarity>::cosine(v1, v2) {
        Ok(cos)
      } else {
        let (c1, r1) = v1.as_chunks::<8>();
        let (c2, r2) = v2.as_chunks::<8>();
        let mut dot0 = 0.0;
        let mut dot1 = 0.0;
        let mut dot2 = 0.0;
        let mut dot3 = 0.0;
        let mut n1_0 = 0.0;
        let mut n1_1 = 0.0;
        let mut n1_2 = 0.0;
        let mut n1_3 = 0.0;
        let mut n2_0 = 0.0;
        let mut n2_1 = 0.0;
        let mut n2_2 = 0.0;
        let mut n2_3 = 0.0;
        for (a, b) in c1.iter().zip(c2.iter()) {
          dot0 += a[0] * b[0] + a[1] * b[1];
          dot1 += a[2] * b[2] + a[3] * b[3];
          dot2 += a[4] * b[4] + a[5] * b[5];
          dot3 += a[6] * b[6] + a[7] * b[7];
          n1_0 += a[0] * a[0] + a[1] * a[1];
          n1_1 += a[2] * a[2] + a[3] * a[3];
          n1_2 += a[4] * a[4] + a[5] * a[5];
          n1_3 += a[6] * a[6] + a[7] * a[7];
          n2_0 += b[0] * b[0] + b[1] * b[1];
          n2_1 += b[2] * b[2] + b[3] * b[3];
          n2_2 += b[4] * b[4] + b[5] * b[5];
          n2_3 += b[6] * b[6] + b[7] * b[7];
        }
        let mut dot = (dot0 + dot1) + (dot2 + dot3);
        let mut sum_sq1 = (n1_0 + n1_1) + (n1_2 + n1_3);
        let mut sum_sq2 = (n2_0 + n2_1) + (n2_2 + n2_3);
        for (&a, &b) in r1.iter().zip(r2.iter()) {
          dot += a * b;
          sum_sq1 += a * a;
          sum_sq2 += b * b;
        }
        let denom = (sum_sq1 * sum_sq2).sqrt();
        if denom == 0.0 || !denom.is_finite() {
          return Ok(1.0);
        }
        let cos = (dot / denom).clamp(-1.0, 1.0);
        Ok(1.0 - cos)
      }
    }
  }
}

/// Parses parameter or binary slice.
/// 从二进制字节数组或 JSON 数组中解析浮点向量(零冗余单次解析)
pub fn parse_vector_from_slice(bytes: &[u8], vector_type: VectorType) -> Result<Vec<f64>> {
  let mut vec = Vec::new();
  parse_vector_from_slice_into(bytes, vector_type, &mut vec)?;
  Ok(vec)
}

/// Parses parameter or binary slice.
/// 从二进制字节数组或 JSON 数组中解析浮点向量至复用缓冲区(零新堆内存分配)
pub fn parse_vector_from_slice_into(
  bytes: &[u8],
  vector_type: VectorType,
  out: &mut Vec<f64>,
) -> Result<()> {
  if bytes.is_empty() {
    return Err(Error::invalid_data("empty vector byte format"));
  }

  // 优先检测 JSON 格式(以 '[' 开头)
  if bytes.starts_with(b"[")
    && let Ok(json_v) = sonic_rs::from_slice::<sonic_rs::Value>(bytes)
    && let Some(arr) = json_v.as_array()
  {
    out.clear();
    out.reserve(arr.len());
    for item in arr {
      if let Some(n) = item.as_f64() {
        out.push(n);
      }
    }
    if !out.is_empty() {
      return Ok(());
    }
  }

  // 二进制字节数组解析 (Float64: 8 字节/元素, Float32: 4 字节/元素)
  let elem_size = vector_type.byte_size();
  if bytes.len().is_multiple_of(elem_size) {
    match vector_type {
      VectorType::Float64 => {
        let count = bytes.len() / 8;
        out.clear();
        out.reserve(count);
        for chunk in bytes.as_chunks::<8>().0 {
          out.push(f64::from_le_bytes(*chunk));
        }
        return Ok(());
      }
      VectorType::Float32 => {
        let count = bytes.len() / 4;
        out.clear();
        out.reserve(count);
        for chunk in bytes.as_chunks::<4>().0 {
          out.push(f32::from_le_bytes(*chunk) as f64);
        }
        return Ok(());
      }
    }
  }

  // 纯文本逗号分隔(含 ',' 且为有效 UTF-8 文本)
  if let Ok(s) = str::from_utf8(bytes)
    && s.contains(',')
  {
    let clean = s.trim().trim_start_matches('[').trim_end_matches(']');
    out.clear();
    let mut valid = true;
    for part in clean.split(',') {
      let p = part.trim();
      if p.is_empty() {
        continue;
      }
      if let Ok(num) = p.parse::<f64>() {
        out.push(num);
      } else {
        valid = false;
        break;
      }
    }
    if valid && !out.is_empty() {
      return Ok(());
    }
  }

  Err(Error::invalid_data("invalid vector byte format or length"))
}