kglite 0.16.5

Pure-Rust embedded Cypher knowledge graph engine with in-memory, mmap, and disk storage, and agent-facing schema introspection
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
//! Coercion-normalized membership testing — the single implementation of
//! "is this value one of those values?" shared by every `IN` evaluation site.
//!
//! # Why this exists
//!
//! `x IN <list>` is answered at five independent places (the pattern
//! matcher's `PropertyMatcher::In`, the EXISTS fast-path's inline property
//! check, and the Cypher executor's `In` / `InLiteralSet` / `InExpression`
//! predicates). Every one of them used to walk the whole list per row with
//! [`values_equal`], making membership `O(rows × |list|)`: a 1 000-element
//! list over 50 000 rows cost 71 ms, a 16 000-element one 576 ms, a 64 000-
//! element one 7.4 s.
//!
//! A plain `HashSet<Value>` cannot replace that scan, which is exactly why
//! the previous `InLiteralSet` "O(1)" set kept a linear fallback behind it
//! (and therefore stayed linear on the *miss* path, where all the time is
//! spent). `Value`'s `Hash`/`PartialEq` are structural, while `values_equal`
//! coerces across the numeric family (`Int64` ↔ `UniqueId` ↔ integral
//! `Float64`) and treats a single-element JSON list string (`["Oslo"]`) as
//! equal to its inner string. A structural set misses every one of those.
//!
//! [`MembershipSet`] closes the gap: each element is normalized to a key
//! that folds exactly the way `values_equal` compares, so one hash probe
//! answers the question that the linear scan answered.
//!
//! # Normalization rules (must mirror [`values_equal`] exactly)
//!
//! | Value | Key |
//! |---|---|
//! | `Int64(i)` | `Int(i)` |
//! | `UniqueId(u)` | `Int(u as i64)` — `u32`, so never negative, matching `values_equal`'s `i >= 0` guard |
//! | `Float64(f)`, integral, `|f| <= 2^53` | `Int(f as i64)` — an `Int64` can only equal an integral float |
//! | `Float64(f)`, otherwise | `Float(canonical bits)` — `-0.0` folded to `0.0` |
//! | `Float64(NaN)` | **no key** — `NaN != NaN` under `values_equal`, so a NaN element can never match and a NaN probe never matches |
//! | `String(s)` | `Str(s)`, plus `Str(inner)` when `s` is `["inner"]` |
//! | `Boolean` / `DateTime` / `Timestamp` | their own key (structural equality only) |
//! | `Null` | **no key** — recorded as [`MembershipSet::has_null`] for the caller's Kleene rule |
//! | anything else (`Point`, `Duration`, `List`, `Map`, `Node`, …) | *residual*: compared with `values_equal` |
//!
//! ## The 2^53 residual
//!
//! `values_equal` compares `Int64` with `Float64` as `(i as f64) == f`, which
//! is **not injective** past 2^53: `Int64(2^53 + 1)` equals
//! `Float64(2^53 as f64)` even though the integers differ. Keys cannot
//! express a non-injective relation, so any integer or integral float of
//! magnitude beyond 2^53 is *also* pushed to the residual list and compared
//! with `values_equal` on a key miss. Realistic lists never populate it, so
//! the cost is one `is_empty()` check.
//!
//! ## Small lists stay linear
//!
//! Below [`LINEAR_MAX`] elements no index is built and probes run the same
//! `values_equal` scan as before — identical work to the pre-index code, so
//! a short `IN ['a', 'b']` cannot regress by paying for hashing.
//!
//! # NULL is the caller's business
//!
//! `MembershipSet` answers one question — *did any element equal this
//! value?* — and never returns a three-valued result. Each site keeps its own
//! Kleene policy and reads [`MembershipSet::has_null`] when it needs to
//! distinguish "no match" from "unknown".

use crate::datatypes::Value;
use crate::graph::core::filtering::{json_single_element_string, values_equal};
use chrono::{NaiveDate, NaiveDateTime};
use rustc_hash::FxHashSet;
use std::sync::Arc;

/// Lists at or below this length are probed by linear scan. Below it the
/// scan is cheaper than hashing the probe value, and building an index for
/// a two-element `IN` list is pure overhead.
const LINEAR_MAX: usize = 8;

/// `Int64` ↔ `Float64` equality (`(i as f64) == f`) stops being injective
/// past this magnitude; such values fall back to `values_equal`.
const EXACT_INT_LIMIT: i64 = 1i64 << 53;

/// A scalar membership key. Two values share a key exactly when
/// [`values_equal`] considers them equal.
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
enum ScalarKey {
    /// Integral values from the `Int64` / `UniqueId` / integral-`Float64` family.
    Int(i64),
    /// Non-integral (or out-of-range) float, by canonical bit pattern.
    Float(u64),
    Bool(bool),
    Date(NaiveDate),
    Timestamp(NaiveDateTime),
}

/// The hash index built for lists longer than [`LINEAR_MAX`].
#[derive(Debug, Clone, Default)]
struct MembershipIndex {
    scalars: FxHashSet<ScalarKey>,
    /// Kept separate from `scalars` so a `&str` probe borrows instead of
    /// allocating a key per row.
    strings: FxHashSet<Box<str>>,
    /// Elements whose equality cannot be expressed as a key (see the
    /// module docs): compared with `values_equal` on a key miss.
    residual: Vec<Value>,
}

/// A list of values prepared for repeated membership testing.
///
/// Construct once per query (never per row) with [`MembershipSet::new`], then
/// probe with [`MembershipSet::matches`]. The original values are retained in
/// order, and the type derefs to `&[Value]`, so planner code that inspects or
/// re-collects the list keeps working unchanged.
#[derive(Debug, Clone, Default)]
pub struct MembershipSet {
    values: Vec<Value>,
    has_null: bool,
    /// `None` for short lists, which probe by linear scan.
    ///
    /// Behind an `Arc` because a pattern carrying an `IN` matcher *and* a
    /// deferred `EqualsVar` is re-resolved (and therefore cloned) per row:
    /// sharing the index keeps that clone at the cost of the value list
    /// alone, which is what it was before the index existed.
    index: Option<Arc<MembershipIndex>>,
}

impl MembershipSet {
    /// Prepare `values` for membership testing.
    pub fn new(values: Vec<Value>) -> Self {
        let has_null = values.iter().any(|v| matches!(v, Value::Null));
        let index = (values.len() > LINEAR_MAX).then(|| Arc::new(build_index(&values)));
        Self {
            values,
            has_null,
            index,
        }
    }

    /// True when some element of the list equals `value` under
    /// [`values_equal`]. `Null` on either side is never equal — a
    /// `Null` probe is always `false`, and `Null` elements are reported
    /// through [`MembershipSet::has_null`] instead.
    #[inline]
    pub fn matches(&self, value: &Value) -> bool {
        match &self.index {
            Some(index) => index.matches(value),
            None => self.values.iter().any(|v| values_equal(value, v)),
        }
    }

    /// True when the list contains a `Null` element — the input every
    /// site's three-valued rule needs to tell "no match" from "unknown".
    #[inline]
    pub fn has_null(&self) -> bool {
        self.has_null
    }

    /// The original values, in construction order.
    #[inline]
    pub fn values(&self) -> &[Value] {
        &self.values
    }

    /// Consume the set, returning the original values.
    pub fn into_values(self) -> Vec<Value> {
        self.values
    }

    /// openCypher's three-valued `value IN <list>`: `None` is UNKNOWN.
    ///
    /// ```text
    /// NULL IN anything                    -> UNKNOWN
    /// x IN [..]  match present            -> true    (NULLs immaterial)
    /// x IN [..]  no match, list has NULL  -> UNKNOWN
    /// x IN [..]  no match, no NULL        -> false
    /// ```
    #[inline]
    pub fn kleene_contains(&self, value: &Value) -> Option<bool> {
        if matches!(value, Value::Null) {
            return None;
        }
        if self.matches(value) {
            return Some(true);
        }
        if self.has_null {
            return None;
        }
        Some(false)
    }
}

/// [`MembershipSet::kleene_contains`] for a list that only exists for this
/// row — nothing to index, so the elements are scanned once with an early
/// exit on the first match.
#[inline]
pub fn kleene_contains_linear(value: &Value, items: &[Value]) -> Option<bool> {
    if matches!(value, Value::Null) {
        return None;
    }
    let mut saw_null = false;
    for item in items {
        match probe_element(value, item) {
            Some(true) => return Some(true),
            Some(false) => {}
            None => saw_null = true,
        }
    }
    if saw_null {
        None
    } else {
        Some(false)
    }
}

/// One element's contribution to `value IN <list>`: `None` when the element
/// is NULL (which makes a non-match UNKNOWN rather than false), otherwise
/// whether it equals `value`.
///
/// The per-element rule of the three-valued IN, factored out so a site that
/// must evaluate its list lazily (per-row expressions) shares the policy with
/// the indexed sites instead of restating it.
#[inline]
pub fn probe_element(value: &Value, element: &Value) -> Option<bool> {
    if matches!(element, Value::Null) {
        return None;
    }
    Some(values_equal(value, element))
}

impl std::ops::Deref for MembershipSet {
    type Target = [Value];

    fn deref(&self) -> &Self::Target {
        &self.values
    }
}

impl<'a> IntoIterator for &'a MembershipSet {
    type Item = &'a Value;
    type IntoIter = std::slice::Iter<'a, Value>;

    fn into_iter(self) -> Self::IntoIter {
        self.values.iter()
    }
}

impl From<Vec<Value>> for MembershipSet {
    fn from(values: Vec<Value>) -> Self {
        Self::new(values)
    }
}

impl FromIterator<Value> for MembershipSet {
    fn from_iter<I: IntoIterator<Item = Value>>(iter: I) -> Self {
        Self::new(iter.into_iter().collect())
    }
}

impl MembershipIndex {
    #[inline]
    fn matches(&self, value: &Value) -> bool {
        if let Value::String(s) = value {
            if self.strings.contains(s.as_str())
                || json_single_element_string(s).is_some_and(|inner| self.strings.contains(inner))
            {
                return true;
            }
        } else if let Some(key) = scalar_key(value) {
            if self.scalars.contains(&key) {
                return true;
            }
        }
        !self.residual.is_empty() && self.residual.iter().any(|v| values_equal(value, v))
    }
}

fn build_index(values: &[Value]) -> MembershipIndex {
    let mut index = MembershipIndex {
        scalars: FxHashSet::with_capacity_and_hasher(values.len(), Default::default()),
        strings: FxHashSet::default(),
        residual: Vec::new(),
    };
    for value in values {
        match value {
            // Never equal to anything: `values_equal` rejects NULL on either
            // side, and NaN fails its own equality check.
            Value::Null => {}
            Value::Float64(f) if f.is_nan() => {}
            Value::String(s) => {
                index.strings.insert(s.as_str().into());
                if let Some(inner) = json_single_element_string(s) {
                    index.strings.insert(inner.into());
                }
            }
            other => match scalar_key(other) {
                Some(key) => {
                    index.scalars.insert(key);
                    if beyond_exact_int_range(other) {
                        index.residual.push(other.clone());
                    }
                }
                None => index.residual.push(other.clone()),
            },
        }
    }
    index
}

/// The key `value` hashes to, or `None` when its equality cannot be
/// expressed as a key (see the module docs).
#[inline]
fn scalar_key(value: &Value) -> Option<ScalarKey> {
    match value {
        Value::Int64(i) => Some(ScalarKey::Int(*i)),
        Value::UniqueId(u) => Some(ScalarKey::Int(*u as i64)),
        Value::Float64(f) => {
            if f.is_nan() {
                None
            } else if f.fract() == 0.0 && f.abs() < EXACT_INT_LIMIT as f64 {
                Some(ScalarKey::Int(*f as i64))
            } else {
                // `-0.0 == 0.0`, so they must share a key.
                let canonical = if *f == 0.0 { 0.0f64 } else { *f };
                Some(ScalarKey::Float(canonical.to_bits()))
            }
        }
        Value::Boolean(b) => Some(ScalarKey::Bool(*b)),
        Value::DateTime(d) => Some(ScalarKey::Date(*d)),
        Value::Timestamp(t) => Some(ScalarKey::Timestamp(*t)),
        _ => None,
    }
}

/// True for integers big enough that `Int64` ↔ `Float64` equality is no
/// longer injective, so a key alone cannot decide membership.
#[inline]
fn beyond_exact_int_range(value: &Value) -> bool {
    match value {
        Value::Int64(i) => i.unsigned_abs() >= EXACT_INT_LIMIT as u64,
        Value::Float64(f) => f.abs() >= EXACT_INT_LIMIT as f64,
        _ => false,
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    /// Every probe must agree with the linear `values_equal` scan the set
    /// replaced — checked at both sides of the linear/hashed threshold.
    fn assert_agrees(list: &[Value], probes: &[Value]) {
        let set = MembershipSet::new(list.to_vec());
        for probe in probes {
            let linear = list.iter().any(|v| values_equal(probe, v));
            assert_eq!(
                set.matches(probe),
                linear,
                "membership disagreed with values_equal for {probe:?} in {list:?}"
            );
        }
    }

    /// Pad a list past `LINEAR_MAX` so the hashed index is exercised, using
    /// filler that cannot collide with the probes.
    fn padded(list: &[Value]) -> Vec<Value> {
        let mut out = list.to_vec();
        out.extend((0..LINEAR_MAX + 2).map(|i| Value::String(format!("__pad_{i}"))));
        out
    }

    #[test]
    fn numeric_family_coerces_like_values_equal() {
        let list = [
            Value::Int64(5),
            Value::Float64(7.5),
            Value::UniqueId(9),
            Value::Float64(11.0),
        ];
        let probes = [
            Value::Int64(5),
            Value::Float64(5.0),
            Value::UniqueId(5),
            Value::Float64(5.5),
            Value::Int64(7),
            Value::Float64(7.5),
            Value::Int64(9),
            Value::Float64(9.0),
            Value::Int64(11),
            Value::UniqueId(11),
            Value::Int64(-5),
            Value::Float64(-0.0),
            Value::Int64(0),
        ];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn nan_never_matches_on_either_side() {
        let list = [Value::Float64(f64::NAN), Value::Int64(1)];
        let probes = [Value::Float64(f64::NAN), Value::Int64(1)];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
        assert!(!MembershipSet::new(padded(&list)).matches(&Value::Float64(f64::NAN)));
    }

    #[test]
    fn signed_zero_shares_a_key() {
        let list = [Value::Float64(-0.0)];
        let probes = [Value::Float64(0.0), Value::Int64(0), Value::UniqueId(0)];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn json_single_element_strings_match_their_inner_value() {
        let list = [
            Value::String("[\"Oslo\"]".to_string()),
            Value::String("Bergen".to_string()),
        ];
        let probes = [
            Value::String("Oslo".to_string()),
            Value::String("[\"Oslo\"]".to_string()),
            Value::String("[\"Bergen\"]".to_string()),
            Value::String("Bergen".to_string()),
            Value::String("Tromso".to_string()),
            // Degenerate short strings that share the delimiters.
            Value::String("[\"]".to_string()),
            Value::String("[\"\"]".to_string()),
        ];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn huge_integers_fall_back_to_values_equal() {
        let big = EXACT_INT_LIMIT + 1;
        let list = [Value::Int64(big), Value::Float64(EXACT_INT_LIMIT as f64)];
        let probes = [
            Value::Int64(big),
            Value::Float64(big as f64),
            Value::Int64(EXACT_INT_LIMIT),
            Value::Float64(EXACT_INT_LIMIT as f64),
        ];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn null_is_reported_not_matched() {
        let set = MembershipSet::new(padded(&[Value::Null, Value::Int64(1)]));
        assert!(set.has_null());
        assert!(!set.matches(&Value::Null));
        assert!(set.matches(&Value::Int64(1)));
        assert!(!MembershipSet::new(vec![Value::Int64(1)]).has_null());
    }

    #[test]
    fn non_scalar_values_compare_structurally() {
        let list = [
            Value::List(vec![Value::Int64(1), Value::Int64(2)]),
            Value::Point { lat: 1.0, lon: 2.0 },
        ];
        let probes = [
            Value::List(vec![Value::Int64(1), Value::Int64(2)]),
            Value::List(vec![Value::Int64(1)]),
            Value::Point { lat: 1.0, lon: 2.0 },
            Value::Point { lat: 9.0, lon: 2.0 },
        ];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn cross_type_probes_stay_disjoint() {
        let list = [
            Value::Boolean(true),
            Value::Int64(1),
            Value::String("1".to_string()),
        ];
        let probes = [
            Value::Boolean(true),
            Value::Boolean(false),
            Value::Int64(1),
            Value::String("1".to_string()),
            Value::String("true".to_string()),
        ];
        assert_agrees(&list, &probes);
        assert_agrees(&padded(&list), &probes);
    }

    #[test]
    fn threshold_crossing_preserves_answers() {
        // One list, grown one element at a time across LINEAR_MAX: the answer
        // for a fixed probe must never depend on which strategy is chosen.
        let mut list = Vec::new();
        for i in 0..(LINEAR_MAX * 3) as i64 {
            list.push(Value::Int64(i * 2));
            let set = MembershipSet::new(list.clone());
            for probe in 0..(LINEAR_MAX * 6) as i64 {
                let expected = list.iter().any(|v| values_equal(&Value::Int64(probe), v));
                assert_eq!(set.matches(&Value::Int64(probe)), expected, "n={i}");
            }
        }
    }
}