mz_expr/relation/canonicalize.rs
1// Copyright Materialize, Inc. and contributors. All rights reserved.
2//
3// Use of this software is governed by the Business Source License
4// included in the LICENSE file.
5//
6// As of the Change Date specified in that file, in accordance with
7// the Business Source License, use of this software will be governed
8// by the Apache License, Version 2.0.
9
10//! Utility functions to transform parts of a single `MirRelationExpr`
11//! into canonical form.
12
13use std::cmp::Ordering;
14use std::collections::{BTreeMap, BTreeSet};
15use std::rc::Rc;
16
17use itertools::Itertools;
18use mz_ore::soft_assert_or_log;
19use mz_repr::{ReprColumnType, ReprScalarType};
20
21use crate::visit::Visit;
22use crate::{MirScalarExpr, UnaryFunc, VariadicFunc, func};
23
24/// Canonicalize equivalence classes of a join and expressions contained in them.
25///
26/// `input_types` can be the [ReprColumnType]s of the join or the [ReprColumnType]s of
27/// the individual inputs of the join in order.
28///
29/// This function:
30/// * simplifies expressions to involve the least number of non-literal nodes.
31/// This ensures that we only replace expressions by "even simpler"
32/// expressions and that repeated substitutions reduce the complexity of
33/// expressions and a fixed point is certain to be reached. Without this
34/// rule, we might repeatedly replace a simple expression with an equivalent
35/// complex expression containing that (or another replaceable) simple
36/// expression, and repeat indefinitely.
37/// * reduces all expressions contained in `equivalences`.
38/// * Does everything that [canonicalize_equivalence_classes] does.
39pub fn canonicalize_equivalences<'a, I>(
40 equivalences: &mut Vec<Vec<MirScalarExpr>>,
41 input_column_types: I,
42) where
43 I: Iterator<Item = &'a Vec<ReprColumnType>>,
44{
45 let repr_column_types = input_column_types
46 .flat_map(|f| f.clone())
47 .collect::<Vec<_>>();
48 // Calculate the number of non-leaves for each expression.
49 let mut to_reduce = equivalences
50 .drain(..)
51 .filter_map(|mut cls| {
52 let mut result = cls
53 .drain(..)
54 .map(|expr| (rank_complexity(&expr), expr))
55 .collect::<Vec<_>>();
56 result.sort();
57 result.dedup();
58 if result.len() > 1 { Some(result) } else { None }
59 })
60 .collect::<Vec<_>>();
61
62 let mut expressions_rewritten = true;
63 while expressions_rewritten {
64 expressions_rewritten = false;
65 for i in 0..to_reduce.len() {
66 // `to_reduce` will be borrowed as immutable, so in order to modify
67 // elements of `to_reduce[i]`, we are going to pop them out of
68 // `to_reduce[i]` and put the modified version in `new_equivalence`,
69 // which will then replace `to_reduce[i]`.
70 let mut new_equivalence = Vec::with_capacity(to_reduce[i].len());
71 while let Some((_, mut popped_expr)) = to_reduce[i].pop() {
72 popped_expr.visit_mut_post(&mut |e: &mut MirScalarExpr| {
73 // If a simpler expression can be found that is equivalent
74 // to e,
75 if let Some(simpler_e) = to_reduce.iter().find_map(|cls| {
76 if cls.iter().skip(1).position(|(_, expr)| e == expr).is_some() {
77 Some(cls[0].1.clone())
78 } else {
79 None
80 }
81 }) {
82 // Replace e with the simpler expression.
83 *e = simpler_e;
84 expressions_rewritten = true;
85 }
86 });
87 popped_expr.reduce(&repr_column_types);
88 new_equivalence.push((rank_complexity(&popped_expr), popped_expr));
89 }
90 new_equivalence.sort();
91 new_equivalence.dedup();
92 to_reduce[i] = new_equivalence;
93 }
94 }
95
96 // Map away the complexity rating.
97 *equivalences = to_reduce
98 .drain(..)
99 .map(|mut cls| cls.drain(..).map(|(_, expr)| expr).collect::<Vec<_>>())
100 .collect::<Vec<_>>();
101
102 canonicalize_equivalence_classes(equivalences);
103}
104
105/// Canonicalize only the equivalence classes of a join.
106///
107/// This function:
108/// * ensures the same expression appears in only one equivalence class.
109/// * ensures the equivalence classes are sorted and dedupped.
110/// ```rust
111/// use mz_expr::MirScalarExpr;
112/// use mz_expr::canonicalize::canonicalize_equivalence_classes;
113///
114/// let mut equivalences = vec![
115/// vec![MirScalarExpr::column(1), MirScalarExpr::column(4)],
116/// vec![MirScalarExpr::column(3), MirScalarExpr::column(5)],
117/// vec![MirScalarExpr::column(0), MirScalarExpr::column(3)],
118/// vec![MirScalarExpr::column(2), MirScalarExpr::column(2)],
119/// ];
120/// let expected = vec![
121/// vec![MirScalarExpr::column(0),
122/// MirScalarExpr::column(3),
123/// MirScalarExpr::column(5)],
124/// vec![MirScalarExpr::column(1), MirScalarExpr::column(4)],
125/// ];
126/// canonicalize_equivalence_classes(&mut equivalences);
127/// assert_eq!(expected, equivalences)
128/// ````
129pub fn canonicalize_equivalence_classes(equivalences: &mut Vec<Vec<MirScalarExpr>>) {
130 let mut uf = BTreeMap::new();
131 for class in equivalences.iter_mut() {
132 let mut iter = class.drain(..);
133 if let Some(first) = iter.next() {
134 let head = Rc::new(first);
135 for rest in iter {
136 uf.union(&head, &Rc::new(rest));
137 }
138 }
139 }
140
141 let mut eqs: BTreeMap<Rc<MirScalarExpr>, BTreeSet<Rc<MirScalarExpr>>> = BTreeMap::new();
142 for (k, v) in uf {
143 eqs.entry(v).or_default().insert(Rc::clone(&k));
144 }
145
146 let classes = eqs.into_values().collect::<Vec<_>>();
147 equivalences.resize(classes.len(), Vec::new());
148 equivalences
149 .iter_mut()
150 .zip_eq(classes)
151 .for_each(|(equivalence, class)| {
152 equivalence.extend(
153 class
154 .into_iter()
155 .map(|e| Rc::try_unwrap(e).expect("there to be only one strong ref")),
156 );
157 });
158
159 equivalences.retain(|es| es.len() > 1);
160 equivalences.sort();
161}
162
163/// Gives a relative complexity ranking for an expression. Higher numbers mean
164/// greater complexity.
165///
166/// Currently, this method weighs literals as the least complex and weighs all
167/// other expressions by the number of non-literals. In the future, we can
168/// change how complexity is ranked so that repeated substitutions would result
169/// in arriving at "better" fixed points. For example, we could try to improve
170/// performance by ranking expressions by their estimated computation time.
171///
172/// To ensure we arrive at a fixed point after repeated substitutions, valid
173/// complexity rankings must fulfill the following property:
174/// For any expression `e`, there does not exist a SQL function `f` such
175/// that `complexity(e) >= complexity(f(e))`.
176///
177/// For ease of intuiting the fixed point that we will arrive at after
178/// repeated substitutions, it is nice but not required that complexity
179/// rankings additionally fulfill the following property:
180/// If expressions `e1` and `e2` are such that
181/// `complexity(e1) < complexity(e2)` then for all SQL functions `f`,
182/// `complexity(f(e1)) < complexity(f(e2))`.
183fn rank_complexity(expr: &MirScalarExpr) -> usize {
184 if expr.is_literal() {
185 // literals are the least complex
186 return 0;
187 }
188 let mut non_literal_count = 1;
189 expr.visit_pre(|e| {
190 if !e.is_literal() {
191 non_literal_count += 1
192 }
193 });
194 non_literal_count
195}
196
197/// Applies a flat_map on a Vec, and overwrites the vec with the result.
198fn flat_map_modify<T, I, F>(v: &mut Vec<T>, f: F)
199where
200 F: FnMut(T) -> I,
201 I: IntoIterator<Item = T>,
202{
203 let mut xx = v.drain(..).flat_map(f).collect();
204 v.append(&mut xx);
205}
206
207/// Canonicalize predicates of a filter.
208///
209/// This function reduces and canonicalizes the structure of each individual
210/// predicate. Then, it transforms predicates of the form "A and B" into two: "A"
211/// and "B". Afterwards, it reduces predicates based on information from other
212/// predicates in the set. Finally, it sorts and deduplicates the predicates.
213///
214/// Additionally, it also removes IS NOT NULL predicates if there is another
215/// null rejecting predicate for the same sub-expression.
216pub fn canonicalize_predicates(
217 predicates: &mut Vec<MirScalarExpr>,
218 repr_column_types: &[ReprColumnType],
219) {
220 soft_assert_or_log!(
221 predicates
222 .iter()
223 .all(|p| p.typ(repr_column_types).scalar_type == ReprScalarType::Bool),
224 "cannot canonicalize predicates that are not of type bool"
225 );
226
227 // 1) Reduce each individual predicate.
228 predicates
229 .iter_mut()
230 .for_each(|p| p.reduce(repr_column_types));
231
232 // 2) Split "A and B" into two predicates: "A" and "B"
233 // Relies on the `reduce` above having flattened nested ANDs.
234 flat_map_modify(predicates, |p| {
235 if let MirScalarExpr::CallVariadic {
236 func: VariadicFunc::And(_),
237 exprs,
238 } = p
239 {
240 exprs
241 } else {
242 vec![p]
243 }
244 });
245
246 // 3) Make non-null requirements explicit as predicates in order for
247 // step 4) to be able to simplify AND/OR expressions with IS NULL
248 // sub-predicates. This redundancy is removed later by step 5).
249 let mut non_null_columns = BTreeSet::new();
250 for p in predicates.iter() {
251 p.non_null_requirements(&mut non_null_columns);
252 }
253 predicates.extend(non_null_columns.iter().map(|c| {
254 MirScalarExpr::column(*c)
255 .call_unary(UnaryFunc::IsNull(func::IsNull))
256 .call_unary(UnaryFunc::Not(func::Not))
257 }));
258
259 // 4) Reduce across `predicates`.
260 // If a predicate `p` cannot be null, and `f(p)` is a nullable bool
261 // then the predicate `p & f(p)` is equal to `p & f(true)`, and
262 // `!p & f(p)` is equal to `!p & f(false)`. For any index i, the `Vec` of
263 // predicates `[p1, ... pi, ... pn]` is equivalent to the single predicate
264 // `pi & (p1 & ... & p(i-1) & p(i+1) ... & pn)`. Thus, if `pi`
265 // (resp. `!pi`) cannot be null, it is valid to replace with `true` (resp.
266 // `false`) every subexpression in `(p1 & ... & p(i-1) & p(i+1) ... & pn)`
267 // that is equal to `pi`.
268
269 // If `p` is null and `q` is a nullable bool, then `p & q` can be either
270 // `null` or `false` depending on what `q`. Our rendering pipeline treats
271 // both as "remove this row." Thus, in the specific context of filter
272 // predicates, it is acceptable to make the aforementioned substitution
273 // even if `pi` can be null.
274
275 // Note that this does some dedupping of predicates since if `p1 = p2`
276 // then this reduction process will replace `p1` with true.
277
278 // Maintain respectively:
279 // 1) A list of predicates for which we have checked for matching
280 // subexpressions
281 // 2) A list of predicates for which we have yet to do so.
282 let mut completed = Vec::new();
283 let mut todo = Vec::new();
284 // Seed `todo` with all predicates.
285 std::mem::swap(&mut todo, predicates);
286
287 while let Some(predicate_to_apply) = todo.pop() {
288 // Helper method: for each predicate `p`, see if all other predicates
289 // (a.k.a. the union of todo & completed) contains `p` as a
290 // subexpression, and replace the subexpression accordingly.
291 // This method lives inside the loop because in order to comply with
292 // Rust rules that only one mutable reference to `todo` can be held at a
293 // time.
294 let mut replace_subexpr_other_predicates =
295 |expr: &MirScalarExpr, constant_bool: &MirScalarExpr| {
296 // Do not replace subexpressions equal to `expr` if `expr` is a
297 // literal to avoid infinite looping.
298 if !expr.is_literal() {
299 for other_predicate in todo.iter_mut() {
300 replace_subexpr_and_reduce(
301 other_predicate,
302 expr,
303 constant_bool,
304 repr_column_types,
305 );
306 }
307 for other_idx in (0..completed.len()).rev() {
308 if replace_subexpr_and_reduce(
309 &mut completed[other_idx],
310 expr,
311 constant_bool,
312 repr_column_types,
313 ) {
314 // If a predicate in the `completed` list has
315 // been simplified, stick it back into the `todo` list.
316 todo.push(completed.remove(other_idx));
317 }
318 }
319 }
320 };
321 // Meat of loop starts here. If a predicate p is of the form `!q`, replace
322 // every instance of `q` in every other predicate with `false.`
323 // Otherwise, replace every instance of `p` in every other predicate
324 // with `true`.
325 if let MirScalarExpr::CallUnary {
326 func: UnaryFunc::Not(func::Not),
327 expr,
328 } = &predicate_to_apply
329 {
330 replace_subexpr_other_predicates(expr, &MirScalarExpr::literal_false())
331 } else {
332 replace_subexpr_other_predicates(&predicate_to_apply, &MirScalarExpr::literal_true());
333 }
334 completed.push(predicate_to_apply);
335 }
336
337 // 5) Remove redundant !isnull/isnull predicates after performing the replacements
338 // in the loop above.
339 std::mem::swap(&mut todo, &mut completed);
340 while let Some(predicate_to_apply) = todo.pop() {
341 // Remove redundant !isnull(x) predicates if there is another predicate
342 // that evaluates to NULL when `x` is NULL.
343 if let Some(operand) = is_not_null(&predicate_to_apply) {
344 if todo
345 .iter_mut()
346 .chain(completed.iter_mut())
347 .any(|p| is_null_rejecting_predicate(p, &operand))
348 {
349 // skip this predicate
350 continue;
351 }
352 } else if let MirScalarExpr::CallUnary {
353 func: UnaryFunc::IsNull(func::IsNull),
354 expr,
355 } = &predicate_to_apply
356 {
357 if todo
358 .iter_mut()
359 .chain(completed.iter_mut())
360 .any(|p| is_null_rejecting_predicate(p, expr))
361 {
362 completed.push(MirScalarExpr::literal_false());
363 break;
364 }
365 }
366 completed.push(predicate_to_apply);
367 }
368
369 if completed.iter().any(|p| {
370 (p.is_literal_false() || p.is_literal_null()) &&
371 // This extra check is only needed if we determine that the soft-assert
372 // at the top of this function would ever fail for a good reason.
373 p.typ(repr_column_types).scalar_type == ReprScalarType::Bool
374 }) {
375 // all rows get filtered away if any predicate is null or false.
376 *predicates = vec![MirScalarExpr::literal_false()]
377 } else {
378 // Remove any predicates that have been reduced to "true"
379 completed.retain(|p| !p.is_literal_true());
380 *predicates = completed;
381 }
382
383 // 6) Sort and dedup predicates.
384 predicates.sort_by(compare_predicates);
385 predicates.dedup();
386}
387
388/// Replace any matching subexpressions in `predicate`, and if `predicate` has
389/// changed, reduce it. Return whether `predicate` has changed.
390fn replace_subexpr_and_reduce(
391 predicate: &mut MirScalarExpr,
392 replace_if_equal_to: &MirScalarExpr,
393 replace_with: &MirScalarExpr,
394 repr_column_types: &[ReprColumnType],
395) -> bool {
396 let mut changed = false;
397 predicate.visit_mut_pre_post(
398 &mut |e| {
399 // The `cond` of an if statement is not visited to prevent `then`
400 // or `els` from being evaluated before `cond`, resulting in a
401 // correctness error.
402 if let MirScalarExpr::If { then, els, .. } = e {
403 return Some(vec![then, els]);
404 }
405 None
406 },
407 &mut |e| {
408 if e == replace_if_equal_to {
409 *e = replace_with.clone();
410 changed = true;
411 } else if let MirScalarExpr::CallBinary {
412 func: r_func,
413 expr1: r_expr1,
414 expr2: r_expr2,
415 } = replace_if_equal_to
416 {
417 if let Some(negation) = r_func.negate() {
418 if let MirScalarExpr::CallBinary {
419 func: l_func,
420 expr1: l_expr1,
421 expr2: l_expr2,
422 } = e
423 {
424 if negation == *l_func && l_expr1 == r_expr1 && l_expr2 == r_expr2 {
425 *e = MirScalarExpr::CallUnary {
426 func: UnaryFunc::Not(func::Not),
427 expr: Box::new(replace_with.clone()),
428 };
429 changed = true;
430 }
431 }
432 }
433 }
434 },
435 );
436 if changed {
437 predicate.reduce(repr_column_types);
438 }
439 changed
440}
441
442/// Returns the inner operand if the given predicate is an IS NOT NULL expression.
443fn is_not_null(predicate: &MirScalarExpr) -> Option<MirScalarExpr> {
444 if let MirScalarExpr::CallUnary {
445 func: UnaryFunc::Not(func::Not),
446 expr,
447 } = &predicate
448 {
449 if let MirScalarExpr::CallUnary {
450 func: UnaryFunc::IsNull(func::IsNull),
451 expr,
452 } = &**expr
453 {
454 return Some((**expr).clone());
455 }
456 }
457 None
458}
459
460/// Whether the given predicate evaluates to NULL when the given operand expression is NULL.
461#[inline(always)]
462fn is_null_rejecting_predicate(predicate: &MirScalarExpr, operand: &MirScalarExpr) -> bool {
463 propagates_null_from_subexpression(predicate, operand)
464}
465
466fn propagates_null_from_subexpression(expr: &MirScalarExpr, operand: &MirScalarExpr) -> bool {
467 if operand == expr {
468 true
469 } else if let MirScalarExpr::CallVariadic { func, exprs } = &expr {
470 func.propagates_nulls()
471 && (exprs
472 .iter()
473 .any(|e| propagates_null_from_subexpression(e, operand)))
474 } else if let MirScalarExpr::CallBinary { func, expr1, expr2 } = &expr {
475 func.propagates_nulls()
476 && (propagates_null_from_subexpression(expr1, operand)
477 || propagates_null_from_subexpression(expr2, operand))
478 } else if let MirScalarExpr::CallUnary { func, expr } = &expr {
479 func.propagates_nulls() && propagates_null_from_subexpression(expr, operand)
480 } else {
481 false
482 }
483}
484
485/// Comparison method for sorting predicates by their complexity, measured by the total
486/// number of non-literal expression nodes within the expression.
487fn compare_predicates(x: &MirScalarExpr, y: &MirScalarExpr) -> Ordering {
488 (rank_complexity(x), x).cmp(&(rank_complexity(y), y))
489}
490
491/// For each equivalence class, it finds the simplest expression, which will be the canonical one.
492/// Returns a Map that maps from each expression in each equivalence class to the canonical
493/// expression in the same equivalence class.
494pub fn get_canonicalizer_map(
495 equivalences: &Vec<Vec<MirScalarExpr>>,
496) -> BTreeMap<MirScalarExpr, MirScalarExpr> {
497 let mut canonicalizer_map = BTreeMap::new();
498 for equivalence in equivalences {
499 // The unwrap is ok, because a join equivalence class can't be empty.
500 let canonical_expr = equivalence
501 .iter()
502 .min_by(|a, b| compare_predicates(*a, *b))
503 .unwrap();
504 for e in equivalence {
505 if e != canonical_expr {
506 canonicalizer_map.insert(e.clone(), canonical_expr.clone());
507 }
508 }
509 }
510 canonicalizer_map
511}
512
513/// A trait for a union-find data structure.
514pub trait UnionFind<T> {
515 /// Sets `self[x]` to the root from `x`, and returns a reference to the root.
516 fn find<'a>(&'a mut self, x: &T) -> Option<&'a T>;
517 /// Ensures that `x` and `y` have the same root.
518 fn union(&mut self, x: &T, y: &T);
519}
520
521impl<T: Clone + Ord> UnionFind<T> for BTreeMap<T, T> {
522 fn find<'a>(&'a mut self, x: &T) -> Option<&'a T> {
523 if !self.contains_key(x) {
524 None
525 } else {
526 if self[x] != self[&self[x]] {
527 // Path halving
528 let mut y = self[x].clone();
529 while y != self[&y] {
530 let grandparent = self[&self[&y]].clone();
531 *self.get_mut(&y).unwrap() = grandparent;
532 y.clone_from(&self[&y]);
533 }
534 *self.get_mut(x).unwrap() = y;
535 }
536 Some(&self[x])
537 }
538 }
539
540 fn union(&mut self, x: &T, y: &T) {
541 match (self.find(x).is_some(), self.find(y).is_some()) {
542 (true, true) => {
543 if self[x] != self[y] {
544 let root_x = self[x].clone();
545 let root_y = self[y].clone();
546 self.insert(root_x, root_y);
547 }
548 }
549 (false, true) => {
550 self.insert(x.clone(), self[y].clone());
551 }
552 (true, false) => {
553 self.insert(y.clone(), self[x].clone());
554 }
555 (false, false) => {
556 self.insert(x.clone(), x.clone());
557 self.insert(y.clone(), x.clone());
558 }
559 }
560 }
561}