Line data Source code
1 : /*-------------------------------------------------------------------------
2 : *
3 : * dependencies.c
4 : * POSTGRES functional dependencies
5 : *
6 : * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
7 : * Portions Copyright (c) 1994, Regents of the University of California
8 : *
9 : * IDENTIFICATION
10 : * src/backend/statistics/dependencies.c
11 : *
12 : *-------------------------------------------------------------------------
13 : */
14 : #include "postgres.h"
15 :
16 : #include "access/htup_details.h"
17 : #include "catalog/pg_statistic_ext.h"
18 : #include "catalog/pg_statistic_ext_data.h"
19 : #include "lib/stringinfo.h"
20 : #include "nodes/nodeFuncs.h"
21 : #include "nodes/nodes.h"
22 : #include "nodes/pathnodes.h"
23 : #include "optimizer/clauses.h"
24 : #include "optimizer/optimizer.h"
25 : #include "parser/parsetree.h"
26 : #include "statistics/extended_stats_internal.h"
27 : #include "statistics/statistics.h"
28 : #include "utils/fmgroids.h"
29 : #include "utils/fmgrprotos.h"
30 : #include "utils/lsyscache.h"
31 : #include "utils/memutils.h"
32 : #include "utils/selfuncs.h"
33 : #include "utils/syscache.h"
34 : #include "utils/typcache.h"
35 : #include "varatt.h"
36 :
37 : /* size of the struct header fields (magic, type, ndeps) */
38 : #define SizeOfHeader (3 * sizeof(uint32))
39 :
40 : /* size of a serialized dependency (degree, natts, atts) */
41 : #define SizeOfItem(natts) \
42 : (sizeof(double) + sizeof(AttrNumber) * (1 + (natts)))
43 :
44 : /* minimal size of a dependency (with two attributes) */
45 : #define MinSizeOfItem SizeOfItem(2)
46 :
47 : /* minimal size of dependencies, when all deps are minimal */
48 : #define MinSizeOfItems(ndeps) \
49 : (SizeOfHeader + (ndeps) * MinSizeOfItem)
50 :
51 : /*
52 : * Internal state for DependencyGenerator of dependencies. Dependencies are similar to
53 : * k-permutations of n elements, except that the order does not matter for the
54 : * first (k-1) elements. That is, (a,b=>c) and (b,a=>c) are equivalent.
55 : */
56 : typedef struct DependencyGeneratorData
57 : {
58 : int k; /* size of the dependency */
59 : int n; /* number of possible attributes */
60 : int current; /* next dependency to return (index) */
61 : AttrNumber ndependencies; /* number of dependencies generated */
62 : AttrNumber *dependencies; /* array of pre-generated dependencies */
63 : } DependencyGeneratorData;
64 :
65 : typedef DependencyGeneratorData *DependencyGenerator;
66 :
67 : static void generate_dependencies_recurse(DependencyGenerator state,
68 : int index, AttrNumber start, AttrNumber *current);
69 : static void generate_dependencies(DependencyGenerator state);
70 : static DependencyGenerator DependencyGenerator_init(int n, int k);
71 : static void DependencyGenerator_free(DependencyGenerator state);
72 : static AttrNumber *DependencyGenerator_next(DependencyGenerator state);
73 : static double dependency_degree(StatsBuildData *data, int k, AttrNumber *dependency);
74 : static bool dependency_is_fully_matched(MVDependency *dependency,
75 : Bitmapset *attnums);
76 : static bool dependency_is_compatible_clause(Node *clause, Index relid,
77 : AttrNumber *attnum);
78 : static bool dependency_is_compatible_expression(Node *clause, Index relid,
79 : List *statlist, Node **expr);
80 : static MVDependency *find_strongest_dependency(MVDependencies **dependencies,
81 : int ndependencies, Bitmapset *attnums);
82 : static Selectivity clauselist_apply_dependencies(PlannerInfo *root, List *clauses,
83 : int varRelid, JoinType jointype,
84 : SpecialJoinInfo *sjinfo,
85 : MVDependency **dependencies,
86 : int ndependencies,
87 : AttrNumber *list_attnums,
88 : Bitmapset **estimatedclauses);
89 :
90 : static void
91 780 : generate_dependencies_recurse(DependencyGenerator state, int index,
92 : AttrNumber start, AttrNumber *current)
93 : {
94 : /*
95 : * The generator handles the first (k-1) elements differently from the
96 : * last element.
97 : */
98 780 : if (index < (state->k - 1))
99 : {
100 : AttrNumber i;
101 :
102 : /*
103 : * The first (k-1) values have to be in ascending order, which we
104 : * generate recursively.
105 : */
106 :
107 924 : for (i = start; i < state->n; i++)
108 : {
109 600 : current[index] = i;
110 600 : generate_dependencies_recurse(state, (index + 1), (i + 1), current);
111 : }
112 : }
113 : else
114 : {
115 : int i;
116 :
117 : /*
118 : * the last element is the implied value, which does not respect the
119 : * ascending order. We just need to check that the value is not in the
120 : * first (k-1) elements.
121 : */
122 :
123 1656 : for (i = 0; i < state->n; i++)
124 : {
125 : int j;
126 1200 : bool match = false;
127 :
128 1200 : current[index] = i;
129 :
130 2088 : for (j = 0; j < index; j++)
131 : {
132 1488 : if (current[j] == i)
133 : {
134 600 : match = true;
135 600 : break;
136 : }
137 : }
138 :
139 : /*
140 : * If the value is not found in the first part of the dependency,
141 : * we're done.
142 : */
143 1200 : if (!match)
144 : {
145 1200 : state->dependencies = (AttrNumber *) repalloc(state->dependencies,
146 600 : state->k * (state->ndependencies + 1) * sizeof(AttrNumber));
147 600 : memcpy(&state->dependencies[(state->k * state->ndependencies)],
148 600 : current, state->k * sizeof(AttrNumber));
149 600 : state->ndependencies++;
150 : }
151 : }
152 : }
153 780 : }
154 :
155 : /* generate all dependencies (k-permutations of n elements) */
156 : static void
157 180 : generate_dependencies(DependencyGenerator state)
158 : {
159 180 : AttrNumber *current = (AttrNumber *) palloc0(sizeof(AttrNumber) * state->k);
160 :
161 180 : generate_dependencies_recurse(state, 0, 0, current);
162 :
163 180 : pfree(current);
164 180 : }
165 :
166 : /*
167 : * initialize the DependencyGenerator of variations, and prebuild the variations
168 : *
169 : * This pre-builds all the variations. We could also generate them in
170 : * DependencyGenerator_next(), but this seems simpler.
171 : */
172 : static DependencyGenerator
173 180 : DependencyGenerator_init(int n, int k)
174 : {
175 : DependencyGenerator state;
176 :
177 : Assert((n >= k) && (k > 0));
178 :
179 : /* allocate the DependencyGenerator state */
180 180 : state = (DependencyGenerator) palloc0(sizeof(DependencyGeneratorData));
181 180 : state->dependencies = (AttrNumber *) palloc(k * sizeof(AttrNumber));
182 :
183 180 : state->ndependencies = 0;
184 180 : state->current = 0;
185 180 : state->k = k;
186 180 : state->n = n;
187 :
188 : /* now actually pre-generate all the variations */
189 180 : generate_dependencies(state);
190 :
191 180 : return state;
192 : }
193 :
194 : /* free the DependencyGenerator state */
195 : static void
196 180 : DependencyGenerator_free(DependencyGenerator state)
197 : {
198 180 : pfree(state->dependencies);
199 180 : pfree(state);
200 180 : }
201 :
202 : /* generate next combination */
203 : static AttrNumber *
204 780 : DependencyGenerator_next(DependencyGenerator state)
205 : {
206 780 : if (state->current == state->ndependencies)
207 180 : return NULL;
208 :
209 600 : return &state->dependencies[state->k * state->current++];
210 : }
211 :
212 :
213 : /*
214 : * validates functional dependency on the data
215 : *
216 : * An actual work horse of detecting functional dependencies. Given a variation
217 : * of k attributes, it checks that the first (k-1) are sufficient to determine
218 : * the last one.
219 : */
220 : static double
221 600 : dependency_degree(StatsBuildData *data, int k, AttrNumber *dependency)
222 : {
223 : int i,
224 : nitems;
225 : MultiSortSupport mss;
226 : SortItem *items;
227 : AttrNumber *attnums_dep;
228 :
229 : /* counters valid within a group */
230 600 : int group_size = 0;
231 600 : int n_violations = 0;
232 :
233 : /* total number of rows supporting (consistent with) the dependency */
234 600 : int n_supporting_rows = 0;
235 :
236 : /* Make sure we have at least two input attributes. */
237 : Assert(k >= 2);
238 :
239 : /* sort info for all attributes columns */
240 600 : mss = multi_sort_init(k);
241 :
242 : /*
243 : * Translate the array of indexes to regular attnums for the dependency
244 : * (we will need this to identify the columns in StatsBuildData).
245 : */
246 600 : attnums_dep = (AttrNumber *) palloc(k * sizeof(AttrNumber));
247 1944 : for (i = 0; i < k; i++)
248 1344 : attnums_dep[i] = data->attnums[dependency[i]];
249 :
250 : /*
251 : * Verify the dependency (a,b,...)->z, using a rather simple algorithm:
252 : *
253 : * (a) sort the data lexicographically
254 : *
255 : * (b) split the data into groups by first (k-1) columns
256 : *
257 : * (c) for each group count different values in the last column
258 : *
259 : * We use the column data types' default sort operators and collations;
260 : * perhaps at some point it'd be worth using column-specific collations?
261 : */
262 :
263 : /* prepare the sort function for the dimensions */
264 1944 : for (i = 0; i < k; i++)
265 : {
266 1344 : VacAttrStats *colstat = data->stats[dependency[i]];
267 : TypeCacheEntry *type;
268 :
269 1344 : type = lookup_type_cache(colstat->attrtypid, TYPECACHE_LT_OPR);
270 1344 : if (type->lt_opr == InvalidOid) /* shouldn't happen */
271 0 : elog(ERROR, "cache lookup failed for ordering operator for type %u",
272 : colstat->attrtypid);
273 :
274 : /* prepare the sort function for this dimension */
275 1344 : multi_sort_add_dimension(mss, i, type->lt_opr, colstat->attrcollid);
276 : }
277 :
278 : /*
279 : * build an array of SortItem(s) sorted using the multi-sort support
280 : *
281 : * XXX This relies on all stats entries pointing to the same tuple
282 : * descriptor. For now that assumption holds, but it might change in the
283 : * future for example if we support statistics on multiple tables.
284 : */
285 600 : items = build_sorted_items(data, &nitems, mss, k, attnums_dep);
286 :
287 : /*
288 : * Walk through the sorted array, split it into rows according to the
289 : * first (k-1) columns. If there's a single value in the last column, we
290 : * count the group as 'supporting' the functional dependency. Otherwise we
291 : * count it as contradicting.
292 : */
293 :
294 : /* start with the first row forming a group */
295 600 : group_size = 1;
296 :
297 : /* loop 1 beyond the end of the array so that we count the final group */
298 1505466 : for (i = 1; i <= nitems; i++)
299 : {
300 : /*
301 : * Check if the group ended, which may be either because we processed
302 : * all the items (i==nitems), or because the i-th item is not equal to
303 : * the preceding one.
304 : */
305 3009132 : if (i == nitems ||
306 1504266 : multi_sort_compare_dims(0, k - 2, &items[i - 1], &items[i], mss) != 0)
307 : {
308 : /*
309 : * If no violations were found in the group then track the rows of
310 : * the group as supporting the functional dependency.
311 : */
312 32268 : if (n_violations == 0)
313 19578 : n_supporting_rows += group_size;
314 :
315 : /* Reset counters for the new group */
316 32268 : n_violations = 0;
317 32268 : group_size = 1;
318 32268 : continue;
319 : }
320 : /* first columns match, but the last one does not (so contradicting) */
321 1472598 : else if (multi_sort_compare_dim(k - 1, &items[i - 1], &items[i], mss) != 0)
322 60102 : n_violations++;
323 :
324 1472598 : group_size++;
325 : }
326 :
327 : /* Compute the 'degree of validity' as (supporting/total). */
328 600 : return (n_supporting_rows * 1.0 / data->numrows);
329 : }
330 :
331 : /*
332 : * detects functional dependencies between groups of columns
333 : *
334 : * Generates all possible subsets of columns (variations) and computes
335 : * the degree of validity for each one. For example when creating statistics
336 : * on three columns (a,b,c) there are 9 possible dependencies
337 : *
338 : * two columns three columns
339 : * ----------- -------------
340 : * (a) -> b (a,b) -> c
341 : * (a) -> c (a,c) -> b
342 : * (b) -> a (b,c) -> a
343 : * (b) -> c
344 : * (c) -> a
345 : * (c) -> b
346 : */
347 : MVDependencies *
348 132 : statext_dependencies_build(StatsBuildData *data)
349 : {
350 : int i,
351 : k;
352 :
353 : /* result */
354 132 : MVDependencies *dependencies = NULL;
355 : MemoryContext cxt;
356 :
357 : Assert(data->nattnums >= 2);
358 :
359 : /* tracks memory allocated by dependency_degree calls */
360 132 : cxt = AllocSetContextCreate(CurrentMemoryContext,
361 : "dependency_degree cxt",
362 : ALLOCSET_DEFAULT_SIZES);
363 :
364 : /*
365 : * We'll try build functional dependencies starting from the smallest ones
366 : * covering just 2 columns, to the largest ones, covering all columns
367 : * included in the statistics object. We start from the smallest ones
368 : * because we want to be able to skip already implied ones.
369 : */
370 312 : for (k = 2; k <= data->nattnums; k++)
371 : {
372 : AttrNumber *dependency; /* array with k elements */
373 :
374 : /* prepare a DependencyGenerator of variation */
375 180 : DependencyGenerator DependencyGenerator = DependencyGenerator_init(data->nattnums, k);
376 :
377 : /* generate all possible variations of k values (out of n) */
378 780 : while ((dependency = DependencyGenerator_next(DependencyGenerator)))
379 : {
380 : double degree;
381 : MVDependency *d;
382 : MemoryContext oldcxt;
383 :
384 : /* release memory used by dependency degree calculation */
385 600 : oldcxt = MemoryContextSwitchTo(cxt);
386 :
387 : /* compute how valid the dependency seems */
388 600 : degree = dependency_degree(data, k, dependency);
389 :
390 600 : MemoryContextSwitchTo(oldcxt);
391 600 : MemoryContextReset(cxt);
392 :
393 : /*
394 : * if the dependency seems entirely invalid, don't store it
395 : */
396 600 : if (degree == 0.0)
397 252 : continue;
398 :
399 348 : d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
400 348 : + k * sizeof(AttrNumber));
401 :
402 : /* copy the dependency (and keep the indexes into stxkeys) */
403 348 : d->degree = degree;
404 348 : d->nattributes = k;
405 1116 : for (i = 0; i < k; i++)
406 768 : d->attributes[i] = data->attnums[dependency[i]];
407 :
408 : /* initialize the list of dependencies */
409 348 : if (dependencies == NULL)
410 : {
411 : dependencies
412 114 : = (MVDependencies *) palloc0(sizeof(MVDependencies));
413 :
414 114 : dependencies->magic = STATS_DEPS_MAGIC;
415 114 : dependencies->type = STATS_DEPS_TYPE_BASIC;
416 114 : dependencies->ndeps = 0;
417 : }
418 :
419 348 : dependencies->ndeps++;
420 348 : dependencies = (MVDependencies *) repalloc(dependencies,
421 : offsetof(MVDependencies, deps)
422 348 : + dependencies->ndeps * sizeof(MVDependency *));
423 :
424 348 : dependencies->deps[dependencies->ndeps - 1] = d;
425 : }
426 :
427 : /*
428 : * we're done with variations of k elements, so free the
429 : * DependencyGenerator
430 : */
431 180 : DependencyGenerator_free(DependencyGenerator);
432 : }
433 :
434 132 : MemoryContextDelete(cxt);
435 :
436 132 : return dependencies;
437 : }
438 :
439 :
440 : /*
441 : * Serialize list of dependencies into a bytea value.
442 : */
443 : bytea *
444 114 : statext_dependencies_serialize(MVDependencies *dependencies)
445 : {
446 : int i;
447 : bytea *output;
448 : char *tmp;
449 : Size len;
450 :
451 : /* we need to store ndeps, with a number of attributes for each one */
452 114 : len = VARHDRSZ + SizeOfHeader;
453 :
454 : /* and also include space for the actual attribute numbers and degrees */
455 462 : for (i = 0; i < dependencies->ndeps; i++)
456 348 : len += SizeOfItem(dependencies->deps[i]->nattributes);
457 :
458 114 : output = (bytea *) palloc0(len);
459 114 : SET_VARSIZE(output, len);
460 :
461 114 : tmp = VARDATA(output);
462 :
463 : /* Store the base struct values (magic, type, ndeps) */
464 114 : memcpy(tmp, &dependencies->magic, sizeof(uint32));
465 114 : tmp += sizeof(uint32);
466 114 : memcpy(tmp, &dependencies->type, sizeof(uint32));
467 114 : tmp += sizeof(uint32);
468 114 : memcpy(tmp, &dependencies->ndeps, sizeof(uint32));
469 114 : tmp += sizeof(uint32);
470 :
471 : /* store number of attributes and attribute numbers for each dependency */
472 462 : for (i = 0; i < dependencies->ndeps; i++)
473 : {
474 348 : MVDependency *d = dependencies->deps[i];
475 :
476 348 : memcpy(tmp, &d->degree, sizeof(double));
477 348 : tmp += sizeof(double);
478 :
479 348 : memcpy(tmp, &d->nattributes, sizeof(AttrNumber));
480 348 : tmp += sizeof(AttrNumber);
481 :
482 348 : memcpy(tmp, d->attributes, sizeof(AttrNumber) * d->nattributes);
483 348 : tmp += sizeof(AttrNumber) * d->nattributes;
484 :
485 : /* protect against overflow */
486 : Assert(tmp <= ((char *) output + len));
487 : }
488 :
489 : /* make sure we've produced exactly the right amount of data */
490 : Assert(tmp == ((char *) output + len));
491 :
492 114 : return output;
493 : }
494 :
495 : /*
496 : * Reads serialized dependencies into MVDependencies structure.
497 : */
498 : MVDependencies *
499 1120 : statext_dependencies_deserialize(bytea *data)
500 : {
501 : int i;
502 : Size min_expected_size;
503 : MVDependencies *dependencies;
504 : char *tmp;
505 :
506 1120 : if (data == NULL)
507 0 : return NULL;
508 :
509 1120 : if (VARSIZE_ANY_EXHDR(data) < SizeOfHeader)
510 0 : elog(ERROR, "invalid MVDependencies size %zu (expected at least %zu)",
511 : VARSIZE_ANY_EXHDR(data), SizeOfHeader);
512 :
513 : /* read the MVDependencies header */
514 1120 : dependencies = (MVDependencies *) palloc0(sizeof(MVDependencies));
515 :
516 : /* initialize pointer to the data part (skip the varlena header) */
517 1120 : tmp = VARDATA_ANY(data);
518 :
519 : /* read the header fields and perform basic sanity checks */
520 1120 : memcpy(&dependencies->magic, tmp, sizeof(uint32));
521 1120 : tmp += sizeof(uint32);
522 1120 : memcpy(&dependencies->type, tmp, sizeof(uint32));
523 1120 : tmp += sizeof(uint32);
524 1120 : memcpy(&dependencies->ndeps, tmp, sizeof(uint32));
525 1120 : tmp += sizeof(uint32);
526 :
527 1120 : if (dependencies->magic != STATS_DEPS_MAGIC)
528 0 : elog(ERROR, "invalid dependency magic %d (expected %d)",
529 : dependencies->magic, STATS_DEPS_MAGIC);
530 :
531 1120 : if (dependencies->type != STATS_DEPS_TYPE_BASIC)
532 0 : elog(ERROR, "invalid dependency type %d (expected %d)",
533 : dependencies->type, STATS_DEPS_TYPE_BASIC);
534 :
535 1120 : if (dependencies->ndeps == 0)
536 0 : elog(ERROR, "invalid zero-length item array in MVDependencies");
537 :
538 : /* what minimum bytea size do we expect for those parameters */
539 1120 : min_expected_size = SizeOfItem(dependencies->ndeps);
540 :
541 1120 : if (VARSIZE_ANY_EXHDR(data) < min_expected_size)
542 0 : elog(ERROR, "invalid dependencies size %zu (expected at least %zu)",
543 : VARSIZE_ANY_EXHDR(data), min_expected_size);
544 :
545 : /* allocate space for the MCV items */
546 1120 : dependencies = repalloc(dependencies, offsetof(MVDependencies, deps)
547 1120 : + (dependencies->ndeps * sizeof(MVDependency *)));
548 :
549 6594 : for (i = 0; i < dependencies->ndeps; i++)
550 : {
551 : double degree;
552 : AttrNumber k;
553 : MVDependency *d;
554 :
555 : /* degree of validity */
556 5474 : memcpy(°ree, tmp, sizeof(double));
557 5474 : tmp += sizeof(double);
558 :
559 : /* number of attributes */
560 5474 : memcpy(&k, tmp, sizeof(AttrNumber));
561 5474 : tmp += sizeof(AttrNumber);
562 :
563 : /* is the number of attributes valid? */
564 : Assert((k >= 2) && (k <= STATS_MAX_DIMENSIONS));
565 :
566 : /* now that we know the number of attributes, allocate the dependency */
567 5474 : d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
568 5474 : + (k * sizeof(AttrNumber)));
569 :
570 5474 : d->degree = degree;
571 5474 : d->nattributes = k;
572 :
573 : /* copy attribute numbers */
574 5474 : memcpy(d->attributes, tmp, sizeof(AttrNumber) * d->nattributes);
575 5474 : tmp += sizeof(AttrNumber) * d->nattributes;
576 :
577 5474 : dependencies->deps[i] = d;
578 :
579 : /* still within the bytea */
580 : Assert(tmp <= ((char *) data + VARSIZE_ANY(data)));
581 : }
582 :
583 : /* we should have consumed the whole bytea exactly */
584 : Assert(tmp == ((char *) data + VARSIZE_ANY(data)));
585 :
586 1120 : return dependencies;
587 : }
588 :
589 : /*
590 : * dependency_is_fully_matched
591 : * checks that a functional dependency is fully matched given clauses on
592 : * attributes (assuming the clauses are suitable equality clauses)
593 : */
594 : static bool
595 4644 : dependency_is_fully_matched(MVDependency *dependency, Bitmapset *attnums)
596 : {
597 : int j;
598 :
599 : /*
600 : * Check that the dependency actually is fully covered by clauses. We have
601 : * to translate all attribute numbers, as those are referenced
602 : */
603 12114 : for (j = 0; j < dependency->nattributes; j++)
604 : {
605 9534 : int attnum = dependency->attributes[j];
606 :
607 9534 : if (!bms_is_member(attnum, attnums))
608 2064 : return false;
609 : }
610 :
611 2580 : return true;
612 : }
613 :
614 : /*
615 : * statext_dependencies_load
616 : * Load the functional dependencies for the indicated pg_statistic_ext tuple
617 : */
618 : MVDependencies *
619 1104 : statext_dependencies_load(Oid mvoid, bool inh)
620 : {
621 : MVDependencies *result;
622 : bool isnull;
623 : Datum deps;
624 : HeapTuple htup;
625 :
626 1104 : htup = SearchSysCache2(STATEXTDATASTXOID,
627 : ObjectIdGetDatum(mvoid),
628 : BoolGetDatum(inh));
629 1104 : if (!HeapTupleIsValid(htup))
630 0 : elog(ERROR, "cache lookup failed for statistics object %u", mvoid);
631 :
632 1104 : deps = SysCacheGetAttr(STATEXTDATASTXOID, htup,
633 : Anum_pg_statistic_ext_data_stxddependencies, &isnull);
634 1104 : if (isnull)
635 0 : elog(ERROR,
636 : "requested statistics kind \"%c\" is not yet built for statistics object %u",
637 : STATS_EXT_DEPENDENCIES, mvoid);
638 :
639 1104 : result = statext_dependencies_deserialize(DatumGetByteaPP(deps));
640 :
641 1104 : ReleaseSysCache(htup);
642 :
643 1104 : return result;
644 : }
645 :
646 : /*
647 : * pg_dependencies_in - input routine for type pg_dependencies.
648 : *
649 : * pg_dependencies is real enough to be a table column, but it has no operations
650 : * of its own, and disallows input too
651 : */
652 : Datum
653 0 : pg_dependencies_in(PG_FUNCTION_ARGS)
654 : {
655 : /*
656 : * pg_node_list stores the data in binary form and parsing text input is
657 : * not needed, so disallow this.
658 : */
659 0 : ereport(ERROR,
660 : (errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
661 : errmsg("cannot accept a value of type %s", "pg_dependencies")));
662 :
663 : PG_RETURN_VOID(); /* keep compiler quiet */
664 : }
665 :
666 : /*
667 : * pg_dependencies - output routine for type pg_dependencies.
668 : */
669 : Datum
670 16 : pg_dependencies_out(PG_FUNCTION_ARGS)
671 : {
672 16 : bytea *data = PG_GETARG_BYTEA_PP(0);
673 16 : MVDependencies *dependencies = statext_dependencies_deserialize(data);
674 : int i,
675 : j;
676 : StringInfoData str;
677 :
678 16 : initStringInfo(&str);
679 16 : appendStringInfoChar(&str, '{');
680 :
681 96 : for (i = 0; i < dependencies->ndeps; i++)
682 : {
683 80 : MVDependency *dependency = dependencies->deps[i];
684 :
685 80 : if (i > 0)
686 64 : appendStringInfoString(&str, ", ");
687 :
688 80 : appendStringInfoChar(&str, '"');
689 272 : for (j = 0; j < dependency->nattributes; j++)
690 : {
691 192 : if (j == dependency->nattributes - 1)
692 80 : appendStringInfoString(&str, " => ");
693 112 : else if (j > 0)
694 32 : appendStringInfoString(&str, ", ");
695 :
696 192 : appendStringInfo(&str, "%d", dependency->attributes[j]);
697 : }
698 80 : appendStringInfo(&str, "\": %f", dependency->degree);
699 : }
700 :
701 16 : appendStringInfoChar(&str, '}');
702 :
703 16 : PG_RETURN_CSTRING(str.data);
704 : }
705 :
706 : /*
707 : * pg_dependencies_recv - binary input routine for type pg_dependencies.
708 : */
709 : Datum
710 0 : pg_dependencies_recv(PG_FUNCTION_ARGS)
711 : {
712 0 : ereport(ERROR,
713 : (errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
714 : errmsg("cannot accept a value of type %s", "pg_dependencies")));
715 :
716 : PG_RETURN_VOID(); /* keep compiler quiet */
717 : }
718 :
719 : /*
720 : * pg_dependencies_send - binary output routine for type pg_dependencies.
721 : *
722 : * Functional dependencies are serialized in a bytea value (although the type
723 : * is named differently), so let's just send that.
724 : */
725 : Datum
726 0 : pg_dependencies_send(PG_FUNCTION_ARGS)
727 : {
728 0 : return byteasend(fcinfo);
729 : }
730 :
731 : /*
732 : * dependency_is_compatible_clause
733 : * Determines if the clause is compatible with functional dependencies
734 : *
735 : * Only clauses that have the form of equality to a pseudoconstant, or can be
736 : * interpreted that way, are currently accepted. Furthermore the variable
737 : * part of the clause must be a simple Var belonging to the specified
738 : * relation, whose attribute number we return in *attnum on success.
739 : */
740 : static bool
741 2952 : dependency_is_compatible_clause(Node *clause, Index relid, AttrNumber *attnum)
742 : {
743 : Var *var;
744 : Node *clause_expr;
745 :
746 2952 : if (IsA(clause, RestrictInfo))
747 : {
748 2832 : RestrictInfo *rinfo = (RestrictInfo *) clause;
749 :
750 : /* Pseudoconstants are not interesting (they couldn't contain a Var) */
751 2832 : if (rinfo->pseudoconstant)
752 6 : return false;
753 :
754 : /* Clauses referencing multiple, or no, varnos are incompatible */
755 2826 : if (bms_membership(rinfo->clause_relids) != BMS_SINGLETON)
756 0 : return false;
757 :
758 2826 : clause = (Node *) rinfo->clause;
759 : }
760 :
761 2946 : if (is_opclause(clause))
762 : {
763 : /* If it's an opclause, check for Var = Const or Const = Var. */
764 1134 : OpExpr *expr = (OpExpr *) clause;
765 :
766 : /* Only expressions with two arguments are candidates. */
767 1134 : if (list_length(expr->args) != 2)
768 0 : return false;
769 :
770 : /* Make sure non-selected argument is a pseudoconstant. */
771 1134 : if (is_pseudo_constant_clause(lsecond(expr->args)))
772 1134 : clause_expr = linitial(expr->args);
773 0 : else if (is_pseudo_constant_clause(linitial(expr->args)))
774 0 : clause_expr = lsecond(expr->args);
775 : else
776 0 : return false;
777 :
778 : /*
779 : * If it's not an "=" operator, just ignore the clause, as it's not
780 : * compatible with functional dependencies.
781 : *
782 : * This uses the function for estimating selectivity, not the operator
783 : * directly (a bit awkward, but well ...).
784 : *
785 : * XXX this is pretty dubious; probably it'd be better to check btree
786 : * or hash opclass membership, so as not to be fooled by custom
787 : * selectivity functions, and to be more consistent with decisions
788 : * elsewhere in the planner.
789 : */
790 1134 : if (get_oprrest(expr->opno) != F_EQSEL)
791 36 : return false;
792 :
793 : /* OK to proceed with checking "var" */
794 : }
795 1812 : else if (IsA(clause, ScalarArrayOpExpr))
796 : {
797 : /* If it's a scalar array operator, check for Var IN Const. */
798 1740 : ScalarArrayOpExpr *expr = (ScalarArrayOpExpr *) clause;
799 :
800 : /*
801 : * Reject ALL() variant, we only care about ANY/IN.
802 : *
803 : * XXX Maybe we should check if all the values are the same, and allow
804 : * ALL in that case? Doesn't seem very practical, though.
805 : */
806 1740 : if (!expr->useOr)
807 36 : return false;
808 :
809 : /* Only expressions with two arguments are candidates. */
810 1704 : if (list_length(expr->args) != 2)
811 0 : return false;
812 :
813 : /*
814 : * We know it's always (Var IN Const), so we assume the var is the
815 : * first argument, and pseudoconstant is the second one.
816 : */
817 1704 : if (!is_pseudo_constant_clause(lsecond(expr->args)))
818 0 : return false;
819 :
820 1704 : clause_expr = linitial(expr->args);
821 :
822 : /*
823 : * If it's not an "=" operator, just ignore the clause, as it's not
824 : * compatible with functional dependencies. The operator is identified
825 : * simply by looking at which function it uses to estimate
826 : * selectivity. That's a bit strange, but it's what other similar
827 : * places do.
828 : */
829 1704 : if (get_oprrest(expr->opno) != F_EQSEL)
830 180 : return false;
831 :
832 : /* OK to proceed with checking "var" */
833 : }
834 72 : else if (is_orclause(clause))
835 : {
836 72 : BoolExpr *bool_expr = (BoolExpr *) clause;
837 : ListCell *lc;
838 :
839 : /* start with no attribute number */
840 72 : *attnum = InvalidAttrNumber;
841 :
842 150 : foreach(lc, bool_expr->args)
843 : {
844 : AttrNumber clause_attnum;
845 :
846 : /*
847 : * Had we found incompatible clause in the arguments, treat the
848 : * whole clause as incompatible.
849 : */
850 120 : if (!dependency_is_compatible_clause((Node *) lfirst(lc),
851 : relid, &clause_attnum))
852 42 : return false;
853 :
854 84 : if (*attnum == InvalidAttrNumber)
855 36 : *attnum = clause_attnum;
856 :
857 : /* ensure all the variables are the same (same attnum) */
858 84 : if (*attnum != clause_attnum)
859 6 : return false;
860 : }
861 :
862 : /* the Var is already checked by the recursive call */
863 30 : return true;
864 : }
865 0 : else if (is_notclause(clause))
866 : {
867 : /*
868 : * "NOT x" can be interpreted as "x = false", so get the argument and
869 : * proceed with seeing if it's a suitable Var.
870 : */
871 0 : clause_expr = (Node *) get_notclausearg(clause);
872 : }
873 : else
874 : {
875 : /*
876 : * A boolean expression "x" can be interpreted as "x = true", so
877 : * proceed with seeing if it's a suitable Var.
878 : */
879 0 : clause_expr = (Node *) clause;
880 : }
881 :
882 : /*
883 : * We may ignore any RelabelType node above the operand. (There won't be
884 : * more than one, since eval_const_expressions has been applied already.)
885 : */
886 2622 : if (IsA(clause_expr, RelabelType))
887 0 : clause_expr = (Node *) ((RelabelType *) clause_expr)->arg;
888 :
889 : /* We only support plain Vars for now */
890 2622 : if (!IsA(clause_expr, Var))
891 288 : return false;
892 :
893 : /* OK, we know we have a Var */
894 2334 : var = (Var *) clause_expr;
895 :
896 : /* Ensure Var is from the correct relation */
897 2334 : if (var->varno != relid)
898 0 : return false;
899 :
900 : /* We also better ensure the Var is from the current level */
901 2334 : if (var->varlevelsup != 0)
902 0 : return false;
903 :
904 : /* Also ignore system attributes (we don't allow stats on those) */
905 2334 : if (!AttrNumberIsForUserDefinedAttr(var->varattno))
906 0 : return false;
907 :
908 2334 : *attnum = var->varattno;
909 2334 : return true;
910 : }
911 :
912 : /*
913 : * find_strongest_dependency
914 : * find the strongest dependency on the attributes
915 : *
916 : * When applying functional dependencies, we start with the strongest
917 : * dependencies. That is, we select the dependency that:
918 : *
919 : * (a) has all attributes covered by equality clauses
920 : *
921 : * (b) has the most attributes
922 : *
923 : * (c) has the highest degree of validity
924 : *
925 : * This guarantees that we eliminate the most redundant conditions first
926 : * (see the comment in dependencies_clauselist_selectivity).
927 : */
928 : static MVDependency *
929 2478 : find_strongest_dependency(MVDependencies **dependencies, int ndependencies,
930 : Bitmapset *attnums)
931 : {
932 : int i,
933 : j;
934 2478 : MVDependency *strongest = NULL;
935 :
936 : /* number of attnums in clauses */
937 2478 : int nattnums = bms_num_members(attnums);
938 :
939 : /*
940 : * Iterate over the MVDependency items and find the strongest one from the
941 : * fully-matched dependencies. We do the cheap checks first, before
942 : * matching it against the attnums.
943 : */
944 4992 : for (i = 0; i < ndependencies; i++)
945 : {
946 14232 : for (j = 0; j < dependencies[i]->ndeps; j++)
947 : {
948 11718 : MVDependency *dependency = dependencies[i]->deps[j];
949 :
950 : /*
951 : * Skip dependencies referencing more attributes than available
952 : * clauses, as those can't be fully matched.
953 : */
954 11718 : if (dependency->nattributes > nattnums)
955 7074 : continue;
956 :
957 4644 : if (strongest)
958 : {
959 : /* skip dependencies on fewer attributes than the strongest. */
960 2928 : if (dependency->nattributes < strongest->nattributes)
961 0 : continue;
962 :
963 : /* also skip weaker dependencies when attribute count matches */
964 2928 : if (strongest->nattributes == dependency->nattributes &&
965 2646 : strongest->degree > dependency->degree)
966 0 : continue;
967 : }
968 :
969 : /*
970 : * this dependency is stronger, but we must still check that it's
971 : * fully matched to these attnums. We perform this check last as
972 : * it's slightly more expensive than the previous checks.
973 : */
974 4644 : if (dependency_is_fully_matched(dependency, attnums))
975 2580 : strongest = dependency; /* save new best match */
976 : }
977 : }
978 :
979 2478 : return strongest;
980 : }
981 :
982 : /*
983 : * clauselist_apply_dependencies
984 : * Apply the specified functional dependencies to a list of clauses and
985 : * return the estimated selectivity of the clauses that are compatible
986 : * with any of the given dependencies.
987 : *
988 : * This will estimate all not-already-estimated clauses that are compatible
989 : * with functional dependencies, and which have an attribute mentioned by any
990 : * of the given dependencies (either as an implying or implied attribute).
991 : *
992 : * Given (lists of) clauses on attributes (a,b) and a functional dependency
993 : * (a=>b), the per-column selectivities P(a) and P(b) are notionally combined
994 : * using the formula
995 : *
996 : * P(a,b) = f * P(a) + (1-f) * P(a) * P(b)
997 : *
998 : * where 'f' is the degree of dependency. This reflects the fact that we
999 : * expect a fraction f of all rows to be consistent with the dependency
1000 : * (a=>b), and so have a selectivity of P(a), while the remaining rows are
1001 : * treated as independent.
1002 : *
1003 : * In practice, we use a slightly modified version of this formula, which uses
1004 : * a selectivity of Min(P(a), P(b)) for the dependent rows, since the result
1005 : * should obviously not exceed either column's individual selectivity. I.e.,
1006 : * we actually combine selectivities using the formula
1007 : *
1008 : * P(a,b) = f * Min(P(a), P(b)) + (1-f) * P(a) * P(b)
1009 : *
1010 : * This can make quite a difference if the specific values matching the
1011 : * clauses are not consistent with the functional dependency.
1012 : */
1013 : static Selectivity
1014 1092 : clauselist_apply_dependencies(PlannerInfo *root, List *clauses,
1015 : int varRelid, JoinType jointype,
1016 : SpecialJoinInfo *sjinfo,
1017 : MVDependency **dependencies, int ndependencies,
1018 : AttrNumber *list_attnums,
1019 : Bitmapset **estimatedclauses)
1020 : {
1021 : Bitmapset *attnums;
1022 : int i;
1023 : int j;
1024 : int nattrs;
1025 : Selectivity *attr_sel;
1026 : int attidx;
1027 : int listidx;
1028 : ListCell *l;
1029 : Selectivity s1;
1030 :
1031 : /*
1032 : * Extract the attnums of all implying and implied attributes from all the
1033 : * given dependencies. Each of these attributes is expected to have at
1034 : * least 1 not-already-estimated compatible clause that we will estimate
1035 : * here.
1036 : */
1037 1092 : attnums = NULL;
1038 2478 : for (i = 0; i < ndependencies; i++)
1039 : {
1040 4440 : for (j = 0; j < dependencies[i]->nattributes; j++)
1041 : {
1042 3054 : AttrNumber attnum = dependencies[i]->attributes[j];
1043 :
1044 3054 : attnums = bms_add_member(attnums, attnum);
1045 : }
1046 : }
1047 :
1048 : /*
1049 : * Compute per-column selectivity estimates for each of these attributes,
1050 : * and mark all the corresponding clauses as estimated.
1051 : */
1052 1092 : nattrs = bms_num_members(attnums);
1053 1092 : attr_sel = (Selectivity *) palloc(sizeof(Selectivity) * nattrs);
1054 :
1055 1092 : attidx = 0;
1056 1092 : i = -1;
1057 3582 : while ((i = bms_next_member(attnums, i)) >= 0)
1058 : {
1059 2490 : List *attr_clauses = NIL;
1060 : Selectivity simple_sel;
1061 :
1062 2490 : listidx = -1;
1063 8412 : foreach(l, clauses)
1064 : {
1065 5922 : Node *clause = (Node *) lfirst(l);
1066 :
1067 5922 : listidx++;
1068 5922 : if (list_attnums[listidx] == i)
1069 : {
1070 2490 : attr_clauses = lappend(attr_clauses, clause);
1071 2490 : *estimatedclauses = bms_add_member(*estimatedclauses, listidx);
1072 : }
1073 : }
1074 :
1075 2490 : simple_sel = clauselist_selectivity_ext(root, attr_clauses, varRelid,
1076 : jointype, sjinfo, false);
1077 2490 : attr_sel[attidx++] = simple_sel;
1078 : }
1079 :
1080 : /*
1081 : * Now combine these selectivities using the dependency information. For
1082 : * chains of dependencies such as a -> b -> c, the b -> c dependency will
1083 : * come before the a -> b dependency in the array, so we traverse the
1084 : * array backwards to ensure such chains are computed in the right order.
1085 : *
1086 : * As explained above, pairs of selectivities are combined using the
1087 : * formula
1088 : *
1089 : * P(a,b) = f * Min(P(a), P(b)) + (1-f) * P(a) * P(b)
1090 : *
1091 : * to ensure that the combined selectivity is never greater than either
1092 : * individual selectivity.
1093 : *
1094 : * Where multiple dependencies apply (e.g., a -> b -> c), we use
1095 : * conditional probabilities to compute the overall result as follows:
1096 : *
1097 : * P(a,b,c) = P(c|a,b) * P(a,b) = P(c|a,b) * P(b|a) * P(a)
1098 : *
1099 : * so we replace the selectivities of all implied attributes with
1100 : * conditional probabilities, that are conditional on all their implying
1101 : * attributes. The selectivities of all other non-implied attributes are
1102 : * left as they are.
1103 : */
1104 2478 : for (i = ndependencies - 1; i >= 0; i--)
1105 : {
1106 1386 : MVDependency *dependency = dependencies[i];
1107 : AttrNumber attnum;
1108 : Selectivity s2;
1109 : double f;
1110 :
1111 : /* Selectivity of all the implying attributes */
1112 1386 : s1 = 1.0;
1113 3054 : for (j = 0; j < dependency->nattributes - 1; j++)
1114 : {
1115 1668 : attnum = dependency->attributes[j];
1116 1668 : attidx = bms_member_index(attnums, attnum);
1117 1668 : s1 *= attr_sel[attidx];
1118 : }
1119 :
1120 : /* Original selectivity of the implied attribute */
1121 1386 : attnum = dependency->attributes[j];
1122 1386 : attidx = bms_member_index(attnums, attnum);
1123 1386 : s2 = attr_sel[attidx];
1124 :
1125 : /*
1126 : * Replace s2 with the conditional probability s2 given s1, computed
1127 : * using the formula P(b|a) = P(a,b) / P(a), which simplifies to
1128 : *
1129 : * P(b|a) = f * Min(P(a), P(b)) / P(a) + (1-f) * P(b)
1130 : *
1131 : * where P(a) = s1, the selectivity of the implying attributes, and
1132 : * P(b) = s2, the selectivity of the implied attribute.
1133 : */
1134 1386 : f = dependency->degree;
1135 :
1136 1386 : if (s1 <= s2)
1137 1326 : attr_sel[attidx] = f + (1 - f) * s2;
1138 : else
1139 60 : attr_sel[attidx] = f * s2 / s1 + (1 - f) * s2;
1140 : }
1141 :
1142 : /*
1143 : * The overall selectivity of all the clauses on all these attributes is
1144 : * then the product of all the original (non-implied) probabilities and
1145 : * the new conditional (implied) probabilities.
1146 : */
1147 1092 : s1 = 1.0;
1148 3582 : for (i = 0; i < nattrs; i++)
1149 2490 : s1 *= attr_sel[i];
1150 :
1151 1092 : CLAMP_PROBABILITY(s1);
1152 :
1153 1092 : pfree(attr_sel);
1154 1092 : bms_free(attnums);
1155 :
1156 1092 : return s1;
1157 : }
1158 :
1159 : /*
1160 : * dependency_is_compatible_expression
1161 : * Determines if the expression is compatible with functional dependencies
1162 : *
1163 : * Similar to dependency_is_compatible_clause, but doesn't enforce that the
1164 : * expression is a simple Var. On success, return the matching statistics
1165 : * expression into *expr.
1166 : */
1167 : static bool
1168 642 : dependency_is_compatible_expression(Node *clause, Index relid, List *statlist, Node **expr)
1169 : {
1170 : ListCell *lc,
1171 : *lc2;
1172 : Node *clause_expr;
1173 :
1174 642 : if (IsA(clause, RestrictInfo))
1175 : {
1176 552 : RestrictInfo *rinfo = (RestrictInfo *) clause;
1177 :
1178 : /* Pseudoconstants are not interesting (they couldn't contain a Var) */
1179 552 : if (rinfo->pseudoconstant)
1180 6 : return false;
1181 :
1182 : /* Clauses referencing multiple, or no, varnos are incompatible */
1183 546 : if (bms_membership(rinfo->clause_relids) != BMS_SINGLETON)
1184 0 : return false;
1185 :
1186 546 : clause = (Node *) rinfo->clause;
1187 : }
1188 :
1189 636 : if (is_opclause(clause))
1190 : {
1191 : /* If it's an opclause, check for Var = Const or Const = Var. */
1192 204 : OpExpr *expr = (OpExpr *) clause;
1193 :
1194 : /* Only expressions with two arguments are candidates. */
1195 204 : if (list_length(expr->args) != 2)
1196 0 : return false;
1197 :
1198 : /* Make sure non-selected argument is a pseudoconstant. */
1199 204 : if (is_pseudo_constant_clause(lsecond(expr->args)))
1200 204 : clause_expr = linitial(expr->args);
1201 0 : else if (is_pseudo_constant_clause(linitial(expr->args)))
1202 0 : clause_expr = lsecond(expr->args);
1203 : else
1204 0 : return false;
1205 :
1206 : /*
1207 : * If it's not an "=" operator, just ignore the clause, as it's not
1208 : * compatible with functional dependencies.
1209 : *
1210 : * This uses the function for estimating selectivity, not the operator
1211 : * directly (a bit awkward, but well ...).
1212 : *
1213 : * XXX this is pretty dubious; probably it'd be better to check btree
1214 : * or hash opclass membership, so as not to be fooled by custom
1215 : * selectivity functions, and to be more consistent with decisions
1216 : * elsewhere in the planner.
1217 : */
1218 204 : if (get_oprrest(expr->opno) != F_EQSEL)
1219 36 : return false;
1220 :
1221 : /* OK to proceed with checking "var" */
1222 : }
1223 432 : else if (IsA(clause, ScalarArrayOpExpr))
1224 : {
1225 : /* If it's a scalar array operator, check for Var IN Const. */
1226 390 : ScalarArrayOpExpr *expr = (ScalarArrayOpExpr *) clause;
1227 :
1228 : /*
1229 : * Reject ALL() variant, we only care about ANY/IN.
1230 : *
1231 : * FIXME Maybe we should check if all the values are the same, and
1232 : * allow ALL in that case? Doesn't seem very practical, though.
1233 : */
1234 390 : if (!expr->useOr)
1235 36 : return false;
1236 :
1237 : /* Only expressions with two arguments are candidates. */
1238 354 : if (list_length(expr->args) != 2)
1239 0 : return false;
1240 :
1241 : /*
1242 : * We know it's always (Var IN Const), so we assume the var is the
1243 : * first argument, and pseudoconstant is the second one.
1244 : */
1245 354 : if (!is_pseudo_constant_clause(lsecond(expr->args)))
1246 0 : return false;
1247 :
1248 354 : clause_expr = linitial(expr->args);
1249 :
1250 : /*
1251 : * If it's not an "=" operator, just ignore the clause, as it's not
1252 : * compatible with functional dependencies. The operator is identified
1253 : * simply by looking at which function it uses to estimate
1254 : * selectivity. That's a bit strange, but it's what other similar
1255 : * places do.
1256 : */
1257 354 : if (get_oprrest(expr->opno) != F_EQSEL)
1258 180 : return false;
1259 :
1260 : /* OK to proceed with checking "var" */
1261 : }
1262 42 : else if (is_orclause(clause))
1263 : {
1264 42 : BoolExpr *bool_expr = (BoolExpr *) clause;
1265 :
1266 : /* start with no expression (we'll use the first match) */
1267 42 : *expr = NULL;
1268 :
1269 120 : foreach(lc, bool_expr->args)
1270 : {
1271 90 : Node *or_expr = NULL;
1272 :
1273 : /*
1274 : * Had we found incompatible expression in the arguments, treat
1275 : * the whole expression as incompatible.
1276 : */
1277 90 : if (!dependency_is_compatible_expression((Node *) lfirst(lc), relid,
1278 : statlist, &or_expr))
1279 12 : return false;
1280 :
1281 84 : if (*expr == NULL)
1282 36 : *expr = or_expr;
1283 :
1284 : /* ensure all the expressions are the same */
1285 84 : if (!equal(or_expr, *expr))
1286 6 : return false;
1287 : }
1288 :
1289 : /* the expression is already checked by the recursive call */
1290 30 : return true;
1291 : }
1292 0 : else if (is_notclause(clause))
1293 : {
1294 : /*
1295 : * "NOT x" can be interpreted as "x = false", so get the argument and
1296 : * proceed with seeing if it's a suitable Var.
1297 : */
1298 0 : clause_expr = (Node *) get_notclausearg(clause);
1299 : }
1300 : else
1301 : {
1302 : /*
1303 : * A boolean expression "x" can be interpreted as "x = true", so
1304 : * proceed with seeing if it's a suitable Var.
1305 : */
1306 0 : clause_expr = (Node *) clause;
1307 : }
1308 :
1309 : /*
1310 : * We may ignore any RelabelType node above the operand. (There won't be
1311 : * more than one, since eval_const_expressions has been applied already.)
1312 : */
1313 342 : if (IsA(clause_expr, RelabelType))
1314 0 : clause_expr = (Node *) ((RelabelType *) clause_expr)->arg;
1315 :
1316 : /*
1317 : * Search for a matching statistics expression.
1318 : */
1319 348 : foreach(lc, statlist)
1320 : {
1321 342 : StatisticExtInfo *info = (StatisticExtInfo *) lfirst(lc);
1322 :
1323 : /* ignore stats without dependencies */
1324 342 : if (info->kind != STATS_EXT_DEPENDENCIES)
1325 0 : continue;
1326 :
1327 558 : foreach(lc2, info->exprs)
1328 : {
1329 552 : Node *stat_expr = (Node *) lfirst(lc2);
1330 :
1331 552 : if (equal(clause_expr, stat_expr))
1332 : {
1333 336 : *expr = stat_expr;
1334 336 : return true;
1335 : }
1336 : }
1337 : }
1338 :
1339 6 : return false;
1340 : }
1341 :
1342 : /*
1343 : * dependencies_clauselist_selectivity
1344 : * Return the estimated selectivity of (a subset of) the given clauses
1345 : * using functional dependency statistics, or 1.0 if no useful functional
1346 : * dependency statistic exists.
1347 : *
1348 : * 'estimatedclauses' is an input/output argument that gets a bit set
1349 : * corresponding to the (zero-based) list index of each clause that is included
1350 : * in the estimated selectivity.
1351 : *
1352 : * Given equality clauses on attributes (a,b) we find the strongest dependency
1353 : * between them, i.e. either (a=>b) or (b=>a). Assuming (a=>b) is the selected
1354 : * dependency, we then combine the per-clause selectivities using the formula
1355 : *
1356 : * P(a,b) = f * P(a) + (1-f) * P(a) * P(b)
1357 : *
1358 : * where 'f' is the degree of the dependency. (Actually we use a slightly
1359 : * modified version of this formula -- see clauselist_apply_dependencies()).
1360 : *
1361 : * With clauses on more than two attributes, the dependencies are applied
1362 : * recursively, starting with the widest/strongest dependencies. For example
1363 : * P(a,b,c) is first split like this:
1364 : *
1365 : * P(a,b,c) = f * P(a,b) + (1-f) * P(a,b) * P(c)
1366 : *
1367 : * assuming (a,b=>c) is the strongest dependency.
1368 : */
1369 : Selectivity
1370 1734 : dependencies_clauselist_selectivity(PlannerInfo *root,
1371 : List *clauses,
1372 : int varRelid,
1373 : JoinType jointype,
1374 : SpecialJoinInfo *sjinfo,
1375 : RelOptInfo *rel,
1376 : Bitmapset **estimatedclauses)
1377 : {
1378 1734 : Selectivity s1 = 1.0;
1379 : ListCell *l;
1380 1734 : Bitmapset *clauses_attnums = NULL;
1381 : AttrNumber *list_attnums;
1382 : int listidx;
1383 : MVDependencies **func_dependencies;
1384 : int nfunc_dependencies;
1385 : int total_ndeps;
1386 : MVDependency **dependencies;
1387 : int ndependencies;
1388 : int i;
1389 : AttrNumber attnum_offset;
1390 1734 : RangeTblEntry *rte = planner_rt_fetch(rel->relid, root);
1391 :
1392 : /* unique expressions */
1393 : Node **unique_exprs;
1394 : int unique_exprs_cnt;
1395 :
1396 : /* check if there's any stats that might be useful for us. */
1397 1734 : if (!has_stats_of_kind(rel->statlist, STATS_EXT_DEPENDENCIES))
1398 450 : return 1.0;
1399 :
1400 1284 : list_attnums = (AttrNumber *) palloc(sizeof(AttrNumber) *
1401 1284 : list_length(clauses));
1402 :
1403 : /*
1404 : * We allocate space as if every clause was a unique expression, although
1405 : * that's probably overkill. Some will be simple column references that
1406 : * we'll translate to attnums, and there might be duplicates. But it's
1407 : * easier and cheaper to just do one allocation than repalloc later.
1408 : */
1409 1284 : unique_exprs = (Node **) palloc(sizeof(Node *) * list_length(clauses));
1410 1284 : unique_exprs_cnt = 0;
1411 :
1412 : /*
1413 : * Pre-process the clauses list to extract the attnums seen in each item.
1414 : * We need to determine if there's any clauses which will be useful for
1415 : * dependency selectivity estimations. Along the way we'll record all of
1416 : * the attnums for each clause in a list which we'll reference later so we
1417 : * don't need to repeat the same work again. We'll also keep track of all
1418 : * attnums seen.
1419 : *
1420 : * We also skip clauses that we already estimated using different types of
1421 : * statistics (we treat them as incompatible).
1422 : *
1423 : * To handle expressions, we assign them negative attnums, as if it was a
1424 : * system attribute (this is fine, as we only allow extended stats on user
1425 : * attributes). And then we offset everything by the number of
1426 : * expressions, so that we can store the values in a bitmapset.
1427 : */
1428 1284 : listidx = 0;
1429 4158 : foreach(l, clauses)
1430 : {
1431 2874 : Node *clause = (Node *) lfirst(l);
1432 : AttrNumber attnum;
1433 2874 : Node *expr = NULL;
1434 :
1435 : /* ignore clause by default */
1436 2874 : list_attnums[listidx] = InvalidAttrNumber;
1437 :
1438 2874 : if (!bms_is_member(listidx, *estimatedclauses))
1439 : {
1440 : /*
1441 : * If it's a simple column reference, just extract the attnum. If
1442 : * it's an expression, assign a negative attnum as if it was a
1443 : * system attribute.
1444 : */
1445 2832 : if (dependency_is_compatible_clause(clause, rel->relid, &attnum))
1446 : {
1447 2280 : list_attnums[listidx] = attnum;
1448 : }
1449 552 : else if (dependency_is_compatible_expression(clause, rel->relid,
1450 : rel->statlist,
1451 : &expr))
1452 : {
1453 : /* special attnum assigned to this expression */
1454 282 : attnum = InvalidAttrNumber;
1455 :
1456 : Assert(expr != NULL);
1457 :
1458 : /* If the expression is duplicate, use the same attnum. */
1459 474 : for (i = 0; i < unique_exprs_cnt; i++)
1460 : {
1461 192 : if (equal(unique_exprs[i], expr))
1462 : {
1463 : /* negative attribute number to expression */
1464 0 : attnum = -(i + 1);
1465 0 : break;
1466 : }
1467 : }
1468 :
1469 : /* not found in the list, so add it */
1470 282 : if (attnum == InvalidAttrNumber)
1471 : {
1472 282 : unique_exprs[unique_exprs_cnt++] = expr;
1473 :
1474 : /* after incrementing the value, to get -1, -2, ... */
1475 282 : attnum = (-unique_exprs_cnt);
1476 : }
1477 :
1478 : /* remember which attnum was assigned to this clause */
1479 282 : list_attnums[listidx] = attnum;
1480 : }
1481 : }
1482 :
1483 2874 : listidx++;
1484 : }
1485 :
1486 : Assert(listidx == list_length(clauses));
1487 :
1488 : /*
1489 : * How much we need to offset the attnums? If there are no expressions,
1490 : * then no offset is needed. Otherwise we need to offset enough for the
1491 : * lowest value (-unique_exprs_cnt) to become 1.
1492 : */
1493 1284 : if (unique_exprs_cnt > 0)
1494 132 : attnum_offset = (unique_exprs_cnt + 1);
1495 : else
1496 1152 : attnum_offset = 0;
1497 :
1498 : /*
1499 : * Now that we know how many expressions there are, we can offset the
1500 : * values just enough to build the bitmapset.
1501 : */
1502 4158 : for (i = 0; i < list_length(clauses); i++)
1503 : {
1504 : AttrNumber attnum;
1505 :
1506 : /* ignore incompatible or already estimated clauses */
1507 2874 : if (list_attnums[i] == InvalidAttrNumber)
1508 312 : continue;
1509 :
1510 : /* make sure the attnum is in the expected range */
1511 : Assert(list_attnums[i] >= (-unique_exprs_cnt));
1512 : Assert(list_attnums[i] <= MaxHeapAttributeNumber);
1513 :
1514 : /* make sure the attnum is positive (valid AttrNumber) */
1515 2562 : attnum = list_attnums[i] + attnum_offset;
1516 :
1517 : /*
1518 : * Either it's a regular attribute, or it's an expression, in which
1519 : * case we must not have seen it before (expressions are unique).
1520 : *
1521 : * XXX Check whether it's a regular attribute has to be done using the
1522 : * original attnum, while the second check has to use the value with
1523 : * an offset.
1524 : */
1525 : Assert(AttrNumberIsForUserDefinedAttr(list_attnums[i]) ||
1526 : !bms_is_member(attnum, clauses_attnums));
1527 :
1528 : /*
1529 : * Remember the offset attnum, both for attributes and expressions.
1530 : * We'll pass list_attnums to clauselist_apply_dependencies, which
1531 : * uses it to identify clauses in a bitmap. We could also pass the
1532 : * offset, but this is more convenient.
1533 : */
1534 2562 : list_attnums[i] = attnum;
1535 :
1536 2562 : clauses_attnums = bms_add_member(clauses_attnums, attnum);
1537 : }
1538 :
1539 : /*
1540 : * If there's not at least two distinct attnums and expressions, then
1541 : * reject the whole list of clauses. We must return 1.0 so the calling
1542 : * function's selectivity is unaffected.
1543 : */
1544 1284 : if (bms_membership(clauses_attnums) != BMS_MULTIPLE)
1545 : {
1546 192 : bms_free(clauses_attnums);
1547 192 : pfree(list_attnums);
1548 192 : return 1.0;
1549 : }
1550 :
1551 : /*
1552 : * Load all functional dependencies matching at least two parameters. We
1553 : * can simply consider all dependencies at once, without having to search
1554 : * for the best statistics object.
1555 : *
1556 : * To not waste cycles and memory, we deserialize dependencies only for
1557 : * statistics that match at least two attributes. The array is allocated
1558 : * with the assumption that all objects match - we could grow the array to
1559 : * make it just the right size, but it's likely wasteful anyway thanks to
1560 : * moving the freed chunks to freelists etc.
1561 : */
1562 1092 : func_dependencies = (MVDependencies **) palloc(sizeof(MVDependencies *) *
1563 1092 : list_length(rel->statlist));
1564 1092 : nfunc_dependencies = 0;
1565 1092 : total_ndeps = 0;
1566 :
1567 2322 : foreach(l, rel->statlist)
1568 : {
1569 1230 : StatisticExtInfo *stat = (StatisticExtInfo *) lfirst(l);
1570 : int nmatched;
1571 : int nexprs;
1572 : int k;
1573 : MVDependencies *deps;
1574 :
1575 : /* skip statistics that are not of the correct type */
1576 1230 : if (stat->kind != STATS_EXT_DEPENDENCIES)
1577 108 : continue;
1578 :
1579 : /* skip statistics with mismatching stxdinherit value */
1580 1122 : if (stat->inherit != rte->inh)
1581 0 : continue;
1582 :
1583 : /*
1584 : * Count matching attributes - we have to undo the attnum offsets. The
1585 : * input attribute numbers are not offset (expressions are not
1586 : * included in stat->keys, so it's not necessary). But we need to
1587 : * offset it before checking against clauses_attnums.
1588 : */
1589 1122 : nmatched = 0;
1590 1122 : k = -1;
1591 4104 : while ((k = bms_next_member(stat->keys, k)) >= 0)
1592 : {
1593 2982 : AttrNumber attnum = (AttrNumber) k;
1594 :
1595 : /* skip expressions */
1596 2982 : if (!AttrNumberIsForUserDefinedAttr(attnum))
1597 0 : continue;
1598 :
1599 : /* apply the same offset as above */
1600 2982 : attnum += attnum_offset;
1601 :
1602 2982 : if (bms_is_member(attnum, clauses_attnums))
1603 2232 : nmatched++;
1604 : }
1605 :
1606 : /* count matching expressions */
1607 1122 : nexprs = 0;
1608 1380 : for (i = 0; i < unique_exprs_cnt; i++)
1609 : {
1610 : ListCell *lc;
1611 :
1612 1032 : foreach(lc, stat->exprs)
1613 : {
1614 774 : Node *stat_expr = (Node *) lfirst(lc);
1615 :
1616 : /* try to match it */
1617 774 : if (equal(stat_expr, unique_exprs[i]))
1618 258 : nexprs++;
1619 : }
1620 : }
1621 :
1622 : /*
1623 : * Skip objects matching fewer than two attributes/expressions from
1624 : * clauses.
1625 : */
1626 1122 : if (nmatched + nexprs < 2)
1627 18 : continue;
1628 :
1629 1104 : deps = statext_dependencies_load(stat->statOid, rte->inh);
1630 :
1631 : /*
1632 : * The expressions may be represented by different attnums in the
1633 : * stats, we need to remap them to be consistent with the clauses.
1634 : * That will make the later steps (e.g. picking the strongest item and
1635 : * so on) much simpler and cheaper, because it won't need to care
1636 : * about the offset at all.
1637 : *
1638 : * When we're at it, we can ignore dependencies that are not fully
1639 : * matched by clauses (i.e. referencing attributes or expressions that
1640 : * are not in the clauses).
1641 : *
1642 : * We have to do this for all statistics, as long as there are any
1643 : * expressions - we need to shift the attnums in all dependencies.
1644 : *
1645 : * XXX Maybe we should do this always, because it also eliminates some
1646 : * of the dependencies early. It might be cheaper than having to walk
1647 : * the longer list in find_strongest_dependency later, especially as
1648 : * we need to do that repeatedly?
1649 : *
1650 : * XXX We have to do this even when there are no expressions in
1651 : * clauses, otherwise find_strongest_dependency may fail for stats
1652 : * with expressions (due to lookup of negative value in bitmap). So we
1653 : * need to at least filter out those dependencies. Maybe we could do
1654 : * it in a cheaper way (if there are no expr clauses, we can just
1655 : * discard all negative attnums without any lookups).
1656 : */
1657 1104 : if (unique_exprs_cnt > 0 || stat->exprs != NIL)
1658 : {
1659 108 : int ndeps = 0;
1660 :
1661 648 : for (i = 0; i < deps->ndeps; i++)
1662 : {
1663 540 : bool skip = false;
1664 540 : MVDependency *dep = deps->deps[i];
1665 : int j;
1666 :
1667 1506 : for (j = 0; j < dep->nattributes; j++)
1668 : {
1669 : int idx;
1670 : Node *expr;
1671 1230 : AttrNumber unique_attnum = InvalidAttrNumber;
1672 : AttrNumber attnum;
1673 :
1674 : /* undo the per-statistics offset */
1675 1230 : attnum = dep->attributes[j];
1676 :
1677 : /*
1678 : * For regular attributes we can simply check if it
1679 : * matches any clause. If there's no matching clause, we
1680 : * can just ignore it. We need to offset the attnum
1681 : * though.
1682 : */
1683 1230 : if (AttrNumberIsForUserDefinedAttr(attnum))
1684 : {
1685 0 : dep->attributes[j] = attnum + attnum_offset;
1686 :
1687 0 : if (!bms_is_member(dep->attributes[j], clauses_attnums))
1688 : {
1689 0 : skip = true;
1690 0 : break;
1691 : }
1692 :
1693 0 : continue;
1694 : }
1695 :
1696 : /*
1697 : * the attnum should be a valid system attnum (-1, -2,
1698 : * ...)
1699 : */
1700 : Assert(AttributeNumberIsValid(attnum));
1701 :
1702 : /*
1703 : * For expressions, we need to do two translations. First
1704 : * we have to translate the negative attnum to index in
1705 : * the list of expressions (in the statistics object).
1706 : * Then we need to see if there's a matching clause. The
1707 : * index of the unique expression determines the attnum
1708 : * (and we offset it).
1709 : */
1710 1230 : idx = -(1 + attnum);
1711 :
1712 : /* Is the expression index is valid? */
1713 : Assert((idx >= 0) && (idx < list_length(stat->exprs)));
1714 :
1715 1230 : expr = (Node *) list_nth(stat->exprs, idx);
1716 :
1717 : /* try to find the expression in the unique list */
1718 2460 : for (int m = 0; m < unique_exprs_cnt; m++)
1719 : {
1720 : /*
1721 : * found a matching unique expression, use the attnum
1722 : * (derived from index of the unique expression)
1723 : */
1724 2196 : if (equal(unique_exprs[m], expr))
1725 : {
1726 966 : unique_attnum = -(m + 1) + attnum_offset;
1727 966 : break;
1728 : }
1729 : }
1730 :
1731 : /*
1732 : * Found no matching expression, so we can simply skip
1733 : * this dependency, because there's no chance it will be
1734 : * fully covered.
1735 : */
1736 1230 : if (unique_attnum == InvalidAttrNumber)
1737 : {
1738 264 : skip = true;
1739 264 : break;
1740 : }
1741 :
1742 : /* otherwise remap it to the new attnum */
1743 966 : dep->attributes[j] = unique_attnum;
1744 : }
1745 :
1746 : /* if found a matching dependency, keep it */
1747 540 : if (!skip)
1748 : {
1749 : /* maybe we've skipped something earlier, so move it */
1750 276 : if (ndeps != i)
1751 0 : deps->deps[ndeps] = deps->deps[i];
1752 :
1753 276 : ndeps++;
1754 : }
1755 : }
1756 :
1757 108 : deps->ndeps = ndeps;
1758 : }
1759 :
1760 : /*
1761 : * It's possible we've removed all dependencies, in which case we
1762 : * don't bother adding it to the list.
1763 : */
1764 1104 : if (deps->ndeps > 0)
1765 : {
1766 1104 : func_dependencies[nfunc_dependencies] = deps;
1767 1104 : total_ndeps += deps->ndeps;
1768 1104 : nfunc_dependencies++;
1769 : }
1770 : }
1771 :
1772 : /* if no matching stats could be found then we've nothing to do */
1773 1092 : if (nfunc_dependencies == 0)
1774 : {
1775 0 : pfree(func_dependencies);
1776 0 : bms_free(clauses_attnums);
1777 0 : pfree(list_attnums);
1778 0 : pfree(unique_exprs);
1779 0 : return 1.0;
1780 : }
1781 :
1782 : /*
1783 : * Work out which dependencies we can apply, starting with the
1784 : * widest/strongest ones, and proceeding to smaller/weaker ones.
1785 : */
1786 1092 : dependencies = (MVDependency **) palloc(sizeof(MVDependency *) *
1787 : total_ndeps);
1788 1092 : ndependencies = 0;
1789 :
1790 : while (true)
1791 1386 : {
1792 : MVDependency *dependency;
1793 : AttrNumber attnum;
1794 :
1795 : /* the widest/strongest dependency, fully matched by clauses */
1796 2478 : dependency = find_strongest_dependency(func_dependencies,
1797 : nfunc_dependencies,
1798 : clauses_attnums);
1799 2478 : if (!dependency)
1800 1092 : break;
1801 :
1802 1386 : dependencies[ndependencies++] = dependency;
1803 :
1804 : /* Ignore dependencies using this implied attribute in later loops */
1805 1386 : attnum = dependency->attributes[dependency->nattributes - 1];
1806 1386 : clauses_attnums = bms_del_member(clauses_attnums, attnum);
1807 : }
1808 :
1809 : /*
1810 : * If we found applicable dependencies, use them to estimate all
1811 : * compatible clauses on attributes that they refer to.
1812 : */
1813 1092 : if (ndependencies != 0)
1814 1092 : s1 = clauselist_apply_dependencies(root, clauses, varRelid, jointype,
1815 : sjinfo, dependencies, ndependencies,
1816 : list_attnums, estimatedclauses);
1817 :
1818 : /* free deserialized functional dependencies (and then the array) */
1819 2196 : for (i = 0; i < nfunc_dependencies; i++)
1820 1104 : pfree(func_dependencies[i]);
1821 :
1822 1092 : pfree(dependencies);
1823 1092 : pfree(func_dependencies);
1824 1092 : bms_free(clauses_attnums);
1825 1092 : pfree(list_attnums);
1826 1092 : pfree(unique_exprs);
1827 :
1828 1092 : return s1;
1829 : }
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