1102 lines
31 KiB
C
1102 lines
31 KiB
C
/*-------------------------------------------------------------------------
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*
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* dependencies.c
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* POSTGRES functional dependencies
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*
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* Portions Copyright (c) 1996-2019, PostgreSQL Global Development Group
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* Portions Copyright (c) 1994, Regents of the University of California
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*
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* IDENTIFICATION
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* src/backend/statistics/dependencies.c
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*
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*-------------------------------------------------------------------------
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*/
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#include "postgres.h"
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#include "access/htup_details.h"
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#include "access/sysattr.h"
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#include "catalog/pg_operator.h"
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#include "catalog/pg_statistic_ext.h"
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#include "lib/stringinfo.h"
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#include "nodes/nodeFuncs.h"
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#include "optimizer/clauses.h"
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#include "optimizer/optimizer.h"
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#include "nodes/nodes.h"
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#include "nodes/pathnodes.h"
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#include "statistics/extended_stats_internal.h"
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#include "statistics/statistics.h"
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#include "utils/bytea.h"
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#include "utils/fmgroids.h"
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#include "utils/fmgrprotos.h"
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#include "utils/lsyscache.h"
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#include "utils/syscache.h"
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#include "utils/typcache.h"
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/* size of the struct header fields (magic, type, ndeps) */
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#define SizeOfHeader (3 * sizeof(uint32))
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/* size of a serialized dependency (degree, natts, atts) */
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#define SizeOfItem(natts) \
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(sizeof(double) + sizeof(AttrNumber) * (1 + (natts)))
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/* minimal size of a dependency (with two attributes) */
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#define MinSizeOfItem SizeOfItem(2)
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/* minimal size of dependencies, when all deps are minimal */
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#define MinSizeOfItems(ndeps) \
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(SizeOfHeader + (ndeps) * MinSizeOfItem)
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/*
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* Internal state for DependencyGenerator of dependencies. Dependencies are similar to
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* k-permutations of n elements, except that the order does not matter for the
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* first (k-1) elements. That is, (a,b=>c) and (b,a=>c) are equivalent.
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*/
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typedef struct DependencyGeneratorData
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{
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int k; /* size of the dependency */
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int n; /* number of possible attributes */
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int current; /* next dependency to return (index) */
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AttrNumber ndependencies; /* number of dependencies generated */
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AttrNumber *dependencies; /* array of pre-generated dependencies */
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} DependencyGeneratorData;
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typedef DependencyGeneratorData *DependencyGenerator;
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static void generate_dependencies_recurse(DependencyGenerator state,
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int index, AttrNumber start, AttrNumber *current);
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static void generate_dependencies(DependencyGenerator state);
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static DependencyGenerator DependencyGenerator_init(int n, int k);
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static void DependencyGenerator_free(DependencyGenerator state);
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static AttrNumber *DependencyGenerator_next(DependencyGenerator state);
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static double dependency_degree(int numrows, HeapTuple *rows, int k,
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AttrNumber *dependency, VacAttrStats **stats, Bitmapset *attrs);
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static bool dependency_is_fully_matched(MVDependency *dependency,
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Bitmapset *attnums);
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static bool dependency_implies_attribute(MVDependency *dependency,
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AttrNumber attnum);
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static bool dependency_is_compatible_clause(Node *clause, Index relid,
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AttrNumber *attnum);
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static MVDependency *find_strongest_dependency(StatisticExtInfo *stats,
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MVDependencies *dependencies,
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Bitmapset *attnums);
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static void
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generate_dependencies_recurse(DependencyGenerator state, int index,
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AttrNumber start, AttrNumber *current)
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{
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/*
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* The generator handles the first (k-1) elements differently from the
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* last element.
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*/
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if (index < (state->k - 1))
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{
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AttrNumber i;
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/*
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* The first (k-1) values have to be in ascending order, which we
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* generate recursively.
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*/
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for (i = start; i < state->n; i++)
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{
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current[index] = i;
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generate_dependencies_recurse(state, (index + 1), (i + 1), current);
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}
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}
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else
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{
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int i;
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/*
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* the last element is the implied value, which does not respect the
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* ascending order. We just need to check that the value is not in the
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* first (k-1) elements.
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*/
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for (i = 0; i < state->n; i++)
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{
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int j;
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bool match = false;
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current[index] = i;
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for (j = 0; j < index; j++)
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{
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if (current[j] == i)
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{
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match = true;
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break;
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}
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}
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/*
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* If the value is not found in the first part of the dependency,
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* we're done.
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*/
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if (!match)
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{
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state->dependencies = (AttrNumber *) repalloc(state->dependencies,
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state->k * (state->ndependencies + 1) * sizeof(AttrNumber));
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memcpy(&state->dependencies[(state->k * state->ndependencies)],
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current, state->k * sizeof(AttrNumber));
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state->ndependencies++;
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}
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}
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}
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}
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/* generate all dependencies (k-permutations of n elements) */
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static void
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generate_dependencies(DependencyGenerator state)
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{
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AttrNumber *current = (AttrNumber *) palloc0(sizeof(AttrNumber) * state->k);
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generate_dependencies_recurse(state, 0, 0, current);
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pfree(current);
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}
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/*
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* initialize the DependencyGenerator of variations, and prebuild the variations
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*
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* This pre-builds all the variations. We could also generate them in
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* DependencyGenerator_next(), but this seems simpler.
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*/
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static DependencyGenerator
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DependencyGenerator_init(int n, int k)
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{
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DependencyGenerator state;
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Assert((n >= k) && (k > 0));
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/* allocate the DependencyGenerator state */
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state = (DependencyGenerator) palloc0(sizeof(DependencyGeneratorData));
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state->dependencies = (AttrNumber *) palloc(k * sizeof(AttrNumber));
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state->ndependencies = 0;
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state->current = 0;
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state->k = k;
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state->n = n;
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/* now actually pre-generate all the variations */
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generate_dependencies(state);
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return state;
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}
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/* free the DependencyGenerator state */
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static void
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DependencyGenerator_free(DependencyGenerator state)
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{
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pfree(state->dependencies);
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pfree(state);
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}
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/* generate next combination */
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static AttrNumber *
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DependencyGenerator_next(DependencyGenerator state)
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{
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if (state->current == state->ndependencies)
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return NULL;
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return &state->dependencies[state->k * state->current++];
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}
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/*
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* validates functional dependency on the data
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*
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* An actual work horse of detecting functional dependencies. Given a variation
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* of k attributes, it checks that the first (k-1) are sufficient to determine
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* the last one.
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*/
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static double
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dependency_degree(int numrows, HeapTuple *rows, int k, AttrNumber *dependency,
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VacAttrStats **stats, Bitmapset *attrs)
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{
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int i,
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nitems;
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MultiSortSupport mss;
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SortItem *items;
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AttrNumber *attnums;
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AttrNumber *attnums_dep;
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int numattrs;
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/* counters valid within a group */
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int group_size = 0;
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int n_violations = 0;
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/* total number of rows supporting (consistent with) the dependency */
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int n_supporting_rows = 0;
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/* Make sure we have at least two input attributes. */
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Assert(k >= 2);
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/* sort info for all attributes columns */
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mss = multi_sort_init(k);
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/*
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* Transform the attrs from bitmap to an array to make accessing the i-th
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* member easier, and then construct a filtered version with only attnums
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* referenced by the dependency we validate.
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*/
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attnums = build_attnums_array(attrs, &numattrs);
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attnums_dep = (AttrNumber *) palloc(k * sizeof(AttrNumber));
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for (i = 0; i < k; i++)
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attnums_dep[i] = attnums[dependency[i]];
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/*
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* Verify the dependency (a,b,...)->z, using a rather simple algorithm:
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*
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* (a) sort the data lexicographically
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*
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* (b) split the data into groups by first (k-1) columns
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*
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* (c) for each group count different values in the last column
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*
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* We use the column data types' default sort operators and collations;
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* perhaps at some point it'd be worth using column-specific collations?
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*/
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/* prepare the sort function for the dimensions */
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for (i = 0; i < k; i++)
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{
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VacAttrStats *colstat = stats[dependency[i]];
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TypeCacheEntry *type;
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type = lookup_type_cache(colstat->attrtypid, TYPECACHE_LT_OPR);
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if (type->lt_opr == InvalidOid) /* shouldn't happen */
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elog(ERROR, "cache lookup failed for ordering operator for type %u",
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colstat->attrtypid);
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/* prepare the sort function for this dimension */
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multi_sort_add_dimension(mss, i, type->lt_opr, type->typcollation);
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}
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/*
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* build an array of SortItem(s) sorted using the multi-sort support
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*
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* XXX This relies on all stats entries pointing to the same tuple
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* descriptor. For now that assumption holds, but it might change in the
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* future for example if we support statistics on multiple tables.
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*/
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items = build_sorted_items(numrows, &nitems, rows, stats[0]->tupDesc,
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mss, k, attnums_dep);
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/*
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* Walk through the sorted array, split it into rows according to the
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* first (k-1) columns. If there's a single value in the last column, we
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* count the group as 'supporting' the functional dependency. Otherwise we
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* count it as contradicting.
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*/
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/* start with the first row forming a group */
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group_size = 1;
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/* loop 1 beyond the end of the array so that we count the final group */
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for (i = 1; i <= nitems; i++)
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{
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/*
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* Check if the group ended, which may be either because we processed
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* all the items (i==nitems), or because the i-th item is not equal to
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* the preceding one.
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*/
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if (i == nitems ||
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multi_sort_compare_dims(0, k - 2, &items[i - 1], &items[i], mss) != 0)
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{
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/*
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* If no violations were found in the group then track the rows of
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* the group as supporting the functional dependency.
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*/
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if (n_violations == 0)
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n_supporting_rows += group_size;
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/* Reset counters for the new group */
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n_violations = 0;
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group_size = 1;
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continue;
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}
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/* first columns match, but the last one does not (so contradicting) */
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else if (multi_sort_compare_dim(k - 1, &items[i - 1], &items[i], mss) != 0)
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n_violations++;
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group_size++;
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}
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if (items)
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pfree(items);
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pfree(mss);
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pfree(attnums);
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pfree(attnums_dep);
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/* Compute the 'degree of validity' as (supporting/total). */
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return (n_supporting_rows * 1.0 / numrows);
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}
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/*
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* detects functional dependencies between groups of columns
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*
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* Generates all possible subsets of columns (variations) and computes
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* the degree of validity for each one. For example when creating statistics
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* on three columns (a,b,c) there are 9 possible dependencies
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*
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* two columns three columns
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* ----------- -------------
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* (a) -> b (a,b) -> c
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* (a) -> c (a,c) -> b
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* (b) -> a (b,c) -> a
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* (b) -> c
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* (c) -> a
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* (c) -> b
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*/
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MVDependencies *
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statext_dependencies_build(int numrows, HeapTuple *rows, Bitmapset *attrs,
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VacAttrStats **stats)
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{
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int i,
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k;
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int numattrs;
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AttrNumber *attnums;
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/* result */
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MVDependencies *dependencies = NULL;
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/*
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* Transform the bms into an array, to make accessing i-th member easier.
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*/
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attnums = build_attnums_array(attrs, &numattrs);
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Assert(numattrs >= 2);
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/*
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* We'll try build functional dependencies starting from the smallest ones
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* covering just 2 columns, to the largest ones, covering all columns
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* included in the statistics object. We start from the smallest ones
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* because we want to be able to skip already implied ones.
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*/
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for (k = 2; k <= numattrs; k++)
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{
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AttrNumber *dependency; /* array with k elements */
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/* prepare a DependencyGenerator of variation */
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DependencyGenerator DependencyGenerator = DependencyGenerator_init(numattrs, k);
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/* generate all possible variations of k values (out of n) */
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while ((dependency = DependencyGenerator_next(DependencyGenerator)))
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{
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double degree;
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MVDependency *d;
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/* compute how valid the dependency seems */
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degree = dependency_degree(numrows, rows, k, dependency, stats, attrs);
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/*
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* if the dependency seems entirely invalid, don't store it
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*/
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if (degree == 0.0)
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continue;
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d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
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+ k * sizeof(AttrNumber));
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/* copy the dependency (and keep the indexes into stxkeys) */
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d->degree = degree;
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d->nattributes = k;
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for (i = 0; i < k; i++)
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d->attributes[i] = attnums[dependency[i]];
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/* initialize the list of dependencies */
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if (dependencies == NULL)
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{
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dependencies
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= (MVDependencies *) palloc0(sizeof(MVDependencies));
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dependencies->magic = STATS_DEPS_MAGIC;
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dependencies->type = STATS_DEPS_TYPE_BASIC;
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dependencies->ndeps = 0;
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}
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dependencies->ndeps++;
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dependencies = (MVDependencies *) repalloc(dependencies,
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offsetof(MVDependencies, deps)
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+ dependencies->ndeps * sizeof(MVDependency *));
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dependencies->deps[dependencies->ndeps - 1] = d;
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}
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/*
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* we're done with variations of k elements, so free the
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* DependencyGenerator
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*/
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DependencyGenerator_free(DependencyGenerator);
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}
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return dependencies;
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}
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/*
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* Serialize list of dependencies into a bytea value.
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*/
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bytea *
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statext_dependencies_serialize(MVDependencies *dependencies)
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{
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int i;
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bytea *output;
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char *tmp;
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Size len;
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/* we need to store ndeps, with a number of attributes for each one */
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len = VARHDRSZ + SizeOfHeader;
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/* and also include space for the actual attribute numbers and degrees */
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for (i = 0; i < dependencies->ndeps; i++)
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len += SizeOfItem(dependencies->deps[i]->nattributes);
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output = (bytea *) palloc0(len);
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SET_VARSIZE(output, len);
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tmp = VARDATA(output);
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/* Store the base struct values (magic, type, ndeps) */
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memcpy(tmp, &dependencies->magic, sizeof(uint32));
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tmp += sizeof(uint32);
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memcpy(tmp, &dependencies->type, sizeof(uint32));
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tmp += sizeof(uint32);
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memcpy(tmp, &dependencies->ndeps, sizeof(uint32));
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tmp += sizeof(uint32);
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/* store number of attributes and attribute numbers for each dependency */
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for (i = 0; i < dependencies->ndeps; i++)
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{
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MVDependency *d = dependencies->deps[i];
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memcpy(tmp, &d->degree, sizeof(double));
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tmp += sizeof(double);
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memcpy(tmp, &d->nattributes, sizeof(AttrNumber));
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tmp += sizeof(AttrNumber);
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memcpy(tmp, d->attributes, sizeof(AttrNumber) * d->nattributes);
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tmp += sizeof(AttrNumber) * d->nattributes;
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/* protect against overflow */
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Assert(tmp <= ((char *) output + len));
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}
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/* make sure we've produced exactly the right amount of data */
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Assert(tmp == ((char *) output + len));
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return output;
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}
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|
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/*
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* Reads serialized dependencies into MVDependencies structure.
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*/
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MVDependencies *
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statext_dependencies_deserialize(bytea *data)
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{
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int i;
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Size min_expected_size;
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MVDependencies *dependencies;
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char *tmp;
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if (data == NULL)
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return NULL;
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if (VARSIZE_ANY_EXHDR(data) < SizeOfHeader)
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elog(ERROR, "invalid MVDependencies size %zd (expected at least %zd)",
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VARSIZE_ANY_EXHDR(data), SizeOfHeader);
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/* read the MVDependencies header */
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dependencies = (MVDependencies *) palloc0(sizeof(MVDependencies));
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|
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/* initialize pointer to the data part (skip the varlena header) */
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tmp = VARDATA_ANY(data);
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/* read the header fields and perform basic sanity checks */
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memcpy(&dependencies->magic, tmp, sizeof(uint32));
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tmp += sizeof(uint32);
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memcpy(&dependencies->type, tmp, sizeof(uint32));
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tmp += sizeof(uint32);
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memcpy(&dependencies->ndeps, tmp, sizeof(uint32));
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tmp += sizeof(uint32);
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|
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if (dependencies->magic != STATS_DEPS_MAGIC)
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elog(ERROR, "invalid dependency magic %d (expected %d)",
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dependencies->magic, STATS_DEPS_MAGIC);
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|
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if (dependencies->type != STATS_DEPS_TYPE_BASIC)
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elog(ERROR, "invalid dependency type %d (expected %d)",
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dependencies->type, STATS_DEPS_TYPE_BASIC);
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|
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if (dependencies->ndeps == 0)
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ereport(ERROR,
|
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(errcode(ERRCODE_DATA_CORRUPTED),
|
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errmsg("invalid zero-length item array in MVDependencies")));
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|
|
/* what minimum bytea size do we expect for those parameters */
|
|
min_expected_size = SizeOfItem(dependencies->ndeps);
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|
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if (VARSIZE_ANY_EXHDR(data) < min_expected_size)
|
|
elog(ERROR, "invalid dependencies size %zd (expected at least %zd)",
|
|
VARSIZE_ANY_EXHDR(data), min_expected_size);
|
|
|
|
/* allocate space for the MCV items */
|
|
dependencies = repalloc(dependencies, offsetof(MVDependencies, deps)
|
|
+ (dependencies->ndeps * sizeof(MVDependency *)));
|
|
|
|
for (i = 0; i < dependencies->ndeps; i++)
|
|
{
|
|
double degree;
|
|
AttrNumber k;
|
|
MVDependency *d;
|
|
|
|
/* degree of validity */
|
|
memcpy(°ree, tmp, sizeof(double));
|
|
tmp += sizeof(double);
|
|
|
|
/* number of attributes */
|
|
memcpy(&k, tmp, sizeof(AttrNumber));
|
|
tmp += sizeof(AttrNumber);
|
|
|
|
/* is the number of attributes valid? */
|
|
Assert((k >= 2) && (k <= STATS_MAX_DIMENSIONS));
|
|
|
|
/* now that we know the number of attributes, allocate the dependency */
|
|
d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
|
|
+ (k * sizeof(AttrNumber)));
|
|
|
|
d->degree = degree;
|
|
d->nattributes = k;
|
|
|
|
/* copy attribute numbers */
|
|
memcpy(d->attributes, tmp, sizeof(AttrNumber) * d->nattributes);
|
|
tmp += sizeof(AttrNumber) * d->nattributes;
|
|
|
|
dependencies->deps[i] = d;
|
|
|
|
/* still within the bytea */
|
|
Assert(tmp <= ((char *) data + VARSIZE_ANY(data)));
|
|
}
|
|
|
|
/* we should have consumed the whole bytea exactly */
|
|
Assert(tmp == ((char *) data + VARSIZE_ANY(data)));
|
|
|
|
return dependencies;
|
|
}
|
|
|
|
/*
|
|
* dependency_is_fully_matched
|
|
* checks that a functional dependency is fully matched given clauses on
|
|
* attributes (assuming the clauses are suitable equality clauses)
|
|
*/
|
|
static bool
|
|
dependency_is_fully_matched(MVDependency *dependency, Bitmapset *attnums)
|
|
{
|
|
int j;
|
|
|
|
/*
|
|
* Check that the dependency actually is fully covered by clauses. We have
|
|
* to translate all attribute numbers, as those are referenced
|
|
*/
|
|
for (j = 0; j < dependency->nattributes; j++)
|
|
{
|
|
int attnum = dependency->attributes[j];
|
|
|
|
if (!bms_is_member(attnum, attnums))
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
/*
|
|
* dependency_implies_attribute
|
|
* check that the attnum matches is implied by the functional dependency
|
|
*/
|
|
static bool
|
|
dependency_implies_attribute(MVDependency *dependency, AttrNumber attnum)
|
|
{
|
|
if (attnum == dependency->attributes[dependency->nattributes - 1])
|
|
return true;
|
|
|
|
return false;
|
|
}
|
|
|
|
/*
|
|
* statext_dependencies_load
|
|
* Load the functional dependencies for the indicated pg_statistic_ext tuple
|
|
*/
|
|
MVDependencies *
|
|
statext_dependencies_load(Oid mvoid)
|
|
{
|
|
MVDependencies *result;
|
|
bool isnull;
|
|
Datum deps;
|
|
HeapTuple htup;
|
|
|
|
htup = SearchSysCache1(STATEXTOID, ObjectIdGetDatum(mvoid));
|
|
if (!HeapTupleIsValid(htup))
|
|
elog(ERROR, "cache lookup failed for statistics object %u", mvoid);
|
|
|
|
deps = SysCacheGetAttr(STATEXTOID, htup,
|
|
Anum_pg_statistic_ext_stxdependencies, &isnull);
|
|
if (isnull)
|
|
elog(ERROR,
|
|
"requested statistic kind \"%c\" is not yet built for statistics object %u",
|
|
STATS_EXT_DEPENDENCIES, mvoid);
|
|
|
|
result = statext_dependencies_deserialize(DatumGetByteaPP(deps));
|
|
|
|
ReleaseSysCache(htup);
|
|
|
|
return result;
|
|
}
|
|
|
|
/*
|
|
* pg_dependencies_in - input routine for type pg_dependencies.
|
|
*
|
|
* pg_dependencies is real enough to be a table column, but it has no operations
|
|
* of its own, and disallows input too
|
|
*/
|
|
Datum
|
|
pg_dependencies_in(PG_FUNCTION_ARGS)
|
|
{
|
|
/*
|
|
* pg_node_list stores the data in binary form and parsing text input is
|
|
* not needed, so disallow this.
|
|
*/
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("cannot accept a value of type %s", "pg_dependencies")));
|
|
|
|
PG_RETURN_VOID(); /* keep compiler quiet */
|
|
}
|
|
|
|
/*
|
|
* pg_dependencies - output routine for type pg_dependencies.
|
|
*/
|
|
Datum
|
|
pg_dependencies_out(PG_FUNCTION_ARGS)
|
|
{
|
|
bytea *data = PG_GETARG_BYTEA_PP(0);
|
|
MVDependencies *dependencies = statext_dependencies_deserialize(data);
|
|
int i,
|
|
j;
|
|
StringInfoData str;
|
|
|
|
initStringInfo(&str);
|
|
appendStringInfoChar(&str, '{');
|
|
|
|
for (i = 0; i < dependencies->ndeps; i++)
|
|
{
|
|
MVDependency *dependency = dependencies->deps[i];
|
|
|
|
if (i > 0)
|
|
appendStringInfoString(&str, ", ");
|
|
|
|
appendStringInfoChar(&str, '"');
|
|
for (j = 0; j < dependency->nattributes; j++)
|
|
{
|
|
if (j == dependency->nattributes - 1)
|
|
appendStringInfoString(&str, " => ");
|
|
else if (j > 0)
|
|
appendStringInfoString(&str, ", ");
|
|
|
|
appendStringInfo(&str, "%d", dependency->attributes[j]);
|
|
}
|
|
appendStringInfo(&str, "\": %f", dependency->degree);
|
|
}
|
|
|
|
appendStringInfoChar(&str, '}');
|
|
|
|
PG_RETURN_CSTRING(str.data);
|
|
}
|
|
|
|
/*
|
|
* pg_dependencies_recv - binary input routine for type pg_dependencies.
|
|
*/
|
|
Datum
|
|
pg_dependencies_recv(PG_FUNCTION_ARGS)
|
|
{
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("cannot accept a value of type %s", "pg_dependencies")));
|
|
|
|
PG_RETURN_VOID(); /* keep compiler quiet */
|
|
}
|
|
|
|
/*
|
|
* pg_dependencies_send - binary output routine for type pg_dependencies.
|
|
*
|
|
* Functional dependencies are serialized in a bytea value (although the type
|
|
* is named differently), so let's just send that.
|
|
*/
|
|
Datum
|
|
pg_dependencies_send(PG_FUNCTION_ARGS)
|
|
{
|
|
return byteasend(fcinfo);
|
|
}
|
|
|
|
/*
|
|
* dependency_is_compatible_clause
|
|
* Determines if the clause is compatible with functional dependencies
|
|
*
|
|
* Only clauses that have the form of equality to a pseudoconstant, or can be
|
|
* interpreted that way, are currently accepted. Furthermore the variable
|
|
* part of the clause must be a simple Var belonging to the specified
|
|
* relation, whose attribute number we return in *attnum on success.
|
|
*/
|
|
static bool
|
|
dependency_is_compatible_clause(Node *clause, Index relid, AttrNumber *attnum)
|
|
{
|
|
RestrictInfo *rinfo = (RestrictInfo *) clause;
|
|
Var *var;
|
|
|
|
if (!IsA(rinfo, RestrictInfo))
|
|
return false;
|
|
|
|
/* Pseudoconstants are not interesting (they couldn't contain a Var) */
|
|
if (rinfo->pseudoconstant)
|
|
return false;
|
|
|
|
/* Clauses referencing multiple, or no, varnos are incompatible */
|
|
if (bms_membership(rinfo->clause_relids) != BMS_SINGLETON)
|
|
return false;
|
|
|
|
if (is_opclause(rinfo->clause))
|
|
{
|
|
/* If it's an opclause, check for Var = Const or Const = Var. */
|
|
OpExpr *expr = (OpExpr *) rinfo->clause;
|
|
|
|
/* Only expressions with two arguments are candidates. */
|
|
if (list_length(expr->args) != 2)
|
|
return false;
|
|
|
|
/* Make sure non-selected argument is a pseudoconstant. */
|
|
if (is_pseudo_constant_clause(lsecond(expr->args)))
|
|
var = linitial(expr->args);
|
|
else if (is_pseudo_constant_clause(linitial(expr->args)))
|
|
var = lsecond(expr->args);
|
|
else
|
|
return false;
|
|
|
|
/*
|
|
* If it's not an "=" operator, just ignore the clause, as it's not
|
|
* compatible with functional dependencies.
|
|
*
|
|
* This uses the function for estimating selectivity, not the operator
|
|
* directly (a bit awkward, but well ...).
|
|
*
|
|
* XXX this is pretty dubious; probably it'd be better to check btree
|
|
* or hash opclass membership, so as not to be fooled by custom
|
|
* selectivity functions, and to be more consistent with decisions
|
|
* elsewhere in the planner.
|
|
*/
|
|
if (get_oprrest(expr->opno) != F_EQSEL)
|
|
return false;
|
|
|
|
/* OK to proceed with checking "var" */
|
|
}
|
|
else if (is_notclause(rinfo->clause))
|
|
{
|
|
/*
|
|
* "NOT x" can be interpreted as "x = false", so get the argument and
|
|
* proceed with seeing if it's a suitable Var.
|
|
*/
|
|
var = (Var *) get_notclausearg(rinfo->clause);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* A boolean expression "x" can be interpreted as "x = true", so
|
|
* proceed with seeing if it's a suitable Var.
|
|
*/
|
|
var = (Var *) rinfo->clause;
|
|
}
|
|
|
|
/*
|
|
* We may ignore any RelabelType node above the operand. (There won't be
|
|
* more than one, since eval_const_expressions has been applied already.)
|
|
*/
|
|
if (IsA(var, RelabelType))
|
|
var = (Var *) ((RelabelType *) var)->arg;
|
|
|
|
/* We only support plain Vars for now */
|
|
if (!IsA(var, Var))
|
|
return false;
|
|
|
|
/* Ensure Var is from the correct relation */
|
|
if (var->varno != relid)
|
|
return false;
|
|
|
|
/* We also better ensure the Var is from the current level */
|
|
if (var->varlevelsup != 0)
|
|
return false;
|
|
|
|
/* Also ignore system attributes (we don't allow stats on those) */
|
|
if (!AttrNumberIsForUserDefinedAttr(var->varattno))
|
|
return false;
|
|
|
|
*attnum = var->varattno;
|
|
return true;
|
|
}
|
|
|
|
/*
|
|
* find_strongest_dependency
|
|
* find the strongest dependency on the attributes
|
|
*
|
|
* When applying functional dependencies, we start with the strongest
|
|
* dependencies. That is, we select the dependency that:
|
|
*
|
|
* (a) has all attributes covered by equality clauses
|
|
*
|
|
* (b) has the most attributes
|
|
*
|
|
* (c) has the highest degree of validity
|
|
*
|
|
* This guarantees that we eliminate the most redundant conditions first
|
|
* (see the comment in dependencies_clauselist_selectivity).
|
|
*/
|
|
static MVDependency *
|
|
find_strongest_dependency(StatisticExtInfo *stats, MVDependencies *dependencies,
|
|
Bitmapset *attnums)
|
|
{
|
|
int i;
|
|
MVDependency *strongest = NULL;
|
|
|
|
/* number of attnums in clauses */
|
|
int nattnums = bms_num_members(attnums);
|
|
|
|
/*
|
|
* Iterate over the MVDependency items and find the strongest one from the
|
|
* fully-matched dependencies. We do the cheap checks first, before
|
|
* matching it against the attnums.
|
|
*/
|
|
for (i = 0; i < dependencies->ndeps; i++)
|
|
{
|
|
MVDependency *dependency = dependencies->deps[i];
|
|
|
|
/*
|
|
* Skip dependencies referencing more attributes than available
|
|
* clauses, as those can't be fully matched.
|
|
*/
|
|
if (dependency->nattributes > nattnums)
|
|
continue;
|
|
|
|
if (strongest)
|
|
{
|
|
/* skip dependencies on fewer attributes than the strongest. */
|
|
if (dependency->nattributes < strongest->nattributes)
|
|
continue;
|
|
|
|
/* also skip weaker dependencies when attribute count matches */
|
|
if (strongest->nattributes == dependency->nattributes &&
|
|
strongest->degree > dependency->degree)
|
|
continue;
|
|
}
|
|
|
|
/*
|
|
* this dependency is stronger, but we must still check that it's
|
|
* fully matched to these attnums. We perform this check last as it's
|
|
* slightly more expensive than the previous checks.
|
|
*/
|
|
if (dependency_is_fully_matched(dependency, attnums))
|
|
strongest = dependency; /* save new best match */
|
|
}
|
|
|
|
return strongest;
|
|
}
|
|
|
|
/*
|
|
* dependencies_clauselist_selectivity
|
|
* Return the estimated selectivity of (a subset of) the given clauses
|
|
* using functional dependency statistics, or 1.0 if no useful functional
|
|
* dependency statistic exists.
|
|
*
|
|
* 'estimatedclauses' is an input/output argument that gets a bit set
|
|
* corresponding to the (zero-based) list index of each clause that is included
|
|
* in the estimated selectivity.
|
|
*
|
|
* Given equality clauses on attributes (a,b) we find the strongest dependency
|
|
* between them, i.e. either (a=>b) or (b=>a). Assuming (a=>b) is the selected
|
|
* dependency, we then combine the per-clause selectivities using the formula
|
|
*
|
|
* P(a,b) = P(a) * [f + (1-f)*P(b)]
|
|
*
|
|
* where 'f' is the degree of the dependency.
|
|
*
|
|
* With clauses on more than two attributes, the dependencies are applied
|
|
* recursively, starting with the widest/strongest dependencies. For example
|
|
* P(a,b,c) is first split like this:
|
|
*
|
|
* P(a,b,c) = P(a,b) * [f + (1-f)*P(c)]
|
|
*
|
|
* assuming (a,b=>c) is the strongest dependency.
|
|
*/
|
|
Selectivity
|
|
dependencies_clauselist_selectivity(PlannerInfo *root,
|
|
List *clauses,
|
|
int varRelid,
|
|
JoinType jointype,
|
|
SpecialJoinInfo *sjinfo,
|
|
RelOptInfo *rel,
|
|
Bitmapset **estimatedclauses)
|
|
{
|
|
Selectivity s1 = 1.0;
|
|
ListCell *l;
|
|
Bitmapset *clauses_attnums = NULL;
|
|
StatisticExtInfo *stat;
|
|
MVDependencies *dependencies;
|
|
AttrNumber *list_attnums;
|
|
int listidx;
|
|
|
|
/* check if there's any stats that might be useful for us. */
|
|
if (!has_stats_of_kind(rel->statlist, STATS_EXT_DEPENDENCIES))
|
|
return 1.0;
|
|
|
|
list_attnums = (AttrNumber *) palloc(sizeof(AttrNumber) *
|
|
list_length(clauses));
|
|
|
|
/*
|
|
* Pre-process the clauses list to extract the attnums seen in each item.
|
|
* We need to determine if there's any clauses which will be useful for
|
|
* dependency selectivity estimations. Along the way we'll record all of
|
|
* the attnums for each clause in a list which we'll reference later so we
|
|
* don't need to repeat the same work again. We'll also keep track of all
|
|
* attnums seen.
|
|
*
|
|
* We also skip clauses that we already estimated using different types of
|
|
* statistics (we treat them as incompatible).
|
|
*/
|
|
listidx = 0;
|
|
foreach(l, clauses)
|
|
{
|
|
Node *clause = (Node *) lfirst(l);
|
|
AttrNumber attnum;
|
|
|
|
if (!bms_is_member(listidx, *estimatedclauses) &&
|
|
dependency_is_compatible_clause(clause, rel->relid, &attnum))
|
|
{
|
|
list_attnums[listidx] = attnum;
|
|
clauses_attnums = bms_add_member(clauses_attnums, attnum);
|
|
}
|
|
else
|
|
list_attnums[listidx] = InvalidAttrNumber;
|
|
|
|
listidx++;
|
|
}
|
|
|
|
/*
|
|
* If there's not at least two distinct attnums then reject the whole list
|
|
* of clauses. We must return 1.0 so the calling function's selectivity is
|
|
* unaffected.
|
|
*/
|
|
if (bms_num_members(clauses_attnums) < 2)
|
|
{
|
|
pfree(list_attnums);
|
|
return 1.0;
|
|
}
|
|
|
|
/* find the best suited statistics object for these attnums */
|
|
stat = choose_best_statistics(rel->statlist, clauses_attnums,
|
|
STATS_EXT_DEPENDENCIES);
|
|
|
|
/* if no matching stats could be found then we've nothing to do */
|
|
if (!stat)
|
|
{
|
|
pfree(list_attnums);
|
|
return 1.0;
|
|
}
|
|
|
|
/* load the dependency items stored in the statistics object */
|
|
dependencies = statext_dependencies_load(stat->statOid);
|
|
|
|
/*
|
|
* Apply the dependencies recursively, starting with the widest/strongest
|
|
* ones, and proceeding to the smaller/weaker ones. At the end of each
|
|
* round we factor in the selectivity of clauses on the implied attribute,
|
|
* and remove the clauses from the list.
|
|
*/
|
|
while (true)
|
|
{
|
|
Selectivity s2 = 1.0;
|
|
MVDependency *dependency;
|
|
|
|
/* the widest/strongest dependency, fully matched by clauses */
|
|
dependency = find_strongest_dependency(stat, dependencies,
|
|
clauses_attnums);
|
|
|
|
/* if no suitable dependency was found, we're done */
|
|
if (!dependency)
|
|
break;
|
|
|
|
/*
|
|
* We found an applicable dependency, so find all the clauses on the
|
|
* implied attribute - with dependency (a,b => c) we look for clauses
|
|
* on 'c'.
|
|
*/
|
|
listidx = -1;
|
|
foreach(l, clauses)
|
|
{
|
|
Node *clause;
|
|
|
|
listidx++;
|
|
|
|
/*
|
|
* Skip incompatible clauses, and ones we've already estimated on.
|
|
*/
|
|
if (list_attnums[listidx] == InvalidAttrNumber)
|
|
continue;
|
|
|
|
/*
|
|
* Technically we could find more than one clause for a given
|
|
* attnum. Since these clauses must be equality clauses, we choose
|
|
* to only take the selectivity estimate from the final clause in
|
|
* the list for this attnum. If the attnum happens to be compared
|
|
* to a different Const in another clause then no rows will match
|
|
* anyway. If it happens to be compared to the same Const, then
|
|
* ignoring the additional clause is just the thing to do.
|
|
*/
|
|
if (dependency_implies_attribute(dependency,
|
|
list_attnums[listidx]))
|
|
{
|
|
clause = (Node *) lfirst(l);
|
|
|
|
s2 = clause_selectivity(root, clause, varRelid, jointype,
|
|
sjinfo);
|
|
|
|
/* mark this one as done, so we don't touch it again. */
|
|
*estimatedclauses = bms_add_member(*estimatedclauses, listidx);
|
|
|
|
/*
|
|
* Mark that we've got and used the dependency on this clause.
|
|
* We'll want to ignore this when looking for the next
|
|
* strongest dependency above.
|
|
*/
|
|
clauses_attnums = bms_del_member(clauses_attnums,
|
|
list_attnums[listidx]);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Now factor in the selectivity for all the "implied" clauses into
|
|
* the final one, using this formula:
|
|
*
|
|
* P(a,b) = P(a) * (f + (1-f) * P(b))
|
|
*
|
|
* where 'f' is the degree of validity of the dependency.
|
|
*/
|
|
s1 *= (dependency->degree + (1 - dependency->degree) * s2);
|
|
}
|
|
|
|
pfree(dependencies);
|
|
pfree(list_attnums);
|
|
|
|
return s1;
|
|
}
|