/*------------------------------------------------------------------------- * * selfuncs.h * Selectivity functions for standard operators, and assorted * infrastructure for selectivity and cost estimation. * * * Portions Copyright (c) 1996-2022, PostgreSQL Global Development Group * Portions Copyright (c) 1994, Regents of the University of California * * src/include/utils/selfuncs.h * *------------------------------------------------------------------------- */ #ifndef SELFUNCS_H #define SELFUNCS_H #include "access/htup.h" #include "fmgr.h" #include "nodes/pathnodes.h" /* * Note: the default selectivity estimates are not chosen entirely at random. * We want them to be small enough to ensure that indexscans will be used if * available, for typical table densities of ~100 tuples/page. Thus, for * example, 0.01 is not quite small enough, since that makes it appear that * nearly all pages will be hit anyway. Also, since we sometimes estimate * eqsel as 1/num_distinct, we probably want DEFAULT_NUM_DISTINCT to equal * 1/DEFAULT_EQ_SEL. */ /* default selectivity estimate for equalities such as "A = b" */ #define DEFAULT_EQ_SEL 0.005 /* default selectivity estimate for inequalities such as "A < b" */ #define DEFAULT_INEQ_SEL 0.3333333333333333 /* default selectivity estimate for range inequalities "A > b AND A < c" */ #define DEFAULT_RANGE_INEQ_SEL 0.005 /* default selectivity estimate for multirange inequalities "A > b AND A < c" */ #define DEFAULT_MULTIRANGE_INEQ_SEL 0.005 /* default selectivity estimate for pattern-match operators such as LIKE */ #define DEFAULT_MATCH_SEL 0.005 /* default selectivity estimate for other matching operators */ #define DEFAULT_MATCHING_SEL 0.010 /* default number of distinct values in a table */ #define DEFAULT_NUM_DISTINCT 200 /* default selectivity estimate for boolean and null test nodes */ #define DEFAULT_UNK_SEL 0.005 #define DEFAULT_NOT_UNK_SEL (1.0 - DEFAULT_UNK_SEL) /* * Clamp a computed probability estimate (which may suffer from roundoff or * estimation errors) to valid range. Argument must be a float variable. */ #define CLAMP_PROBABILITY(p) \ do { \ if (p < 0.0) \ p = 0.0; \ else if (p > 1.0) \ p = 1.0; \ } while (0) /* * A set of flags which some selectivity estimation functions can pass back to * callers to provide further details about some assumptions which were made * during the estimation. */ #define SELFLAG_USED_DEFAULT (1 << 0) /* Estimation fell back on one * of the DEFAULTs as defined * above. */ typedef struct EstimationInfo { uint32 flags; /* Flags, as defined above to mark special * properties of the estimation. */ } EstimationInfo; /* Return data from examine_variable and friends */ typedef struct VariableStatData { Node *var; /* the Var or expression tree */ RelOptInfo *rel; /* Relation, or NULL if not identifiable */ HeapTuple statsTuple; /* pg_statistic tuple, or NULL if none */ /* NB: if statsTuple!=NULL, it must be freed when caller is done */ void (*freefunc) (HeapTuple tuple); /* how to free statsTuple */ Oid vartype; /* exposed type of expression */ Oid atttype; /* actual type (after stripping relabel) */ int32 atttypmod; /* actual typmod (after stripping relabel) */ bool isunique; /* matches unique index or DISTINCT clause */ bool acl_ok; /* result of ACL check on table or column */ } VariableStatData; #define ReleaseVariableStats(vardata) \ do { \ if (HeapTupleIsValid((vardata).statsTuple)) \ (vardata).freefunc((vardata).statsTuple); \ } while(0) /* * genericcostestimate is a general-purpose estimator that can be used for * most index types. In some cases we use genericcostestimate as the base * code and then incorporate additional index-type-specific knowledge in * the type-specific calling function. To avoid code duplication, we make * genericcostestimate return a number of intermediate values as well as * its preliminary estimates of the output cost values. The GenericCosts * struct includes all these values. * * Callers should initialize all fields of GenericCosts to zero. In addition, * they can set numIndexTuples to some positive value if they have a better * than default way of estimating the number of leaf index tuples visited. */ typedef struct { /* These are the values the cost estimator must return to the planner */ Cost indexStartupCost; /* index-related startup cost */ Cost indexTotalCost; /* total index-related scan cost */ Selectivity indexSelectivity; /* selectivity of index */ double indexCorrelation; /* order correlation of index */ /* Intermediate values we obtain along the way */ double numIndexPages; /* number of leaf pages visited */ double numIndexTuples; /* number of leaf tuples visited */ double spc_random_page_cost; /* relevant random_page_cost value */ double num_sa_scans; /* # indexscans from ScalarArrayOpExprs */ } GenericCosts; /* Hooks for plugins to get control when we ask for stats */ typedef bool (*get_relation_stats_hook_type) (PlannerInfo *root, RangeTblEntry *rte, AttrNumber attnum, VariableStatData *vardata); extern PGDLLIMPORT get_relation_stats_hook_type get_relation_stats_hook; typedef bool (*get_index_stats_hook_type) (PlannerInfo *root, Oid indexOid, AttrNumber indexattnum, VariableStatData *vardata); extern PGDLLIMPORT get_index_stats_hook_type get_index_stats_hook; /* Functions in selfuncs.c */ extern void examine_variable(PlannerInfo *root, Node *node, int varRelid, VariableStatData *vardata); extern bool statistic_proc_security_check(VariableStatData *vardata, Oid func_oid); extern bool get_restriction_variable(PlannerInfo *root, List *args, int varRelid, VariableStatData *vardata, Node **other, bool *varonleft); extern void get_join_variables(PlannerInfo *root, List *args, SpecialJoinInfo *sjinfo, VariableStatData *vardata1, VariableStatData *vardata2, bool *join_is_reversed); extern double get_variable_numdistinct(VariableStatData *vardata, bool *isdefault); extern double mcv_selectivity(VariableStatData *vardata, FmgrInfo *opproc, Oid collation, Datum constval, bool varonleft, double *sumcommonp); extern double histogram_selectivity(VariableStatData *vardata, FmgrInfo *opproc, Oid collation, Datum constval, bool varonleft, int min_hist_size, int n_skip, int *hist_size); extern double generic_restriction_selectivity(PlannerInfo *root, Oid oproid, Oid collation, List *args, int varRelid, double default_selectivity); extern double ineq_histogram_selectivity(PlannerInfo *root, VariableStatData *vardata, Oid opoid, FmgrInfo *opproc, bool isgt, bool iseq, Oid collation, Datum constval, Oid consttype); extern double var_eq_const(VariableStatData *vardata, Oid operator, Oid collation, Datum constval, bool constisnull, bool varonleft, bool negate); extern double var_eq_non_const(VariableStatData *vardata, Oid operator, Oid collation, Node *other, bool varonleft, bool negate); extern Selectivity boolvarsel(PlannerInfo *root, Node *arg, int varRelid); extern Selectivity booltestsel(PlannerInfo *root, BoolTestType booltesttype, Node *arg, int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo); extern Selectivity nulltestsel(PlannerInfo *root, NullTestType nulltesttype, Node *arg, int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo); extern Selectivity scalararraysel(PlannerInfo *root, ScalarArrayOpExpr *clause, bool is_join_clause, int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo); extern int estimate_array_length(Node *arrayexpr); extern Selectivity rowcomparesel(PlannerInfo *root, RowCompareExpr *clause, int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo); extern void mergejoinscansel(PlannerInfo *root, Node *clause, Oid opfamily, int strategy, bool nulls_first, Selectivity *leftstart, Selectivity *leftend, Selectivity *rightstart, Selectivity *rightend); extern double estimate_num_groups(PlannerInfo *root, List *groupExprs, double input_rows, List **pgset, EstimationInfo *estinfo); extern double estimate_num_groups_incremental(PlannerInfo *root, List *groupExprs, double input_rows, List **pgset, EstimationInfo *estinfo, List **cache_varinfos, int prevNExprs); extern void estimate_hash_bucket_stats(PlannerInfo *root, Node *hashkey, double nbuckets, Selectivity *mcv_freq, Selectivity *bucketsize_frac); extern double estimate_hashagg_tablesize(PlannerInfo *root, Path *path, const AggClauseCosts *agg_costs, double dNumGroups); extern List *get_quals_from_indexclauses(List *indexclauses); extern Cost index_other_operands_eval_cost(PlannerInfo *root, List *indexquals); extern List *add_predicate_to_index_quals(IndexOptInfo *index, List *indexQuals); extern void genericcostestimate(PlannerInfo *root, IndexPath *path, double loop_count, GenericCosts *costs); /* Functions in array_selfuncs.c */ extern Selectivity scalararraysel_containment(PlannerInfo *root, Node *leftop, Node *rightop, Oid elemtype, bool isEquality, bool useOr, int varRelid); #endif /* SELFUNCS_H */