/*------------------------------------------------------------------------- * * selfuncs.h * Selectivity functions for standard operators, and assorted * infrastructure for selectivity and cost estimation. * * * Portions Copyright (c) 1996-2017, 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 "fmgr.h" #include "access/htup.h" #include "nodes/relation.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 pattern-match operators such as LIKE */ #define DEFAULT_MATCH_SEL 0.005 /* 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) /* 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; /* type to pass to get_attstatsslot */ int32 atttypmod; /* typmod to pass to get_attstatsslot */ bool isunique; /* matches unique index or DISTINCT clause */ } VariableStatData; #define ReleaseVariableStats(vardata) \ do { \ if (HeapTupleIsValid((vardata).statsTuple)) \ (* (vardata).freefunc) ((vardata).statsTuple); \ } while(0) typedef enum { Pattern_Type_Like, Pattern_Type_Like_IC, Pattern_Type_Regex, Pattern_Type_Regex_IC } Pattern_Type; typedef enum { Pattern_Prefix_None, Pattern_Prefix_Partial, Pattern_Prefix_Exact } Pattern_Prefix_Status; /* * deconstruct_indexquals is a simple function to examine the indexquals * attached to a proposed IndexPath. It returns a list of IndexQualInfo * structs, one per qual expression. */ typedef struct { RestrictInfo *rinfo; /* the indexqual itself */ int indexcol; /* zero-based index column number */ bool varonleft; /* true if index column is on left of qual */ Oid clause_op; /* qual's operator OID, if relevant */ Node *other_operand; /* non-index operand of qual's operator */ } IndexQualInfo; /* * 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 ScalarArrayOps */ } 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 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, Datum constval, bool varonleft, double *sumcommonp); extern double histogram_selectivity(VariableStatData *vardata, FmgrInfo *opproc, Datum constval, bool varonleft, int min_hist_size, int n_skip, int *hist_size); extern Pattern_Prefix_Status pattern_fixed_prefix(Const *patt, Pattern_Type ptype, Oid collation, Const **prefix, Selectivity *rest_selec); extern Const *make_greater_string(const Const *str_const, FmgrInfo *ltproc, Oid collation); 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); extern Selectivity estimate_hash_bucketsize(PlannerInfo *root, Node *hashkey, double nbuckets); extern List *deconstruct_indexquals(IndexPath *path); extern void genericcostestimate(PlannerInfo *root, IndexPath *path, double loop_count, List *qinfos, 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 */