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Recognizing the real-life complexity where columns in the table often have functional dependencies, PostgreSQL's estimation of the number of distinct values over a set of columns can be underestimated (or much rarely, overestimated) when dealing with multi-clause JOIN. In the case of hash join, it can end up with a small number of predicted hash buckets and, as a result, picking non-optimal merge join. To improve the situation, we introduce one additional stage of bucket size estimation - having two or more join clauses estimator lookup for extended statistics and use it for multicolumn estimation. Clauses are grouped into lists, each containing expressions referencing the same relation. The result of the multicolumn estimation made over such a list is combined with others according to the caller's logic. Clauses that are not estimated are returned to the caller for further estimation. Discussion: https://postgr.es/m/52257607-57f6-850d-399a-ec33a654457b%40postgrespro.ru Author: Andrei Lepikhov <lepihov@gmail.com> Reviewed-by: Andy Fan <zhihui.fan1213@gmail.com> Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com> Reviewed-by: Alena Rybakina <lena.ribackina@yandex.ru> Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com>
250 lines
9.7 KiB
C
250 lines
9.7 KiB
C
/*-------------------------------------------------------------------------
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*
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* selfuncs.h
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* Selectivity functions for standard operators, and assorted
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* infrastructure for selectivity and cost estimation.
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*
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*
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* Portions Copyright (c) 1996-2025, 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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* src/include/utils/selfuncs.h
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*
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*-------------------------------------------------------------------------
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*/
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#ifndef SELFUNCS_H
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#define SELFUNCS_H
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#include "access/htup.h"
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#include "fmgr.h"
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#include "nodes/pathnodes.h"
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/*
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* Note: the default selectivity estimates are not chosen entirely at random.
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* We want them to be small enough to ensure that indexscans will be used if
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* available, for typical table densities of ~100 tuples/page. Thus, for
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* example, 0.01 is not quite small enough, since that makes it appear that
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* nearly all pages will be hit anyway. Also, since we sometimes estimate
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* eqsel as 1/num_distinct, we probably want DEFAULT_NUM_DISTINCT to equal
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* 1/DEFAULT_EQ_SEL.
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*/
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/* default selectivity estimate for equalities such as "A = b" */
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#define DEFAULT_EQ_SEL 0.005
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/* default selectivity estimate for inequalities such as "A < b" */
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#define DEFAULT_INEQ_SEL 0.3333333333333333
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/* default selectivity estimate for range inequalities "A > b AND A < c" */
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#define DEFAULT_RANGE_INEQ_SEL 0.005
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/* default selectivity estimate for multirange inequalities "A > b AND A < c" */
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#define DEFAULT_MULTIRANGE_INEQ_SEL 0.005
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/* default selectivity estimate for pattern-match operators such as LIKE */
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#define DEFAULT_MATCH_SEL 0.005
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/* default selectivity estimate for other matching operators */
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#define DEFAULT_MATCHING_SEL 0.010
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/* default number of distinct values in a table */
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#define DEFAULT_NUM_DISTINCT 200
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/* default selectivity estimate for boolean and null test nodes */
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#define DEFAULT_UNK_SEL 0.005
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#define DEFAULT_NOT_UNK_SEL (1.0 - DEFAULT_UNK_SEL)
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/*
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* Clamp a computed probability estimate (which may suffer from roundoff or
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* estimation errors) to valid range. Argument must be a float variable.
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*/
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#define CLAMP_PROBABILITY(p) \
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do { \
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if (p < 0.0) \
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p = 0.0; \
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else if (p > 1.0) \
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p = 1.0; \
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} while (0)
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/*
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* A set of flags which some selectivity estimation functions can pass back to
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* callers to provide further details about some assumptions which were made
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* during the estimation.
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*/
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#define SELFLAG_USED_DEFAULT (1 << 0) /* Estimation fell back on one
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* of the DEFAULTs as defined
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* above. */
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typedef struct EstimationInfo
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{
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uint32 flags; /* Flags, as defined above to mark special
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* properties of the estimation. */
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} EstimationInfo;
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/* Return data from examine_variable and friends */
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typedef struct VariableStatData
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{
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Node *var; /* the Var or expression tree */
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RelOptInfo *rel; /* Relation, or NULL if not identifiable */
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HeapTuple statsTuple; /* pg_statistic tuple, or NULL if none */
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/* NB: if statsTuple!=NULL, it must be freed when caller is done */
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void (*freefunc) (HeapTuple tuple); /* how to free statsTuple */
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Oid vartype; /* exposed type of expression */
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Oid atttype; /* actual type (after stripping relabel) */
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int32 atttypmod; /* actual typmod (after stripping relabel) */
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bool isunique; /* matches unique index, DISTINCT or GROUP-BY
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* clause */
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bool acl_ok; /* result of ACL check on table or column */
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} VariableStatData;
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#define ReleaseVariableStats(vardata) \
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do { \
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if (HeapTupleIsValid((vardata).statsTuple)) \
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(vardata).freefunc((vardata).statsTuple); \
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} while(0)
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/*
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* genericcostestimate is a general-purpose estimator that can be used for
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* most index types. In some cases we use genericcostestimate as the base
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* code and then incorporate additional index-type-specific knowledge in
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* the type-specific calling function. To avoid code duplication, we make
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* genericcostestimate return a number of intermediate values as well as
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* its preliminary estimates of the output cost values. The GenericCosts
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* struct includes all these values.
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*
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* Callers should initialize all fields of GenericCosts to zero. In addition,
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* they can set numIndexTuples to some positive value if they have a better
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* than default way of estimating the number of leaf index tuples visited.
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* Similarly, they can set num_sa_scans to some value >= 1 for an index AM
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* that doesn't necessarily perform exactly one primitive index scan per
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* distinct combination of ScalarArrayOp array elements.
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*/
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typedef struct
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{
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/* These are the values the cost estimator must return to the planner */
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Cost indexStartupCost; /* index-related startup cost */
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Cost indexTotalCost; /* total index-related scan cost */
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Selectivity indexSelectivity; /* selectivity of index */
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double indexCorrelation; /* order correlation of index */
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/* Intermediate values we obtain along the way */
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double numIndexPages; /* number of leaf pages visited */
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double numIndexTuples; /* number of leaf tuples visited */
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double spc_random_page_cost; /* relevant random_page_cost value */
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double num_sa_scans; /* # indexscans from ScalarArrayOpExprs */
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} GenericCosts;
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/* Hooks for plugins to get control when we ask for stats */
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typedef bool (*get_relation_stats_hook_type) (PlannerInfo *root,
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RangeTblEntry *rte,
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AttrNumber attnum,
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VariableStatData *vardata);
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extern PGDLLIMPORT get_relation_stats_hook_type get_relation_stats_hook;
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typedef bool (*get_index_stats_hook_type) (PlannerInfo *root,
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Oid indexOid,
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AttrNumber indexattnum,
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VariableStatData *vardata);
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extern PGDLLIMPORT get_index_stats_hook_type get_index_stats_hook;
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/* Functions in selfuncs.c */
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extern void examine_variable(PlannerInfo *root, Node *node, int varRelid,
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VariableStatData *vardata);
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extern bool statistic_proc_security_check(VariableStatData *vardata, Oid func_oid);
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extern bool get_restriction_variable(PlannerInfo *root, List *args,
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int varRelid,
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VariableStatData *vardata, Node **other,
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bool *varonleft);
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extern void get_join_variables(PlannerInfo *root, List *args,
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SpecialJoinInfo *sjinfo,
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VariableStatData *vardata1,
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VariableStatData *vardata2,
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bool *join_is_reversed);
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extern double get_variable_numdistinct(VariableStatData *vardata,
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bool *isdefault);
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extern double mcv_selectivity(VariableStatData *vardata,
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FmgrInfo *opproc, Oid collation,
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Datum constval, bool varonleft,
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double *sumcommonp);
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extern double histogram_selectivity(VariableStatData *vardata,
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FmgrInfo *opproc, Oid collation,
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Datum constval, bool varonleft,
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int min_hist_size, int n_skip,
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int *hist_size);
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extern double generic_restriction_selectivity(PlannerInfo *root,
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Oid oproid, Oid collation,
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List *args, int varRelid,
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double default_selectivity);
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extern double ineq_histogram_selectivity(PlannerInfo *root,
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VariableStatData *vardata,
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Oid opoid, FmgrInfo *opproc,
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bool isgt, bool iseq,
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Oid collation,
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Datum constval, Oid consttype);
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extern double var_eq_const(VariableStatData *vardata,
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Oid oproid, Oid collation,
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Datum constval, bool constisnull,
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bool varonleft, bool negate);
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extern double var_eq_non_const(VariableStatData *vardata,
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Oid oproid, Oid collation,
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Node *other,
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bool varonleft, bool negate);
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extern Selectivity boolvarsel(PlannerInfo *root, Node *arg, int varRelid);
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extern Selectivity booltestsel(PlannerInfo *root, BoolTestType booltesttype,
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Node *arg, int varRelid,
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JoinType jointype, SpecialJoinInfo *sjinfo);
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extern Selectivity nulltestsel(PlannerInfo *root, NullTestType nulltesttype,
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Node *arg, int varRelid,
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JoinType jointype, SpecialJoinInfo *sjinfo);
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extern Selectivity scalararraysel(PlannerInfo *root,
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ScalarArrayOpExpr *clause,
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bool is_join_clause,
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int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo);
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extern double estimate_array_length(PlannerInfo *root, Node *arrayexpr);
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extern Selectivity rowcomparesel(PlannerInfo *root,
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RowCompareExpr *clause,
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int varRelid, JoinType jointype, SpecialJoinInfo *sjinfo);
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extern void mergejoinscansel(PlannerInfo *root, Node *clause,
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Oid opfamily, int strategy, bool nulls_first,
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Selectivity *leftstart, Selectivity *leftend,
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Selectivity *rightstart, Selectivity *rightend);
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extern double estimate_num_groups(PlannerInfo *root, List *groupExprs,
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double input_rows, List **pgset,
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EstimationInfo *estinfo);
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extern List *estimate_multivariate_bucketsize(PlannerInfo *root,
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RelOptInfo *inner,
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List *hashclauses,
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Selectivity *innerbucketsize);
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extern void estimate_hash_bucket_stats(PlannerInfo *root,
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Node *hashkey, double nbuckets,
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Selectivity *mcv_freq,
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Selectivity *bucketsize_frac);
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extern double estimate_hashagg_tablesize(PlannerInfo *root, Path *path,
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const AggClauseCosts *agg_costs,
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double dNumGroups);
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extern List *get_quals_from_indexclauses(List *indexclauses);
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extern Cost index_other_operands_eval_cost(PlannerInfo *root,
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List *indexquals);
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extern List *add_predicate_to_index_quals(IndexOptInfo *index,
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List *indexQuals);
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extern void genericcostestimate(PlannerInfo *root, IndexPath *path,
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double loop_count,
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GenericCosts *costs);
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/* Functions in array_selfuncs.c */
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extern Selectivity scalararraysel_containment(PlannerInfo *root,
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Node *leftop, Node *rightop,
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Oid elemtype, bool isEquality, bool useOr,
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int varRelid);
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#endif /* SELFUNCS_H */
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