/*------------------------------------------------------------------------- * * pg_statistic.h * definition of the "statistics" system catalog (pg_statistic) * * * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group * Portions Copyright (c) 1994, Regents of the University of California * * src/include/catalog/pg_statistic.h * * NOTES * The Catalog.pm module reads this file and derives schema * information. * *------------------------------------------------------------------------- */ #ifndef PG_STATISTIC_H #define PG_STATISTIC_H #include "catalog/genbki.h" #include "catalog/pg_statistic_d.h" /* ---------------- * pg_statistic definition. cpp turns this into * typedef struct FormData_pg_statistic * ---------------- */ CATALOG(pg_statistic,2619,StatisticRelationId) { /* These fields form the unique key for the entry: */ Oid starelid BKI_LOOKUP(pg_class); /* relation containing * attribute */ int16 staattnum; /* attribute (column) stats are for */ bool stainherit; /* true if inheritance children are included */ /* the fraction of the column's entries that are NULL: */ float4 stanullfrac; /* * stawidth is the average width in bytes of non-null entries. For * fixed-width datatypes this is of course the same as the typlen, but for * var-width types it is more useful. Note that this is the average width * of the data as actually stored, post-TOASTing (eg, for a * moved-out-of-line value, only the size of the pointer object is * counted). This is the appropriate definition for the primary use of * the statistic, which is to estimate sizes of in-memory hash tables of * tuples. */ int32 stawidth; /* ---------------- * stadistinct indicates the (approximate) number of distinct non-null * data values in the column. The interpretation is: * 0 unknown or not computed * > 0 actual number of distinct values * < 0 negative of multiplier for number of rows * The special negative case allows us to cope with columns that are * unique (stadistinct = -1) or nearly so (for example, a column in which * non-null values appear about twice on the average could be represented * by stadistinct = -0.5 if there are no nulls, or -0.4 if 20% of the * column is nulls). Because the number-of-rows statistic in pg_class may * be updated more frequently than pg_statistic is, it's important to be * able to describe such situations as a multiple of the number of rows, * rather than a fixed number of distinct values. But in other cases a * fixed number is correct (eg, a boolean column). * ---------------- */ float4 stadistinct; /* ---------------- * To allow keeping statistics on different kinds of datatypes, * we do not hard-wire any particular meaning for the remaining * statistical fields. Instead, we provide several "slots" in which * statistical data can be placed. Each slot includes: * kind integer code identifying kind of data (see below) * op OID of associated operator, if needed * coll OID of relevant collation, or 0 if none * numbers float4 array (for statistical values) * values anyarray (for representations of data values) * The ID, operator, and collation fields are never NULL; they are zeroes * in an unused slot. The numbers and values fields are NULL in an * unused slot, and might also be NULL in a used slot if the slot kind * has no need for one or the other. * ---------------- */ int16 stakind1; int16 stakind2; int16 stakind3; int16 stakind4; int16 stakind5; Oid staop1 BKI_LOOKUP_OPT(pg_operator); Oid staop2 BKI_LOOKUP_OPT(pg_operator); Oid staop3 BKI_LOOKUP_OPT(pg_operator); Oid staop4 BKI_LOOKUP_OPT(pg_operator); Oid staop5 BKI_LOOKUP_OPT(pg_operator); Oid stacoll1 BKI_LOOKUP_OPT(pg_collation); Oid stacoll2 BKI_LOOKUP_OPT(pg_collation); Oid stacoll3 BKI_LOOKUP_OPT(pg_collation); Oid stacoll4 BKI_LOOKUP_OPT(pg_collation); Oid stacoll5 BKI_LOOKUP_OPT(pg_collation); #ifdef CATALOG_VARLEN /* variable-length fields start here */ float4 stanumbers1[1]; float4 stanumbers2[1]; float4 stanumbers3[1]; float4 stanumbers4[1]; float4 stanumbers5[1]; /* * Values in these arrays are values of the column's data type, or of some * related type such as an array element type. We presently have to cheat * quite a bit to allow polymorphic arrays of this kind, but perhaps * someday it'll be a less bogus facility. */ anyarray stavalues1; anyarray stavalues2; anyarray stavalues3; anyarray stavalues4; anyarray stavalues5; #endif } FormData_pg_statistic; #define STATISTIC_NUM_SLOTS 5 /* ---------------- * Form_pg_statistic corresponds to a pointer to a tuple with * the format of pg_statistic relation. * ---------------- */ typedef FormData_pg_statistic *Form_pg_statistic; DECLARE_TOAST(pg_statistic, 2840, 2841); DECLARE_UNIQUE_INDEX_PKEY(pg_statistic_relid_att_inh_index, 2696, StatisticRelidAttnumInhIndexId, pg_statistic, btree(starelid oid_ops, staattnum int2_ops, stainherit bool_ops)); MAKE_SYSCACHE(STATRELATTINH, pg_statistic_relid_att_inh_index, 128); DECLARE_FOREIGN_KEY((starelid, staattnum), pg_attribute, (attrelid, attnum)); #ifdef EXPOSE_TO_CLIENT_CODE /* * Several statistical slot "kinds" are defined by core PostgreSQL, as * documented below. Also, custom data types can define their own "kind" * codes by mutual agreement between a custom typanalyze routine and the * selectivity estimation functions of the type's operators. * * Code reading the pg_statistic relation should not assume that a particular * data "kind" will appear in any particular slot. Instead, search the * stakind fields to see if the desired data is available. (The standard * function get_attstatsslot() may be used for this.) * * Note: The pg_stats view needs to be modified whenever a new slot kind is * added to core. */ /* * The present allocation of "kind" codes is: * * 1-99: reserved for assignment by the core PostgreSQL project * (values in this range will be documented in this file) * 100-199: reserved for assignment by the PostGIS project * (values to be documented in PostGIS documentation) * 200-299: reserved for assignment by the ESRI ST_Geometry project * (values to be documented in ESRI ST_Geometry documentation) * 300-9999: reserved for future public assignments * * For private use you may choose a "kind" code at random in the range * 10000-30000. However, for code that is to be widely disseminated it is * better to obtain a publicly defined "kind" code by request from the * PostgreSQL Global Development Group. */ /* * In a "most common values" slot, staop is the OID of the "=" operator * used to decide whether values are the same or not, and stacoll is the * collation used (same as column's collation). stavalues contains * the K most common non-null values appearing in the column, and stanumbers * contains their frequencies (fractions of total row count). The values * shall be ordered in decreasing frequency. Note that since the arrays are * variable-size, K may be chosen may be chosen at ANALYZE time. Values should * not appear in MCV unless they have been observed to occur more than once; * a unique column will have no MCV slot. */ #define STATISTIC_KIND_MCV 1 /* * A "histogram" slot describes the distribution of scalar data. staop is * the OID of the "<" operator that describes the sort ordering, and stacoll * is the relevant collation. (In theory more than one histogram could appear, * if a datatype has more than one useful sort operator or we care about more * than one collation. Currently the collation will always be that of the * underlying column.) stavalues contains M (>=2) non-null values that * divide the non-null column data values into M-1 bins of approximately equal * population. The first stavalues item is the MIN and the last is the MAX. * stanumbers is not used and should be NULL. IMPORTANT POINT: if an MCV * slot is also provided, then the histogram describes the data distribution * *after removing the values listed in MCV* (thus, it's a "compressed * histogram" in the technical parlance). This allows a more accurate * representation of the distribution of a column with some very-common * values. In a column with only a few distinct values, it's possible that * the MCV list describes the entire data population; in this case the * histogram reduces to empty and should be omitted. */ #define STATISTIC_KIND_HISTOGRAM 2 /* * A "correlation" slot describes the correlation between the physical order * of table tuples and the ordering of data values of this column, as seen * by the "<" operator identified by staop with the collation identified by * stacoll. (As with the histogram, more than one entry could theoretically * appear.) stavalues is not used and should be NULL. stanumbers contains * a single entry, the correlation coefficient between the sequence of data * values and the sequence of their actual tuple positions. The coefficient * ranges from +1 to -1. */ #define STATISTIC_KIND_CORRELATION 3 /* * A "most common elements" slot is similar to a "most common values" slot, * except that it stores the most common non-null *elements* of the column * values. This is useful when the column datatype is an array or some other * type with identifiable elements (for instance, tsvector). staop contains * the equality operator appropriate to the element type, and stacoll * contains the collation to use with it. stavalues contains * the most common element values, and stanumbers their frequencies. Unlike * MCV slots, frequencies are measured as the fraction of non-null rows the * element value appears in, not the frequency of all rows. Also unlike * MCV slots, the values are sorted into the element type's default order * (to support binary search for a particular value). Since this puts the * minimum and maximum frequencies at unpredictable spots in stanumbers, * there are two extra members of stanumbers, holding copies of the minimum * and maximum frequencies. Optionally, there can be a third extra member, * which holds the frequency of null elements (expressed in the same terms: * the fraction of non-null rows that contain at least one null element). If * this member is omitted, the column is presumed to contain no null elements. * * Note: in current usage for tsvector columns, the stavalues elements are of * type text, even though their representation within tsvector is not * exactly text. */ #define STATISTIC_KIND_MCELEM 4 /* * A "distinct elements count histogram" slot describes the distribution of * the number of distinct element values present in each row of an array-type * column. Only non-null rows are considered, and only non-null elements. * staop contains the equality operator appropriate to the element type, * and stacoll contains the collation to use with it. * stavalues is not used and should be NULL. The last member of stanumbers is * the average count of distinct element values over all non-null rows. The * preceding M (>=2) members form a histogram that divides the population of * distinct-elements counts into M-1 bins of approximately equal population. * The first of these is the minimum observed count, and the last the maximum. */ #define STATISTIC_KIND_DECHIST 5 /* * A "length histogram" slot describes the distribution of range lengths in * rows of a range-type column. stanumbers contains a single entry, the * fraction of empty ranges. stavalues is a histogram of non-empty lengths, in * a format similar to STATISTIC_KIND_HISTOGRAM: it contains M (>=2) range * values that divide the column data values into M-1 bins of approximately * equal population. The lengths are stored as float8s, as measured by the * range type's subdiff function. Only non-null, non-empty rows are * considered. */ #define STATISTIC_KIND_RANGE_LENGTH_HISTOGRAM 6 /* * A "bounds histogram" slot is similar to STATISTIC_KIND_HISTOGRAM, but for * a range-type column. stavalues contains M (>=2) range values that divide * the column data values into M-1 bins of approximately equal population. * Unlike a regular scalar histogram, this is actually two histograms combined * into a single array, with the lower bounds of each value forming a * histogram of lower bounds, and the upper bounds a histogram of upper * bounds. Only non-NULL, non-empty ranges are included. */ #define STATISTIC_KIND_BOUNDS_HISTOGRAM 7 #endif /* EXPOSE_TO_CLIENT_CODE */ #endif /* PG_STATISTIC_H */