pg_statistic.h

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/*-------------------------------------------------------------------------
 *
 * pg_statistic.h
 *    definition of the system "statistic" relation (pg_statistic)
 *    along with the relation's initial contents.
 *
 *
 * Portions Copyright (c) 1996-2013, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * src/include/catalog/pg_statistic.h
 *
 * NOTES
 *    the genbki.pl script reads this file and generates .bki
 *    information from the DATA() statements.
 *
 *-------------------------------------------------------------------------
 */
#ifndef PG_STATISTIC_H
#define PG_STATISTIC_H

#include "catalog/genbki.h"

/* ----------------
 *      pg_statistic definition.  cpp turns this into
 *      typedef struct FormData_pg_statistic
 * ----------------
 */
#define StatisticRelationId  2619

CATALOG(pg_statistic,2619) BKI_WITHOUT_OIDS
{
    /* These fields form the unique key for the entry: */
    Oid         starelid;       /* 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 values appear about twice on the average could be represented
     * by stadistinct = -0.5).  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
     *      numbers         float4 array (for statistical values)
     *      values          anyarray (for representations of data values)
     * The ID and operator 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;
    Oid         staop2;
    Oid         staop3;
    Oid         staop4;
    Oid         staop5;

#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;

/* ----------------
 *      compiler constants for pg_statistic
 * ----------------
 */
#define Natts_pg_statistic              26
#define Anum_pg_statistic_starelid      1
#define Anum_pg_statistic_staattnum     2
#define Anum_pg_statistic_stainherit    3
#define Anum_pg_statistic_stanullfrac   4
#define Anum_pg_statistic_stawidth      5
#define Anum_pg_statistic_stadistinct   6
#define Anum_pg_statistic_stakind1      7
#define Anum_pg_statistic_stakind2      8
#define Anum_pg_statistic_stakind3      9
#define Anum_pg_statistic_stakind4      10
#define Anum_pg_statistic_stakind5      11
#define Anum_pg_statistic_staop1        12
#define Anum_pg_statistic_staop2        13
#define Anum_pg_statistic_staop3        14
#define Anum_pg_statistic_staop4        15
#define Anum_pg_statistic_staop5        16
#define Anum_pg_statistic_stanumbers1   17
#define Anum_pg_statistic_stanumbers2   18
#define Anum_pg_statistic_stanumbers3   19
#define Anum_pg_statistic_stanumbers4   20
#define Anum_pg_statistic_stanumbers5   21
#define Anum_pg_statistic_stavalues1    22
#define Anum_pg_statistic_stavalues2    23
#define Anum_pg_statistic_stavalues3    24
#define Anum_pg_statistic_stavalues4    25
#define Anum_pg_statistic_stavalues5    26

/*
 * Currently, five statistical slot "kinds" are defined by core PostgreSQL,
 * as documented below.  Additional "kinds" will probably appear in
 * future to help cope with non-scalar datatypes.  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.)
 */

/*
 * 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.  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 by the statistics collector.  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.  (In theory,
 * more than one histogram could appear, if a datatype has more than one
 * useful sort operator.)  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.  (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.  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.
 * 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 stores as float8s, as measured by the
 * range type's subdiff function. Only non-null 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   /* PG_STATISTIC_H */