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postgis/postgis/gserialized_estimate.c
Paul Ramsey f0e94e2845 Handle selectivity estimation on smaller tables a little less ham-handedly. 
Ensure the histogram ends up with more than one cell per dimension,
allow tune the histogram size a little to allow for larger stats targets
to be effectively handled.
2022-12-13 16:24:57 -08:00

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/**********************************************************************
*
* PostGIS - Spatial Types for PostgreSQL
* http://postgis.net
*
* PostGIS is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 2 of the License, or
* (at your option) any later version.
*
* PostGIS is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with PostGIS. If not, see <http://www.gnu.org/licenses/>.
*
**********************************************************************
*
* Copyright 2012 (C) Paul Ramsey <pramsey@cleverelephant.ca>
*
**********************************************************************/
/**********************************************************************
THEORY OF OPERATION
The ANALYZE command hooks to a callback (gserialized_analyze_nd) that
calculates (compute_gserialized_stats_mode) two histograms of occurances of
features, once for the 2D domain (and the && operator) one for the
ND domain (and the &&& operator).
Queries in PostgreSQL call into the selectivity sub-system to find out
the relative effectiveness of different clauses in sub-setting
relations. Queries with constant arguments call gserialized_gist_sel,
queries with relations on both sides call gserialized_gist_joinsel.
gserialized_gist_sel sums up the values in the histogram that overlap
the contant search box.
gserialized_gist_joinsel sums up the product of the overlapping
cells in each relation's histogram.
Depending on the operator and type, the mode of selectivity calculation
will be 2D or ND.
- geometry && geometry ==> 2D
- geometry &&& geometry ==> ND
- geography && geography ==> ND
The 2D mode is put in effect by retrieving the 2D histogram from the
statistics cache and then allowing the generic ND calculations to
go to work.
TO DO: More testing and examination of the &&& operator and mixed
dimensionality cases. (2D geometry) &&& (3D column), etc.
**********************************************************************/
#include "postgres.h"
#include "access/genam.h"
#include "access/gin.h"
#include "access/gist.h"
#include "access/gist_private.h"
#include "access/gistscan.h"
#if PG_VERSION_NUM < 130000
#include "access/tuptoaster.h" /* For toast_raw_datum_size */
#else
#include "access/detoast.h" /* For toast_raw_datum_size */
#endif
#include "utils/datum.h"
#include "access/heapam.h"
#include "catalog/index.h"
#include "catalog/pg_am.h"
#include "miscadmin.h"
#include "storage/lmgr.h"
#include "catalog/namespace.h"
#include "catalog/indexing.h"
#if PG_VERSION_NUM >= 100000
#include "utils/regproc.h"
#include "utils/varlena.h"
#endif
#include "utils/builtins.h"
#include "utils/datum.h"
#include "utils/snapmgr.h"
#include "utils/fmgroids.h"
#include "funcapi.h"
#include "access/heapam.h"
#include "catalog/pg_type.h"
#include "access/relscan.h"
#include "executor/spi.h"
#include "fmgr.h"
#include "commands/vacuum.h"
#if PG_VERSION_NUM < 120000
#include "nodes/relation.h"
#else
#include "nodes/pathnodes.h"
#endif
#include "parser/parsetree.h"
#include "utils/array.h"
#include "utils/lsyscache.h"
#include "utils/builtins.h"
#include "utils/syscache.h"
#include "utils/rel.h"
#include "utils/selfuncs.h"
#include "../postgis_config.h"
#include "access/htup_details.h"
#include "stringbuffer.h"
#include "liblwgeom.h"
#include "lwgeom_pg.h" /* For debugging macros. */
#include "gserialized_gist.h" /* For index common functions */
#include <math.h>
#if HAVE_IEEEFP_H
#include <ieeefp.h>
#endif
#include <float.h>
#include <string.h>
#include <stdio.h>
#include <ctype.h>
/************************************************************************/
/* Prototypes */
Datum gserialized_gist_joinsel(PG_FUNCTION_ARGS);
Datum gserialized_gist_joinsel_2d(PG_FUNCTION_ARGS);
Datum gserialized_gist_joinsel_nd(PG_FUNCTION_ARGS);
Datum gserialized_gist_sel(PG_FUNCTION_ARGS);
Datum gserialized_gist_sel_2d(PG_FUNCTION_ARGS);
Datum gserialized_gist_sel_nd(PG_FUNCTION_ARGS);
Datum gserialized_analyze_nd(PG_FUNCTION_ARGS);
Datum gserialized_estimated_extent(PG_FUNCTION_ARGS);
Datum _postgis_gserialized_index_extent(PG_FUNCTION_ARGS);
Datum _postgis_gserialized_sel(PG_FUNCTION_ARGS);
Datum _postgis_gserialized_joinsel(PG_FUNCTION_ARGS);
Datum _postgis_gserialized_stats(PG_FUNCTION_ARGS);
/* Local prototypes */
static Oid table_get_spatial_index(Oid tbl_oid, text *col, int *key_type, int *att_num);
static GBOX * spatial_index_read_extent(Oid idx_oid, int key_type, int att_num);
/* Other prototypes */
float8 gserialized_joinsel_internal(PlannerInfo *root, List *args, JoinType jointype, int mode);
float8 gserialized_sel_internal(PlannerInfo *root, List *args, int varRelid, int mode);
/* Old Prototype */
Datum geometry_estimated_extent(PG_FUNCTION_ARGS);
/*
* Assign a number to the n-dimensional statistics kind
*
* tgl suggested:
*
* 1-100: reserved for assignment by the core Postgres project
* 100-199: reserved for assignment by PostGIS
* 200-9999: reserved for other globally-known stats kinds
* 10000-32767: reserved for private site-local use
*/
#define STATISTIC_KIND_ND 102
#define STATISTIC_KIND_2D 103
/*
* Postgres does not pin its slots and uses them as they come.
* We need to preserve its Correlation for brin to work
* 0 may be MCV
* 1 may be Histogram
* 2 may be Correlation
* We take 3 and 4.
*/
#define STATISTIC_SLOT_ND 3
#define STATISTIC_SLOT_2D 4
/*
* The SD factor restricts the side of the statistics histogram
* based on the standard deviation of the extent of the data.
* SDFACTOR is the number of standard deviations from the mean
* the histogram will extend.
*/
#define SDFACTOR 3.25
/**
* The maximum number of dimensions our code can handle.
* We'll use this to statically allocate a bunch of
* arrays below.
*/
#define ND_DIMS 4
/**
* Minimum width of a dimension that we'll bother trying to
* compute statistics on. Bearing in mind we have no control
* over units, but noting that for geographics, 10E-5 is in the
* range of meters, we go lower than that.
*/
#define MIN_DIMENSION_WIDTH 0.000000001
/**
* Maximum width of a dimension that we'll bother trying to
* compute statistics on.
*/
#define MAX_DIMENSION_WIDTH 1.0E+20
/**
* Default geometry selectivity factor
*/
#define DEFAULT_ND_SEL 0.0001
#define DEFAULT_ND_JOINSEL 0.001
/**
* More modest fallback selectivity factor
*/
#define FALLBACK_ND_SEL 0.2
#define FALLBACK_ND_JOINSEL 0.3
/**
* N-dimensional box type for calculations, to avoid doing
* explicit axis conversions from GBOX in all calculations
* at every step.
*/
typedef struct ND_BOX_T
{
float4 min[ND_DIMS];
float4 max[ND_DIMS];
} ND_BOX;
/**
* N-dimensional box index type
*/
typedef struct ND_IBOX_T
{
int min[ND_DIMS];
int max[ND_DIMS];
} ND_IBOX;
/**
* N-dimensional statistics structure. Well, actually
* four-dimensional, but set up to handle arbirary dimensions
* if necessary (really, we just want to get the 2,3,4-d cases
* into one shared piece of code).
*/
typedef struct ND_STATS_T
{
/* Dimensionality of the histogram. */
float4 ndims;
/* Size of n-d histogram in each dimension. */
float4 size[ND_DIMS];
/* Lower-left (min) and upper-right (max) spatial bounds of histogram. */
ND_BOX extent;
/* How many rows in the table itself? */
float4 table_features;
/* How many rows were in the sample that built this histogram? */
float4 sample_features;
/* How many not-Null/Empty features were in the sample? */
float4 not_null_features;
/* How many features actually got sampled in the histogram? */
float4 histogram_features;
/* How many cells in histogram? (sizex*sizey*sizez*sizem) */
float4 histogram_cells;
/* How many cells did those histogram features cover? */
/* Since we are pro-rating coverage, this number should */
/* now always equal histogram_features */
float4 cells_covered;
/* Variable length # of floats for histogram */
float4 value[1];
} ND_STATS;
typedef struct {
/* Saved state from std_typanalyze() */
AnalyzeAttrComputeStatsFunc std_compute_stats;
void *std_extra_data;
} GserializedAnalyzeExtraData;
/**
* Given that geodetic boxes are X/Y/Z regardless of the
* underlying geometry dimensionality and other boxes
* are guided by HAS_Z/HAS_M in their dimesionality,
* we have a little utility function to make it easy.
*/
static int
gbox_ndims(const GBOX* gbox)
{
int dims = 2;
if ( FLAGS_GET_GEODETIC(gbox->flags) )
return 3;
if ( FLAGS_GET_Z(gbox->flags) )
dims++;
if ( FLAGS_GET_M(gbox->flags) )
dims++;
return dims;
}
/**
* Utility function to see if the first
* letter of the mode argument is 'N'. Used
* by the _postgis_* functions.
*/
static int
text_p_get_mode(const text *txt)
{
int mode = 2;
char *modestr;
if (VARSIZE_ANY_EXHDR(txt) <= 0)
return mode;
modestr = (char*)VARDATA(txt);
if ( modestr[0] == 'N' )
mode = 0;
return mode;
}
/**
* Integer comparison function for qsort
*/
static int
cmp_int (const void *a, const void *b)
{
int ia = *((const int*)a);
int ib = *((const int*)b);
if ( ia == ib )
return 0;
else if ( ia > ib )
return 1;
else
return -1;
}
/**
* The difference between the fourth and first quintile values,
* the "inter-quintile range"
*/
// static int
// range_quintile(int *vals, int nvals)
// {
// qsort(vals, nvals, sizeof(int), cmp_int);
// return vals[4*nvals/5] - vals[nvals/5];
// }
/**
* Lowest and highest bin values
*/
static int
range_full(int *vals, int nvals)
{
qsort(vals, nvals, sizeof(int), cmp_int);
return vals[nvals-1] - vals[0];
}
/**
* Given double array, return sum of values.
*/
static double
total_double(const double *vals, int nvals)
{
int i;
float total = 0;
/* Calculate total */
for ( i = 0; i < nvals; i++ )
total += vals[i];
return total;
}
#if POSTGIS_DEBUG_LEVEL >= 3
/**
* Given int array, return sum of values.
*/
static int
total_int(const int *vals, int nvals)
{
int i;
int total = 0;
/* Calculate total */
for ( i = 0; i < nvals; i++ )
total += vals[i];
return total;
}
/**
* The average of an array of integers.
*/
static double
avg(const int *vals, int nvals)
{
int t = total_int(vals, nvals);
return (double)t / (double)nvals;
}
/**
* The standard deviation of an array of integers.
*/
static double
stddev(const int *vals, int nvals)
{
int i;
double sigma2 = 0;
double mean = avg(vals, nvals);
/* Calculate sigma2 */
for ( i = 0; i < nvals; i++ )
{
double v = (double)(vals[i]);
sigma2 += (mean - v) * (mean - v);
}
return sqrt(sigma2 / nvals);
}
#endif /* POSTGIS_DEBUG_LEVEL >= 3 */
/**
* Given a position in the n-d histogram (i,j,k) return the
* position in the 1-d values array.
*/
static int
nd_stats_value_index(const ND_STATS *stats, int *indexes)
{
int d;
int accum = 1, vdx = 0;
/* Calculate the index into the 1-d values array that the (i,j,k,l) */
/* n-d histogram coordinate implies. */
/* index = x + y * sizex + z * sizex * sizey + m * sizex * sizey * sizez */
for ( d = 0; d < (int)(stats->ndims); d++ )
{
int size = (int)(stats->size[d]);
if ( indexes[d] < 0 || indexes[d] >= size )
{
POSTGIS_DEBUGF(3, " bad index at (%d, %d)", indexes[0], indexes[1]);
return -1;
}
vdx += indexes[d] * accum;
accum *= size;
}
return vdx;
}
/**
* Convert an #ND_BOX to a JSON string for printing
*/
static char*
nd_box_to_json(const ND_BOX *nd_box, int ndims)
{
char *rv;
int i;
stringbuffer_t *sb = stringbuffer_create();
stringbuffer_append(sb, "{\"min\":[");
for ( i = 0; i < ndims; i++ )
{
if ( i ) stringbuffer_append(sb, ",");
stringbuffer_aprintf(sb, "%.6g", nd_box->min[i]);
}
stringbuffer_append(sb, "],\"max\":[");
for ( i = 0; i < ndims; i++ )
{
if ( i ) stringbuffer_append(sb, ",");
stringbuffer_aprintf(sb, "%.6g", nd_box->max[i]);
}
stringbuffer_append(sb, "]}");
rv = stringbuffer_getstringcopy(sb);
stringbuffer_destroy(sb);
return rv;
}
/**
* Convert an #ND_STATS to a JSON representation for
* external use.
*/
static char*
nd_stats_to_json(const ND_STATS *nd_stats)
{
char *json_extent, *str;
int d;
stringbuffer_t *sb = stringbuffer_create();
int ndims = (int)roundf(nd_stats->ndims);
stringbuffer_append(sb, "{");
stringbuffer_aprintf(sb, "\"ndims\":%d,", ndims);
/* Size */
stringbuffer_append(sb, "\"size\":[");
for ( d = 0; d < ndims; d++ )
{
if ( d ) stringbuffer_append(sb, ",");
stringbuffer_aprintf(sb, "%d", (int)roundf(nd_stats->size[d]));
}
stringbuffer_append(sb, "],");
/* Extent */
json_extent = nd_box_to_json(&(nd_stats->extent), ndims);
stringbuffer_aprintf(sb, "\"extent\":%s,", json_extent);
pfree(json_extent);
stringbuffer_aprintf(sb, "\"table_features\":%d,", (int)roundf(nd_stats->table_features));
stringbuffer_aprintf(sb, "\"sample_features\":%d,", (int)roundf(nd_stats->sample_features));
stringbuffer_aprintf(sb, "\"not_null_features\":%d,", (int)roundf(nd_stats->not_null_features));
stringbuffer_aprintf(sb, "\"histogram_features\":%d,", (int)roundf(nd_stats->histogram_features));
stringbuffer_aprintf(sb, "\"histogram_cells\":%d,", (int)roundf(nd_stats->histogram_cells));
stringbuffer_aprintf(sb, "\"cells_covered\":%d", (int)roundf(nd_stats->cells_covered));
stringbuffer_append(sb, "}");
str = stringbuffer_getstringcopy(sb);
stringbuffer_destroy(sb);
return str;
}
/**
* Create a printable view of the #ND_STATS histogram.
* Caller is responsible for freeing.
* Currently only prints first two dimensions.
*/
static char*
nd_stats_to_grid(const ND_STATS *stats)
{
char *rv;
int j, k;
int sizex = (int)roundf(stats->size[0]);
int sizey = (int)roundf(stats->size[1]);
stringbuffer_t *sb = stringbuffer_create();
for ( k = 0; k < sizey; k++ )
{
for ( j = 0; j < sizex; j++ )
{
stringbuffer_aprintf(sb, "%3d ", (int)roundf(stats->value[j + k*sizex]));
}
stringbuffer_append(sb, "\n");
}
rv = stringbuffer_getstringcopy(sb);
stringbuffer_destroy(sb);
return rv;
}
/** Expand the bounds of target to include source */
static int
nd_box_merge(const ND_BOX *source, ND_BOX *target)
{
int d;
for ( d = 0; d < ND_DIMS; d++ )
{
target->min[d] = Min(target->min[d], source->min[d]);
target->max[d] = Max(target->max[d], source->max[d]);
}
return true;
}
/** Zero out an ND_BOX */
static int
nd_box_init(ND_BOX *a)
{
memset(a, 0, sizeof(ND_BOX));
return true;
}
/**
* Prepare an ND_BOX for bounds calculation:
* set the maxes to the smallest thing possible and
* the mins to the largest.
*/
static int
nd_box_init_bounds(ND_BOX *a)
{
int d;
for ( d = 0; d < ND_DIMS; d++ )
{
a->min[d] = FLT_MAX;
a->max[d] = -1 * FLT_MAX;
}
return true;
}
/** Set the values of an #ND_BOX from a #GBOX */
static void
nd_box_from_gbox(const GBOX *gbox, ND_BOX *nd_box)
{
volatile int d = 0;
POSTGIS_DEBUGF(3, " %s", gbox_to_string(gbox));
nd_box_init(nd_box);
nd_box->min[d] = gbox->xmin;
nd_box->max[d] = gbox->xmax;
d++;
nd_box->min[d] = gbox->ymin;
nd_box->max[d] = gbox->ymax;
d++;
if ( FLAGS_GET_GEODETIC(gbox->flags) )
{
nd_box->min[d] = gbox->zmin;
nd_box->max[d] = gbox->zmax;
return;
}
if ( FLAGS_GET_Z(gbox->flags) )
{
nd_box->min[d] = gbox->zmin;
nd_box->max[d] = gbox->zmax;
d++;
}
if ( FLAGS_GET_M(gbox->flags) )
{
nd_box->min[d] = gbox->mmin;
nd_box->max[d] = gbox->mmax;
d++;
}
return;
}
/**
* Return true if #ND_BOX a overlaps b, false otherwise.
*/
static int
nd_box_intersects(const ND_BOX *a, const ND_BOX *b, int ndims)
{
int d;
for ( d = 0; d < ndims; d++ )
{
if ( (a->min[d] > b->max[d]) || (a->max[d] < b->min[d]) )
return false;
}
return true;
}
/**
* Return true if #ND_BOX a contains b, false otherwise.
*/
static int
nd_box_contains(const ND_BOX *a, const ND_BOX *b, int ndims)
{
int d;
for ( d = 0; d < ndims; d++ )
{
if ( ! ((a->min[d] < b->min[d]) && (a->max[d] > b->max[d])) )
return false;
}
return true;
}
/**
* Expand an #ND_BOX ever so slightly. Expand parameter is the proportion
* of total width to add.
*/
static int
nd_box_expand(ND_BOX *nd_box, double expansion_factor)
{
int d;
double size;
for ( d = 0; d < ND_DIMS; d++ )
{
size = nd_box->max[d] - nd_box->min[d];
/* Avoid expanding boxes that are either too wide or too narrow*/
if (size < MIN_DIMENSION_WIDTH || size > MAX_DIMENSION_WIDTH)
continue;
nd_box->min[d] -= size * expansion_factor / 2;
nd_box->max[d] += size * expansion_factor / 2;
}
return true;
}
/**
* What stats cells overlap with this ND_BOX? Put the lowest cell
* addresses in ND_IBOX->min and the highest in ND_IBOX->max
*/
static inline int
nd_box_overlap(const ND_STATS *nd_stats, const ND_BOX *nd_box, ND_IBOX *nd_ibox)
{
int d;
POSTGIS_DEBUGF(4, " nd_box: %s", nd_box_to_json(nd_box, nd_stats->ndims));
/* Initialize ibox */
memset(nd_ibox, 0, sizeof(ND_IBOX));
/* In each dimension... */
for ( d = 0; d < nd_stats->ndims; d++ )
{
double smin = nd_stats->extent.min[d];
double smax = nd_stats->extent.max[d];
double width = smax - smin;
if (width < MIN_DIMENSION_WIDTH)
{
nd_ibox->min[d] = nd_ibox->max[d] = nd_stats->extent.min[d];
}
else
{
int size = (int)roundf(nd_stats->size[d]);
/* ... find cells the box overlaps with in this dimension */
nd_ibox->min[d] = floor(size * (nd_box->min[d] - smin) / width);
nd_ibox->max[d] = floor(size * (nd_box->max[d] - smin) / width);
POSTGIS_DEBUGF(5, " stats: dim %d: min %g: max %g: width %g", d, smin, smax, width);
POSTGIS_DEBUGF(5, " overlap: dim %d: (%d, %d)", d, nd_ibox->min[d], nd_ibox->max[d]);
/* Push any out-of range values into range */
nd_ibox->min[d] = Max(nd_ibox->min[d], 0);
nd_ibox->max[d] = Min(nd_ibox->max[d], size - 1);
}
}
return true;
}
/**
* Returns the proportion of b2 that is covered by b1.
*/
static inline double
nd_box_ratio(const ND_BOX *b1, const ND_BOX *b2, int ndims)
{
int d;
bool covered = true;
double ivol = 1.0;
double vol2 = 1.0;
for ( d = 0 ; d < ndims; d++ )
{
if ( b1->max[d] <= b2->min[d] || b1->min[d] >= b2->max[d] )
return 0.0; /* Disjoint */
if ( b1->min[d] > b2->min[d] || b1->max[d] < b2->max[d] )
covered = false;
}
if ( covered )
return 1.0;
for ( d = 0; d < ndims; d++ )
{
double width2 = b2->max[d] - b2->min[d];
double imin, imax, iwidth;
vol2 *= width2;
imin = Max(b1->min[d], b2->min[d]);
imax = Min(b1->max[d], b2->max[d]);
iwidth = imax - imin;
iwidth = Max(0.0, iwidth);
ivol *= iwidth;
}
if ( vol2 == 0.0 )
return vol2;
return ivol / vol2;
}
/* How many bins shall we use in figuring out the distribution? */
#define MAX_NUM_BINS 50
#define BIN_MIN_SIZE 10
/**
* Calculate how much a set of boxes is homogenously distributed
* or contentrated within one dimension, returning the range_quintile of
* of the overlap counts per cell in a uniform
* partition of the extent of the dimension.
* A uniform distribution of counts will have a small range
* and will require few cells in a selectivity histogram.
* A diverse distribution of counts will have a larger range
* and require more cells in a selectivity histogram (to
* distinguish between areas of feature density and areas
* of feature sparseness. This measurement should help us
* identify cases like X/Y/Z data where there is lots of variability
* in density in X/Y (diversely in a multi-kilometer range) and far
* less in Z (in a few-hundred meter range).
*/
static int
nd_box_array_distribution(const ND_BOX **nd_boxes, int num_boxes, const ND_BOX *extent, int ndims, double *distribution)
{
int d, i, k, range;
int *counts;
double smin, smax; /* Spatial min, spatial max */
double swidth; /* Spatial width of dimension */
#if POSTGIS_DEBUG_LEVEL >= 3
double average, sdev, sdev_ratio;
#endif
int bmin, bmax; /* Bin min, bin max */
const ND_BOX *ndb;
int num_bins = Min(Max(2, num_boxes/BIN_MIN_SIZE), MAX_NUM_BINS);
counts = palloc0(num_bins * sizeof(int));
/* For each dimension... */
for ( d = 0; d < ndims; d++ )
{
/* Initialize counts for this dimension */
memset(counts, 0, num_bins * sizeof(int));
smin = extent->min[d];
smax = extent->max[d];
swidth = smax - smin;
/* Don't try and calculate distribution of overly narrow */
/* or overly wide dimensions. Here we're being pretty geographical, */
/* expecting "normal" planar or geographic coordinates. */
/* Otherwise we have to "handle" +/- Inf bounded features and */
/* the assumptions needed for that are as bad as this hack. */
if ( swidth < MIN_DIMENSION_WIDTH || swidth > MAX_DIMENSION_WIDTH )
{
distribution[d] = 0;
continue;
}
/* Sum up the overlaps of each feature with the dimensional bins */
for ( i = 0; i < num_boxes; i++ )
{
double minoffset, maxoffset;
/* Skip null entries */
ndb = nd_boxes[i];
if ( ! ndb ) continue;
/* Where does box fall relative to the working range */
minoffset = ndb->min[d] - smin;
maxoffset = ndb->max[d] - smin;
/* Skip boxes that our outside our working range */
if ( minoffset < 0 || minoffset > swidth ||
maxoffset < 0 || maxoffset > swidth )
{
continue;
}
/* What bins does this range correspond to? */
bmin = floor(num_bins * minoffset / swidth);
bmax = floor(num_bins * maxoffset / swidth);
/* Should only happen when maxoffset==swidth */
if (bmax >= num_bins)
bmax = num_bins-1;
POSTGIS_DEBUGF(4, " dimension %d, feature %d: bin %d to bin %d", d, i, bmin, bmax);
/* Increment the counts in all the bins this feature overlaps */
for ( k = bmin; k <= bmax; k++ )
{
counts[k] += 1;
}
}
/* How dispersed is the distribution of features across bins? */
// range = range_quintile(counts, num_bins);
range = range_full(counts, num_bins);
#if POSTGIS_DEBUG_LEVEL >= 3
average = avg(counts, num_bins);
sdev = stddev(counts, num_bins);
sdev_ratio = sdev/average;
POSTGIS_DEBUGF(3, " dimension %d: range = %d", d, range);
POSTGIS_DEBUGF(3, " dimension %d: average = %.6g", d, average);
POSTGIS_DEBUGF(3, " dimension %d: stddev = %.6g", d, sdev);
POSTGIS_DEBUGF(3, " dimension %d: stddev_ratio = %.6g", d, sdev_ratio);
#endif
distribution[d] = range;
}
pfree(counts);
return true;
}
/**
* Given an n-d index array (counter), and a domain to increment it
* in (ibox) increment it by one, unless it's already at the max of
* the domain, in which case return false.
*/
static inline int
nd_increment(ND_IBOX *ibox, int ndims, int *counter)
{
int d = 0;
while ( d < ndims )
{
if ( counter[d] < ibox->max[d] )
{
counter[d] += 1;
break;
}
counter[d] = ibox->min[d];
d++;
}
/* That's it, cannot increment any more! */
if ( d == ndims )
return false;
/* Increment complete! */
return true;
}
static ND_STATS*
pg_nd_stats_from_tuple(HeapTuple stats_tuple, int mode)
{
int stats_kind = STATISTIC_KIND_ND;
int rv;
ND_STATS *nd_stats;
/* If we're in 2D mode, set the kind appropriately */
if ( mode == 2 ) stats_kind = STATISTIC_KIND_2D;
/* Then read the geom status histogram from that */
{
AttStatsSlot sslot;
rv = get_attstatsslot(&sslot, stats_tuple, stats_kind, InvalidOid,
ATTSTATSSLOT_NUMBERS);
if ( ! rv ) {
POSTGIS_DEBUGF(2, "no slot of kind %d in stats tuple", stats_kind);
return NULL;
}
/* Clone the stats here so we can release the attstatsslot immediately */
nd_stats = palloc(sizeof(float4) * sslot.nnumbers);
memcpy(nd_stats, sslot.numbers, sizeof(float4) * sslot.nnumbers);
free_attstatsslot(&sslot);
}
return nd_stats;
}
/**
* Pull the stats object from the PgSQL system catalogs. Used
* by the selectivity functions and the debugging functions.
*/
static ND_STATS*
pg_get_nd_stats(const Oid table_oid, AttrNumber att_num, int mode, bool only_parent)
{
HeapTuple stats_tuple = NULL;
ND_STATS *nd_stats;
/* First pull the stats tuple for the whole tree */
if ( ! only_parent )
{
POSTGIS_DEBUGF(2, "searching whole tree stats for \"%s\"", get_rel_name(table_oid)? get_rel_name(table_oid) : "NULL");
stats_tuple = SearchSysCache3(STATRELATTINH, ObjectIdGetDatum(table_oid), Int16GetDatum(att_num), BoolGetDatum(true));
if ( stats_tuple )
POSTGIS_DEBUGF(2, "found whole tree stats for \"%s\"", get_rel_name(table_oid)? get_rel_name(table_oid) : "NULL");
}
/* Fall-back to main table stats only, if not found for whole tree or explicitly ignored */
if ( only_parent || ! stats_tuple )
{
POSTGIS_DEBUGF(2, "searching parent table stats for \"%s\"", get_rel_name(table_oid)? get_rel_name(table_oid) : "NULL");
stats_tuple = SearchSysCache3(STATRELATTINH, ObjectIdGetDatum(table_oid), Int16GetDatum(att_num), BoolGetDatum(false));
if ( stats_tuple )
POSTGIS_DEBUGF(2, "found parent table stats for \"%s\"", get_rel_name(table_oid)? get_rel_name(table_oid) : "NULL");
}
if ( ! stats_tuple )
{
POSTGIS_DEBUGF(2, "stats for \"%s\" do not exist", get_rel_name(table_oid)? get_rel_name(table_oid) : "NULL");
return NULL;
}
nd_stats = pg_nd_stats_from_tuple(stats_tuple, mode);
ReleaseSysCache(stats_tuple);
if ( ! nd_stats )
{
POSTGIS_DEBUGF(2,
"histogram for attribute %d of table \"%s\" does not exist?",
att_num, get_rel_name(table_oid));
}
return nd_stats;
}
/**
* Pull the stats object from the PgSQL system catalogs. The
* debugging functions are taking human input (table names)
* and columns, so we have to look those up first.
* In case of parent tables whith INHERITS, when "only_parent"
* is true this function only searchs for stats in the parent
* table ignoring any statistic collected from the children.
*/
static ND_STATS*
pg_get_nd_stats_by_name(const Oid table_oid, const text *att_text, int mode, bool only_parent)
{
const char *att_name = text_to_cstring(att_text);
AttrNumber att_num;
/* We know the name? Look up the num */
if ( att_text )
{
/* Get the attribute number */
att_num = get_attnum(table_oid, att_name);
if ( ! att_num ) {
elog(ERROR, "attribute \"%s\" does not exist", att_name);
return NULL;
}
}
else
{
elog(ERROR, "attribute name is null");
return NULL;
}
return pg_get_nd_stats(table_oid, att_num, mode, only_parent);
}
/**
* Given two statistics histograms, what is the selectivity
* of a join driven by the && or &&& operator?
*
* Join selectivity is defined as the number of rows returned by the
* join operator divided by the number of rows that an
* unconstrained join would return (nrows1*nrows2).
*
* To get the estimate of join rows, we walk through the cells
* of one histogram, and multiply the cell value by the
* proportion of the cells in the other histogram the cell
* overlaps: val += val1 * ( val2 * overlap_ratio )
*/
static float8
estimate_join_selectivity(const ND_STATS *s1, const ND_STATS *s2)
{
int ncells1, ncells2;
int ndims1, ndims2, ndims;
double ntuples_max;
double ntuples_not_null1, ntuples_not_null2;
ND_BOX extent1, extent2;
ND_IBOX ibox1, ibox2;
int at1[ND_DIMS];
int at2[ND_DIMS];
double min1[ND_DIMS];
double width1[ND_DIMS];
double cellsize1[ND_DIMS];
int size2[ND_DIMS];
double min2[ND_DIMS];
double width2[ND_DIMS];
double cellsize2[ND_DIMS];
int size1[ND_DIMS];
int d;
double val = 0;
float8 selectivity;
/* Drop out on null inputs */
if ( ! ( s1 && s2 ) )
{
elog(NOTICE, " estimate_join_selectivity called with null inputs");
return FALLBACK_ND_SEL;
}
/* We need to know how many cells each side has... */
ncells1 = (int)roundf(s1->histogram_cells);
ncells2 = (int)roundf(s2->histogram_cells);
/* ...so that we can drive the summation loop with the smaller histogram. */
if ( ncells1 > ncells2 )
{
const ND_STATS *stats_tmp = s1;
s1 = s2;
s2 = stats_tmp;
}
POSTGIS_DEBUGF(3, "s1: %s", nd_stats_to_json(s1));
POSTGIS_DEBUGF(3, "s2: %s", nd_stats_to_json(s2));
/* Re-read that info after the swap */
ncells1 = (int)roundf(s1->histogram_cells);
ncells2 = (int)roundf(s2->histogram_cells);
/* Q: What's the largest possible join size these relations can create? */
/* A: The product of the # of non-null rows in each relation. */
ntuples_not_null1 = s1->table_features * (s1->not_null_features / s1->sample_features);
ntuples_not_null2 = s2->table_features * (s2->not_null_features / s2->sample_features);
ntuples_max = ntuples_not_null1 * ntuples_not_null2;
/* Get the ndims as ints */
ndims1 = (int)roundf(s1->ndims);
ndims2 = (int)roundf(s2->ndims);
ndims = Max(ndims1, ndims2);
/* Get the extents */
extent1 = s1->extent;
extent2 = s2->extent;
/* If relation stats do not intersect, join is very very selective. */
if ( ! nd_box_intersects(&extent1, &extent2, ndims) )
{
POSTGIS_DEBUG(3, "relation stats do not intersect, returning 0");
PG_RETURN_FLOAT8(0.0);
}
/*
* First find the index range of the part of the smaller
* histogram that overlaps the larger one.
*/
if ( ! nd_box_overlap(s1, &extent2, &ibox1) )
{
POSTGIS_DEBUG(3, "could not calculate overlap of relations");
PG_RETURN_FLOAT8(FALLBACK_ND_JOINSEL);
}
/* Initialize counters / constants on s1 */
for ( d = 0; d < ndims1; d++ )
{
at1[d] = ibox1.min[d];
min1[d] = s1->extent.min[d];
width1[d] = s1->extent.max[d] - s1->extent.min[d];
size1[d] = (int)roundf(s1->size[d]);
cellsize1[d] = width1[d] / size1[d];
}
/* Initialize counters / constants on s2 */
for ( d = 0; d < ndims2; d++ )
{
min2[d] = s2->extent.min[d];
width2[d] = s2->extent.max[d] - s2->extent.min[d];
size2[d] = (int)roundf(s2->size[d]);
cellsize2[d] = width2[d] / size2[d];
}
/* For each affected cell of s1... */
do
{
double val1;
/* Construct the bounds of this cell */
ND_BOX nd_cell1;
nd_box_init(&nd_cell1);
for ( d = 0; d < ndims1; d++ )
{
nd_cell1.min[d] = min1[d] + (at1[d]+0) * cellsize1[d];
nd_cell1.max[d] = min1[d] + (at1[d]+1) * cellsize1[d];
}
/* Find the cells of s2 that cell1 overlaps.. */
nd_box_overlap(s2, &nd_cell1, &ibox2);
/* Initialize counter */
for ( d = 0; d < ndims2; d++ )
{
at2[d] = ibox2.min[d];
}
POSTGIS_DEBUGF(3, "at1 %d,%d %s", at1[0], at1[1], nd_box_to_json(&nd_cell1, ndims1));
/* Get the value at this cell */
val1 = s1->value[nd_stats_value_index(s1, at1)];
/* For each overlapped cell of s2... */
do
{
double ratio2;
double val2;
/* Construct the bounds of this cell */
ND_BOX nd_cell2;
nd_box_init(&nd_cell2);
for ( d = 0; d < ndims2; d++ )
{
nd_cell2.min[d] = min2[d] + (at2[d]+0) * cellsize2[d];
nd_cell2.max[d] = min2[d] + (at2[d]+1) * cellsize2[d];
}
POSTGIS_DEBUGF(3, " at2 %d,%d %s", at2[0], at2[1], nd_box_to_json(&nd_cell2, ndims2));
/* Calculate overlap ratio of the cells */
ratio2 = nd_box_ratio(&nd_cell1, &nd_cell2, Max(ndims1, ndims2));
/* Multiply the cell counts, scaled by overlap ratio */
val2 = s2->value[nd_stats_value_index(s2, at2)];
POSTGIS_DEBUGF(3, " val1 %.6g val2 %.6g ratio %.6g", val1, val2, ratio2);
val += val1 * (val2 * ratio2);
}
while ( nd_increment(&ibox2, ndims2, at2) );
}
while( nd_increment(&ibox1, ndims1, at1) );
POSTGIS_DEBUGF(3, "val of histogram = %g", val);
/*
* In order to compare our total cell count "val" to the
* ntuples_max, we need to scale val up to reflect a full
* table estimate. So, multiply by ratio of table size to
* sample size.
*/
val *= (s1->table_features / s1->sample_features);
val *= (s2->table_features / s2->sample_features);
POSTGIS_DEBUGF(3, "val scaled to full table size = %g", val);
/*
* Because the cell counts are over-determined due to
* double counting of features that overlap multiple cells
* (see the compute_gserialized_stats routine)
* we also have to scale our cell count "val" *down*
* to adjust for the double counting.
*/
// val /= (s1->cells_covered / s1->histogram_features);
// val /= (s2->cells_covered / s2->histogram_features);
/*
* Finally, the selectivity is the estimated number of
* rows to be returned divided by the maximum possible
* number of rows that can be returned.
*/
selectivity = val / ntuples_max;
/* Guard against over-estimates and crazy numbers :) */
if ( isnan(selectivity) || ! isfinite(selectivity) || selectivity < 0.0 )
{
selectivity = DEFAULT_ND_JOINSEL;
}
else if ( selectivity > 1.0 )
{
selectivity = 1.0;
}
return selectivity;
}
/**
* For (geometry &&& geometry) and (geography && geography)
* we call into the N-D mode.
*/
PG_FUNCTION_INFO_V1(gserialized_gist_joinsel_nd);
Datum gserialized_gist_joinsel_nd(PG_FUNCTION_ARGS)
{
PG_RETURN_DATUM(DirectFunctionCall5(
gserialized_gist_joinsel,
PG_GETARG_DATUM(0), PG_GETARG_DATUM(1),
PG_GETARG_DATUM(2), PG_GETARG_DATUM(3),
Int32GetDatum(0) /* ND mode */
));
}
/**
* For (geometry && geometry)
* we call into the 2-D mode.
*/
PG_FUNCTION_INFO_V1(gserialized_gist_joinsel_2d);
Datum gserialized_gist_joinsel_2d(PG_FUNCTION_ARGS)
{
PG_RETURN_DATUM(DirectFunctionCall5(
gserialized_gist_joinsel,
PG_GETARG_DATUM(0), PG_GETARG_DATUM(1),
PG_GETARG_DATUM(2), PG_GETARG_DATUM(3),
Int32GetDatum(2) /* 2D mode */
));
}
double
gserialized_joinsel_internal(PlannerInfo *root, List *args, JoinType jointype, int mode)
{
float8 selectivity;
Oid relid1, relid2;
ND_STATS *stats1, *stats2;
Node *arg1 = (Node*) linitial(args);
Node *arg2 = (Node*) lsecond(args);
Var *var1 = (Var*) arg1;
Var *var2 = (Var*) arg2;
POSTGIS_DEBUGF(2, "%s: entered function", __func__);
/* We only do column joins right now, no functional joins */
/* TODO: handle g1 && ST_Expand(g2) */
if (!IsA(arg1, Var) || !IsA(arg2, Var))
{
POSTGIS_DEBUGF(1, "%s called with arguments that are not column references", __func__);
return DEFAULT_ND_JOINSEL;
}
/* What are the Oids of our tables/relations? */
relid1 = rt_fetch(var1->varno, root->parse->rtable)->relid;
relid2 = rt_fetch(var2->varno, root->parse->rtable)->relid;
/* Pull the stats from the stats system. */
stats1 = pg_get_nd_stats(relid1, var1->varattno, mode, false);
stats2 = pg_get_nd_stats(relid2, var2->varattno, mode, false);
/* If we can't get stats, we have to stop here! */
if (!stats1)
{
POSTGIS_DEBUGF(2, "%s: cannot find stats for \"%s\"", __func__, get_rel_name(relid2) ? get_rel_name(relid2) : "NULL");
return DEFAULT_ND_JOINSEL;
}
else if (!stats2)
{
POSTGIS_DEBUGF(2, "%s: cannot find stats for \"%s\"", __func__, get_rel_name(relid2) ? get_rel_name(relid2) : "NULL");
return DEFAULT_ND_JOINSEL;
}
selectivity = estimate_join_selectivity(stats1, stats2);
POSTGIS_DEBUGF(2, "got selectivity %g", selectivity);
pfree(stats1);
pfree(stats2);
return selectivity;
}
/**
* Join selectivity of the && operator. The selectivity
* is the ratio of the number of rows we think will be
* returned divided the maximum number of rows the join
* could possibly return (the full combinatoric join).
*
* joinsel = estimated_nrows / (totalrows1 * totalrows2)
*/
PG_FUNCTION_INFO_V1(gserialized_gist_joinsel);
Datum gserialized_gist_joinsel(PG_FUNCTION_ARGS)
{
PlannerInfo *root = (PlannerInfo *) PG_GETARG_POINTER(0);
/* Oid operator = PG_GETARG_OID(1); */
List *args = (List *) PG_GETARG_POINTER(2);
JoinType jointype = (JoinType) PG_GETARG_INT16(3);
int mode = PG_GETARG_INT32(4);
POSTGIS_DEBUGF(2, "%s: entered function", __func__);
/* Check length of args and punt on > 2 */
if (list_length(args) != 2)
{
POSTGIS_DEBUGF(2, "%s: got nargs == %d", __func__, list_length(args));
PG_RETURN_FLOAT8(DEFAULT_ND_JOINSEL);
}
/* Only respond to an inner join/unknown context join */
if (jointype != JOIN_INNER)
{
POSTGIS_DEBUGF(1, "%s: jointype %d not supported", __func__, jointype);
PG_RETURN_FLOAT8(DEFAULT_ND_JOINSEL);
}
PG_RETURN_FLOAT8(gserialized_joinsel_internal(root, args, jointype, mode));
}
/**
* The gserialized_analyze_nd sets this function as a
* callback on the stats object when called by the ANALYZE
* command. ANALYZE then gathers the requisite number of
* sample rows and then calls this function.
*
* We could also pass stats->extra_data in from
* gserialized_analyze_nd (things like the column type or
* other stuff from the system catalogs) but so far we
* don't use that capability.
*
* Our job is to build some statistics on the sample data
* for use by operator estimators.
*
* We will populate an n-d histogram using the provided
* sample rows. The selectivity estimators (sel and joinsel)
* can then use the histogram
*/
static void
compute_gserialized_stats_mode(VacAttrStats *stats, AnalyzeAttrFetchFunc fetchfunc,
int sample_rows, double total_rows, int mode)
{
MemoryContext old_context;
int d, i; /* Counters */
int notnull_cnt = 0; /* # not null rows in the sample */
int null_cnt = 0; /* # null rows in the sample */
int histogram_features = 0; /* # rows that actually got counted in the histogram */
ND_STATS *nd_stats; /* Our histogram */
size_t nd_stats_size; /* Size to allocate */
double total_width = 0; /* # of bytes used by sample */
double total_cell_count = 0; /* # of cells in histogram affected by sample */
ND_BOX sum; /* Sum of extents of sample boxes */
ND_BOX avg; /* Avg of extents of sample boxes */
ND_BOX stddev; /* StdDev of extents of sample boxes */
const ND_BOX **sample_boxes; /* ND_BOXes for each of the sample features */
ND_BOX sample_extent; /* Extent of the raw sample */
int histo_size[ND_DIMS]; /* histogram nrows, ncols, etc */
ND_BOX histo_extent; /* Spatial extent of the histogram */
ND_BOX histo_extent_new; /* Temporary variable */
int histo_cells_target; /* Number of cells we will shoot for, given the stats target */
int histo_cells; /* Number of cells in the histogram */
int histo_cells_new = 1; /* Temporary variable */
int ndims = 2; /* Dimensionality of the sample */
int histo_ndims = 0; /* Dimensionality of the histogram */
double sample_distribution[ND_DIMS]; /* How homogeneous is distribution of sample in each axis? */
double total_distribution; /* Total of sample_distribution */
int stats_slot; /* What slot is this data going into? (2D vs ND) */
int stats_kind; /* And this is what? (2D vs ND) */
/* Initialize sum and stddev */
nd_box_init(&sum);
nd_box_init(&stddev);
nd_box_init(&avg);
nd_box_init(&histo_extent);
nd_box_init(&histo_extent_new);
/*
* This is where gserialized_analyze_nd
* should put its' custom parameters.
*/
/* void *mystats = stats->extra_data; */
POSTGIS_DEBUG(2, "compute_gserialized_stats called");
POSTGIS_DEBUGF(3, " # sample_rows: %d", sample_rows);
POSTGIS_DEBUGF(3, " estimate of total_rows: %.6g", total_rows);
/*
* We might need less space, but don't think
* its worth saving...
*/
sample_boxes = palloc(sizeof(ND_BOX*) * sample_rows);
/*
* First scan:
* o read boxes
* o find dimensionality of the sample
* o find extent of the sample
* o count null-infinite/not-null values
* o compute total_width
* o compute total features's box area (for avgFeatureArea)
* o sum features box coordinates (for standard deviation)
*/
for ( i = 0; i < sample_rows; i++ )
{
Datum datum;
GBOX gbox = {0};
ND_BOX *nd_box;
bool is_null;
datum = fetchfunc(stats, i, &is_null);
/* Skip all NULLs. */
if ( is_null )
{
POSTGIS_DEBUGF(4, " skipped null geometry %d", i);
null_cnt++;
continue;
}
/* Read the bounds from the gserialized. */
if (LW_FAILURE == gserialized_datum_get_gbox_p(datum, &gbox))
{
/* Skip empties too. */
POSTGIS_DEBUGF(3, " skipped empty geometry %d", i);
continue;
}
/* If we're in 2D mode, zero out the higher dimensions for "safety" */
if ( mode == 2 )
gbox.zmin = gbox.zmax = gbox.mmin = gbox.mmax = 0.0;
/* Check bounds for validity (finite and not NaN) */
if ( ! gbox_is_valid(&gbox) )
{
POSTGIS_DEBUGF(3, " skipped infinite/nan geometry %d", i);
continue;
}
/*
* In N-D mode, set the ndims to the maximum dimensionality found
* in the sample. Otherwise, leave at ndims == 2.
*/
if ( mode != 2 )
ndims = Max(gbox_ndims(&gbox), ndims);
/* Convert gbox to n-d box */
nd_box = palloc(sizeof(ND_BOX));
nd_box_from_gbox(&gbox, nd_box);
/* Cache n-d bounding box */
sample_boxes[notnull_cnt] = nd_box;
/* Initialize sample extent before merging first entry */
if ( ! notnull_cnt )
nd_box_init_bounds(&sample_extent);
/* Add current sample to overall sample extent */
nd_box_merge(nd_box, &sample_extent);
/* How many bytes does this sample use? */
total_width += toast_raw_datum_size(datum);
/* Add bounds coordinates to sums for stddev calculation */
for ( d = 0; d < ndims; d++ )
{
sum.min[d] += nd_box->min[d];
sum.max[d] += nd_box->max[d];
}
/* Increment our "good feature" count */
notnull_cnt++;
/* Give backend a chance of interrupting us */
vacuum_delay_point();
}
/*
* We'll build a histogram having stats->attr->attstattarget
* (default 100) cells on each side, within reason...
* we'll use ndims*100000 as the maximum number of cells.
* Also, if we're sampling a relatively small table, we'll try to ensure that
* we have a smaller grid.
*/
histo_cells_target = (int)pow((double)(stats->attr->attstattarget), (double)ndims);
histo_cells_target = Min(histo_cells_target, ndims * 100000);
histo_cells_target = Min(histo_cells_target, (int)(10 * ndims * total_rows));
POSTGIS_DEBUGF(3, " stats->attr->attstattarget: %d", stats->attr->attstattarget);
POSTGIS_DEBUGF(3, " target # of histogram cells: %d", histo_cells_target);
/* If there's no useful features, we can't work out stats */
if ( ! notnull_cnt )
{
#if POSTGIS_DEBUG_LEVEL > 0
Oid relation_oid = stats->attr->attrelid;
char *relation_name = get_rel_name(relation_oid);
char *namespace = get_namespace_name(get_rel_namespace(relation_oid));
elog(DEBUG1,
"PostGIS: Unable to compute statistics for \"%s.%s.%s\": No non-null/empty features",
namespace ? namespace : "(NULL)",
relation_name ? relation_name : "(NULL)",
stats->attr->attname.data);
#endif /* POSTGIS_DEBUG_LEVEL > 0 */
stats->stats_valid = false;
return;
}
POSTGIS_DEBUGF(3, " sample_extent: %s", nd_box_to_json(&sample_extent, ndims));
/*
* Second scan:
* o compute standard deviation
*/
for ( d = 0; d < ndims; d++ )
{
/* Calculate average bounds values */
avg.min[d] = sum.min[d] / notnull_cnt;
avg.max[d] = sum.max[d] / notnull_cnt;
/* Calculate standard deviation for this dimension bounds */
for ( i = 0; i < notnull_cnt; i++ )
{
const ND_BOX *ndb = sample_boxes[i];
stddev.min[d] += (ndb->min[d] - avg.min[d]) * (ndb->min[d] - avg.min[d]);
stddev.max[d] += (ndb->max[d] - avg.max[d]) * (ndb->max[d] - avg.max[d]);
}
stddev.min[d] = sqrt(stddev.min[d] / notnull_cnt);
stddev.max[d] = sqrt(stddev.max[d] / notnull_cnt);
/* Histogram bounds for this dimension bounds is avg +/- SDFACTOR * stdev */
histo_extent.min[d] = Max(avg.min[d] - SDFACTOR * stddev.min[d], sample_extent.min[d]);
histo_extent.max[d] = Min(avg.max[d] + SDFACTOR * stddev.max[d], sample_extent.max[d]);
}
/*
* Third scan:
* o skip hard deviants
* o compute new histogram box
*/
nd_box_init_bounds(&histo_extent_new);
for ( i = 0; i < notnull_cnt; i++ )
{
const ND_BOX *ndb = sample_boxes[i];
/* Skip any hard deviants (boxes entirely outside our histo_extent */
if ( ! nd_box_intersects(&histo_extent, ndb, ndims) )
{
POSTGIS_DEBUGF(4, " feature %d is a hard deviant, skipped", i);
sample_boxes[i] = NULL;
continue;
}
/* Expand our new box to fit all the other features. */
nd_box_merge(ndb, &histo_extent_new);
}
/*
* Expand the box slightly (1%) to avoid edge effects
* with objects that are on the boundary
*/
nd_box_expand(&histo_extent_new, 0.01);
histo_extent = histo_extent_new;
/*
* How should we allocate our histogram cells to the
* different dimensions? We can't do it by raw dimensional width,
* because in x/y/z space, the z can have different units
* from the x/y. Similarly for x/y/t space.
* So, we instead calculate how much features overlap
* each other in their dimension to figure out which
* dimensions have useful selectivity characteristics (more
* variability in density) and therefor would find
* more cells useful (to distinguish between dense places and
* homogeneous places).
*/
nd_box_array_distribution(sample_boxes, notnull_cnt, &histo_extent, ndims,
sample_distribution);
/*
* The sample_distribution array now tells us how spread out the
* data is in each dimension, so we use that data to allocate
* the histogram cells we have available.
* At this point, histo_cells_target is the approximate target number
* of cells.
*/
/*
* Some dimensions have basically a uniform distribution, we want
* to allocate no cells to those dimensions, only to dimensions
* that have some interesting differences in data distribution.
* Here we count up the number of interesting dimensions
*/
for ( d = 0; d < ndims; d++ )
{
if ( sample_distribution[d] > 0 )
histo_ndims++;
}
if ( histo_ndims == 0 )
{
/* Special case: all our dimensions had low variability! */
/* We just divide the cells up evenly */
POSTGIS_DEBUG(3, " special case: no axes have variability");
histo_cells_new = 1;
for ( d = 0; d < ndims; d++ )
{
histo_size[d] = (int)pow((double)histo_cells_target, 1/(double)ndims);
if ( ! histo_size[d] )
histo_size[d] = 1;
POSTGIS_DEBUGF(3, " histo_size[d]: %d", histo_size[d]);
histo_cells_new *= histo_size[d];
}
POSTGIS_DEBUGF(3, " histo_cells_new: %d", histo_cells_new);
}
else
{
/*
* We're going to express the amount of variability in each dimension
* as a proportion of the total variability and allocate cells in that
* dimension relative to that proportion.
*/
POSTGIS_DEBUG(3, " allocating histogram axes based on axis variability");
total_distribution = total_double(sample_distribution, ndims); /* First get the total */
POSTGIS_DEBUGF(3, " total_distribution: %.8g", total_distribution);
histo_cells_new = 1; /* For the number of cells in the final histogram */
for ( d = 0; d < ndims; d++ )
{
if ( sample_distribution[d] == 0 ) /* Uninteresting dimensions don't get any room */
{
histo_size[d] = 1;
}
else /* Interesting dimension */
{
/* How does this dims variability compare to the total? */
float edge_ratio = (float)sample_distribution[d] / (float)total_distribution;
/*
* Scale the target cells number by the # of dims and ratio,
* then take the appropriate root to get the estimated number of cells
* on this axis (eg, pow(0.5) for 2d, pow(0.333) for 3d, pow(0.25) for 4d)
*/
histo_size[d] = (int)pow(histo_cells_target * histo_ndims * edge_ratio, 1/(double)histo_ndims);
/* If something goes awry, just give this dim one slot */
if ( ! histo_size[d] )
histo_size[d] = 1;
}
histo_cells_new *= histo_size[d];
}
POSTGIS_DEBUGF(3, " histo_cells_new: %d", histo_cells_new);
}
/* Update histo_cells to the actual number of cells we need to allocate */
histo_cells = histo_cells_new;
POSTGIS_DEBUGF(3, " histo_cells: %d", histo_cells);
/*
* Create the histogram (ND_STATS) in the stats memory context
*/
old_context = MemoryContextSwitchTo(stats->anl_context);
nd_stats_size = sizeof(ND_STATS) + ((histo_cells - 1) * sizeof(float4));
nd_stats = palloc(nd_stats_size);
memset(nd_stats, 0, nd_stats_size); /* Initialize all values to 0 */
MemoryContextSwitchTo(old_context);
/* Initialize the #ND_STATS objects */
nd_stats->ndims = ndims;
nd_stats->extent = histo_extent;
nd_stats->sample_features = sample_rows;
nd_stats->table_features = total_rows;
nd_stats->not_null_features = notnull_cnt;
/* Copy in the histogram dimensions */
for ( d = 0; d < ndims; d++ )
nd_stats->size[d] = histo_size[d];
/*
* Fourth scan:
* o fill histogram values with the proportion of
* features' bbox overlaps: a feature's bvol
* can fully overlap (1) or partially overlap
* (fraction of 1) an histogram cell.
*
* Note that we are filling each cell with the "portion of
* the feature's box that overlaps the cell". So, if we sum
* up the values in the histogram, we could get the
* histogram feature count.
*
*/
for ( i = 0; i < notnull_cnt; i++ )
{
const ND_BOX *nd_box;
ND_IBOX nd_ibox;
int at[ND_DIMS];
int d;
double num_cells = 0;
double min[ND_DIMS] = {0.0, 0.0, 0.0, 0.0};
double max[ND_DIMS] = {0.0, 0.0, 0.0, 0.0};
double cellsize[ND_DIMS] = {0.0, 0.0, 0.0, 0.0};
nd_box = sample_boxes[i];
if ( ! nd_box ) continue; /* Skip Null'ed out hard deviants */
/* Give backend a chance of interrupting us */
vacuum_delay_point();
/* Find the cells that overlap with this box and put them into the ND_IBOX */
nd_box_overlap(nd_stats, nd_box, &nd_ibox);
memset(at, 0, sizeof(int)*ND_DIMS);
POSTGIS_DEBUGF(3, " feature %d: ibox (%d, %d, %d, %d) (%d, %d, %d, %d)", i,
nd_ibox.min[0], nd_ibox.min[1], nd_ibox.min[2], nd_ibox.min[3],
nd_ibox.max[0], nd_ibox.max[1], nd_ibox.max[2], nd_ibox.max[3]);
for ( d = 0; d < nd_stats->ndims; d++ )
{
/* Initialize the starting values */
at[d] = nd_ibox.min[d];
min[d] = nd_stats->extent.min[d];
max[d] = nd_stats->extent.max[d];
cellsize[d] = (max[d] - min[d])/(nd_stats->size[d]);
}
/*
* Move through all the overlaped histogram cells values and
* add the box overlap proportion to them.
*/
do
{
ND_BOX nd_cell = { {0.0, 0.0, 0.0, 0.0}, {0.0, 0.0, 0.0, 0.0} };
double ratio;
/* Create a box for this histogram cell */
for ( d = 0; d < nd_stats->ndims; d++ )
{
nd_cell.min[d] = min[d] + (at[d]+0) * cellsize[d];
nd_cell.max[d] = min[d] + (at[d]+1) * cellsize[d];
}
/*
* If a feature box is completely inside one cell the ratio will be
* 1.0. If a feature box is 50% in two cells, each cell will get
* 0.5 added on.
*/
ratio = nd_box_ratio(&nd_cell, nd_box, nd_stats->ndims);
nd_stats->value[nd_stats_value_index(nd_stats, at)] += ratio;
num_cells += ratio;
POSTGIS_DEBUGF(3, " ratio (%.8g) num_cells (%.8g)", ratio, num_cells);
POSTGIS_DEBUGF(3, " at (%d, %d, %d, %d)", at[0], at[1], at[2], at[3]);
}
while ( nd_increment(&nd_ibox, nd_stats->ndims, at) );
/* Keep track of overall number of overlaps counted */
total_cell_count += num_cells;
/* How many features have we added to this histogram? */
histogram_features++;
}
POSTGIS_DEBUGF(3, " histogram_features: %d", histogram_features);
POSTGIS_DEBUGF(3, " sample_rows: %d", sample_rows);
POSTGIS_DEBUGF(3, " table_rows: %.6g", total_rows);
/* Error out if we got no sample information */
if ( ! histogram_features )
{
POSTGIS_DEBUG(3, " no stats have been gathered");
elog(NOTICE, " no features lie in the stats histogram, invalid stats");
stats->stats_valid = false;
return;
}
nd_stats->histogram_features = histogram_features;
nd_stats->histogram_cells = histo_cells;
nd_stats->cells_covered = total_cell_count;
/* Put this histogram data into the right slot/kind */
if ( mode == 2 )
{
stats_slot = STATISTIC_SLOT_2D;
stats_kind = STATISTIC_KIND_2D;
}
else
{
stats_slot = STATISTIC_SLOT_ND;
stats_kind = STATISTIC_KIND_ND;
}
/* Write the statistics data */
stats->stakind[stats_slot] = stats_kind;
stats->staop[stats_slot] = InvalidOid;
stats->stanumbers[stats_slot] = (float4*)nd_stats;
stats->numnumbers[stats_slot] = nd_stats_size/sizeof(float4);
stats->stanullfrac = (float4)null_cnt/sample_rows;
stats->stawidth = total_width/notnull_cnt;
stats->stadistinct = -1.0;
stats->stats_valid = true;
POSTGIS_DEBUGF(3, " out: slot 0: kind %d (STATISTIC_KIND_ND)", stats->stakind[0]);
POSTGIS_DEBUGF(3, " out: slot 0: op %d (InvalidOid)", stats->staop[0]);
POSTGIS_DEBUGF(3, " out: slot 0: numnumbers %d", stats->numnumbers[0]);
POSTGIS_DEBUGF(3, " out: null fraction: %f=%d/%d", stats->stanullfrac, null_cnt, sample_rows);
POSTGIS_DEBUGF(3, " out: average width: %d bytes", stats->stawidth);
POSTGIS_DEBUG (3, " out: distinct values: all (no check done)");
POSTGIS_DEBUGF(3, " out: %s", nd_stats_to_json(nd_stats));
/*
POSTGIS_DEBUGF(3, " out histogram:\n%s", nd_stats_to_grid(nd_stats));
*/
return;
}
/**
* In order to do useful selectivity calculations in both 2-D and N-D
* modes, we actually have to generate two stats objects, one for 2-D
* and one for N-D.
* You would think that an N-D histogram would be sufficient for 2-D
* calculations of selectivity, but you'd be wrong. For features that
* overlap multiple cells, the N-D histogram over-estimates the number
* of hits, and can't contain the requisite information to correct
* that over-estimate.
* We use the convenient PgSQL facility of stats slots to store
* one 2-D and one N-D stats object, and here in the compute function
* we just call the computation twice, once in each mode.
* It would be more efficient to have the computation calculate
* the two histograms simultaneously, but that would also complicate
* the (already complicated) logic in the function,
* so we'll take the CPU hit and do the computation twice.
*/
static void
compute_gserialized_stats(VacAttrStats *stats, AnalyzeAttrFetchFunc fetchfunc,
int sample_rows, double total_rows)
{
GserializedAnalyzeExtraData *extra_data = (GserializedAnalyzeExtraData *)stats->extra_data;
/* Call standard statistics calculation routine to fill in correlation for BRIN to work */
stats->extra_data = extra_data->std_extra_data;
extra_data->std_compute_stats(stats, fetchfunc, sample_rows, total_rows);
stats->extra_data = extra_data;
/* 2D Mode */
compute_gserialized_stats_mode(stats, fetchfunc, sample_rows, total_rows, 2);
if (stats->stats_valid)
{
/* ND Mode: Only computed if 2D was computed too (not NULL and valid) */
compute_gserialized_stats_mode(stats, fetchfunc, sample_rows, total_rows, 0);
}
}
/**
* This function will be called when the ANALYZE command is run
* on a column of the "geometry" or "geography" type.
*
* It will need to return a stats builder function reference
* and a "minimum" sample rows to feed it.
* If we want analisys to be completely skipped we can return
* false and leave output vals untouched.
*
* What we know from this call is:
*
* o The pg_attribute row referring to the specific column.
* Could be used to get reltuples from pg_class (which
* might quite inexact though...) and use them to set an
* appropriate minimum number of sample rows to feed to
* the stats builder. The stats builder will also receive
* a more accurate "estimation" of the number or rows.
*
* o The pg_type row for the specific column.
* Could be used to set stat builder / sample rows
* based on domain type (when postgis will be implemented
* that way).
*
* Being this experimental we'll stick to a static stat_builder/sample_rows
* value for now.
*/
PG_FUNCTION_INFO_V1(gserialized_analyze_nd);
Datum gserialized_analyze_nd(PG_FUNCTION_ARGS)
{
VacAttrStats *stats = (VacAttrStats *)PG_GETARG_POINTER(0);
GserializedAnalyzeExtraData *extra_data =
(GserializedAnalyzeExtraData *)palloc(sizeof(GserializedAnalyzeExtraData));
/* Ask for standard analyze to fill in as much as possible */
if (!std_typanalyze(stats))
PG_RETURN_BOOL(false);
/* Save old compute_stats and extra_data for scalar statistics ... */
extra_data->std_compute_stats = stats->compute_stats;
extra_data->std_extra_data = stats->extra_data;
/* ... and replace with our info */
stats->compute_stats = compute_gserialized_stats;
stats->extra_data = extra_data;
/* Indicate we are done successfully */
PG_RETURN_BOOL(true);
}
/**
* This function returns an estimate of the selectivity
* of a search GBOX by looking at data in the ND_STATS
* structure. The selectivity is a float from 0-1, that estimates
* the proportion of the rows in the table that will be returned
* as a result of the search box.
*
* To get our estimate,
* we need "only" sum up the values * the proportion of each cell
* in the histogram that falls within the search box, then
* divide by the number of features that generated the histogram.
*/
static float8
estimate_selectivity(const GBOX *box, const ND_STATS *nd_stats, int mode)
{
int d; /* counter */
float8 selectivity;
ND_BOX nd_box;
ND_IBOX nd_ibox;
int at[ND_DIMS];
double cell_size[ND_DIMS];
double min[ND_DIMS];
double max[ND_DIMS];
double total_count = 0.0;
int ndims_max;
/* Calculate the overlap of the box on the histogram */
if ( ! nd_stats )
{
elog(NOTICE, " estimate_selectivity called with null input");
return FALLBACK_ND_SEL;
}
ndims_max = Max(nd_stats->ndims, gbox_ndims(box));
/* Initialize nd_box. */
nd_box_from_gbox(box, &nd_box);
/*
* To return 2D stats on an ND sample, we need to make the
* 2D box cover the full range of the other dimensions in the
* histogram.
*/
POSTGIS_DEBUGF(3, " mode: %d", mode);
if ( mode == 2 )
{
POSTGIS_DEBUG(3, " in 2d mode, stripping the computation down to 2d");
ndims_max = 2;
}
POSTGIS_DEBUGF(3, " nd_stats->extent: %s", nd_box_to_json(&(nd_stats->extent), nd_stats->ndims));
POSTGIS_DEBUGF(3, " nd_box: %s", nd_box_to_json(&(nd_box), gbox_ndims(box)));
// elog(DEBUG1, "out histogram:\n%s", nd_stats_to_grid(nd_stats));
/*
* Search box completely misses histogram extent?
* We have to intersect in all N dimensions or else we have
* zero interaction under the &&& operator. It's important
* to short circuit in this case, as some of the tests below
* will return junk results when run on non-intersecting inputs.
*/
if ( ! nd_box_intersects(&nd_box, &(nd_stats->extent), ndims_max) )
{
POSTGIS_DEBUG(3, " search box does not overlap histogram, returning 0");
return 0.0;
}
/* Search box completely contains histogram extent! */
if ( nd_box_contains(&nd_box, &(nd_stats->extent), ndims_max) )
{
POSTGIS_DEBUG(3, " search box contains histogram, returning 1");
return 1.0;
}
/* Calculate the overlap of the box on the histogram */
if ( ! nd_box_overlap(nd_stats, &nd_box, &nd_ibox) )
{
POSTGIS_DEBUG(3, " search box overlap with stats histogram failed");
return FALLBACK_ND_SEL;
}
/* Work out some measurements of the histogram */
for ( d = 0; d < nd_stats->ndims; d++ )
{
/* Cell size in each dim */
min[d] = nd_stats->extent.min[d];
max[d] = nd_stats->extent.max[d];
cell_size[d] = (max[d] - min[d]) / nd_stats->size[d];
POSTGIS_DEBUGF(3, " cell_size[%d] : %.9g", d, cell_size[d]);
/* Initialize the counter */
at[d] = nd_ibox.min[d];
}
/* Move through all the overlap values and sum them */
do
{
float cell_count, ratio;
ND_BOX nd_cell = { {0.0, 0.0, 0.0, 0.0}, {0.0, 0.0, 0.0, 0.0} };
/* We have to pro-rate partially overlapped cells. */
for ( d = 0; d < nd_stats->ndims; d++ )
{
nd_cell.min[d] = min[d] + (at[d]+0) * cell_size[d];
nd_cell.max[d] = min[d] + (at[d]+1) * cell_size[d];
}
ratio = nd_box_ratio(&nd_box, &nd_cell, nd_stats->ndims);
cell_count = nd_stats->value[nd_stats_value_index(nd_stats, at)];
/* Add the pro-rated count for this cell to the overall total */
total_count += cell_count * ratio;
POSTGIS_DEBUGF(4, " cell (%d,%d), cell value %.6f, ratio %.6f", at[0], at[1], cell_count, ratio);
}
while ( nd_increment(&nd_ibox, nd_stats->ndims, at) );
/* Scale by the number of features in our histogram to get the proportion */
selectivity = total_count / nd_stats->histogram_features;
POSTGIS_DEBUGF(3, " nd_stats->histogram_features = %f", nd_stats->histogram_features);
POSTGIS_DEBUGF(3, " nd_stats->histogram_cells = %f", nd_stats->histogram_cells);
POSTGIS_DEBUGF(3, " sum(overlapped histogram cells) = %f", total_count);
POSTGIS_DEBUGF(3, " selectivity = %f", selectivity);
/* Prevent rounding overflows */
if (selectivity > 1.0) selectivity = 1.0;
else if (selectivity < 0.0) selectivity = 0.0;
return selectivity;
}
/**
* Utility function to print the statistics information for a
* given table/column in JSON. Used for debugging the selectivity code.
*/
PG_FUNCTION_INFO_V1(_postgis_gserialized_stats);
Datum _postgis_gserialized_stats(PG_FUNCTION_ARGS)
{
Oid table_oid = PG_GETARG_OID(0);
text *att_text = PG_GETARG_TEXT_P(1);
ND_STATS *nd_stats;
char *str;
text *json;
int mode = 2; /* default to 2D mode */
bool only_parent = false; /* default to whole tree stats */
/* Check if we've been asked to not use 2d mode */
if ( ! PG_ARGISNULL(2) )
mode = text_p_get_mode(PG_GETARG_TEXT_P(2));
/* Retrieve the stats object */
nd_stats = pg_get_nd_stats_by_name(table_oid, att_text, mode, only_parent);
if ( ! nd_stats )
elog(ERROR, "stats for \"%s.%s\" do not exist", get_rel_name(table_oid), text_to_cstring(att_text));
/* Convert to JSON */
elog(DEBUG1, "stats grid:\n%s", nd_stats_to_grid(nd_stats));
str = nd_stats_to_json(nd_stats);
json = cstring_to_text(str);
pfree(str);
pfree(nd_stats);
PG_RETURN_TEXT_P(json);
}
/**
* Utility function to read the calculated selectivity for a given search
* box and table/column. Used for debugging the selectivity code.
*/
PG_FUNCTION_INFO_V1(_postgis_gserialized_sel);
Datum _postgis_gserialized_sel(PG_FUNCTION_ARGS)
{
Oid table_oid = PG_GETARG_OID(0);
text *att_text = PG_GETARG_TEXT_P(1);
Datum geom_datum = PG_GETARG_DATUM(2);
GBOX gbox; /* search box read from gserialized datum */
float8 selectivity = 0;
ND_STATS *nd_stats;
int mode = 2; /* 2D mode by default */
/* Check if we've been asked to not use 2d mode */
if ( ! PG_ARGISNULL(3) )
mode = text_p_get_mode(PG_GETARG_TEXT_P(3));
/* Retrieve the stats object */
nd_stats = pg_get_nd_stats_by_name(table_oid, att_text, mode, false);
if ( ! nd_stats )
elog(ERROR, "stats for \"%s.%s\" do not exist", get_rel_name(table_oid), text_to_cstring(att_text));
/* Calculate the gbox */
if ( ! gserialized_datum_get_gbox_p(geom_datum, &gbox) )
elog(ERROR, "unable to calculate bounding box from geometry");
POSTGIS_DEBUGF(3, " %s", gbox_to_string(&gbox));
/* Do the estimation */
selectivity = estimate_selectivity(&gbox, nd_stats, mode);
pfree(nd_stats);
PG_RETURN_FLOAT8(selectivity);
}
/**
* Utility function to read the calculated join selectivity for a
* pair of tables. Used for debugging the selectivity code.
*/
PG_FUNCTION_INFO_V1(_postgis_gserialized_joinsel);
Datum _postgis_gserialized_joinsel(PG_FUNCTION_ARGS)
{
Oid table_oid1 = PG_GETARG_OID(0);
text *att_text1 = PG_GETARG_TEXT_P(1);
Oid table_oid2 = PG_GETARG_OID(2);
text *att_text2 = PG_GETARG_TEXT_P(3);
ND_STATS *nd_stats1, *nd_stats2;
float8 selectivity = 0;
int mode = 2; /* 2D mode by default */
/* Retrieve the stats object */
nd_stats1 = pg_get_nd_stats_by_name(table_oid1, att_text1, mode, false);
nd_stats2 = pg_get_nd_stats_by_name(table_oid2, att_text2, mode, false);
if ( ! nd_stats1 )
elog(ERROR, "stats for \"%s.%s\" do not exist", get_rel_name(table_oid1), text_to_cstring(att_text1));
if ( ! nd_stats2 )
elog(ERROR, "stats for \"%s.%s\" do not exist", get_rel_name(table_oid2), text_to_cstring(att_text2));
/* Check if we've been asked to not use 2d mode */
if ( ! PG_ARGISNULL(4) )
{
text *modetxt = PG_GETARG_TEXT_P(4);
char *modestr = text_to_cstring(modetxt);
if ( modestr[0] == 'N' )
mode = 0;
}
/* Do the estimation */
selectivity = estimate_join_selectivity(nd_stats1, nd_stats2);
pfree(nd_stats1);
pfree(nd_stats2);
PG_RETURN_FLOAT8(selectivity);
}
/**
* For (geometry && geometry)
* we call into the 2-D mode.
*/
PG_FUNCTION_INFO_V1(gserialized_gist_sel_2d);
Datum gserialized_gist_sel_2d(PG_FUNCTION_ARGS)
{
PG_RETURN_DATUM(DirectFunctionCall5(
gserialized_gist_sel,
PG_GETARG_DATUM(0), PG_GETARG_DATUM(1),
PG_GETARG_DATUM(2), PG_GETARG_DATUM(3),
Int32GetDatum(2) /* 2-D mode */
));
}
/**
* For (geometry &&& geometry) and (geography && geography)
* we call into the N-D mode.
*/
PG_FUNCTION_INFO_V1(gserialized_gist_sel_nd);
Datum gserialized_gist_sel_nd(PG_FUNCTION_ARGS)
{
PG_RETURN_DATUM(DirectFunctionCall5(
gserialized_gist_sel,
PG_GETARG_DATUM(0), PG_GETARG_DATUM(1),
PG_GETARG_DATUM(2), PG_GETARG_DATUM(3),
Int32GetDatum(0) /* N-D mode */
));
}
/**
* This function should return an estimation of the number of
* rows returned by a query involving an overlap check
* ( it's the restrict function for the && operator )
*
* It can make use (if available) of the statistics collected
* by the geometry analyzer function.
*
* Note that the good work is done by estimate_selectivity() above.
* This function just tries to find the search_box, loads the statistics
* and invoke the work-horse.
*
*/
float8
gserialized_sel_internal(PlannerInfo *root, List *args, int varRelid, int mode)
{
VariableStatData vardata;
Node *other = NULL;
bool varonleft;
ND_STATS *nd_stats = NULL;
GBOX search_box;
float8 selectivity = 0;
Const *otherConst;
POSTGIS_DEBUGF(2, "%s: entered function", __func__);
if (!get_restriction_variable(root, args, varRelid, &vardata, &other, &varonleft))
{
POSTGIS_DEBUGF(2, "%s: could not find vardata", __func__);
return DEFAULT_ND_SEL;
}
if (!IsA(other, Const))
{
ReleaseVariableStats(vardata);
POSTGIS_DEBUGF(2, "%s: no constant argument, returning default selectivity %g", __func__, DEFAULT_ND_SEL);
return DEFAULT_ND_SEL;
}
otherConst = (Const*)other;
if ((!otherConst) || otherConst->constisnull)
{
ReleaseVariableStats(vardata);
POSTGIS_DEBUGF(2, "%s: constant argument is NULL", __func__);
return DEFAULT_ND_SEL;
}
if (!gserialized_datum_get_gbox_p(otherConst->constvalue, &search_box))
{
ReleaseVariableStats(vardata);
POSTGIS_DEBUGF(2, "%s: search box is EMPTY", __func__);
return 0.0;
}
if (!vardata.statsTuple)
{
POSTGIS_DEBUGF(1, "%s: no statistics available on table. Empty? Need to ANALYZE?", __func__);
return DEFAULT_ND_SEL;
}
nd_stats = pg_nd_stats_from_tuple(vardata.statsTuple, mode);
ReleaseVariableStats(vardata);
selectivity = estimate_selectivity(&search_box, nd_stats, mode);
pfree(nd_stats);
return selectivity;
}
PG_FUNCTION_INFO_V1(gserialized_gist_sel);
Datum gserialized_gist_sel(PG_FUNCTION_ARGS)
{
PlannerInfo *root = (PlannerInfo *) PG_GETARG_POINTER(0);
// Oid operator_oid = PG_GETARG_OID(1);
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
int mode = PG_GETARG_INT32(4);
float8 selectivity = gserialized_sel_internal(root, args, varRelid, mode);
POSTGIS_DEBUGF(2, "%s: selectivity is %g", __func__, selectivity);
PG_RETURN_FLOAT8(selectivity);
}
/**
* Return the estimated extent of the table
* looking at gathered statistics (or NULL if
* no statistics have been gathered).
*/
PG_FUNCTION_INFO_V1(gserialized_estimated_extent);
Datum gserialized_estimated_extent(PG_FUNCTION_ARGS)
{
char *nsp = NULL;
char *tbl = NULL;
text *col = NULL;
char *nsp_tbl = NULL;
Oid tbl_oid, idx_oid = 0;
ND_STATS *nd_stats;
GBOX *gbox = NULL;
bool only_parent = false;
int key_type, att_num;
size_t sz;
/* We need to initialize the internal cache to access it later via postgis_oid() */
postgis_initialize_cache();
if ( PG_NARGS() == 4 )
{
nsp = text_to_cstring(PG_GETARG_TEXT_P(0));
tbl = text_to_cstring(PG_GETARG_TEXT_P(1));
col = PG_GETARG_TEXT_P(2);
only_parent = PG_GETARG_BOOL(3);
sz = strlen(nsp) + strlen(tbl) + 6;
nsp_tbl = palloc(sz);
snprintf(nsp_tbl, sz, "\"%s\".\"%s\"", nsp, tbl);
tbl_oid = DatumGetObjectId(DirectFunctionCall1(regclassin, CStringGetDatum(nsp_tbl)));
pfree(nsp_tbl);
}
else if ( PG_NARGS() == 3 )
{
nsp = text_to_cstring(PG_GETARG_TEXT_P(0));
tbl = text_to_cstring(PG_GETARG_TEXT_P(1));
col = PG_GETARG_TEXT_P(2);
sz = strlen(nsp) + strlen(tbl) + 6;
nsp_tbl = palloc(sz);
snprintf(nsp_tbl, sz, "\"%s\".\"%s\"", nsp, tbl);
tbl_oid = DatumGetObjectId(DirectFunctionCall1(regclassin, CStringGetDatum(nsp_tbl)));
pfree(nsp_tbl);
}
else if ( PG_NARGS() == 2 )
{
tbl = text_to_cstring(PG_GETARG_TEXT_P(0));
col = PG_GETARG_TEXT_P(1);
sz = strlen(tbl) + 3;
nsp_tbl = palloc(sz);
snprintf(nsp_tbl, sz, "\"%s\"", tbl);
tbl_oid = DatumGetObjectId(DirectFunctionCall1(regclassin, CStringGetDatum(nsp_tbl)));
pfree(nsp_tbl);
}
else
{
elog(ERROR, "estimated_extent() called with wrong number of arguments");
PG_RETURN_NULL();
}
/* Read the extent from the head of the spatial index, if there is one */
idx_oid = table_get_spatial_index(tbl_oid, col, &key_type, &att_num);
if (idx_oid)
{
/* TODO: how about only_parent ? */
gbox = spatial_index_read_extent(idx_oid, key_type, att_num);
POSTGIS_DEBUGF(2, "index for \"%s.%s\" exists, reading gbox from there", tbl, text_to_cstring(col));
if ( ! gbox ) PG_RETURN_NULL();
}
else
{
POSTGIS_DEBUGF(2, "index for \"%s.%s\" does not exist", tbl, text_to_cstring(col));
/* Fall back to reading the stats, if no index is found */
/* Estimated extent only returns 2D bounds, so use mode 2 */
nd_stats = pg_get_nd_stats_by_name(tbl_oid, col, 2, only_parent);
/* Error out on no stats */
if ( ! nd_stats ) {
elog(WARNING, "stats for \"%s.%s\" do not exist", tbl, text_to_cstring(col));
PG_RETURN_NULL();
}
/* Construct the box */
gbox = palloc(sizeof(GBOX));
FLAGS_SET_GEODETIC(gbox->flags, 0);
FLAGS_SET_Z(gbox->flags, 0);
FLAGS_SET_M(gbox->flags, 0);
gbox->xmin = nd_stats->extent.min[0];
gbox->xmax = nd_stats->extent.max[0];
gbox->ymin = nd_stats->extent.min[1];
gbox->ymax = nd_stats->extent.max[1];
pfree(nd_stats);
}
PG_RETURN_POINTER(gbox);
}
/**
* Return the estimated extent of the table
* looking at gathered statistics (or NULL if
* no statistics have been gathered).
*/
PG_FUNCTION_INFO_V1(geometry_estimated_extent);
Datum geometry_estimated_extent(PG_FUNCTION_ARGS)
{
if ( PG_NARGS() == 3 )
{
PG_RETURN_DATUM(
DirectFunctionCall3(gserialized_estimated_extent,
PG_GETARG_DATUM(0),
PG_GETARG_DATUM(1),
PG_GETARG_DATUM(2)));
}
else if ( PG_NARGS() == 2 )
{
PG_RETURN_DATUM(
DirectFunctionCall2(gserialized_estimated_extent,
PG_GETARG_DATUM(0),
PG_GETARG_DATUM(1)));
}
elog(ERROR, "geometry_estimated_extent() called with wrong number of arguments");
PG_RETURN_NULL();
}
/************************************************************************/
static Oid
table_get_spatial_index(Oid tbl_oid, text *col, int *key_type, int *att_num)
{
Relation tbl_rel;
ListCell *lc;
List *idx_list;
Oid result = InvalidOid;
char *colname = text_to_cstring(col);
/* Lookup our spatial index key types */
Oid b2d_oid = postgis_oid(BOX2DFOID);
Oid gdx_oid = postgis_oid(BOX3DOID);
if (!(b2d_oid && gdx_oid))
return InvalidOid;
tbl_rel = RelationIdGetRelation(tbl_oid);
idx_list = RelationGetIndexList(tbl_rel);
RelationClose(tbl_rel);
/* For each index associated with this table... */
foreach(lc, idx_list)
{
Form_pg_class idx_form;
HeapTuple idx_tup;
int idx_relam;
Oid idx_oid = lfirst_oid(lc);
idx_tup = SearchSysCache1(RELOID, ObjectIdGetDatum(idx_oid));
if (!HeapTupleIsValid(idx_tup))
elog(ERROR, "%s: unable to lookup index %u in syscache", __func__, idx_oid);
idx_form = (Form_pg_class) GETSTRUCT(idx_tup);
idx_relam = idx_form->relam;
ReleaseSysCache(idx_tup);
/* Does the index use a GIST access method? */
if (idx_relam == GIST_AM_OID)
{
Form_pg_attribute att;
Oid atttypid;
int attnum;
/* Is the index on the column name we are looking for? */
HeapTuple att_tup = SearchSysCache2(ATTNAME,
ObjectIdGetDatum(idx_oid),
PointerGetDatum(colname));
if (!HeapTupleIsValid(att_tup))
continue;
att = (Form_pg_attribute) GETSTRUCT(att_tup);
atttypid = att->atttypid;
attnum = att->attnum;
ReleaseSysCache(att_tup);
/* Is the column actually spatial? */
if (b2d_oid == atttypid || gdx_oid == atttypid)
{
/* Save result, clean up, and break out */
result = idx_oid;
if (att_num)
*att_num = attnum;
if (key_type)
*key_type = (atttypid == b2d_oid ? STATISTIC_KIND_2D : STATISTIC_KIND_ND);
break;
}
}
}
return result;
}
static GBOX *
spatial_index_read_extent(Oid idx_oid, int key_type, int att_num)
{
BOX2DF *bounds_2df = NULL;
GIDX *bounds_gidx = NULL;
GBOX *gbox = NULL;
Relation idx_rel;
Buffer buffer;
Page page;
OffsetNumber offset;
unsigned long offset_max;
if (!idx_oid)
return NULL;
idx_rel = index_open(idx_oid, AccessShareLock);
buffer = ReadBuffer(idx_rel, GIST_ROOT_BLKNO);
page = (Page) BufferGetPage(buffer);
offset = FirstOffsetNumber;
offset_max = PageGetMaxOffsetNumber(page);
while (offset <= offset_max)
{
ItemId iid = PageGetItemId(page, offset);
IndexTuple ituple;
if (!iid)
{
ReleaseBuffer(buffer);
index_close(idx_rel, AccessShareLock);
return NULL;
}
ituple = (IndexTuple) PageGetItem(page, iid);
if (!GistTupleIsInvalid(ituple))
{
bool isnull;
Datum idx_attr = index_getattr(ituple, att_num, idx_rel->rd_att, &isnull);
if (!isnull)
{
if (key_type == STATISTIC_KIND_2D)
{
BOX2DF *b = (BOX2DF*)DatumGetPointer(idx_attr);
if (bounds_2df)
box2df_merge(bounds_2df, b);
else
bounds_2df = box2df_copy(b);
}
else
{
GIDX *b = (GIDX*)DatumGetPointer(idx_attr);
if (bounds_gidx)
gidx_merge(&bounds_gidx, b);
else
bounds_gidx = gidx_copy(b);
}
}
}
offset++;
}
ReleaseBuffer(buffer);
index_close(idx_rel, AccessShareLock);
if (key_type == STATISTIC_KIND_2D && bounds_2df)
{
if (box2df_is_empty(bounds_2df))
return NULL;
gbox = gbox_new(0);
box2df_to_gbox_p(bounds_2df, gbox);
}
else if (key_type == STATISTIC_KIND_ND && bounds_gidx)
{
if (gidx_is_unknown(bounds_gidx))
return NULL;
gbox = gbox_new(0);
gbox_from_gidx(bounds_gidx, gbox, 0);
}
else
return NULL;
return gbox;
}
/*
CREATE OR REPLACE FUNCTION _postgis_index_extent(tbl regclass, col text)
RETURNS box2d
AS '$libdir/postgis-2.5','_postgis_gserialized_index_extent'
LANGUAGE 'c' STABLE STRICT;
*/
PG_FUNCTION_INFO_V1(_postgis_gserialized_index_extent);
Datum _postgis_gserialized_index_extent(PG_FUNCTION_ARGS)
{
GBOX *gbox = NULL;
int key_type;
int att_num;
Oid tbl_oid = PG_GETARG_DATUM(0);
text *col = PG_GETARG_TEXT_P(1);
Oid idx_oid;
if(!tbl_oid)
PG_RETURN_NULL();
/* We need to initialize the internal cache to access it later via postgis_oid() */
postgis_initialize_cache();
idx_oid = table_get_spatial_index(tbl_oid, col, &key_type, &att_num);
if (!idx_oid)
PG_RETURN_NULL();
gbox = spatial_index_read_extent(idx_oid, key_type, att_num);
if (!gbox)
PG_RETURN_NULL();
else
PG_RETURN_POINTER(gbox);
}
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