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Add a planner support function for numeric generate_series().

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This allows the planner to estimate the number of rows returned by
generate_series(numeric, numeric[, numeric]), when the input values
can be estimated at plan time.

Song Jinzhou, reviewed by Dean Rasheed and David Rowley.

Discussion: https://postgr.es/m/tencent_F43E7F4DD50EF5986D1051DE8DE547910206%40qq.com
Discussion: https://postgr.es/m/tencent_1F6D5B9A1545E02FD7D0EE508DFD056DE50A%40qq.com
This commit is contained in:
Dean Rasheed 2024-12-02 11:37:57 +00:00
parent 3315235845
commit 97173536ed
5 changed files with 232 additions and 3 deletions
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121
src/backend/utils/adt/numeric.c
View File

@ -34,6 +34,7 @@
#include "miscadmin.h"
#include "nodes/nodeFuncs.h"
#include "nodes/supportnodes.h"
#include "optimizer/optimizer.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
@ -1827,6 +1828,126 @@ generate_series_step_numeric(PG_FUNCTION_ARGS)
SRF_RETURN_DONE(funcctx);
}
/*
* Planner support function for generate_series(numeric, numeric [, numeric])
*/
Datum
generate_series_numeric_support(PG_FUNCTION_ARGS)
{
Node *rawreq = (Node *) PG_GETARG_POINTER(0);
Node *ret = NULL;
if (IsA(rawreq, SupportRequestRows))
{
/* Try to estimate the number of rows returned */
SupportRequestRows *req = (SupportRequestRows *) rawreq;
if (is_funcclause(req->node)) /* be paranoid */
{
List *args = ((FuncExpr *) req->node)->args;
Node *arg1,
*arg2,
*arg3;
/* We can use estimated argument values here */
arg1 = estimate_expression_value(req->root, linitial(args));
arg2 = estimate_expression_value(req->root, lsecond(args));
if (list_length(args) >= 3)
arg3 = estimate_expression_value(req->root, lthird(args));
else
arg3 = NULL;
/*
* If any argument is constant NULL, we can safely assume that
* zero rows are returned. Otherwise, if they're all non-NULL
* constants, we can calculate the number of rows that will be
* returned.
*/
if ((IsA(arg1, Const) &&
((Const *) arg1)->constisnull) ||
(IsA(arg2, Const) &&
((Const *) arg2)->constisnull) ||
(arg3 != NULL && IsA(arg3, Const) &&
((Const *) arg3)->constisnull))
{
req->rows = 0;
ret = (Node *) req;
}
else if (IsA(arg1, Const) &&
IsA(arg2, Const) &&
(arg3 == NULL || IsA(arg3, Const)))
{
Numeric start_num;
Numeric stop_num;
NumericVar step = const_one;
/*
* If any argument is NaN or infinity, generate_series() will
* error out, so we needn't produce an estimate.
*/
start_num = DatumGetNumeric(((Const *) arg1)->constvalue);
stop_num = DatumGetNumeric(((Const *) arg2)->constvalue);
if (NUMERIC_IS_SPECIAL(start_num) ||
NUMERIC_IS_SPECIAL(stop_num))
PG_RETURN_POINTER(NULL);
if (arg3)
{
Numeric step_num;
step_num = DatumGetNumeric(((Const *) arg3)->constvalue);
if (NUMERIC_IS_SPECIAL(step_num))
PG_RETURN_POINTER(NULL);
init_var_from_num(step_num, &step);
}
/*
* The number of rows that will be returned is given by
* floor((stop - start) / step) + 1, if the sign of step
* matches the sign of stop - start. Otherwise, no rows will
* be returned.
*/
if (cmp_var(&step, &const_zero) != 0)
{
NumericVar start;
NumericVar stop;
NumericVar res;
init_var_from_num(start_num, &start);
init_var_from_num(stop_num, &stop);
init_var(&res);
sub_var(&stop, &start, &res);
if (step.sign != res.sign)
{
/* no rows will be returned */
req->rows = 0;
ret = (Node *) req;
}
else
{
if (arg3)
div_var(&res, &step, &res, 0, false, false);
else
trunc_var(&res, 0); /* step = 1 */
req->rows = numericvar_to_double_no_overflow(&res) + 1;
ret = (Node *) req;
}
free_var(&res);
}
}
}
}
PG_RETURN_POINTER(ret);
}
/*
* Implements the numeric version of the width_bucket() function

2
src/include/catalog/catversion.h
View File

@ -57,6 +57,6 @@
*/
/* yyyymmddN */
#define CATALOG_VERSION_NO 202411111
#define CATALOG_VERSION_NO 202412021
#endif

9
src/include/catalog/pg_proc.dat
View File

@ -8464,13 +8464,18 @@
proname => 'generate_series_int8_support', prorettype => 'internal',
proargtypes => 'internal', prosrc => 'generate_series_int8_support' },
{ oid => '3259', descr => 'non-persistent series generator',
proname => 'generate_series', prorows => '1000', proretset => 't',
proname => 'generate_series', prorows => '1000',
prosupport => 'generate_series_numeric_support', proretset => 't',
prorettype => 'numeric', proargtypes => 'numeric numeric numeric',
prosrc => 'generate_series_step_numeric' },
{ oid => '3260', descr => 'non-persistent series generator',
proname => 'generate_series', prorows => '1000', proretset => 't',
proname => 'generate_series', prorows => '1000',
prosupport => 'generate_series_numeric_support', proretset => 't',
prorettype => 'numeric', proargtypes => 'numeric numeric',
prosrc => 'generate_series_numeric' },
{ oid => '8405', descr => 'planner support for generate_series',
proname => 'generate_series_numeric_support', prorettype => 'internal',
proargtypes => 'internal', prosrc => 'generate_series_numeric_support' },
{ oid => '938', descr => 'non-persistent series generator',
proname => 'generate_series', prorows => '1000',
prosupport => 'generate_series_timestamp_support', proretset => 't',

65
src/test/regress/expected/misc_functions.out
View File

@ -712,6 +712,71 @@ false, true, false, true);
-- the support function.
SELECT * FROM generate_series(TIMESTAMPTZ '2024-02-01', TIMESTAMPTZ '2024-03-01', INTERVAL '0 day') g(s);
ERROR: step size cannot equal zero
--
-- Test the SupportRequestRows support function for generate_series_numeric()
--
-- Ensure the row estimate matches the actual rows
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0) g(s);$$,
true, true, false, true);
explain_mask_costs
------------------------------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=25 width=N) (actual rows=25 loops=1)
(1 row)
-- As above but with non-default step
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0, 2.0) g(s);$$,
true, true, false, true);
explain_mask_costs
------------------------------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=13 width=N) (actual rows=13 loops=1)
(1 row)
-- Ensure the estimates match when step is decreasing
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 1.0, -1.0) g(s);$$,
true, true, false, true);
explain_mask_costs
------------------------------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=25 width=N) (actual rows=25 loops=1)
(1 row)
-- Ensure an empty range estimates 1 row
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 1.0, 1.0) g(s);$$,
true, true, false, true);
explain_mask_costs
----------------------------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=1 width=N) (actual rows=0 loops=1)
(1 row)
-- Ensure we get the default row estimate for error cases (infinity/NaN values
-- and zero step size)
SELECT explain_mask_costs($$
SELECT * FROM generate_series('-infinity'::NUMERIC, 'infinity'::NUMERIC, 1.0) g(s);$$,
false, true, false, true);
explain_mask_costs
-------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=1000 width=N)
(1 row)
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0, 'NaN'::NUMERIC) g(s);$$,
false, true, false, true);
explain_mask_costs
-------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=1000 width=N)
(1 row)
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 2.0, 0.0) g(s);$$,
false, true, false, true);
explain_mask_costs
-------------------------------------------------------------------
Function Scan on generate_series g (cost=N..N rows=1000 width=N)
(1 row)
-- Test functions for control data
SELECT count(*) > 0 AS ok FROM pg_control_checkpoint();
ok

38
src/test/regress/sql/misc_functions.sql
View File

@ -311,6 +311,44 @@ false, true, false, true);
-- the support function.
SELECT * FROM generate_series(TIMESTAMPTZ '2024-02-01', TIMESTAMPTZ '2024-03-01', INTERVAL '0 day') g(s);
--
-- Test the SupportRequestRows support function for generate_series_numeric()
--
-- Ensure the row estimate matches the actual rows
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0) g(s);$$,
true, true, false, true);
-- As above but with non-default step
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0, 2.0) g(s);$$,
true, true, false, true);
-- Ensure the estimates match when step is decreasing
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 1.0, -1.0) g(s);$$,
true, true, false, true);
-- Ensure an empty range estimates 1 row
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 1.0, 1.0) g(s);$$,
true, true, false, true);
-- Ensure we get the default row estimate for error cases (infinity/NaN values
-- and zero step size)
SELECT explain_mask_costs($$
SELECT * FROM generate_series('-infinity'::NUMERIC, 'infinity'::NUMERIC, 1.0) g(s);$$,
false, true, false, true);
SELECT explain_mask_costs($$
SELECT * FROM generate_series(1.0, 25.0, 'NaN'::NUMERIC) g(s);$$,
false, true, false, true);
SELECT explain_mask_costs($$
SELECT * FROM generate_series(25.0, 2.0, 0.0) g(s);$$,
false, true, false, true);
-- Test functions for control data
SELECT count(*) > 0 AS ok FROM pg_control_checkpoint();
SELECT count(*) > 0 AS ok FROM pg_control_init();