Functions to return random numbers in a given range

From 15d0ba981ff03eca7143726fe7512adf00ee3a84 Mon Sep 17 00:00:00 2001
From: Dean Rasheed <dean.a.rasheed@gmail.com>
Date: Fri, 25 Aug 2023 10:42:38 +0100
Subject: [PATCH v2] Add random-number-in-range functions.

This adds 3 functions:

    random(min int, max int) returns int
    random(min bigint, max bigint) returns bigint
    random(min numeric, max numeric) returns numeric

Each returns a random number in the range [min, max].

In the numeric case, the result scale is Max(scale(min), scale(max)).
---
 doc/src/sgml/func.sgml                    |  39 ++-
 src/backend/utils/adt/Makefile            |   1 +
 src/backend/utils/adt/float.c             |  95 ------
 src/backend/utils/adt/meson.build         |   1 +
 src/backend/utils/adt/numeric.c           | 219 +++++++++++++
 src/backend/utils/adt/pseudorandomfuncs.c | 185 +++++++++++
 src/common/pg_prng.c                      |  36 +++
 src/include/catalog/pg_proc.dat           |  12 +
 src/include/common/pg_prng.h              |   1 +
 src/include/utils/numeric.h               |   4 +
 src/test/regress/expected/random.out      | 360 ++++++++++++++++++++++
 src/test/regress/sql/random.sql           | 164 ++++++++++
 12 files changed, 1017 insertions(+), 100 deletions(-)
 create mode 100644 src/backend/utils/adt/pseudorandomfuncs.c

diff --git a/doc/src/sgml/func.sgml b/doc/src/sgml/func.sgml
index 6788ba8ef4..6d76fb5853 100644
--- a/doc/src/sgml/func.sgml
+++ b/doc/src/sgml/func.sgml
@@ -1862,6 +1862,36 @@ SELECT NOT(ROW(table.*) IS NOT NULL) FROM TABLE; -- detect at least one null in
        </para></entry>
       </row>
 
+      <row>
+       <entry role="func_table_entry"><para role="func_signature">
+        <indexterm>
+         <primary>random</primary>
+        </indexterm>
+        <function>random</function> ( <parameter>min</parameter> <type>integer</type>, <parameter>max</parameter> <type>integer</type> )
+        <returnvalue>integer</returnvalue>
+       </para>
+       <para role="func_signature">
+        <function>random</function> ( <parameter>min</parameter> <type>bigint</type>, <parameter>max</parameter> <type>bigint</type> )
+        <returnvalue>bigint</returnvalue>
+       </para>
+       <para role="func_signature">
+        <function>random</function> ( <parameter>min</parameter> <type>numeric</type>, <parameter>max</parameter> <type>numeric</type> )
+        <returnvalue>numeric</returnvalue>
+       </para>
+       <para>
+        Return a random value in the range
+        <parameter>min</parameter> &lt;= x &lt;= <parameter>max</parameter>.
+       </para>
+       <para>
+        <literal>random(1, 10)</literal>
+        <returnvalue>7</returnvalue>
+       </para>
+       <para>
+        <literal>random(-0.499, 0.499)</literal>
+        <returnvalue>0.347</returnvalue>
+       </para></entry>
+      </row>
+
       <row>
        <entry role="func_table_entry"><para role="func_signature">
         <indexterm>
@@ -1906,19 +1936,18 @@ SELECT NOT(ROW(table.*) IS NOT NULL) FROM TABLE; -- detect at least one null in
    </table>
 
   <para>
-   The <function>random()</function> function uses a deterministic
-   pseudo-random number generator.
+   The random functions listed in <xref linkend="functions-math-random-table"/>
+   use a deterministic pseudo-random number generator.
    It is fast but not suitable for cryptographic
    applications; see the <xref linkend="pgcrypto"/> module for a more
    secure alternative.
    If <function>setseed()</function> is called, the series of results of
-   subsequent <function>random()</function> calls in the current session
+   subsequent calls to these random functions in the current session
    can be repeated by re-issuing <function>setseed()</function> with the same
    argument.
    Without any prior <function>setseed()</function> call in the same
-   session, the first <function>random()</function> call obtains a seed
+   session, the first call to any of these random functions obtains a seed
    from a platform-dependent source of random bits.
-   These remarks hold equally for <function>random_normal()</function>.
   </para>
 
   <para>
diff --git a/src/backend/utils/adt/Makefile b/src/backend/utils/adt/Makefile
index 199eae525d..610ccf2f79 100644
--- a/src/backend/utils/adt/Makefile
+++ b/src/backend/utils/adt/Makefile
@@ -82,6 +82,7 @@ OBJS = \
 	pg_lsn.o \
 	pg_upgrade_support.o \
 	pgstatfuncs.o \
+	pseudorandomfuncs.o \
 	pseudotypes.o \
 	quote.o \
 	rangetypes.o \
diff --git a/src/backend/utils/adt/float.c b/src/backend/utils/adt/float.c
index 901edcc896..cbbb8aecaf 100644
--- a/src/backend/utils/adt/float.c
+++ b/src/backend/utils/adt/float.c
@@ -21,10 +21,8 @@
 
 #include "catalog/pg_type.h"
 #include "common/int.h"
-#include "common/pg_prng.h"
 #include "common/shortest_dec.h"
 #include "libpq/pqformat.h"
-#include "miscadmin.h"
 #include "utils/array.h"
 #include "utils/float.h"
 #include "utils/fmgrprotos.h"
@@ -64,10 +62,6 @@ float8		degree_c_sixty = 60.0;
 float8		degree_c_one_half = 0.5;
 float8		degree_c_one = 1.0;
 
-/* State for drandom() and setseed() */
-static bool drandom_seed_set = false;
-static pg_prng_state drandom_seed;
-
 /* Local function prototypes */
 static double sind_q1(double x);
 static double cosd_q1(double x);
@@ -2785,95 +2779,6 @@ derfc(PG_FUNCTION_ARGS)
 }
 
 
-/* ========== RANDOM FUNCTIONS ========== */
-
-
-/*
- * initialize_drandom_seed - initialize drandom_seed if not yet done
- */
-static void
-initialize_drandom_seed(void)
-{
-	/* Initialize random seed, if not done yet in this process */
-	if (unlikely(!drandom_seed_set))
-	{
-		/*
-		 * If possible, initialize the seed using high-quality random bits.
-		 * Should that fail for some reason, we fall back on a lower-quality
-		 * seed based on current time and PID.
-		 */
-		if (unlikely(!pg_prng_strong_seed(&drandom_seed)))
-		{
-			TimestampTz now = GetCurrentTimestamp();
-			uint64		iseed;
-
-			/* Mix the PID with the most predictable bits of the timestamp */
-			iseed = (uint64) now ^ ((uint64) MyProcPid << 32);
-			pg_prng_seed(&drandom_seed, iseed);
-		}
-		drandom_seed_set = true;
-	}
-}
-
-/*
- *		drandom		- returns a random number
- */
-Datum
-drandom(PG_FUNCTION_ARGS)
-{
-	float8		result;
-
-	initialize_drandom_seed();
-
-	/* pg_prng_double produces desired result range [0.0 - 1.0) */
-	result = pg_prng_double(&drandom_seed);
-
-	PG_RETURN_FLOAT8(result);
-}
-
-/*
- *		drandom_normal	- returns a random number from a normal distribution
- */
-Datum
-drandom_normal(PG_FUNCTION_ARGS)
-{
-	float8		mean = PG_GETARG_FLOAT8(0);
-	float8		stddev = PG_GETARG_FLOAT8(1);
-	float8		result,
-				z;
-
-	initialize_drandom_seed();
-
-	/* Get random value from standard normal(mean = 0.0, stddev = 1.0) */
-	z = pg_prng_double_normal(&drandom_seed);
-	/* Transform the normal standard variable (z) */
-	/* using the target normal distribution parameters */
-	result = (stddev * z) + mean;
-
-	PG_RETURN_FLOAT8(result);
-}
-
-/*
- *		setseed		- set seed for the random number generator
- */
-Datum
-setseed(PG_FUNCTION_ARGS)
-{
-	float8		seed = PG_GETARG_FLOAT8(0);
-
-	if (seed < -1 || seed > 1 || isnan(seed))
-		ereport(ERROR,
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("setseed parameter %g is out of allowed range [-1,1]",
-						seed)));
-
-	pg_prng_fseed(&drandom_seed, seed);
-	drandom_seed_set = true;
-
-	PG_RETURN_VOID();
-}
-
-
 
 /*
  *		=========================
diff --git a/src/backend/utils/adt/meson.build b/src/backend/utils/adt/meson.build
index f3dfb52204..48dbcf59a5 100644
--- a/src/backend/utils/adt/meson.build
+++ b/src/backend/utils/adt/meson.build
@@ -69,6 +69,7 @@ backend_sources += files(
   'pg_lsn.c',
   'pg_upgrade_support.c',
   'pgstatfuncs.c',
+  'pseudorandomfuncs.c',
   'pseudotypes.c',
   'quote.c',
   'rangetypes.c',
diff --git a/src/backend/utils/adt/numeric.c b/src/backend/utils/adt/numeric.c
index 015a41dc56..9761d2e931 100644
--- a/src/backend/utils/adt/numeric.c
+++ b/src/backend/utils/adt/numeric.c
@@ -584,6 +584,8 @@ static void power_var(const NumericVar *base, const NumericVar *exp,
 static void power_var_int(const NumericVar *base, int exp, int exp_dscale,
 						  NumericVar *result);
 static void power_ten_int(int exp, NumericVar *result);
+static void random_var(pg_prng_state *state, const NumericVar *rmin,
+					   const NumericVar *rmax, NumericVar *result);
 
 static int	cmp_abs(const NumericVar *var1, const NumericVar *var2);
 static int	cmp_abs_common(const NumericDigit *var1digits, int var1ndigits,
@@ -4220,6 +4222,56 @@ numeric_trim_scale(PG_FUNCTION_ARGS)
 	PG_RETURN_NUMERIC(res);
 }
 
+/*
+ * Return a random numeric value in the range [rmin, rmax].
+ */
+Numeric
+random_numeric(pg_prng_state *state, Numeric rmin, Numeric rmax)
+{
+	NumericVar	rmin_var;
+	NumericVar	rmax_var;
+	NumericVar	result;
+	Numeric		res;
+
+	/* Range bounds must not be NaN/infinity */
+	if (NUMERIC_IS_SPECIAL(rmin))
+	{
+		if (NUMERIC_IS_NAN(rmin))
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("lower bound cannot be NaN"));
+		else
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("lower bound cannot be infinity"));
+	}
+	if (NUMERIC_IS_SPECIAL(rmax))
+	{
+		if (NUMERIC_IS_NAN(rmax))
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("upper bound cannot be NaN"));
+		else
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("upper bound cannot be infinity"));
+	}
+
+	/* Return a random value in the range [rmin, rmax] */
+	init_var_from_num(rmin, &rmin_var);
+	init_var_from_num(rmax, &rmax_var);
+
+	init_var(&result);
+
+	random_var(state, &rmin_var, &rmax_var, &result);
+
+	res = make_result(&result);
+
+	free_var(&result);
+
+	return res;
+}
+
 
 /* ----------------------------------------------------------------------
  *
@@ -11263,6 +11315,173 @@ power_ten_int(int exp, NumericVar *result)
 		result->digits[0] *= 10;
 }
 
+/*
+ * random_var() - return a random value in the range [rmin, rmax].
+ */
+static void
+random_var(pg_prng_state *state, const NumericVar *rmin,
+		   const NumericVar *rmax, NumericVar *result)
+{
+	int			rscale;
+	NumericVar	rlen;
+	int			res_ndigits;
+	int			n;
+	int			pow10;
+	int			i;
+	uint64		rlen64;
+	int			rlen64_ndigits;
+
+	rscale = Max(rmin->dscale, rmax->dscale);
+
+	/* Compute rlen = rmax - rmin and check the range bounds */
+	init_var(&rlen);
+	sub_var(rmax, rmin, &rlen);
+
+	if (rlen.sign == NUMERIC_NEG)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	/* Special case for an empty range */
+	if (rlen.ndigits == 0)
+	{
+		set_var_from_var(rmin, result);
+		result->dscale = rscale;
+		free_var(&rlen);
+		return;
+	}
+
+	/*
+	 * Otherwise, select a random value in the range [0, rlen = rmax - rmin],
+	 * and shift it to the required range by adding rmin.
+	 */
+
+	/* Required result digits */
+	res_ndigits = rlen.weight + 1 + (rscale + DEC_DIGITS - 1) / DEC_DIGITS;
+
+	/*
+	 * To get the required rscale, the final result digit must be a multiple
+	 * of pow10 = 10^n, where n = (-rscale) mod DEC_DIGITS.
+	 */
+	n = ((rscale + DEC_DIGITS - 1) / DEC_DIGITS) * DEC_DIGITS - rscale;
+	pow10 = 1;
+	for (i = 0; i < n; i++)
+		pow10 *= 10;
+
+	/*
+	 * To choose a random value uniformly from the range [0, rlen], we choose
+	 * from the slightly larger range [0, rlen2], where rlen2 is formed from
+	 * rlen by copying the first 4 NBASE digits, and setting all remaining
+	 * decimal digits to "9".
+	 *
+	 * Without loss of generality, we can ignore the weight of rlen2 and treat
+	 * it as a pure integer for the purposes of this discussion.  The process
+	 * above gives rlen2 + 1 = rlen64 * 10^N, for some integer N, where rlen64
+	 * is a 64-bit integer formed from the first 4 NBASE digits copied from
+	 * rlen.  Since this trivially factors into smaller pieces that fit in
+	 * 64-bit integers, the task of choosing a random value uniformly from the
+	 * rlen2 + 1 possible values in [0, rlen2] is much simpler.
+	 *
+	 * If the random value selected is too large, it is rejected, and we try
+	 * again until we get a result <= rlen, ensuring that the overall result
+	 * is uniform (no particular value is any more likely than any other).
+	 *
+	 * Since rlen64 holds 4 NBASE digits from rlen, it contains at least
+	 * DEC_DIGITS * 3 + 1 decimal digits (i.e., at least 13 decimal digits,
+	 * when DEC_DIGITS is 4). Therefore the probability of needing to reject
+	 * the value chosen and retry is less than 1e-13.
+	 */
+	rlen64 = (uint64) rlen.digits[0];
+	rlen64_ndigits = 1;
+	while (rlen64_ndigits < res_ndigits && rlen64_ndigits < 4)
+	{
+		rlen64 *= NBASE;
+		if (rlen64_ndigits < rlen.ndigits)
+			rlen64 += rlen.digits[rlen64_ndigits];
+		rlen64_ndigits++;
+	}
+
+	/* Loop until we get a result <= rlen */
+	do
+	{
+		NumericDigit *res_digits;
+		uint64		rand;
+		int			whole_ndigits;
+
+		alloc_var(result, res_ndigits);
+		result->sign = NUMERIC_POS;
+		result->weight = rlen.weight;
+		result->dscale = rscale;
+		res_digits = result->digits;
+
+		/*
+		 * Set the first rlen64_ndigits using a random value in [0, rlen64].
+		 *
+		 * If this is the whole result, and rscale is not a multiple of
+		 * DEC_DIGITS (pow10 from above is not 1), then we need this to be a
+		 * multiple of pow10.
+		 */
+		if (rlen64_ndigits == res_ndigits && pow10 != 1)
+			rand = pg_prng_uint64_range(state, 0, rlen64 / pow10) * pow10;
+		else
+			rand = pg_prng_uint64_range(state, 0, rlen64);
+
+		for (i = rlen64_ndigits - 1; i >= 0; i--)
+		{
+			res_digits[i] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+		}
+
+		/*
+		 * Set the remaining digits to random values in range [0, NBASE),
+		 * noting that the last digit needs to be a multiple of pow10.
+		 */
+		whole_ndigits = res_ndigits;
+		if (pow10 != 1)
+			whole_ndigits--;
+
+		/* Set whole digits in groups of 4 for best performance */
+		i = rlen64_ndigits;
+		while (i < whole_ndigits - 3)
+		{
+			rand = pg_prng_uint64_range(state, 0,
+										(uint64) NBASE * NBASE * NBASE * NBASE - 1);
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) rand;
+		}
+
+		/* Remaining whole digits */
+		while (i < whole_ndigits)
+		{
+			rand = pg_prng_uint64_range(state, 0, NBASE - 1);
+			res_digits[i++] = (NumericDigit) rand;
+		}
+
+		/* Final partial digit (multiple of pow10) */
+		if (i < res_ndigits)
+		{
+			rand = pg_prng_uint64_range(state, 0, NBASE / pow10 - 1) * pow10;
+			res_digits[i] = (NumericDigit) rand;
+		}
+
+		/* Remove leading/trailing zeroes */
+		strip_var(result);
+
+		/* If result > rlen, try again */
+
+	} while (cmp_var(result, &rlen) > 0);
+
+	/* Offset the result to the required range */
+	add_var(result, rmin, result);
+
+	free_var(&rlen);
+}
+
 
 /* ----------------------------------------------------------------------
  *
diff --git a/src/backend/utils/adt/pseudorandomfuncs.c b/src/backend/utils/adt/pseudorandomfuncs.c
new file mode 100644
index 0000000000..8e82c7078c
--- /dev/null
+++ b/src/backend/utils/adt/pseudorandomfuncs.c
@@ -0,0 +1,185 @@
+/*-------------------------------------------------------------------------
+ *
+ * pseudorandomfuncs.c
+ *	  Functions giving SQL access to a pseudorandom number generator.
+ *
+ * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
+ * Portions Copyright (c) 1994, Regents of the University of California
+ *
+ * IDENTIFICATION
+ *	  src/backend/utils/adt/pseudorandomfuncs.c
+ *
+ *-------------------------------------------------------------------------
+ */
+#include "postgres.h"
+
+#include <math.h>
+
+#include "common/pg_prng.h"
+#include "miscadmin.h"
+#include "utils/fmgrprotos.h"
+#include "utils/numeric.h"
+#include "utils/timestamp.h"
+
+/* Shared PRNG state used by all the random functions */
+static pg_prng_state prng_state;
+static bool prng_seed_set = false;
+
+/*
+ * initialize_prng() -
+ *
+ *	Initialize (seed) the PRNG, if not done yet in this process.
+ */
+static void
+initialize_prng(void)
+{
+	if (unlikely(!prng_seed_set))
+	{
+		/*
+		 * If possible, seed the PRNG using high-quality random bits. Should
+		 * that fail for some reason, we fall back on a lower-quality seed
+		 * based on current time and PID.
+		 */
+		if (unlikely(!pg_prng_strong_seed(&prng_state)))
+		{
+			TimestampTz now = GetCurrentTimestamp();
+			uint64		iseed;
+
+			/* Mix the PID with the most predictable bits of the timestamp */
+			iseed = (uint64) now ^ ((uint64) MyProcPid << 32);
+			pg_prng_seed(&prng_state, iseed);
+		}
+		prng_seed_set = true;
+	}
+}
+
+/*
+ * setseed() -
+ *
+ *	Seed the PRNG from a specified value in the range [-1.0, 1.0].
+ */
+Datum
+setseed(PG_FUNCTION_ARGS)
+{
+	float8		seed = PG_GETARG_FLOAT8(0);
+
+	if (seed < -1 || seed > 1 || isnan(seed))
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("setseed parameter %g is out of allowed range [-1,1]",
+					   seed));
+
+	pg_prng_fseed(&prng_state, seed);
+	prng_seed_set = true;
+
+	PG_RETURN_VOID();
+}
+
+/*
+ * drandom() -
+ *
+ *	Returns a random number chosen uniformly in the range [0.0, 1.0).
+ */
+Datum
+drandom(PG_FUNCTION_ARGS)
+{
+	float8		result;
+
+	initialize_prng();
+
+	/* pg_prng_double produces desired result range [0.0, 1.0) */
+	result = pg_prng_double(&prng_state);
+
+	PG_RETURN_FLOAT8(result);
+}
+
+/*
+ * drandom_normal() -
+ *
+ *	Returns a random number from a normal distribution.
+ */
+Datum
+drandom_normal(PG_FUNCTION_ARGS)
+{
+	float8		mean = PG_GETARG_FLOAT8(0);
+	float8		stddev = PG_GETARG_FLOAT8(1);
+	float8		result,
+				z;
+
+	initialize_prng();
+
+	/* Get random value from standard normal(mean = 0.0, stddev = 1.0) */
+	z = pg_prng_double_normal(&prng_state);
+	/* Transform the normal standard variable (z) */
+	/* using the target normal distribution parameters */
+	result = (stddev * z) + mean;
+
+	PG_RETURN_FLOAT8(result);
+}
+
+/*
+ * int4random() -
+ *
+ *	Returns a random 32-bit integer chosen uniformly in the specified range.
+ */
+Datum
+int4random(PG_FUNCTION_ARGS)
+{
+	int32		rmin = PG_GETARG_INT32(0);
+	int32		rmax = PG_GETARG_INT32(1);
+	int32		result;
+
+	if (rmin > rmax)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	initialize_prng();
+
+	result = (int32) pg_prng_int64_range(&prng_state, rmin, rmax);
+
+	PG_RETURN_INT32(result);
+}
+
+/*
+ * int8random() -
+ *
+ *	Returns a random 64-bit integer chosen uniformly in the specified range.
+ */
+Datum
+int8random(PG_FUNCTION_ARGS)
+{
+	int64		rmin = PG_GETARG_INT64(0);
+	int64		rmax = PG_GETARG_INT64(1);
+	int64		result;
+
+	if (rmin > rmax)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	initialize_prng();
+
+	result = pg_prng_int64_range(&prng_state, rmin, rmax);
+
+	PG_RETURN_INT64(result);
+}
+
+/*
+ * numeric_random() -
+ *
+ *	Returns a random numeric value chosen uniformly in the specified range.
+ */
+Datum
+numeric_random(PG_FUNCTION_ARGS)
+{
+	Numeric		rmin = PG_GETARG_NUMERIC(0);
+	Numeric		rmax = PG_GETARG_NUMERIC(1);
+	Numeric		result;
+
+	initialize_prng();
+
+	result = random_numeric(&prng_state, rmin, rmax);
+
+	PG_RETURN_NUMERIC(result);
+}
diff --git a/src/common/pg_prng.c b/src/common/pg_prng.c
index c1714a02bd..15b39411a9 100644
--- a/src/common/pg_prng.c
+++ b/src/common/pg_prng.c
@@ -184,6 +184,42 @@ pg_prng_int64p(pg_prng_state *state)
 	return (int64) (xoroshiro128ss(state) & UINT64CONST(0x7FFFFFFFFFFFFFFF));
 }
 
+/*
+ * Select a random int64 uniformly from the range [rmin, rmax].
+ * If the range is empty, rmin is always produced.
+ */
+int64
+pg_prng_int64_range(pg_prng_state *state, int64 rmin, int64 rmax)
+{
+	int64		val;
+
+	if (likely(rmax > rmin))
+	{
+		uint64		uval;
+
+		/*
+		 * Use pg_prng_uint64_range().  Can't simply pass it rmin and rmax,
+		 * since (uint64) rmin will be larger than (uint64) rmax if rmin < 0.
+		 */
+		uval = (uint64) rmin +
+			pg_prng_uint64_range(state, 0, (uint64) rmax - (uint64) rmin);
+
+		/*
+		 * Safely convert back to int64, avoiding implementation-defined
+		 * behavior for values larger than PG_INT64_MAX.  Modern compilers
+		 * will reduce this to a simple assignment.
+		 */
+		if (uval > PG_INT64_MAX)
+			val = (int64) (uval - PG_INT64_MIN) + PG_INT64_MIN;
+		else
+			val = (int64) uval;
+	}
+	else
+		val = rmin;
+
+	return val;
+}
+
 /*
  * Select a random uint32 uniformly from the range [0, PG_UINT32_MAX].
  */
diff --git a/src/include/catalog/pg_proc.dat b/src/include/catalog/pg_proc.dat
index 29af4ce65d..b1314d58f5 100644
--- a/src/include/catalog/pg_proc.dat
+++ b/src/include/catalog/pg_proc.dat
@@ -3381,6 +3381,18 @@
   proname => 'random_normal', provolatile => 'v', proparallel => 'r',
   prorettype => 'float8', proargtypes => 'float8 float8',
   prosrc => 'drandom_normal' },
+{ oid => '9719', descr => 'random integer in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'int4', proargtypes => 'int4 int4',
+  proargnames => '{min,max}', prosrc => 'int4random' },
+{ oid => '9720', descr => 'random bigint in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'int8', proargtypes => 'int8 int8',
+  proargnames => '{min,max}', prosrc => 'int8random' },
+{ oid => '9721', descr => 'random numeric in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'numeric', proargtypes => 'numeric numeric',
+  proargnames => '{min,max}', prosrc => 'numeric_random' },
 { oid => '1599', descr => 'set random seed',
   proname => 'setseed', provolatile => 'v', proparallel => 'r',
   prorettype => 'void', proargtypes => 'float8', prosrc => 'setseed' },
diff --git a/src/include/common/pg_prng.h b/src/include/common/pg_prng.h
index e201b95686..c114c6419d 100644
--- a/src/include/common/pg_prng.h
+++ b/src/include/common/pg_prng.h
@@ -51,6 +51,7 @@ extern uint64 pg_prng_uint64(pg_prng_state *state);
 extern uint64 pg_prng_uint64_range(pg_prng_state *state, uint64 rmin, uint64 rmax);
 extern int64 pg_prng_int64(pg_prng_state *state);
 extern int64 pg_prng_int64p(pg_prng_state *state);
+extern int64 pg_prng_int64_range(pg_prng_state *state, int64 rmin, int64 rmax);
 extern uint32 pg_prng_uint32(pg_prng_state *state);
 extern int32 pg_prng_int32(pg_prng_state *state);
 extern int32 pg_prng_int32p(pg_prng_state *state);
diff --git a/src/include/utils/numeric.h b/src/include/utils/numeric.h
index 2f7184e299..43c75c436f 100644
--- a/src/include/utils/numeric.h
+++ b/src/include/utils/numeric.h
@@ -14,6 +14,7 @@
 #ifndef _PG_NUMERIC_H_
 #define _PG_NUMERIC_H_
 
+#include "common/pg_prng.h"
 #include "fmgr.h"
 
 /*
@@ -103,4 +104,7 @@ extern Numeric numeric_mod_opt_error(Numeric num1, Numeric num2,
 extern int32 numeric_int4_opt_error(Numeric num, bool *have_error);
 extern int64 numeric_int8_opt_error(Numeric num, bool *have_error);
 
+extern Numeric random_numeric(pg_prng_state *state,
+							  Numeric rmin, Numeric rmax);
+
 #endif							/* _PG_NUMERIC_H_ */
diff --git a/src/test/regress/expected/random.out b/src/test/regress/expected/random.out
index 223590720c..43cf88a363 100644
--- a/src/test/regress/expected/random.out
+++ b/src/test/regress/expected/random.out
@@ -120,6 +120,229 @@ SELECT ks_test_normal_random() OR
  t
 (1 row)
 
+-- Test random(min, max)
+-- invalid range bounds
+SELECT random(1, 0);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random(1000000000001, 1000000000000);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random(-2.0, -3.0);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random('NaN'::numeric, 10);
+ERROR:  lower bound cannot be NaN
+SELECT random('-Inf'::numeric, 0);
+ERROR:  lower bound cannot be infinity
+SELECT random(0, 'NaN'::numeric);
+ERROR:  upper bound cannot be NaN
+SELECT random(0, 'Inf'::numeric);
+ERROR:  upper bound cannot be infinity
+-- empty range is OK
+SELECT random(101, 101);
+ random 
+--------
+    101
+(1 row)
+
+SELECT random(1000000000001, 1000000000001);
+    random     
+---------------
+ 1000000000001
+(1 row)
+
+SELECT random(3.14, 3.14);
+ random 
+--------
+   3.14
+(1 row)
+
+-- There should be no triple duplicates in 1000 full-range 32-bit random()
+-- values.  (Each of the C(1000, 3) choices of triplets from the 1000 values
+-- has a probability of 1/(2^32)^2 of being a triple duplicate, so the
+-- average number of triple duplicates is 1000 * 999 * 998 / 6 / 2^64, which
+-- is roughly 9e-12.)
+SELECT r, count(*)
+FROM (SELECT random(-2147483648, 2147483647) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 2;
+ r | count 
+---+-------
+(0 rows)
+
+-- There should be no duplicates in 1000 full-range 64-bit random() values.
+SELECT r, count(*)
+FROM (SELECT random_normal(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+ r | count 
+---+-------
+(0 rows)
+
+-- There should be no duplicates in 1000 15-digit random() numeric values.
+SELECT r, count(*)
+FROM (SELECT random_normal(0, 1 - 1e-15) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+ r | count 
+---+-------
+(0 rows)
+
+-- Expect at least one out of 2000 random values to be in the lowest and
+-- highest 1% of the range.
+SELECT (count(*) FILTER (WHERE r < -2104533975)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 2104533974)) > 0 AS has_large
+FROM (SELECT random(-2147483648, 2147483647) r FROM generate_series(1, 2000)) ss;
+ has_small | has_large 
+-----------+-----------
+ t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1500000000 OR r > 1500000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000, 1500000000) r FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+SELECT (count(*) FILTER (WHERE r < -9038904596117680292)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 9038904596117680291)) > 0 AS has_large
+FROM (SELECT random(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 2000)) ss;
+ has_small | has_large 
+-----------+-----------
+ t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1500000000000000 OR r > 1500000000000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000000000, 1500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1.5 OR r > 1.5) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1.47)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1.47)) > 0 AS has_large
+FROM (SELECT random(-1.500000000000000, 1.500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+-- Every possible value should occur at least once in 2500 random() values
+-- chosen from a range with 100 distinct values.
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-50, 49) r FROM generate_series(1, 2500));
+ min | max | count 
+-----+-----+-------
+ -50 |  49 |   100
+(1 row)
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(123000000000, 123000000099) r
+  FROM generate_series(1, 2500));
+     min      |     max      | count 
+--------------+--------------+-------
+ 123000000000 | 123000000099 |   100
+(1 row)
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-0.5, 0.49) r FROM generate_series(1, 2500));
+  min  | max  | count 
+-------+------+-------
+ -0.50 | 0.49 |   100
+(1 row)
+
+-- Check for uniform distribution using the Kolmogorov-Smirnov test.
+CREATE FUNCTION ks_test_uniform_random_int_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999) / 1000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() AS uniform_int;
+ uniform_int 
+-------------
+ t
+(1 row)
+
+CREATE FUNCTION ks_test_uniform_random_bigint_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999999999) / 1000000000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() AS uniform_bigint;
+ uniform_bigint 
+----------------
+ t
+(1 row)
+
+CREATE FUNCTION ks_test_uniform_random_numeric_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 0.999999) r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() AS uniform_numeric;
+ uniform_numeric 
+-----------------
+ t
+(1 row)
+
 -- setseed() should produce a reproducible series of random() values.
 SELECT setseed(0.5);
  setseed 
@@ -176,3 +399,140 @@ SELECT random_normal(mean => 1, stddev => 0.1) r FROM generate_series(1, 10);
  0.96403105557543
 (10 rows)
 
+-- Reproducible random(min, max) values.
+SELECT random(1, 6) FROM generate_series(1, 10);
+ random 
+--------
+      5
+      4
+      5
+      1
+      6
+      1
+      1
+      3
+      6
+      5
+(10 rows)
+
+SELECT random(-2147483648, 2147483647) FROM generate_series(1, 10);
+   random    
+-------------
+   -84380014
+  1287883594
+ -1927252904
+    13516867
+ -1902961616
+ -1824286201
+  -871264469
+ -1225880415
+   229836730
+  -116039023
+(10 rows)
+
+SELECT random(-9223372036854775808, 9223372036854775807) FROM generate_series(1, 10);
+        random        
+----------------------
+ -6205280962992680052
+ -3583519428011353337
+   511801786318122700
+  4672737727839409655
+ -6674868801536280768
+ -7816052100626646489
+ -4340613370136007199
+ -5873174504107419786
+ -2249910101649817824
+ -4493828993910792325
+(10 rows)
+
+SELECT random(-1e30, 1e30) FROM generate_series(1, 10);
+             random              
+---------------------------------
+ -732116469803315942112255539315
+  794641423514877972798449289857
+ -576932746026123093304638334719
+  420625067723533225139761854757
+ -339227806779403187811001078919
+  -77667951539418104959241732636
+  239810941795708162629328071599
+  820784371155896967052141946697
+ -377084684544126871150439048352
+ -979773225250716295007225086726
+(10 rows)
+
+SELECT random(-0.4, 0.4) FROM generate_series(1, 10);
+ random 
+--------
+    0.1
+    0.0
+    0.4
+   -0.2
+    0.1
+    0.2
+    0.3
+    0.0
+   -0.2
+    0.2
+(10 rows)
+
+SELECT random(0, 1 - 1e-30) FROM generate_series(1, 10);
+              random              
+----------------------------------
+ 0.676442053784930109917469287265
+ 0.221310454098356723569995592911
+ 0.060101338174419259555193956224
+ 0.509960354695248239243002172364
+ 0.248680813394555793693952296993
+ 0.353262552880008646603494668901
+ 0.760692600450339509843044233719
+ 0.554987655310094483449494782510
+ 0.330890988458592995280347745733
+ 0.665435298280470361228607881507
+(10 rows)
+
+SELECT n, random(0, trim_scale(abs(1 - 10.0^(-n)))) FROM generate_series(-20, 20) n;
+  n  |         random         
+-----+------------------------
+ -20 |   94174615760837282445
+ -19 |    6692559888531296894
+ -18 |     801114552709125931
+ -17 |      44091460959939971
+ -16 |       2956109297383113
+ -15 |        783332278684523
+ -14 |         81534303241440
+ -13 |          2892623140500
+ -12 |           269397605141
+ -11 |            13027512296
+ -10 |             9178377775
+  -9 |              323534150
+  -8 |               91897803
+  -7 |                6091383
+  -6 |                  13174
+  -5 |                  92714
+  -4 |                   8079
+  -3 |                    429
+  -2 |                     30
+  -1 |                      3
+   0 |                      0
+   1 |                    0.1
+   2 |                   0.69
+   3 |                  0.492
+   4 |                 0.7380
+   5 |                0.77078
+   6 |               0.738142
+   7 |              0.1808815
+   8 |             0.14908933
+   9 |            0.222654042
+  10 |           0.2281295170
+  11 |          0.73655782966
+  12 |         0.056357256884
+  13 |        0.8998407524375
+  14 |       0.28198400530206
+  15 |      0.713478222805230
+  16 |     0.0415046850936909
+  17 |    0.45946350291315119
+  18 |   0.310966980367873753
+  19 |  0.4967623661709676512
+  20 | 0.60795101234744211935
+(41 rows)
+
diff --git a/src/test/regress/sql/random.sql b/src/test/regress/sql/random.sql
index 14cc76bc3c..ebfa7539ed 100644
--- a/src/test/regress/sql/random.sql
+++ b/src/test/regress/sql/random.sql
@@ -100,6 +100,161 @@ SELECT ks_test_normal_random() OR
        ks_test_normal_random() OR
        ks_test_normal_random() AS standard_normal;
 
+-- Test random(min, max)
+
+-- invalid range bounds
+SELECT random(1, 0);
+SELECT random(1000000000001, 1000000000000);
+SELECT random(-2.0, -3.0);
+SELECT random('NaN'::numeric, 10);
+SELECT random('-Inf'::numeric, 0);
+SELECT random(0, 'NaN'::numeric);
+SELECT random(0, 'Inf'::numeric);
+
+-- empty range is OK
+SELECT random(101, 101);
+SELECT random(1000000000001, 1000000000001);
+SELECT random(3.14, 3.14);
+
+-- There should be no triple duplicates in 1000 full-range 32-bit random()
+-- values.  (Each of the C(1000, 3) choices of triplets from the 1000 values
+-- has a probability of 1/(2^32)^2 of being a triple duplicate, so the
+-- average number of triple duplicates is 1000 * 999 * 998 / 6 / 2^64, which
+-- is roughly 9e-12.)
+SELECT r, count(*)
+FROM (SELECT random(-2147483648, 2147483647) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 2;
+
+-- There should be no duplicates in 1000 full-range 64-bit random() values.
+SELECT r, count(*)
+FROM (SELECT random_normal(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+
+-- There should be no duplicates in 1000 15-digit random() numeric values.
+SELECT r, count(*)
+FROM (SELECT random_normal(0, 1 - 1e-15) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+
+-- Expect at least one out of 2000 random values to be in the lowest and
+-- highest 1% of the range.
+SELECT (count(*) FILTER (WHERE r < -2104533975)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 2104533974)) > 0 AS has_large
+FROM (SELECT random(-2147483648, 2147483647) r FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1500000000 OR r > 1500000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000, 1500000000) r FROM generate_series(1, 2000)) ss;
+
+SELECT (count(*) FILTER (WHERE r < -9038904596117680292)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 9038904596117680291)) > 0 AS has_large
+FROM (SELECT random(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1500000000000000 OR r > 1500000000000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000000000, 1500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1.5 OR r > 1.5) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1.47)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1.47)) > 0 AS has_large
+FROM (SELECT random(-1.500000000000000, 1.500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+
+-- Every possible value should occur at least once in 2500 random() values
+-- chosen from a range with 100 distinct values.
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-50, 49) r FROM generate_series(1, 2500));
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(123000000000, 123000000099) r
+  FROM generate_series(1, 2500));
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-0.5, 0.49) r FROM generate_series(1, 2500));
+
+-- Check for uniform distribution using the Kolmogorov-Smirnov test.
+
+CREATE FUNCTION ks_test_uniform_random_int_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999) / 1000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() AS uniform_int;
+
+CREATE FUNCTION ks_test_uniform_random_bigint_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999999999) / 1000000000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() AS uniform_bigint;
+
+CREATE FUNCTION ks_test_uniform_random_numeric_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 0.999999) r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() AS uniform_numeric;
+
 -- setseed() should produce a reproducible series of random() values.
 
 SELECT setseed(0.5);
@@ -113,3 +268,12 @@ SET extra_float_digits = -1;
 
 SELECT random_normal() FROM generate_series(1, 10);
 SELECT random_normal(mean => 1, stddev => 0.1) r FROM generate_series(1, 10);
+
+-- Reproducible random(min, max) values.
+SELECT random(1, 6) FROM generate_series(1, 10);
+SELECT random(-2147483648, 2147483647) FROM generate_series(1, 10);
+SELECT random(-9223372036854775808, 9223372036854775807) FROM generate_series(1, 10);
+SELECT random(-1e30, 1e30) FROM generate_series(1, 10);
+SELECT random(-0.4, 0.4) FROM generate_series(1, 10);
+SELECT random(0, 1 - 1e-30) FROM generate_series(1, 10);
+SELECT n, random(0, trim_scale(abs(1 - 10.0^(-n)))) FROM generate_series(-20, 20) n;
-- 
2.35.3

From b1a63ecce667377435dc16fc262509bff2355b29 Mon Sep 17 00:00:00 2001
From: Dean Rasheed <dean.a.rasheed@gmail.com>
Date: Fri, 25 Aug 2023 10:42:38 +0100
Subject: [PATCH v3] Add random-number-in-range functions.

This adds 3 functions:

    random(min int, max int) returns int
    random(min bigint, max bigint) returns bigint
    random(min numeric, max numeric) returns numeric

Each returns a random number in the range [min, max].

In the numeric case, the result scale is Max(scale(min), scale(max)).
---
 doc/src/sgml/func.sgml                    |  43 ++-
 src/backend/utils/adt/Makefile            |   1 +
 src/backend/utils/adt/float.c             |  95 ------
 src/backend/utils/adt/meson.build         |   1 +
 src/backend/utils/adt/numeric.c           | 219 +++++++++++++
 src/backend/utils/adt/pseudorandomfuncs.c | 185 +++++++++++
 src/common/pg_prng.c                      |  36 +++
 src/include/catalog/pg_proc.dat           |  12 +
 src/include/common/pg_prng.h              |   1 +
 src/include/utils/numeric.h               |   4 +
 src/test/regress/expected/random.out      | 360 ++++++++++++++++++++++
 src/test/regress/sql/random.sql           | 164 ++++++++++
 12 files changed, 1021 insertions(+), 100 deletions(-)
 create mode 100644 src/backend/utils/adt/pseudorandomfuncs.c

diff --git a/doc/src/sgml/func.sgml b/doc/src/sgml/func.sgml
index e5fa82c161..e39e569fb6 100644
--- a/doc/src/sgml/func.sgml
+++ b/doc/src/sgml/func.sgml
@@ -1862,6 +1862,39 @@ SELECT NOT(ROW(table.*) IS NOT NULL) FROM TABLE; -- detect at least one null in
        </para></entry>
       </row>
 
+      <row>
+       <entry role="func_table_entry"><para role="func_signature">
+        <indexterm>
+         <primary>random</primary>
+        </indexterm>
+        <function>random</function> ( <parameter>min</parameter> <type>integer</type>, <parameter>max</parameter> <type>integer</type> )
+        <returnvalue>integer</returnvalue>
+       </para>
+       <para role="func_signature">
+        <function>random</function> ( <parameter>min</parameter> <type>bigint</type>, <parameter>max</parameter> <type>bigint</type> )
+        <returnvalue>bigint</returnvalue>
+       </para>
+       <para role="func_signature">
+        <function>random</function> ( <parameter>min</parameter> <type>numeric</type>, <parameter>max</parameter> <type>numeric</type> )
+        <returnvalue>numeric</returnvalue>
+       </para>
+       <para>
+        Returns a random value in the range
+        <parameter>min</parameter> &lt;= x &lt;= <parameter>max</parameter>.
+        For type <type>numeric</type>, the result will have the same number of
+        fractional decimal digits as <parameter>min</parameter> or
+        <parameter>max</parameter>, whichever has more.
+       </para>
+       <para>
+        <literal>random(1, 10)</literal>
+        <returnvalue>7</returnvalue>
+       </para>
+       <para>
+        <literal>random(-0.499, 0.499)</literal>
+        <returnvalue>0.347</returnvalue>
+       </para></entry>
+      </row>
+
       <row>
        <entry role="func_table_entry"><para role="func_signature">
         <indexterm>
@@ -1906,19 +1939,19 @@ SELECT NOT(ROW(table.*) IS NOT NULL) FROM TABLE; -- detect at least one null in
    </table>
 
   <para>
-   The <function>random()</function> function uses a deterministic
-   pseudo-random number generator.
+   The <function>random()</function> and <function>random_normal()</function>
+   functions listed in <xref linkend="functions-math-random-table"/> use a
+   deterministic pseudo-random number generator.
    It is fast but not suitable for cryptographic
    applications; see the <xref linkend="pgcrypto"/> module for a more
    secure alternative.
    If <function>setseed()</function> is called, the series of results of
-   subsequent <function>random()</function> calls in the current session
+   subsequent calls to these functions in the current session
    can be repeated by re-issuing <function>setseed()</function> with the same
    argument.
    Without any prior <function>setseed()</function> call in the same
-   session, the first <function>random()</function> call obtains a seed
+   session, the first call to any of these functions obtains a seed
    from a platform-dependent source of random bits.
-   These remarks hold equally for <function>random_normal()</function>.
   </para>
 
   <para>
diff --git a/src/backend/utils/adt/Makefile b/src/backend/utils/adt/Makefile
index 199eae525d..610ccf2f79 100644
--- a/src/backend/utils/adt/Makefile
+++ b/src/backend/utils/adt/Makefile
@@ -82,6 +82,7 @@ OBJS = \
 	pg_lsn.o \
 	pg_upgrade_support.o \
 	pgstatfuncs.o \
+	pseudorandomfuncs.o \
 	pseudotypes.o \
 	quote.o \
 	rangetypes.o \
diff --git a/src/backend/utils/adt/float.c b/src/backend/utils/adt/float.c
index 901edcc896..cbbb8aecaf 100644
--- a/src/backend/utils/adt/float.c
+++ b/src/backend/utils/adt/float.c
@@ -21,10 +21,8 @@
 
 #include "catalog/pg_type.h"
 #include "common/int.h"
-#include "common/pg_prng.h"
 #include "common/shortest_dec.h"
 #include "libpq/pqformat.h"
-#include "miscadmin.h"
 #include "utils/array.h"
 #include "utils/float.h"
 #include "utils/fmgrprotos.h"
@@ -64,10 +62,6 @@ float8		degree_c_sixty = 60.0;
 float8		degree_c_one_half = 0.5;
 float8		degree_c_one = 1.0;
 
-/* State for drandom() and setseed() */
-static bool drandom_seed_set = false;
-static pg_prng_state drandom_seed;
-
 /* Local function prototypes */
 static double sind_q1(double x);
 static double cosd_q1(double x);
@@ -2785,95 +2779,6 @@ derfc(PG_FUNCTION_ARGS)
 }
 
 
-/* ========== RANDOM FUNCTIONS ========== */
-
-
-/*
- * initialize_drandom_seed - initialize drandom_seed if not yet done
- */
-static void
-initialize_drandom_seed(void)
-{
-	/* Initialize random seed, if not done yet in this process */
-	if (unlikely(!drandom_seed_set))
-	{
-		/*
-		 * If possible, initialize the seed using high-quality random bits.
-		 * Should that fail for some reason, we fall back on a lower-quality
-		 * seed based on current time and PID.
-		 */
-		if (unlikely(!pg_prng_strong_seed(&drandom_seed)))
-		{
-			TimestampTz now = GetCurrentTimestamp();
-			uint64		iseed;
-
-			/* Mix the PID with the most predictable bits of the timestamp */
-			iseed = (uint64) now ^ ((uint64) MyProcPid << 32);
-			pg_prng_seed(&drandom_seed, iseed);
-		}
-		drandom_seed_set = true;
-	}
-}
-
-/*
- *		drandom		- returns a random number
- */
-Datum
-drandom(PG_FUNCTION_ARGS)
-{
-	float8		result;
-
-	initialize_drandom_seed();
-
-	/* pg_prng_double produces desired result range [0.0 - 1.0) */
-	result = pg_prng_double(&drandom_seed);
-
-	PG_RETURN_FLOAT8(result);
-}
-
-/*
- *		drandom_normal	- returns a random number from a normal distribution
- */
-Datum
-drandom_normal(PG_FUNCTION_ARGS)
-{
-	float8		mean = PG_GETARG_FLOAT8(0);
-	float8		stddev = PG_GETARG_FLOAT8(1);
-	float8		result,
-				z;
-
-	initialize_drandom_seed();
-
-	/* Get random value from standard normal(mean = 0.0, stddev = 1.0) */
-	z = pg_prng_double_normal(&drandom_seed);
-	/* Transform the normal standard variable (z) */
-	/* using the target normal distribution parameters */
-	result = (stddev * z) + mean;
-
-	PG_RETURN_FLOAT8(result);
-}
-
-/*
- *		setseed		- set seed for the random number generator
- */
-Datum
-setseed(PG_FUNCTION_ARGS)
-{
-	float8		seed = PG_GETARG_FLOAT8(0);
-
-	if (seed < -1 || seed > 1 || isnan(seed))
-		ereport(ERROR,
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("setseed parameter %g is out of allowed range [-1,1]",
-						seed)));
-
-	pg_prng_fseed(&drandom_seed, seed);
-	drandom_seed_set = true;
-
-	PG_RETURN_VOID();
-}
-
-
 
 /*
  *		=========================
diff --git a/src/backend/utils/adt/meson.build b/src/backend/utils/adt/meson.build
index f3dfb52204..48dbcf59a5 100644
--- a/src/backend/utils/adt/meson.build
+++ b/src/backend/utils/adt/meson.build
@@ -69,6 +69,7 @@ backend_sources += files(
   'pg_lsn.c',
   'pg_upgrade_support.c',
   'pgstatfuncs.c',
+  'pseudorandomfuncs.c',
   'pseudotypes.c',
   'quote.c',
   'rangetypes.c',
diff --git a/src/backend/utils/adt/numeric.c b/src/backend/utils/adt/numeric.c
index 015a41dc56..9761d2e931 100644
--- a/src/backend/utils/adt/numeric.c
+++ b/src/backend/utils/adt/numeric.c
@@ -584,6 +584,8 @@ static void power_var(const NumericVar *base, const NumericVar *exp,
 static void power_var_int(const NumericVar *base, int exp, int exp_dscale,
 						  NumericVar *result);
 static void power_ten_int(int exp, NumericVar *result);
+static void random_var(pg_prng_state *state, const NumericVar *rmin,
+					   const NumericVar *rmax, NumericVar *result);
 
 static int	cmp_abs(const NumericVar *var1, const NumericVar *var2);
 static int	cmp_abs_common(const NumericDigit *var1digits, int var1ndigits,
@@ -4220,6 +4222,56 @@ numeric_trim_scale(PG_FUNCTION_ARGS)
 	PG_RETURN_NUMERIC(res);
 }
 
+/*
+ * Return a random numeric value in the range [rmin, rmax].
+ */
+Numeric
+random_numeric(pg_prng_state *state, Numeric rmin, Numeric rmax)
+{
+	NumericVar	rmin_var;
+	NumericVar	rmax_var;
+	NumericVar	result;
+	Numeric		res;
+
+	/* Range bounds must not be NaN/infinity */
+	if (NUMERIC_IS_SPECIAL(rmin))
+	{
+		if (NUMERIC_IS_NAN(rmin))
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("lower bound cannot be NaN"));
+		else
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("lower bound cannot be infinity"));
+	}
+	if (NUMERIC_IS_SPECIAL(rmax))
+	{
+		if (NUMERIC_IS_NAN(rmax))
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("upper bound cannot be NaN"));
+		else
+			ereport(ERROR,
+					errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+					errmsg("upper bound cannot be infinity"));
+	}
+
+	/* Return a random value in the range [rmin, rmax] */
+	init_var_from_num(rmin, &rmin_var);
+	init_var_from_num(rmax, &rmax_var);
+
+	init_var(&result);
+
+	random_var(state, &rmin_var, &rmax_var, &result);
+
+	res = make_result(&result);
+
+	free_var(&result);
+
+	return res;
+}
+
 
 /* ----------------------------------------------------------------------
  *
@@ -11263,6 +11315,173 @@ power_ten_int(int exp, NumericVar *result)
 		result->digits[0] *= 10;
 }
 
+/*
+ * random_var() - return a random value in the range [rmin, rmax].
+ */
+static void
+random_var(pg_prng_state *state, const NumericVar *rmin,
+		   const NumericVar *rmax, NumericVar *result)
+{
+	int			rscale;
+	NumericVar	rlen;
+	int			res_ndigits;
+	int			n;
+	int			pow10;
+	int			i;
+	uint64		rlen64;
+	int			rlen64_ndigits;
+
+	rscale = Max(rmin->dscale, rmax->dscale);
+
+	/* Compute rlen = rmax - rmin and check the range bounds */
+	init_var(&rlen);
+	sub_var(rmax, rmin, &rlen);
+
+	if (rlen.sign == NUMERIC_NEG)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	/* Special case for an empty range */
+	if (rlen.ndigits == 0)
+	{
+		set_var_from_var(rmin, result);
+		result->dscale = rscale;
+		free_var(&rlen);
+		return;
+	}
+
+	/*
+	 * Otherwise, select a random value in the range [0, rlen = rmax - rmin],
+	 * and shift it to the required range by adding rmin.
+	 */
+
+	/* Required result digits */
+	res_ndigits = rlen.weight + 1 + (rscale + DEC_DIGITS - 1) / DEC_DIGITS;
+
+	/*
+	 * To get the required rscale, the final result digit must be a multiple
+	 * of pow10 = 10^n, where n = (-rscale) mod DEC_DIGITS.
+	 */
+	n = ((rscale + DEC_DIGITS - 1) / DEC_DIGITS) * DEC_DIGITS - rscale;
+	pow10 = 1;
+	for (i = 0; i < n; i++)
+		pow10 *= 10;
+
+	/*
+	 * To choose a random value uniformly from the range [0, rlen], we choose
+	 * from the slightly larger range [0, rlen2], where rlen2 is formed from
+	 * rlen by copying the first 4 NBASE digits, and setting all remaining
+	 * decimal digits to "9".
+	 *
+	 * Without loss of generality, we can ignore the weight of rlen2 and treat
+	 * it as a pure integer for the purposes of this discussion.  The process
+	 * above gives rlen2 + 1 = rlen64 * 10^N, for some integer N, where rlen64
+	 * is a 64-bit integer formed from the first 4 NBASE digits copied from
+	 * rlen.  Since this trivially factors into smaller pieces that fit in
+	 * 64-bit integers, the task of choosing a random value uniformly from the
+	 * rlen2 + 1 possible values in [0, rlen2] is much simpler.
+	 *
+	 * If the random value selected is too large, it is rejected, and we try
+	 * again until we get a result <= rlen, ensuring that the overall result
+	 * is uniform (no particular value is any more likely than any other).
+	 *
+	 * Since rlen64 holds 4 NBASE digits from rlen, it contains at least
+	 * DEC_DIGITS * 3 + 1 decimal digits (i.e., at least 13 decimal digits,
+	 * when DEC_DIGITS is 4). Therefore the probability of needing to reject
+	 * the value chosen and retry is less than 1e-13.
+	 */
+	rlen64 = (uint64) rlen.digits[0];
+	rlen64_ndigits = 1;
+	while (rlen64_ndigits < res_ndigits && rlen64_ndigits < 4)
+	{
+		rlen64 *= NBASE;
+		if (rlen64_ndigits < rlen.ndigits)
+			rlen64 += rlen.digits[rlen64_ndigits];
+		rlen64_ndigits++;
+	}
+
+	/* Loop until we get a result <= rlen */
+	do
+	{
+		NumericDigit *res_digits;
+		uint64		rand;
+		int			whole_ndigits;
+
+		alloc_var(result, res_ndigits);
+		result->sign = NUMERIC_POS;
+		result->weight = rlen.weight;
+		result->dscale = rscale;
+		res_digits = result->digits;
+
+		/*
+		 * Set the first rlen64_ndigits using a random value in [0, rlen64].
+		 *
+		 * If this is the whole result, and rscale is not a multiple of
+		 * DEC_DIGITS (pow10 from above is not 1), then we need this to be a
+		 * multiple of pow10.
+		 */
+		if (rlen64_ndigits == res_ndigits && pow10 != 1)
+			rand = pg_prng_uint64_range(state, 0, rlen64 / pow10) * pow10;
+		else
+			rand = pg_prng_uint64_range(state, 0, rlen64);
+
+		for (i = rlen64_ndigits - 1; i >= 0; i--)
+		{
+			res_digits[i] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+		}
+
+		/*
+		 * Set the remaining digits to random values in range [0, NBASE),
+		 * noting that the last digit needs to be a multiple of pow10.
+		 */
+		whole_ndigits = res_ndigits;
+		if (pow10 != 1)
+			whole_ndigits--;
+
+		/* Set whole digits in groups of 4 for best performance */
+		i = rlen64_ndigits;
+		while (i < whole_ndigits - 3)
+		{
+			rand = pg_prng_uint64_range(state, 0,
+										(uint64) NBASE * NBASE * NBASE * NBASE - 1);
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) (rand % NBASE);
+			rand = rand / NBASE;
+			res_digits[i++] = (NumericDigit) rand;
+		}
+
+		/* Remaining whole digits */
+		while (i < whole_ndigits)
+		{
+			rand = pg_prng_uint64_range(state, 0, NBASE - 1);
+			res_digits[i++] = (NumericDigit) rand;
+		}
+
+		/* Final partial digit (multiple of pow10) */
+		if (i < res_ndigits)
+		{
+			rand = pg_prng_uint64_range(state, 0, NBASE / pow10 - 1) * pow10;
+			res_digits[i] = (NumericDigit) rand;
+		}
+
+		/* Remove leading/trailing zeroes */
+		strip_var(result);
+
+		/* If result > rlen, try again */
+
+	} while (cmp_var(result, &rlen) > 0);
+
+	/* Offset the result to the required range */
+	add_var(result, rmin, result);
+
+	free_var(&rlen);
+}
+
 
 /* ----------------------------------------------------------------------
  *
diff --git a/src/backend/utils/adt/pseudorandomfuncs.c b/src/backend/utils/adt/pseudorandomfuncs.c
new file mode 100644
index 0000000000..8e82c7078c
--- /dev/null
+++ b/src/backend/utils/adt/pseudorandomfuncs.c
@@ -0,0 +1,185 @@
+/*-------------------------------------------------------------------------
+ *
+ * pseudorandomfuncs.c
+ *	  Functions giving SQL access to a pseudorandom number generator.
+ *
+ * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
+ * Portions Copyright (c) 1994, Regents of the University of California
+ *
+ * IDENTIFICATION
+ *	  src/backend/utils/adt/pseudorandomfuncs.c
+ *
+ *-------------------------------------------------------------------------
+ */
+#include "postgres.h"
+
+#include <math.h>
+
+#include "common/pg_prng.h"
+#include "miscadmin.h"
+#include "utils/fmgrprotos.h"
+#include "utils/numeric.h"
+#include "utils/timestamp.h"
+
+/* Shared PRNG state used by all the random functions */
+static pg_prng_state prng_state;
+static bool prng_seed_set = false;
+
+/*
+ * initialize_prng() -
+ *
+ *	Initialize (seed) the PRNG, if not done yet in this process.
+ */
+static void
+initialize_prng(void)
+{
+	if (unlikely(!prng_seed_set))
+	{
+		/*
+		 * If possible, seed the PRNG using high-quality random bits. Should
+		 * that fail for some reason, we fall back on a lower-quality seed
+		 * based on current time and PID.
+		 */
+		if (unlikely(!pg_prng_strong_seed(&prng_state)))
+		{
+			TimestampTz now = GetCurrentTimestamp();
+			uint64		iseed;
+
+			/* Mix the PID with the most predictable bits of the timestamp */
+			iseed = (uint64) now ^ ((uint64) MyProcPid << 32);
+			pg_prng_seed(&prng_state, iseed);
+		}
+		prng_seed_set = true;
+	}
+}
+
+/*
+ * setseed() -
+ *
+ *	Seed the PRNG from a specified value in the range [-1.0, 1.0].
+ */
+Datum
+setseed(PG_FUNCTION_ARGS)
+{
+	float8		seed = PG_GETARG_FLOAT8(0);
+
+	if (seed < -1 || seed > 1 || isnan(seed))
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("setseed parameter %g is out of allowed range [-1,1]",
+					   seed));
+
+	pg_prng_fseed(&prng_state, seed);
+	prng_seed_set = true;
+
+	PG_RETURN_VOID();
+}
+
+/*
+ * drandom() -
+ *
+ *	Returns a random number chosen uniformly in the range [0.0, 1.0).
+ */
+Datum
+drandom(PG_FUNCTION_ARGS)
+{
+	float8		result;
+
+	initialize_prng();
+
+	/* pg_prng_double produces desired result range [0.0, 1.0) */
+	result = pg_prng_double(&prng_state);
+
+	PG_RETURN_FLOAT8(result);
+}
+
+/*
+ * drandom_normal() -
+ *
+ *	Returns a random number from a normal distribution.
+ */
+Datum
+drandom_normal(PG_FUNCTION_ARGS)
+{
+	float8		mean = PG_GETARG_FLOAT8(0);
+	float8		stddev = PG_GETARG_FLOAT8(1);
+	float8		result,
+				z;
+
+	initialize_prng();
+
+	/* Get random value from standard normal(mean = 0.0, stddev = 1.0) */
+	z = pg_prng_double_normal(&prng_state);
+	/* Transform the normal standard variable (z) */
+	/* using the target normal distribution parameters */
+	result = (stddev * z) + mean;
+
+	PG_RETURN_FLOAT8(result);
+}
+
+/*
+ * int4random() -
+ *
+ *	Returns a random 32-bit integer chosen uniformly in the specified range.
+ */
+Datum
+int4random(PG_FUNCTION_ARGS)
+{
+	int32		rmin = PG_GETARG_INT32(0);
+	int32		rmax = PG_GETARG_INT32(1);
+	int32		result;
+
+	if (rmin > rmax)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	initialize_prng();
+
+	result = (int32) pg_prng_int64_range(&prng_state, rmin, rmax);
+
+	PG_RETURN_INT32(result);
+}
+
+/*
+ * int8random() -
+ *
+ *	Returns a random 64-bit integer chosen uniformly in the specified range.
+ */
+Datum
+int8random(PG_FUNCTION_ARGS)
+{
+	int64		rmin = PG_GETARG_INT64(0);
+	int64		rmax = PG_GETARG_INT64(1);
+	int64		result;
+
+	if (rmin > rmax)
+		ereport(ERROR,
+				errcode(ERRCODE_INVALID_PARAMETER_VALUE),
+				errmsg("lower bound must be less than or equal to upper bound"));
+
+	initialize_prng();
+
+	result = pg_prng_int64_range(&prng_state, rmin, rmax);
+
+	PG_RETURN_INT64(result);
+}
+
+/*
+ * numeric_random() -
+ *
+ *	Returns a random numeric value chosen uniformly in the specified range.
+ */
+Datum
+numeric_random(PG_FUNCTION_ARGS)
+{
+	Numeric		rmin = PG_GETARG_NUMERIC(0);
+	Numeric		rmax = PG_GETARG_NUMERIC(1);
+	Numeric		result;
+
+	initialize_prng();
+
+	result = random_numeric(&prng_state, rmin, rmax);
+
+	PG_RETURN_NUMERIC(result);
+}
diff --git a/src/common/pg_prng.c b/src/common/pg_prng.c
index c1714a02bd..15b39411a9 100644
--- a/src/common/pg_prng.c
+++ b/src/common/pg_prng.c
@@ -184,6 +184,42 @@ pg_prng_int64p(pg_prng_state *state)
 	return (int64) (xoroshiro128ss(state) & UINT64CONST(0x7FFFFFFFFFFFFFFF));
 }
 
+/*
+ * Select a random int64 uniformly from the range [rmin, rmax].
+ * If the range is empty, rmin is always produced.
+ */
+int64
+pg_prng_int64_range(pg_prng_state *state, int64 rmin, int64 rmax)
+{
+	int64		val;
+
+	if (likely(rmax > rmin))
+	{
+		uint64		uval;
+
+		/*
+		 * Use pg_prng_uint64_range().  Can't simply pass it rmin and rmax,
+		 * since (uint64) rmin will be larger than (uint64) rmax if rmin < 0.
+		 */
+		uval = (uint64) rmin +
+			pg_prng_uint64_range(state, 0, (uint64) rmax - (uint64) rmin);
+
+		/*
+		 * Safely convert back to int64, avoiding implementation-defined
+		 * behavior for values larger than PG_INT64_MAX.  Modern compilers
+		 * will reduce this to a simple assignment.
+		 */
+		if (uval > PG_INT64_MAX)
+			val = (int64) (uval - PG_INT64_MIN) + PG_INT64_MIN;
+		else
+			val = (int64) uval;
+	}
+	else
+		val = rmin;
+
+	return val;
+}
+
 /*
  * Select a random uint32 uniformly from the range [0, PG_UINT32_MAX].
  */
diff --git a/src/include/catalog/pg_proc.dat b/src/include/catalog/pg_proc.dat
index 9c120fc2b7..0d2b993e38 100644
--- a/src/include/catalog/pg_proc.dat
+++ b/src/include/catalog/pg_proc.dat
@@ -3381,6 +3381,18 @@
   proname => 'random_normal', provolatile => 'v', proparallel => 'r',
   prorettype => 'float8', proargtypes => 'float8 float8',
   prosrc => 'drandom_normal' },
+{ oid => '9719', descr => 'random integer in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'int4', proargtypes => 'int4 int4',
+  proargnames => '{min,max}', prosrc => 'int4random' },
+{ oid => '9720', descr => 'random bigint in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'int8', proargtypes => 'int8 int8',
+  proargnames => '{min,max}', prosrc => 'int8random' },
+{ oid => '9721', descr => 'random numeric in range',
+  proname => 'random', provolatile => 'v', proparallel => 'r',
+  prorettype => 'numeric', proargtypes => 'numeric numeric',
+  proargnames => '{min,max}', prosrc => 'numeric_random' },
 { oid => '1599', descr => 'set random seed',
   proname => 'setseed', provolatile => 'v', proparallel => 'r',
   prorettype => 'void', proargtypes => 'float8', prosrc => 'setseed' },
diff --git a/src/include/common/pg_prng.h b/src/include/common/pg_prng.h
index e201b95686..c114c6419d 100644
--- a/src/include/common/pg_prng.h
+++ b/src/include/common/pg_prng.h
@@ -51,6 +51,7 @@ extern uint64 pg_prng_uint64(pg_prng_state *state);
 extern uint64 pg_prng_uint64_range(pg_prng_state *state, uint64 rmin, uint64 rmax);
 extern int64 pg_prng_int64(pg_prng_state *state);
 extern int64 pg_prng_int64p(pg_prng_state *state);
+extern int64 pg_prng_int64_range(pg_prng_state *state, int64 rmin, int64 rmax);
 extern uint32 pg_prng_uint32(pg_prng_state *state);
 extern int32 pg_prng_int32(pg_prng_state *state);
 extern int32 pg_prng_int32p(pg_prng_state *state);
diff --git a/src/include/utils/numeric.h b/src/include/utils/numeric.h
index 2f7184e299..43c75c436f 100644
--- a/src/include/utils/numeric.h
+++ b/src/include/utils/numeric.h
@@ -14,6 +14,7 @@
 #ifndef _PG_NUMERIC_H_
 #define _PG_NUMERIC_H_
 
+#include "common/pg_prng.h"
 #include "fmgr.h"
 
 /*
@@ -103,4 +104,7 @@ extern Numeric numeric_mod_opt_error(Numeric num1, Numeric num2,
 extern int32 numeric_int4_opt_error(Numeric num, bool *have_error);
 extern int64 numeric_int8_opt_error(Numeric num, bool *have_error);
 
+extern Numeric random_numeric(pg_prng_state *state,
+							  Numeric rmin, Numeric rmax);
+
 #endif							/* _PG_NUMERIC_H_ */
diff --git a/src/test/regress/expected/random.out b/src/test/regress/expected/random.out
index 223590720c..43cf88a363 100644
--- a/src/test/regress/expected/random.out
+++ b/src/test/regress/expected/random.out
@@ -120,6 +120,229 @@ SELECT ks_test_normal_random() OR
  t
 (1 row)
 
+-- Test random(min, max)
+-- invalid range bounds
+SELECT random(1, 0);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random(1000000000001, 1000000000000);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random(-2.0, -3.0);
+ERROR:  lower bound must be less than or equal to upper bound
+SELECT random('NaN'::numeric, 10);
+ERROR:  lower bound cannot be NaN
+SELECT random('-Inf'::numeric, 0);
+ERROR:  lower bound cannot be infinity
+SELECT random(0, 'NaN'::numeric);
+ERROR:  upper bound cannot be NaN
+SELECT random(0, 'Inf'::numeric);
+ERROR:  upper bound cannot be infinity
+-- empty range is OK
+SELECT random(101, 101);
+ random 
+--------
+    101
+(1 row)
+
+SELECT random(1000000000001, 1000000000001);
+    random     
+---------------
+ 1000000000001
+(1 row)
+
+SELECT random(3.14, 3.14);
+ random 
+--------
+   3.14
+(1 row)
+
+-- There should be no triple duplicates in 1000 full-range 32-bit random()
+-- values.  (Each of the C(1000, 3) choices of triplets from the 1000 values
+-- has a probability of 1/(2^32)^2 of being a triple duplicate, so the
+-- average number of triple duplicates is 1000 * 999 * 998 / 6 / 2^64, which
+-- is roughly 9e-12.)
+SELECT r, count(*)
+FROM (SELECT random(-2147483648, 2147483647) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 2;
+ r | count 
+---+-------
+(0 rows)
+
+-- There should be no duplicates in 1000 full-range 64-bit random() values.
+SELECT r, count(*)
+FROM (SELECT random_normal(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+ r | count 
+---+-------
+(0 rows)
+
+-- There should be no duplicates in 1000 15-digit random() numeric values.
+SELECT r, count(*)
+FROM (SELECT random_normal(0, 1 - 1e-15) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+ r | count 
+---+-------
+(0 rows)
+
+-- Expect at least one out of 2000 random values to be in the lowest and
+-- highest 1% of the range.
+SELECT (count(*) FILTER (WHERE r < -2104533975)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 2104533974)) > 0 AS has_large
+FROM (SELECT random(-2147483648, 2147483647) r FROM generate_series(1, 2000)) ss;
+ has_small | has_large 
+-----------+-----------
+ t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1500000000 OR r > 1500000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000, 1500000000) r FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+SELECT (count(*) FILTER (WHERE r < -9038904596117680292)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 9038904596117680291)) > 0 AS has_large
+FROM (SELECT random(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 2000)) ss;
+ has_small | has_large 
+-----------+-----------
+ t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1500000000000000 OR r > 1500000000000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000000000, 1500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+SELECT count(*) FILTER (WHERE r < -1.5 OR r > 1.5) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1.47)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1.47)) > 0 AS has_large
+FROM (SELECT random(-1.500000000000000, 1.500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+ out_of_range | has_small | has_large 
+--------------+-----------+-----------
+            0 | t         | t
+(1 row)
+
+-- Every possible value should occur at least once in 2500 random() values
+-- chosen from a range with 100 distinct values.
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-50, 49) r FROM generate_series(1, 2500));
+ min | max | count 
+-----+-----+-------
+ -50 |  49 |   100
+(1 row)
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(123000000000, 123000000099) r
+  FROM generate_series(1, 2500));
+     min      |     max      | count 
+--------------+--------------+-------
+ 123000000000 | 123000000099 |   100
+(1 row)
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-0.5, 0.49) r FROM generate_series(1, 2500));
+  min  | max  | count 
+-------+------+-------
+ -0.50 | 0.49 |   100
+(1 row)
+
+-- Check for uniform distribution using the Kolmogorov-Smirnov test.
+CREATE FUNCTION ks_test_uniform_random_int_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999) / 1000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() AS uniform_int;
+ uniform_int 
+-------------
+ t
+(1 row)
+
+CREATE FUNCTION ks_test_uniform_random_bigint_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999999999) / 1000000000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() AS uniform_bigint;
+ uniform_bigint 
+----------------
+ t
+(1 row)
+
+CREATE FUNCTION ks_test_uniform_random_numeric_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 0.999999) r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+SELECT ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() AS uniform_numeric;
+ uniform_numeric 
+-----------------
+ t
+(1 row)
+
 -- setseed() should produce a reproducible series of random() values.
 SELECT setseed(0.5);
  setseed 
@@ -176,3 +399,140 @@ SELECT random_normal(mean => 1, stddev => 0.1) r FROM generate_series(1, 10);
  0.96403105557543
 (10 rows)
 
+-- Reproducible random(min, max) values.
+SELECT random(1, 6) FROM generate_series(1, 10);
+ random 
+--------
+      5
+      4
+      5
+      1
+      6
+      1
+      1
+      3
+      6
+      5
+(10 rows)
+
+SELECT random(-2147483648, 2147483647) FROM generate_series(1, 10);
+   random    
+-------------
+   -84380014
+  1287883594
+ -1927252904
+    13516867
+ -1902961616
+ -1824286201
+  -871264469
+ -1225880415
+   229836730
+  -116039023
+(10 rows)
+
+SELECT random(-9223372036854775808, 9223372036854775807) FROM generate_series(1, 10);
+        random        
+----------------------
+ -6205280962992680052
+ -3583519428011353337
+   511801786318122700
+  4672737727839409655
+ -6674868801536280768
+ -7816052100626646489
+ -4340613370136007199
+ -5873174504107419786
+ -2249910101649817824
+ -4493828993910792325
+(10 rows)
+
+SELECT random(-1e30, 1e30) FROM generate_series(1, 10);
+             random              
+---------------------------------
+ -732116469803315942112255539315
+  794641423514877972798449289857
+ -576932746026123093304638334719
+  420625067723533225139761854757
+ -339227806779403187811001078919
+  -77667951539418104959241732636
+  239810941795708162629328071599
+  820784371155896967052141946697
+ -377084684544126871150439048352
+ -979773225250716295007225086726
+(10 rows)
+
+SELECT random(-0.4, 0.4) FROM generate_series(1, 10);
+ random 
+--------
+    0.1
+    0.0
+    0.4
+   -0.2
+    0.1
+    0.2
+    0.3
+    0.0
+   -0.2
+    0.2
+(10 rows)
+
+SELECT random(0, 1 - 1e-30) FROM generate_series(1, 10);
+              random              
+----------------------------------
+ 0.676442053784930109917469287265
+ 0.221310454098356723569995592911
+ 0.060101338174419259555193956224
+ 0.509960354695248239243002172364
+ 0.248680813394555793693952296993
+ 0.353262552880008646603494668901
+ 0.760692600450339509843044233719
+ 0.554987655310094483449494782510
+ 0.330890988458592995280347745733
+ 0.665435298280470361228607881507
+(10 rows)
+
+SELECT n, random(0, trim_scale(abs(1 - 10.0^(-n)))) FROM generate_series(-20, 20) n;
+  n  |         random         
+-----+------------------------
+ -20 |   94174615760837282445
+ -19 |    6692559888531296894
+ -18 |     801114552709125931
+ -17 |      44091460959939971
+ -16 |       2956109297383113
+ -15 |        783332278684523
+ -14 |         81534303241440
+ -13 |          2892623140500
+ -12 |           269397605141
+ -11 |            13027512296
+ -10 |             9178377775
+  -9 |              323534150
+  -8 |               91897803
+  -7 |                6091383
+  -6 |                  13174
+  -5 |                  92714
+  -4 |                   8079
+  -3 |                    429
+  -2 |                     30
+  -1 |                      3
+   0 |                      0
+   1 |                    0.1
+   2 |                   0.69
+   3 |                  0.492
+   4 |                 0.7380
+   5 |                0.77078
+   6 |               0.738142
+   7 |              0.1808815
+   8 |             0.14908933
+   9 |            0.222654042
+  10 |           0.2281295170
+  11 |          0.73655782966
+  12 |         0.056357256884
+  13 |        0.8998407524375
+  14 |       0.28198400530206
+  15 |      0.713478222805230
+  16 |     0.0415046850936909
+  17 |    0.45946350291315119
+  18 |   0.310966980367873753
+  19 |  0.4967623661709676512
+  20 | 0.60795101234744211935
+(41 rows)
+
diff --git a/src/test/regress/sql/random.sql b/src/test/regress/sql/random.sql
index 14cc76bc3c..ebfa7539ed 100644
--- a/src/test/regress/sql/random.sql
+++ b/src/test/regress/sql/random.sql
@@ -100,6 +100,161 @@ SELECT ks_test_normal_random() OR
        ks_test_normal_random() OR
        ks_test_normal_random() AS standard_normal;
 
+-- Test random(min, max)
+
+-- invalid range bounds
+SELECT random(1, 0);
+SELECT random(1000000000001, 1000000000000);
+SELECT random(-2.0, -3.0);
+SELECT random('NaN'::numeric, 10);
+SELECT random('-Inf'::numeric, 0);
+SELECT random(0, 'NaN'::numeric);
+SELECT random(0, 'Inf'::numeric);
+
+-- empty range is OK
+SELECT random(101, 101);
+SELECT random(1000000000001, 1000000000001);
+SELECT random(3.14, 3.14);
+
+-- There should be no triple duplicates in 1000 full-range 32-bit random()
+-- values.  (Each of the C(1000, 3) choices of triplets from the 1000 values
+-- has a probability of 1/(2^32)^2 of being a triple duplicate, so the
+-- average number of triple duplicates is 1000 * 999 * 998 / 6 / 2^64, which
+-- is roughly 9e-12.)
+SELECT r, count(*)
+FROM (SELECT random(-2147483648, 2147483647) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 2;
+
+-- There should be no duplicates in 1000 full-range 64-bit random() values.
+SELECT r, count(*)
+FROM (SELECT random_normal(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+
+-- There should be no duplicates in 1000 15-digit random() numeric values.
+SELECT r, count(*)
+FROM (SELECT random_normal(0, 1 - 1e-15) r
+      FROM generate_series(1, 1000)) ss
+GROUP BY r HAVING count(*) > 1;
+
+-- Expect at least one out of 2000 random values to be in the lowest and
+-- highest 1% of the range.
+SELECT (count(*) FILTER (WHERE r < -2104533975)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 2104533974)) > 0 AS has_large
+FROM (SELECT random(-2147483648, 2147483647) r FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1500000000 OR r > 1500000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000, 1500000000) r FROM generate_series(1, 2000)) ss;
+
+SELECT (count(*) FILTER (WHERE r < -9038904596117680292)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 9038904596117680291)) > 0 AS has_large
+FROM (SELECT random(-9223372036854775808, 9223372036854775807) r
+      FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1500000000000000 OR r > 1500000000000000) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1470000000000000)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1470000000000000)) > 0 AS has_large
+FROM (SELECT random(-1500000000000000, 1500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+
+SELECT count(*) FILTER (WHERE r < -1.5 OR r > 1.5) AS out_of_range,
+       (count(*) FILTER (WHERE r < -1.47)) > 0 AS has_small,
+       (count(*) FILTER (WHERE r > 1.47)) > 0 AS has_large
+FROM (SELECT random(-1.500000000000000, 1.500000000000000) r
+      FROM generate_series(1, 2000)) ss;
+
+-- Every possible value should occur at least once in 2500 random() values
+-- chosen from a range with 100 distinct values.
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-50, 49) r FROM generate_series(1, 2500));
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(123000000000, 123000000099) r
+  FROM generate_series(1, 2500));
+
+SELECT min(r), max(r), count(r) FROM (
+  SELECT DISTINCT random(-0.5, 0.49) r FROM generate_series(1, 2500));
+
+-- Check for uniform distribution using the Kolmogorov-Smirnov test.
+
+CREATE FUNCTION ks_test_uniform_random_int_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999) / 1000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() OR
+       ks_test_uniform_random_int_in_range() AS uniform_int;
+
+CREATE FUNCTION ks_test_uniform_random_bigint_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 999999999999) / 1000000000000.0 r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() OR
+       ks_test_uniform_random_bigint_in_range() AS uniform_bigint;
+
+CREATE FUNCTION ks_test_uniform_random_numeric_in_range()
+RETURNS boolean AS
+$$
+DECLARE
+  n int := 1000;        -- Number of samples
+  c float8 := 1.94947;  -- Critical value for 99.9% confidence
+  ok boolean;
+BEGIN
+  ok := (
+    WITH samples AS (
+      SELECT random(0, 0.999999) r FROM generate_series(1, n) ORDER BY 1
+    ), indexed_samples AS (
+      SELECT (row_number() OVER())-1.0 i, r FROM samples
+    )
+    SELECT max(abs(i/n-r)) < c / sqrt(n) FROM indexed_samples
+  );
+  RETURN ok;
+END
+$$
+LANGUAGE plpgsql;
+
+SELECT ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() OR
+       ks_test_uniform_random_numeric_in_range() AS uniform_numeric;
+
 -- setseed() should produce a reproducible series of random() values.
 
 SELECT setseed(0.5);
@@ -113,3 +268,12 @@ SET extra_float_digits = -1;
 
 SELECT random_normal() FROM generate_series(1, 10);
 SELECT random_normal(mean => 1, stddev => 0.1) r FROM generate_series(1, 10);
+
+-- Reproducible random(min, max) values.
+SELECT random(1, 6) FROM generate_series(1, 10);
+SELECT random(-2147483648, 2147483647) FROM generate_series(1, 10);
+SELECT random(-9223372036854775808, 9223372036854775807) FROM generate_series(1, 10);
+SELECT random(-1e30, 1e30) FROM generate_series(1, 10);
+SELECT random(-0.4, 0.4) FROM generate_series(1, 10);
+SELECT random(0, 1 - 1e-30) FROM generate_series(1, 10);
+SELECT n, random(0, trim_scale(abs(1 - 10.0^(-n)))) FROM generate_series(-20, 20) n;
-- 
2.35.3