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pgbench: Remove \setrandom.

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You can now do the same thing via \set using the appropriate function,
either random(), random_gaussian(), or random_exponential(), depending
on the desired distribution.  This is not backward-compatible, but per
discussion, it's worth it to avoid having the old syntax hang around
forever.

Fabien Coelho, reviewed by Michael Paquier, and adjusted by me.
pull/11/head
Robert Haas 10 years ago
parent 7abc157165
commit ad9566470b
2 changed files with 2 additions and 233 deletions
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
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  1. 54
      doc/src/sgml/ref/pgbench.sgml
  2. 181
      src/bin/pgbench/pgbench.c

54
doc/src/sgml/ref/pgbench.sgml
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@ -836,60 +836,6 @@ pgbench <optional> <replaceable>options</> </optional> <replaceable>dbname</>
</listitem>
</varlistentry>
<varlistentry>
<term>
<literal>\setrandom <replaceable>varname</> <replaceable>min</> <replaceable>max</> [ uniform | { gaussian | exponential } <replaceable>parameter</> ]</literal>
</term>
<listitem>
<para>
Sets variable <replaceable>varname</> to a random integer value
between the limits <replaceable>min</> and <replaceable>max</> inclusive.
Each limit can be either an integer constant or a
<literal>:</><replaceable>variablename</> reference to a variable
having an integer value.
</para>
<para>
<itemizedlist>
<listitem>
<para>
<literal>\setrandom n 1 10</> or <literal>\setrandom n 1 10 uniform</>
is equivalent to <literal>\set n random(1, 10)</> and uses a uniform
distribution.
</para>
</listitem>
<listitem>
<para>
<literal>\setrandom n 1 10 exponential 3.0</> is equivalent to
<literal>\set n random_exponential(1, 10, 3.0)</> and uses an
exponential distribution.
</para>
</listitem>
<listitem>
<para>
<literal>\setrandom n 1 10 gaussian 2.0</> is equivalent to
<literal>\set n random_gaussian(1, 10, 2.0)</>, and uses a gaussian
distribution.
</para>
</listitem>
</itemizedlist>
See the documentation of these functions below for further information
about the precise shape of these distributions, depending on the value
of the parameter.
</para>
<para>
Example:
<programlisting>
\setrandom aid 1 :naccounts gaussian 5.0
</programlisting></para>
</listitem>
</varlistentry>
<varlistentry>
<term>
<literal>\sleep <replaceable>number</> [ us | ms | s ]</literal>

181
src/bin/pgbench/pgbench.c
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@ -1941,148 +1941,7 @@ top:
fprintf(stderr, "\n");
}
/*
* Note: this section could be removed, as the same functionnality
* is available through \set xxx random_gaussian(...)
*/
if (pg_strcasecmp(argv[0], "setrandom") == 0)
{
char *var;
int64 min,
max;
double parameter = 0;
char res[64];
if (*argv[2] == ':')
{
if ((var = getVariable(st, argv[2] + 1)) == NULL)
{
fprintf(stderr, "%s: undefined variable \"%s\"\n",
argv[0], argv[2]);
st->ecnt++;
return true;
}
min = strtoint64(var);
}
else
min = strtoint64(argv[2]);
if (*argv[3] == ':')
{
if ((var = getVariable(st, argv[3] + 1)) == NULL)
{
fprintf(stderr, "%s: undefined variable \"%s\"\n",
argv[0], argv[3]);
st->ecnt++;
return true;
}
max = strtoint64(var);
}
else
max = strtoint64(argv[3]);
if (max < min)
{
fprintf(stderr, "%s: \\setrandom maximum is less than minimum\n",
argv[0]);
st->ecnt++;
return true;
}
/*
* Generate random number functions need to be able to subtract
* max from min and add one to the result without overflowing.
* Since we know max > min, we can detect overflow just by
* checking for a negative result. But we must check both that the
* subtraction doesn't overflow, and that adding one to the result
* doesn't overflow either.
*/
if (max - min < 0 || (max - min) + 1 < 0)
{
fprintf(stderr, "%s: \\setrandom range is too large\n",
argv[0]);
st->ecnt++;
return true;
}
if (argc == 4 || /* uniform without or with "uniform" keyword */
(argc == 5 && pg_strcasecmp(argv[4], "uniform") == 0))
{
#ifdef DEBUG
printf("min: " INT64_FORMAT " max: " INT64_FORMAT " random: " INT64_FORMAT "\n", min, max, getrand(thread, min, max));
#endif
snprintf(res, sizeof(res), INT64_FORMAT, getrand(thread, min, max));
}
else if (argc == 6 &&
((pg_strcasecmp(argv[4], "gaussian") == 0) ||
(pg_strcasecmp(argv[4], "exponential") == 0)))
{
if (*argv[5] == ':')
{
if ((var = getVariable(st, argv[5] + 1)) == NULL)
{
fprintf(stderr, "%s: invalid parameter: \"%s\"\n",
argv[0], argv[5]);
st->ecnt++;
return true;
}
parameter = strtod(var, NULL);
}
else
parameter = strtod(argv[5], NULL);
if (pg_strcasecmp(argv[4], "gaussian") == 0)
{
if (parameter < MIN_GAUSSIAN_PARAM)
{
fprintf(stderr, "gaussian parameter must be at least %f (not \"%s\")\n", MIN_GAUSSIAN_PARAM, argv[5]);
st->ecnt++;
return true;
}
#ifdef DEBUG
printf("min: " INT64_FORMAT " max: " INT64_FORMAT " random: " INT64_FORMAT "\n",
min, max,
getGaussianRand(thread, min, max, parameter));
#endif
snprintf(res, sizeof(res), INT64_FORMAT,
getGaussianRand(thread, min, max, parameter));
}
else if (pg_strcasecmp(argv[4], "exponential") == 0)
{
if (parameter <= 0.0)
{
fprintf(stderr,
"exponential parameter must be greater than zero (not \"%s\")\n",
argv[5]);
st->ecnt++;
return true;
}
#ifdef DEBUG
printf("min: " INT64_FORMAT " max: " INT64_FORMAT " random: " INT64_FORMAT "\n",
min, max,
getExponentialRand(thread, min, max, parameter));
#endif
snprintf(res, sizeof(res), INT64_FORMAT,
getExponentialRand(thread, min, max, parameter));
}
}
else /* this means an error somewhere in the parsing phase... */
{
fprintf(stderr, "%s: invalid arguments for \\setrandom\n",
argv[0]);
st->ecnt++;
return true;
}
if (!putVariable(st, argv[0], argv[1], res))
{
st->ecnt++;
return true;
}
st->listen = true;
}
else if (pg_strcasecmp(argv[0], "set") == 0)
if (pg_strcasecmp(argv[0], "set") == 0)
{
char res[64];
PgBenchExpr *expr = commands[st->state]->expr;
@ -2880,43 +2739,7 @@ process_backslash_command(PsqlScanState sstate, const char *source)
start_offset,
end_offset);
if (pg_strcasecmp(my_command->argv[0], "setrandom") == 0)
{
/*--------
* parsing:
* \setrandom variable min max [uniform]
* \setrandom variable min max (gaussian|exponential) parameter
*/
if (my_command->argc < 4)
syntax_error(source, lineno, my_command->line, my_command->argv[0],
"missing arguments", NULL, -1);
if (my_command->argc == 4 || /* uniform without/with "uniform"
* keyword */
(my_command->argc == 5 &&
pg_strcasecmp(my_command->argv[4], "uniform") == 0))
{
/* nothing to do */
}
else if ( /* argc >= 5 */
(pg_strcasecmp(my_command->argv[4], "gaussian") == 0) ||
(pg_strcasecmp(my_command->argv[4], "exponential") == 0))
{
if (my_command->argc < 6)
syntax_error(source, lineno, my_command->line, my_command->argv[0],
"missing parameter", NULL, -1);
else if (my_command->argc > 6)
syntax_error(source, lineno, my_command->line, my_command->argv[0],
"too many arguments", NULL,
offsets[6] - start_offset);
}
else /* unrecognized distribution argument */
syntax_error(source, lineno, my_command->line, my_command->argv[0],
"unexpected argument", my_command->argv[4],
offsets[4] - start_offset);
}
else if (pg_strcasecmp(my_command->argv[0], "sleep") == 0)
if (pg_strcasecmp(my_command->argv[0], "sleep") == 0)
{
if (my_command->argc < 2)
syntax_error(source, lineno, my_command->line, my_command->argv[0],

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