Provided by: postgresql-17_17.2-1_amd64 
NAME
pgbench - run a benchmark test on PostgreSQL
SYNOPSIS
pgbench -i [option...] [dbname]
pgbench [option...] [dbname]
DESCRIPTION
pgbench is a simple program for running benchmark tests on PostgreSQL. It runs the same
sequence of SQL commands over and over, possibly in multiple concurrent database sessions,
and then calculates the average transaction rate (transactions per second). By default,
pgbench tests a scenario that is loosely based on TPC-B, involving five SELECT, UPDATE,
and INSERT commands per transaction. However, it is easy to test other cases by writing
your own transaction script files.
Typical output from pgbench looks like:
transaction type: <builtin: TPC-B (sort of)>
scaling factor: 10
query mode: simple
number of clients: 10
number of threads: 1
maximum number of tries: 1
number of transactions per client: 1000
number of transactions actually processed: 10000/10000
number of failed transactions: 0 (0.000%)
latency average = 11.013 ms
latency stddev = 7.351 ms
initial connection time = 45.758 ms
tps = 896.967014 (without initial connection time)
The first seven lines report some of the most important parameter settings. The sixth line
reports the maximum number of tries for transactions with serialization or deadlock errors
(see Failures and Serialization/Deadlock Retries for more information). The eighth line
reports the number of transactions completed and intended (the latter being just the
product of number of clients and number of transactions per client); these will be equal
unless the run failed before completion or some SQL command(s) failed. (In -T mode, only
the actual number of transactions is printed.) The next line reports the number of failed
transactions due to serialization or deadlock errors (see Failures and
Serialization/Deadlock Retries for more information). The last line reports the number of
transactions per second.
The default TPC-B-like transaction test requires specific tables to be set up beforehand.
pgbench should be invoked with the -i (initialize) option to create and populate these
tables. (When you are testing a custom script, you don't need this step, but will instead
need to do whatever setup your test needs.) Initialization looks like:
pgbench -i [ other-options ] dbname
where dbname is the name of the already-created database to test in. (You may also need
-h, -p, and/or -U options to specify how to connect to the database server.)
Caution
pgbench -i creates four tables pgbench_accounts, pgbench_branches, pgbench_history,
and pgbench_tellers, destroying any existing tables of these names. Be very careful to
use another database if you have tables having these names!
At the default “scale factor” of 1, the tables initially contain this many rows:
table # of rows
---------------------------------
pgbench_branches 1
pgbench_tellers 10
pgbench_accounts 100000
pgbench_history 0
You can (and, for most purposes, probably should) increase the number of rows by using the
-s (scale factor) option. The -F (fillfactor) option might also be used at this point.
Once you have done the necessary setup, you can run your benchmark with a command that
doesn't include -i, that is
pgbench [ options ] dbname
In nearly all cases, you'll need some options to make a useful test. The most important
options are -c (number of clients), -t (number of transactions), -T (time limit), and -f
(specify a custom script file). See below for a full list.
OPTIONS
The following is divided into three subsections. Different options are used during
database initialization and while running benchmarks, but some options are useful in both
cases.
Initialization Options
pgbench accepts the following command-line initialization arguments:
[-d] dbname
[--dbname=]dbname
Specifies the name of the database to test in. If this is not specified, the
environment variable PGDATABASE is used. If that is not set, the user name specified
for the connection is used.
-i
--initialize
Required to invoke initialization mode.
-I init_steps
--init-steps=init_steps
Perform just a selected set of the normal initialization steps. init_steps specifies
the initialization steps to be performed, using one character per step. Each step is
invoked in the specified order. The default is dtgvp. The available steps are:
d (Drop)
Drop any existing pgbench tables.
t (create Tables)
Create the tables used by the standard pgbench scenario, namely pgbench_accounts,
pgbench_branches, pgbench_history, and pgbench_tellers.
g or G (Generate data, client-side or server-side)
Generate data and load it into the standard tables, replacing any data already
present.
With g (client-side data generation), data is generated in pgbench client and then
sent to the server. This uses the client/server bandwidth extensively through a
COPY. pgbench uses the FREEZE option with version 14 or later of PostgreSQL to
speed up subsequent VACUUM, except on the pgbench_accounts table if partitions are
enabled. Using g causes logging to print one message every 100,000 rows while
generating data for all tables.
With G (server-side data generation), only small queries are sent from the pgbench
client and then data is actually generated in the server. No significant bandwidth
is required for this variant, but the server will do more work. Using G causes
logging not to print any progress message while generating data.
The default initialization behavior uses client-side data generation (equivalent
to g).
v (Vacuum)
Invoke VACUUM on the standard tables.
p (create Primary keys)
Create primary key indexes on the standard tables.
f (create Foreign keys)
Create foreign key constraints between the standard tables. (Note that this step
is not performed by default.)
-F fillfactor
--fillfactor=fillfactor
Create the pgbench_accounts, pgbench_tellers and pgbench_branches tables with the
given fillfactor. Default is 100.
-n
--no-vacuum
Perform no vacuuming during initialization. (This option suppresses the v
initialization step, even if it was specified in -I.)
-q
--quiet
Switch logging to quiet mode, producing only one progress message per 5 seconds. The
default logging prints one message each 100,000 rows, which often outputs many lines
per second (especially on good hardware).
This setting has no effect if G is specified in -I.
-s scale_factor
--scale=scale_factor
Multiply the number of rows generated by the scale factor. For example, -s 100 will
create 10,000,000 rows in the pgbench_accounts table. Default is 1. When the scale is
20,000 or larger, the columns used to hold account identifiers (aid columns) will
switch to using larger integers (bigint), in order to be big enough to hold the range
of account identifiers.
--foreign-keys
Create foreign key constraints between the standard tables. (This option adds the f
step to the initialization step sequence, if it is not already present.)
--index-tablespace=index_tablespace
Create indexes in the specified tablespace, rather than the default tablespace.
--partition-method=NAME
Create a partitioned pgbench_accounts table with NAME method. Expected values are
range or hash. This option requires that --partitions is set to non-zero. If
unspecified, default is range.
--partitions=NUM
Create a partitioned pgbench_accounts table with NUM partitions of nearly equal size
for the scaled number of accounts. Default is 0, meaning no partitioning.
--tablespace=tablespace
Create tables in the specified tablespace, rather than the default tablespace.
--unlogged-tables
Create all tables as unlogged tables, rather than permanent tables.
Benchmarking Options
pgbench accepts the following command-line benchmarking arguments:
-b scriptname[@weight]
--builtin=scriptname[@weight]
Add the specified built-in script to the list of scripts to be executed. Available
built-in scripts are: tpcb-like, simple-update and select-only. Unambiguous prefixes
of built-in names are accepted. With the special name list, show the list of built-in
scripts and exit immediately.
Optionally, write an integer weight after @ to adjust the probability of selecting
this script versus other ones. The default weight is 1. See below for details.
-c clients
--client=clients
Number of clients simulated, that is, number of concurrent database sessions. Default
is 1.
-C
--connect
Establish a new connection for each transaction, rather than doing it just once per
client session. This is useful to measure the connection overhead.
-D varname=value
--define=varname=value
Define a variable for use by a custom script (see below). Multiple -D options are
allowed.
-f filename[@weight]
--file=filename[@weight]
Add a transaction script read from filename to the list of scripts to be executed.
Optionally, write an integer weight after @ to adjust the probability of selecting
this script versus other ones. The default weight is 1. (To use a script file name
that includes an @ character, append a weight so that there is no ambiguity, for
example filen@me@1.) See below for details.
-j threads
--jobs=threads
Number of worker threads within pgbench. Using more than one thread can be helpful on
multi-CPU machines. Clients are distributed as evenly as possible among available
threads. Default is 1.
-l
--log
Write information about each transaction to a log file. See below for details.
-L limit
--latency-limit=limit
Transactions that last more than limit milliseconds are counted and reported
separately, as late.
When throttling is used (--rate=...), transactions that lag behind schedule by more
than limit ms, and thus have no hope of meeting the latency limit, are not sent to the
server at all. They are counted and reported separately as skipped.
When the --max-tries option is used, a transaction which fails due to a serialization
anomaly or from a deadlock will not be retried if the total time of all its tries is
greater than limit ms. To limit only the time of tries and not their number, use
--max-tries=0. By default, the option --max-tries is set to 1 and transactions with
serialization/deadlock errors are not retried. See Failures and Serialization/Deadlock
Retries for more information about retrying such transactions.
-M querymode
--protocol=querymode
Protocol to use for submitting queries to the server:
• simple: use simple query protocol.
• extended: use extended query protocol.
• prepared: use extended query protocol with prepared statements.
In the prepared mode, pgbench reuses the parse analysis result starting from the
second query iteration, so pgbench runs faster than in other modes.
The default is simple query protocol. (See Chapter 53 for more information.)
-n
--no-vacuum
Perform no vacuuming before running the test. This option is necessary if you are
running a custom test scenario that does not include the standard tables
pgbench_accounts, pgbench_branches, pgbench_history, and pgbench_tellers.
-N
--skip-some-updates
Run built-in simple-update script. Shorthand for -b simple-update.
-P sec
--progress=sec
Show progress report every sec seconds. The report includes the time since the
beginning of the run, the TPS since the last report, and the transaction latency
average, standard deviation, and the number of failed transactions since the last
report. Under throttling (-R), the latency is computed with respect to the transaction
scheduled start time, not the actual transaction beginning time, thus it also includes
the average schedule lag time. When --max-tries is used to enable transaction retries
after serialization/deadlock errors, the report includes the number of retried
transactions and the sum of all retries.
-r
--report-per-command
Report the following statistics for each command after the benchmark finishes: the
average per-statement latency (execution time from the perspective of the client), the
number of failures, and the number of retries after serialization or deadlock errors
in this command. The report displays retry statistics only if the --max-tries option
is not equal to 1.
-R rate
--rate=rate
Execute transactions targeting the specified rate instead of running as fast as
possible (the default). The rate is given in transactions per second. If the targeted
rate is above the maximum possible rate, the rate limit won't impact the results.
The rate is targeted by starting transactions along a Poisson-distributed schedule
time line. The expected start time schedule moves forward based on when the client
first started, not when the previous transaction ended. That approach means that when
transactions go past their original scheduled end time, it is possible for later ones
to catch up again.
When throttling is active, the transaction latency reported at the end of the run is
calculated from the scheduled start times, so it includes the time each transaction
had to wait for the previous transaction to finish. The wait time is called the
schedule lag time, and its average and maximum are also reported separately. The
transaction latency with respect to the actual transaction start time, i.e., the time
spent executing the transaction in the database, can be computed by subtracting the
schedule lag time from the reported latency.
If --latency-limit is used together with --rate, a transaction can lag behind so much
that it is already over the latency limit when the previous transaction ends, because
the latency is calculated from the scheduled start time. Such transactions are not
sent to the server, but are skipped altogether and counted separately.
A high schedule lag time is an indication that the system cannot process transactions
at the specified rate, with the chosen number of clients and threads. When the average
transaction execution time is longer than the scheduled interval between each
transaction, each successive transaction will fall further behind, and the schedule
lag time will keep increasing the longer the test run is. When that happens, you will
have to reduce the specified transaction rate.
-s scale_factor
--scale=scale_factor
Report the specified scale factor in pgbench's output. With the built-in tests, this
is not necessary; the correct scale factor will be detected by counting the number of
rows in the pgbench_branches table. However, when testing only custom benchmarks (-f
option), the scale factor will be reported as 1 unless this option is used.
-S
--select-only
Run built-in select-only script. Shorthand for -b select-only.
-t transactions
--transactions=transactions
Number of transactions each client runs. Default is 10.
-T seconds
--time=seconds
Run the test for this many seconds, rather than a fixed number of transactions per
client. -t and -T are mutually exclusive.
-v
--vacuum-all
Vacuum all four standard tables before running the test. With neither -n nor -v,
pgbench will vacuum the pgbench_tellers and pgbench_branches tables, and will truncate
pgbench_history.
--aggregate-interval=seconds
Length of aggregation interval (in seconds). May be used only with -l option. With
this option, the log contains per-interval summary data, as described below.
--exit-on-abort
Exit immediately when any client is aborted due to some error. Without this option,
even when a client is aborted, other clients could continue their run as specified by
-t or -T option, and pgbench will print an incomplete results in this case.
Note that serialization failures or deadlock failures do not abort the client, so they
are not affected by this option. See Failures and Serialization/Deadlock Retries for
more information.
--failures-detailed
Report failures in per-transaction and aggregation logs, as well as in the main and
per-script reports, grouped by the following types:
• serialization failures;
• deadlock failures;
See Failures and Serialization/Deadlock Retries for more information.
--log-prefix=prefix
Set the filename prefix for the log files created by --log. The default is
pgbench_log.
--max-tries=number_of_tries
Enable retries for transactions with serialization/deadlock errors and set the maximum
number of these tries. This option can be combined with the --latency-limit option
which limits the total time of all transaction tries; moreover, you cannot use an
unlimited number of tries (--max-tries=0) without --latency-limit or --time. The
default value is 1 and transactions with serialization/deadlock errors are not
retried. See Failures and Serialization/Deadlock Retries for more information about
retrying such transactions.
--progress-timestamp
When showing progress (option -P), use a timestamp (Unix epoch) instead of the number
of seconds since the beginning of the run. The unit is in seconds, with millisecond
precision after the dot. This helps compare logs generated by various tools.
--random-seed=seed
Set random generator seed. Seeds the system random number generator, which then
produces a sequence of initial generator states, one for each thread. Values for seed
may be: time (the default, the seed is based on the current time), rand (use a strong
random source, failing if none is available), or an unsigned decimal integer value.
The random generator is invoked explicitly from a pgbench script (random...
functions) or implicitly (for instance option --rate uses it to schedule
transactions). When explicitly set, the value used for seeding is shown on the
terminal. Any value allowed for seed may also be provided through the environment
variable PGBENCH_RANDOM_SEED. To ensure that the provided seed impacts all possible
uses, put this option first or use the environment variable.
Setting the seed explicitly allows to reproduce a pgbench run exactly, as far as
random numbers are concerned. As the random state is managed per thread, this means
the exact same pgbench run for an identical invocation if there is one client per
thread and there are no external or data dependencies. From a statistical viewpoint
reproducing runs exactly is a bad idea because it can hide the performance variability
or improve performance unduly, e.g., by hitting the same pages as a previous run.
However, it may also be of great help for debugging, for instance re-running a tricky
case which leads to an error. Use wisely.
--sampling-rate=rate
Sampling rate, used when writing data into the log, to reduce the amount of log
generated. If this option is given, only the specified fraction of transactions are
logged. 1.0 means all transactions will be logged, 0.05 means only 5% of the
transactions will be logged.
Remember to take the sampling rate into account when processing the log file. For
example, when computing TPS values, you need to multiply the numbers accordingly
(e.g., with 0.01 sample rate, you'll only get 1/100 of the actual TPS).
--show-script=scriptname
Show the actual code of builtin script scriptname on stderr, and exit immediately.
--verbose-errors
Print messages about all errors and failures (errors without retrying) including which
limit for retries was exceeded and how far it was exceeded for the
serialization/deadlock failures. (Note that in this case the output can be
significantly increased.). See Failures and Serialization/Deadlock Retries for more
information.
Common Options
pgbench also accepts the following common command-line arguments for connection parameters
and other common settings:
--debug
Print debugging output.
-h hostname
--host=hostname
The database server's host name
-p port
--port=port
The database server's port number
-U login
--username=login
The user name to connect as
-V
--version
Print the pgbench version and exit.
-?
--help
Show help about pgbench command line arguments, and exit.
EXIT STATUS
A successful run will exit with status 0. Exit status 1 indicates static problems such as
invalid command-line options or internal errors which are supposed to never occur. Early
errors that occur when starting benchmark such as initial connection failures also exit
with status 1. Errors during the run such as database errors or problems in the script
will result in exit status 2. In the latter case, pgbench will print partial results if
--exit-on-abort option is not specified.
ENVIRONMENT
PGDATABASE
PGHOST
PGPORT
PGUSER
Default connection parameters.
This utility, like most other PostgreSQL utilities, uses the environment variables
supported by libpq (see Section 32.15).
The environment variable PG_COLOR specifies whether to use color in diagnostic messages.
Possible values are always, auto and never.
NOTES
What Is the “Transaction” Actually Performed in pgbench?
pgbench executes test scripts chosen randomly from a specified list. The scripts may
include built-in scripts specified with -b and user-provided scripts specified with -f.
Each script may be given a relative weight specified after an @ so as to change its
selection probability. The default weight is 1. Scripts with a weight of 0 are ignored.
The default built-in transaction script (also invoked with -b tpcb-like) issues seven
commands per transaction over randomly chosen aid, tid, bid and delta. The scenario is
inspired by the TPC-B benchmark, but is not actually TPC-B, hence the name.
1. BEGIN;
2. UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
3. SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
4. UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
5. UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
6. INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid,
:delta, CURRENT_TIMESTAMP);
7. END;
If you select the simple-update built-in (also -N), steps 4 and 5 aren't included in the
transaction. This will avoid update contention on these tables, but it makes the test case
even less like TPC-B.
If you select the select-only built-in (also -S), only the SELECT is issued.
Custom Scripts
pgbench has support for running custom benchmark scenarios by replacing the default
transaction script (described above) with a transaction script read from a file (-f
option). In this case a “transaction” counts as one execution of a script file.
A script file contains one or more SQL commands terminated by semicolons. Empty lines and
lines beginning with -- are ignored. Script files can also contain “meta commands”, which
are interpreted by pgbench itself, as described below.
Note
Before PostgreSQL 9.6, SQL commands in script files were terminated by newlines, and
so they could not be continued across lines. Now a semicolon is required to separate
consecutive SQL commands (though an SQL command does not need one if it is followed by
a meta command). If you need to create a script file that works with both old and new
versions of pgbench, be sure to write each SQL command on a single line ending with a
semicolon.
It is assumed that pgbench scripts do not contain incomplete blocks of SQL
transactions. If at runtime the client reaches the end of the script without
completing the last transaction block, it will be aborted.
There is a simple variable-substitution facility for script files. Variable names must
consist of letters (including non-Latin letters), digits, and underscores, with the first
character not being a digit. Variables can be set by the command-line -D option, explained
above, or by the meta commands explained below. In addition to any variables preset by -D
command-line options, there are a few variables that are preset automatically, listed in
Table 298. A value specified for these variables using -D takes precedence over the
automatic presets. Once set, a variable's value can be inserted into an SQL command by
writing :variablename. When running more than one client session, each session has its own
set of variables. pgbench supports up to 255 variable uses in one statement.
Table 298. pgbench Automatic Variables
┌─────────────┬───────────────────────────────┐
│Variable │ Description │
├─────────────┼───────────────────────────────┤
│client_id │ unique number identifying the │
│ │ client session (starts from │
│ │ zero) │
├─────────────┼───────────────────────────────┤
│default_seed │ seed used in hash and │
│ │ pseudorandom permutation │
│ │ functions by default │
├─────────────┼───────────────────────────────┤
│random_seed │ random generator seed (unless │
│ │ overwritten with -D) │
├─────────────┼───────────────────────────────┤
│scale │ current scale factor │
└─────────────┴───────────────────────────────┘
Script file meta commands begin with a backslash (\) and normally extend to the end of the
line, although they can be continued to additional lines by writing backslash-return.
Arguments to a meta command are separated by white space. These meta commands are
supported:
\gset [prefix] \aset [prefix]
These commands may be used to end SQL queries, taking the place of the terminating
semicolon (;).
When the \gset command is used, the preceding SQL query is expected to return one row,
the columns of which are stored into variables named after column names, and prefixed
with prefix if provided.
When the \aset command is used, all combined SQL queries (separated by \;) have their
columns stored into variables named after column names, and prefixed with prefix if
provided. If a query returns no row, no assignment is made and the variable can be
tested for existence to detect this. If a query returns more than one row, the last
value is kept.
\gset and \aset cannot be used in pipeline mode, since the query results are not yet
available by the time the commands would need them.
The following example puts the final account balance from the first query into
variable abalance, and fills variables p_two and p_three with integers from the third
query. The result of the second query is discarded. The result of the two last
combined queries are stored in variables four and five.
UPDATE pgbench_accounts
SET abalance = abalance + :delta
WHERE aid = :aid
RETURNING abalance \gset
-- compound of two queries
SELECT 1 \;
SELECT 2 AS two, 3 AS three \gset p_
SELECT 4 AS four \; SELECT 5 AS five \aset
\if expression
\elif expression
\else
\endif
This group of commands implements nestable conditional blocks, similarly to psql's \if
expression. Conditional expressions are identical to those with \set, with non-zero
values interpreted as true.
\set varname expression
Sets variable varname to a value calculated from expression. The expression may
contain the NULL constant, Boolean constants TRUE and FALSE, integer constants such as
5432, double constants such as 3.14159, references to variables :variablename,
operators with their usual SQL precedence and associativity, function calls, SQL CASE
generic conditional expressions and parentheses.
Functions and most operators return NULL on NULL input.
For conditional purposes, non zero numerical values are TRUE, zero numerical values
and NULL are FALSE.
Too large or small integer and double constants, as well as integer arithmetic
operators (+, -, * and /) raise errors on overflows.
When no final ELSE clause is provided to a CASE, the default value is NULL.
Examples:
\set ntellers 10 * :scale
\set aid (1021 * random(1, 100000 * :scale)) % \
(100000 * :scale) + 1
\set divx CASE WHEN :x <> 0 THEN :y/:x ELSE NULL END
\sleep number [ us | ms | s ]
Causes script execution to sleep for the specified duration in microseconds (us),
milliseconds (ms) or seconds (s). If the unit is omitted then seconds are the default.
number can be either an integer constant or a :variablename reference to a variable
having an integer value.
Example:
\sleep 10 ms
\setshell varname command [ argument ... ]
Sets variable varname to the result of the shell command command with the given
argument(s). The command must return an integer value through its standard output.
command and each argument can be either a text constant or a :variablename reference
to a variable. If you want to use an argument starting with a colon, write an
additional colon at the beginning of argument.
Example:
\setshell variable_to_be_assigned command literal_argument :variable ::literal_starting_with_colon
\shell command [ argument ... ]
Same as \setshell, but the result of the command is discarded.
Example:
\shell command literal_argument :variable ::literal_starting_with_colon
\startpipeline
\syncpipeline
\endpipeline
This group of commands implements pipelining of SQL statements. A pipeline must begin
with a \startpipeline and end with an \endpipeline. In between there may be any number
of \syncpipeline commands, which sends a sync message without ending the ongoing
pipeline and flushing the send buffer. In pipeline mode, statements are sent to the
server without waiting for the results of previous statements. See Section 32.5 for
more details. Pipeline mode requires the use of extended query protocol.
Built-in Operators
The arithmetic, bitwise, comparison and logical operators listed in Table 299 are built
into pgbench and may be used in expressions appearing in \set. The operators are listed in
increasing precedence order. Except as noted, operators taking two numeric inputs will
produce a double value if either input is double, otherwise they produce an integer
result.
Table 299. pgbench Operators
┌─────────────────────────────────────────────────┐
│ │
│ Operator │
│ │
│ .PP Description │
│ │
│ .PP Example(s) │
├─────────────────────────────────────────────────┤
│ │
│ boolean OR boolean → boolean │
│ │
│ .PP Logical OR │
│ │
│ .PP 5 or 0 → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ boolean AND boolean → boolean │
│ │
│ .PP Logical AND │
│ │
│ .PP 3 and 0 → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ NOT boolean → boolean │
│ │
│ .PP Logical NOT │
│ │
│ .PP not false → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ boolean IS [NOT] (NULL|TRUE|FALSE) → │
│ boolean │
│ │
│ .PP Boolean value tests │
│ │
│ .PP 1 is null → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ value ISNULL|NOTNULL → boolean │
│ │
│ .PP Nullness tests │
│ │
│ .PP 1 notnull → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ number = number → boolean │
│ │
│ .PP Equal │
│ │
│ .PP 5 = 4 → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ number <> number → boolean │
│ │
│ .PP Not equal │
│ │
│ .PP 5 <> 4 → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ number != number → boolean │
│ │
│ .PP Not equal │
│ │
│ .PP 5 != 5 → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ number < number → boolean │
│ │
│ .PP Less than │
│ │
│ .PP 5 < 4 → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ number <= number → boolean │
│ │
│ .PP Less than or equal to │
│ │
│ .PP 5 <= 4 → FALSE │
├─────────────────────────────────────────────────┤
│ │
│ number > number → boolean │
│ │
│ .PP Greater than │
│ │
│ .PP 5 > 4 → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ number >= number → boolean │
│ │
│ .PP Greater than or equal to │
│ │
│ .PP 5 >= 4 → TRUE │
├─────────────────────────────────────────────────┤
│ │
│ integer | integer → integer │
│ │
│ .PP Bitwise OR │
│ │
│ .PP 1 | 2 → 3 │
├─────────────────────────────────────────────────┤
│ │
│ integer # integer → integer │
│ │
│ .PP Bitwise XOR │
│ │
│ .PP 1 # 3 → 2 │
├─────────────────────────────────────────────────┤
│ │
│ integer & integer → integer │
│ │
│ .PP Bitwise AND │
│ │
│ .PP 1 & 3 → 1 │
├─────────────────────────────────────────────────┤
│ │
│ ~ integer → integer │
│ │
│ .PP Bitwise NOT │
│ │
│ .PP ~ 1 → -2 │
├─────────────────────────────────────────────────┤
│ │
│ integer << integer → integer │
│ │
│ .PP Bitwise shift left │
│ │
│ .PP 1 << 2 → 4 │
├─────────────────────────────────────────────────┤
│ │
│ integer >> integer → integer │
│ │
│ .PP Bitwise shift right │
│ │
│ .PP 8 >> 2 → 2 │
├─────────────────────────────────────────────────┤
│ │
│ number + number → number │
│ │
│ .PP Addition │
│ │
│ .PP 5 + 4 → 9 │
├─────────────────────────────────────────────────┤
│ │
│ number - number → number │
│ │
│ .PP Subtraction │
│ │
│ .PP 3 - 2.0 → 1.0 │
├─────────────────────────────────────────────────┤
│ │
│ number * number → number │
│ │
│ .PP Multiplication │
│ │
│ .PP 5 * 4 → 20 │
├─────────────────────────────────────────────────┤
│ │
│ number / number → number │
│ │
│ .PP Division (truncates the result │
│ towards zero if both inputs are integers) │
│ │
│ .PP 5 / 3 → 1 │
├─────────────────────────────────────────────────┤
│ │
│ integer % integer → integer │
│ │
│ .PP Modulo (remainder) │
│ │
│ .PP 3 % 2 → 1 │
├─────────────────────────────────────────────────┤
│ │
│ - number → number │
│ │
│ .PP Negation │
│ │
│ .PP - 2.0 → -2.0 │
└─────────────────────────────────────────────────┘
Built-In Functions
The functions listed in Table 300 are built into pgbench and may be used in expressions
appearing in \set.
Table 300. pgbench Functions
┌─────────────────────────────────────────────────┐
│ │
│ Function │
│ │
│ .PP Description │
│ │
│ .PP Example(s) │
├─────────────────────────────────────────────────┤
│ │
│ abs ( number ) → same type as input │
│ │
│ .PP Absolute value │
│ │
│ .PP abs(-17) → 17 │
├─────────────────────────────────────────────────┤
│ │
│ debug ( number ) → same type as input │
│ │
│ .PP Prints the argument to stderr, │
│ and returns the argument. │
│ │
│ .PP debug(5432.1) → 5432.1 │
├─────────────────────────────────────────────────┤
│ │
│ double ( number ) → double │
│ │
│ .PP Casts to double. │
│ │
│ .PP double(5432) → 5432.0 │
├─────────────────────────────────────────────────┤
│ │
│ exp ( number ) → double │
│ │
│ .PP Exponential (e raised to the │
│ given power) │
│ │
│ .PP exp(1.0) → 2.718281828459045 │
├─────────────────────────────────────────────────┤
│ │
│ greatest ( number [, ... ] ) → double if │
│ any argument is double, else integer │
│ │
│ .PP Selects the largest value │
│ among the arguments. │
│ │
│ .PP greatest(5, 4, 3, 2) → 5 │
├─────────────────────────────────────────────────┤
│ │
│ hash ( value [, seed ] ) → integer │
│ │
│ .PP This is an alias for │
│ hash_murmur2. │
│ │
│ .PP hash(10, 5432) → │
│ -5817877081768721676 │
├─────────────────────────────────────────────────┤
│ │
│ hash_fnv1a ( value [, seed ] ) → integer │
│ │
│ .PP Computes FNV-1a hash. │
│ │
│ .PP hash_fnv1a(10, 5432) → │
│ -7793829335365542153 │
├─────────────────────────────────────────────────┤
│ │
│ hash_murmur2 ( value [, seed ] ) → │
│ integer │
│ │
│ .PP Computes MurmurHash2 hash. │
│ │
│ .PP hash_murmur2(10, 5432) → │
│ -5817877081768721676 │
├─────────────────────────────────────────────────┤
│ │
│ int ( number ) → integer │
│ │
│ .PP Casts to integer. │
│ │
│ .PP int(5.4 + 3.8) → 9 │
├─────────────────────────────────────────────────┤
│ │
│ least ( number [, ... ] ) → double if any │
│ argument is double, else integer │
│ │
│ .PP Selects the smallest value │
│ among the arguments. │
│ │
│ .PP least(5, 4, 3, 2.1) → 2.1 │
├─────────────────────────────────────────────────┤
│ │
│ ln ( number ) → double │
│ │
│ .PP Natural logarithm │
│ │
│ .PP ln(2.718281828459045) → 1.0 │
├─────────────────────────────────────────────────┤
│ │
│ mod ( integer, integer ) → integer │
│ │
│ .PP Modulo (remainder) │
│ │
│ .PP mod(54, 32) → 22 │
├─────────────────────────────────────────────────┤
│ │
│ permute ( i, size [, seed ] ) → integer │
│ │
│ .PP Permuted value of i, in the │
│ range [0, size). This is the new position │
│ of i (modulo size) in a pseudorandom │
│ permutation of the integers 0...size-1, │
│ parameterized by seed, see below. │
│ │
│ .PP permute(0, 4) → an integer │
│ between 0 and 3 │
├─────────────────────────────────────────────────┤
│ │
│ pi () → double │
│ │
│ .PP Approximate value of π │
│ │
│ .PP pi() → 3.14159265358979323846 │
├─────────────────────────────────────────────────┤
│ │
│ pow ( x, y ) → double │
│ │
│ .PP power ( x, y ) → double │
│ │
│ .PP x raised to the power of y │
│ │
│ .PP pow(2.0, 10) → 1024.0 │
├─────────────────────────────────────────────────┤
│ │
│ random ( lb, ub ) → integer │
│ │
│ .PP Computes a │
│ uniformly-distributed random integer in │
│ [lb, ub]. │
│ │
│ .PP random(1, 10) → an integer │
│ between 1 and 10 │
├─────────────────────────────────────────────────┤
│ │
│ random_exponential ( lb, ub, parameter ) │
│ → integer │
│ │
│ .PP Computes an │
│ exponentially-distributed random integer │
│ in [lb, ub], see below. │
│ │
│ .PP random_exponential(1, 10, 3.0) │
│ → an integer between 1 and 10 │
├─────────────────────────────────────────────────┤
│ │
│ random_gaussian ( lb, ub, parameter ) → │
│ integer │
│ │
│ .PP Computes a │
│ Gaussian-distributed random integer in │
│ [lb, ub], see below. │
│ │
│ .PP random_gaussian(1, 10, 2.5) → │
│ an integer between 1 and 10 │
├─────────────────────────────────────────────────┤
│ │
│ random_zipfian ( lb, ub, parameter ) → │
│ integer │
│ │
│ .PP Computes a Zipfian-distributed │
│ random integer in [lb, ub], see below. │
│ │
│ .PP random_zipfian(1, 10, 1.5) → │
│ an integer between 1 and 10 │
├─────────────────────────────────────────────────┤
│ │
│ sqrt ( number ) → double │
│ │
│ .PP Square root │
│ │
│ .PP sqrt(2.0) → 1.414213562 │
└─────────────────────────────────────────────────┘
The random function generates values using a uniform distribution, that is all the values
are drawn within the specified range with equal probability. The random_exponential,
random_gaussian and random_zipfian functions require an additional double parameter which
determines the precise shape of the distribution.
• For an exponential distribution, parameter controls the distribution by truncating a
quickly-decreasing exponential distribution at parameter, and then projecting onto
integers between the bounds. To be precise, with
f(x) = exp(-parameter * (x - min) / (max - min + 1)) / (1 - exp(-parameter))
Then value i between min and max inclusive is drawn with probability: f(i) - f(i + 1).
Intuitively, the larger the parameter, the more frequently values close to min are
accessed, and the less frequently values close to max are accessed. The closer to 0
parameter is, the flatter (more uniform) the access distribution. A crude
approximation of the distribution is that the most frequent 1% values in the range,
close to min, are drawn parameter% of the time. The parameter value must be strictly
positive.
• For a Gaussian distribution, the interval is mapped onto a standard normal
distribution (the classical bell-shaped Gaussian curve) truncated at -parameter on the
left and +parameter on the right. Values in the middle of the interval are more likely
to be drawn. To be precise, if PHI(x) is the cumulative distribution function of the
standard normal distribution, with mean mu defined as (max + min) / 2.0, with
f(x) = PHI(2.0 * parameter * (x - mu) / (max - min + 1)) /
(2.0 * PHI(parameter) - 1)
then value i between min and max inclusive is drawn with probability: f(i + 0.5) - f(i
- 0.5). Intuitively, the larger the parameter, the more frequently values close to the
middle of the interval are drawn, and the less frequently values close to the min and
max bounds. About 67% of values are drawn from the middle 1.0 / parameter, that is a
relative 0.5 / parameter around the mean, and 95% in the middle 2.0 / parameter, that
is a relative 1.0 / parameter around the mean; for instance, if parameter is 4.0, 67%
of values are drawn from the middle quarter (1.0 / 4.0) of the interval (i.e., from
3.0 / 8.0 to 5.0 / 8.0) and 95% from the middle half (2.0 / 4.0) of the interval
(second and third quartiles). The minimum allowed parameter value is 2.0.
• random_zipfian generates a bounded Zipfian distribution. parameter defines how skewed
the distribution is. The larger the parameter, the more frequently values closer to
the beginning of the interval are drawn. The distribution is such that, assuming the
range starts from 1, the ratio of the probability of drawing k versus drawing k+1 is
((k+1)/k)**parameter. For example, random_zipfian(1, ..., 2.5) produces the value 1
about (2/1)**2.5 = 5.66 times more frequently than 2, which itself is produced
(3/2)**2.5 = 2.76 times more frequently than 3, and so on.
pgbench's implementation is based on "Non-Uniform Random Variate Generation", Luc
Devroye, p. 550-551, Springer 1986. Due to limitations of that algorithm, the
parameter value is restricted to the range [1.001, 1000].
Note
When designing a benchmark which selects rows non-uniformly, be aware that the rows
chosen may be correlated with other data such as IDs from a sequence or the physical
row ordering, which may skew performance measurements.
To avoid this, you may wish to use the permute function, or some other additional step
with similar effect, to shuffle the selected rows and remove such correlations.
Hash functions hash, hash_murmur2 and hash_fnv1a accept an input value and an optional
seed parameter. In case the seed isn't provided the value of :default_seed is used, which
is initialized randomly unless set by the command-line -D option.
permute accepts an input value, a size, and an optional seed parameter. It generates a
pseudorandom permutation of integers in the range [0, size), and returns the index of the
input value in the permuted values. The permutation chosen is parameterized by the seed,
which defaults to :default_seed, if not specified. Unlike the hash functions, permute
ensures that there are no collisions or holes in the output values. Input values outside
the interval are interpreted modulo the size. The function raises an error if the size is
not positive. permute can be used to scatter the distribution of non-uniform random
functions such as random_zipfian or random_exponential so that values drawn more often are
not trivially correlated. For instance, the following pgbench script simulates a possible
real world workload typical for social media and blogging platforms where a few accounts
generate excessive load:
\set size 1000000
\set r random_zipfian(1, :size, 1.07)
\set k 1 + permute(:r, :size)
In some cases several distinct distributions are needed which don't correlate with each
other and this is when the optional seed parameter comes in handy:
\set k1 1 + permute(:r, :size, :default_seed + 123)
\set k2 1 + permute(:r, :size, :default_seed + 321)
A similar behavior can also be approximated with hash:
\set size 1000000
\set r random_zipfian(1, 100 * :size, 1.07)
\set k 1 + abs(hash(:r)) % :size
However, since hash generates collisions, some values will not be reachable and others
will be more frequent than expected from the original distribution.
As an example, the full definition of the built-in TPC-B-like transaction is:
\set aid random(1, 100000 * :scale)
\set bid random(1, 1 * :scale)
\set tid random(1, 10 * :scale)
\set delta random(-5000, 5000)
BEGIN;
UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid, :delta, CURRENT_TIMESTAMP);
END;
This script allows each iteration of the transaction to reference different,
randomly-chosen rows. (This example also shows why it's important for each client session
to have its own variables — otherwise they'd not be independently touching different
rows.)
Per-Transaction Logging
With the -l option (but without the --aggregate-interval option), pgbench writes
information about each transaction to a log file. The log file will be named prefix.nnn,
where prefix defaults to pgbench_log, and nnn is the PID of the pgbench process. The
prefix can be changed by using the --log-prefix option. If the -j option is 2 or higher,
so that there are multiple worker threads, each will have its own log file. The first
worker will use the same name for its log file as in the standard single worker case. The
additional log files for the other workers will be named prefix.nnn.mmm, where mmm is a
sequential number for each worker starting with 1.
Each line in a log file describes one transaction. It contains the following
space-separated fields:
client_id
identifies the client session that ran the transaction
transaction_no
counts how many transactions have been run by that session
time
transaction's elapsed time, in microseconds
script_no
identifies the script file that was used for the transaction (useful when multiple
scripts are specified with -f or -b)
time_epoch
transaction's completion time, as a Unix-epoch time stamp
time_us
fractional-second part of transaction's completion time, in microseconds
schedule_lag
transaction start delay, that is the difference between the transaction's scheduled
start time and the time it actually started, in microseconds (present only if --rate
is specified)
retries
count of retries after serialization or deadlock errors during the transaction
(present only if --max-tries is not equal to one)
When both --rate and --latency-limit are used, the time for a skipped transaction will be
reported as skipped. If the transaction ends with a failure, its time will be reported as
failed. If you use the --failures-detailed option, the time of the failed transaction will
be reported as serialization or deadlock depending on the type of failure (see Failures
and Serialization/Deadlock Retries for more information).
Here is a snippet of a log file generated in a single-client run:
0 199 2241 0 1175850568 995598
0 200 2465 0 1175850568 998079
0 201 2513 0 1175850569 608
0 202 2038 0 1175850569 2663
Another example with --rate=100 and --latency-limit=5 (note the additional schedule_lag
column):
0 81 4621 0 1412881037 912698 3005
0 82 6173 0 1412881037 914578 4304
0 83 skipped 0 1412881037 914578 5217
0 83 skipped 0 1412881037 914578 5099
0 83 4722 0 1412881037 916203 3108
0 84 4142 0 1412881037 918023 2333
0 85 2465 0 1412881037 919759 740
In this example, transaction 82 was late, because its latency (6.173 ms) was over the 5 ms
limit. The next two transactions were skipped, because they were already late before they
were even started.
The following example shows a snippet of a log file with failures and retries, with the
maximum number of tries set to 10 (note the additional retries column):
3 0 47423 0 1499414498 34501 3
3 1 8333 0 1499414498 42848 0
3 2 8358 0 1499414498 51219 0
4 0 72345 0 1499414498 59433 6
1 3 41718 0 1499414498 67879 4
1 4 8416 0 1499414498 76311 0
3 3 33235 0 1499414498 84469 3
0 0 failed 0 1499414498 84905 9
2 0 failed 0 1499414498 86248 9
3 4 8307 0 1499414498 92788 0
If the --failures-detailed option is used, the type of failure is reported in the time
like this:
3 0 47423 0 1499414498 34501 3
3 1 8333 0 1499414498 42848 0
3 2 8358 0 1499414498 51219 0
4 0 72345 0 1499414498 59433 6
1 3 41718 0 1499414498 67879 4
1 4 8416 0 1499414498 76311 0
3 3 33235 0 1499414498 84469 3
0 0 serialization 0 1499414498 84905 9
2 0 serialization 0 1499414498 86248 9
3 4 8307 0 1499414498 92788 0
When running a long test on hardware that can handle a lot of transactions, the log files
can become very large. The --sampling-rate option can be used to log only a random sample
of transactions.
Aggregated Logging
With the --aggregate-interval option, a different format is used for the log files. Each
log line describes one aggregation interval. It contains the following space-separated
fields:
interval_start
start time of the interval, as a Unix-epoch time stamp
num_transactions
number of transactions within the interval
sum_latency
sum of transaction latencies
sum_latency_2
sum of squares of transaction latencies
min_latency
minimum transaction latency
max_latency
maximum transaction latency
sum_lag
sum of transaction start delays (zero unless --rate is specified)
sum_lag_2
sum of squares of transaction start delays (zero unless --rate is specified)
min_lag
minimum transaction start delay (zero unless --rate is specified)
max_lag
maximum transaction start delay (zero unless --rate is specified)
skipped
number of transactions skipped because they would have started too late (zero unless
--rate and --latency-limit are specified)
retried
number of retried transactions (zero unless --max-tries is not equal to one)
retries
number of retries after serialization or deadlock errors (zero unless --max-tries is
not equal to one)
serialization_failures
number of transactions that got a serialization error and were not retried afterwards
(zero unless --failures-detailed is specified)
deadlock_failures
number of transactions that got a deadlock error and were not retried afterwards (zero
unless --failures-detailed is specified)
Here is some example output generated with this option:
pgbench --aggregate-interval=10 --time=20 --client=10 --log --rate=1000 --latency-limit=10 --failures-detailed --max-tries=10 test
1650260552 5178 26171317 177284491527 1136 44462 2647617 7321113867 0 9866 64 7564 28340 4148 0
1650260562 4808 25573984 220121792172 1171 62083 3037380 9666800914 0 9998 598 7392 26621 4527 0
Notice that while the plain (unaggregated) log format shows which script was used for each
transaction, the aggregated format does not. Therefore if you need per-script data, you
need to aggregate the data on your own.
Per-Statement Report
With the -r option, pgbench collects the following statistics for each statement:
• latency — elapsed transaction time for each statement. pgbench reports an average
value of all successful runs of the statement.
• The number of failures in this statement. See Failures and Serialization/Deadlock
Retries for more information.
• The number of retries after a serialization or a deadlock error in this statement. See
Failures and Serialization/Deadlock Retries for more information.
The report displays retry statistics only if the --max-tries option is not equal to 1.
All values are computed for each statement executed by every client and are reported after
the benchmark has finished.
For the default script, the output will look similar to this:
starting vacuum...end.
transaction type: <builtin: TPC-B (sort of)>
scaling factor: 1
query mode: simple
number of clients: 10
number of threads: 1
maximum number of tries: 1
number of transactions per client: 1000
number of transactions actually processed: 10000/10000
number of failed transactions: 0 (0.000%)
number of transactions above the 50.0 ms latency limit: 1311/10000 (13.110 %)
latency average = 28.488 ms
latency stddev = 21.009 ms
initial connection time = 69.068 ms
tps = 346.224794 (without initial connection time)
statement latencies in milliseconds and failures:
0.012 0 \set aid random(1, 100000 * :scale)
0.002 0 \set bid random(1, 1 * :scale)
0.002 0 \set tid random(1, 10 * :scale)
0.002 0 \set delta random(-5000, 5000)
0.319 0 BEGIN;
0.834 0 UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
0.641 0 SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
11.126 0 UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
12.961 0 UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
0.634 0 INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid, :delta, CURRENT_TIMESTAMP);
1.957 0 END;
Another example of output for the default script using serializable default transaction
isolation level (PGOPTIONS='-c default_transaction_isolation=serializable' pgbench ...):
starting vacuum...end.
transaction type: <builtin: TPC-B (sort of)>
scaling factor: 1
query mode: simple
number of clients: 10
number of threads: 1
maximum number of tries: 10
number of transactions per client: 1000
number of transactions actually processed: 6317/10000
number of failed transactions: 3683 (36.830%)
number of transactions retried: 7667 (76.670%)
total number of retries: 45339
number of transactions above the 50.0 ms latency limit: 106/6317 (1.678 %)
latency average = 17.016 ms
latency stddev = 13.283 ms
initial connection time = 45.017 ms
tps = 186.792667 (without initial connection time)
statement latencies in milliseconds, failures and retries:
0.006 0 0 \set aid random(1, 100000 * :scale)
0.001 0 0 \set bid random(1, 1 * :scale)
0.001 0 0 \set tid random(1, 10 * :scale)
0.001 0 0 \set delta random(-5000, 5000)
0.385 0 0 BEGIN;
0.773 0 1 UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
0.624 0 0 SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
1.098 320 3762 UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
0.582 3363 41576 UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
0.465 0 0 INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid, :delta, CURRENT_TIMESTAMP);
1.933 0 0 END;
If multiple script files are specified, all statistics are reported separately for each
script file.
Note that collecting the additional timing information needed for per-statement latency
computation adds some overhead. This will slow average execution speed and lower the
computed TPS. The amount of slowdown varies significantly depending on platform and
hardware. Comparing average TPS values with and without latency reporting enabled is a
good way to measure if the timing overhead is significant.
Failures and Serialization/Deadlock Retries
When executing pgbench, there are three main types of errors:
• Errors of the main program. They are the most serious and always result in an
immediate exit from pgbench with the corresponding error message. They include:
• errors at the beginning of pgbench (e.g. an invalid option value);
• errors in the initialization mode (e.g. the query to create tables for built-in
scripts fails);
• errors before starting threads (e.g. could not connect to the database server,
syntax error in the meta command, thread creation failure);
• internal pgbench errors (which are supposed to never occur...).
• Errors when the thread manages its clients (e.g. the client could not start a
connection to the database server / the socket for connecting the client to the
database server has become invalid). In such cases all clients of this thread stop
while other threads continue to work. However, --exit-on-abort is specified, all of
the threads stop immediately in this case.
• Direct client errors. They lead to immediate exit from pgbench with the corresponding
error message in the case of an internal pgbench error (which are supposed to never
occur...) or when --exit-on-abort is specified. Otherwise in the worst case they only
lead to the abortion of the failed client while other clients continue their run (but
some client errors are handled without an abortion of the client and reported
separately, see below). Later in this section it is assumed that the discussed errors
are only the direct client errors and they are not internal pgbench errors.
A client's run is aborted in case of a serious error; for example, the connection with the
database server was lost or the end of script was reached without completing the last
transaction. In addition, if execution of an SQL or meta command fails for reasons other
than serialization or deadlock errors, the client is aborted. Otherwise, if an SQL command
fails with serialization or deadlock errors, the client is not aborted. In such cases, the
current transaction is rolled back, which also includes setting the client variables as
they were before the run of this transaction (it is assumed that one transaction script
contains only one transaction; see What Is the "Transaction" Actually Performed in
pgbench? for more information). Transactions with serialization or deadlock errors are
repeated after rollbacks until they complete successfully or reach the maximum number of
tries (specified by the --max-tries option) / the maximum time of retries (specified by
the --latency-limit option) / the end of benchmark (specified by the --time option). If
the last trial run fails, this transaction will be reported as failed but the client is
not aborted and continues to work.
Note
Without specifying the --max-tries option, a transaction will never be retried after a
serialization or deadlock error because its default value is 1. Use an unlimited
number of tries (--max-tries=0) and the --latency-limit option to limit only the
maximum time of tries. You can also use the --time option to limit the benchmark
duration under an unlimited number of tries.
Be careful when repeating scripts that contain multiple transactions: the script is
always retried completely, so successful transactions can be performed several times.
Be careful when repeating transactions with shell commands. Unlike the results of SQL
commands, the results of shell commands are not rolled back, except for the variable
value of the \setshell command.
The latency of a successful transaction includes the entire time of transaction execution
with rollbacks and retries. The latency is measured only for successful transactions and
commands but not for failed transactions or commands.
The main report contains the number of failed transactions. If the --max-tries option is
not equal to 1, the main report also contains statistics related to retries: the total
number of retried transactions and total number of retries. The per-script report inherits
all these fields from the main report. The per-statement report displays retry statistics
only if the --max-tries option is not equal to 1.
If you want to group failures by basic types in per-transaction and aggregation logs, as
well as in the main and per-script reports, use the --failures-detailed option. If you
also want to distinguish all errors and failures (errors without retrying) by type
including which limit for retries was exceeded and how much it was exceeded by for the
serialization/deadlock failures, use the --verbose-errors option.
Table Access Methods
You may specify the Table Access Method for the pgbench tables. The environment variable
PGOPTIONS specifies database configuration options that are passed to PostgreSQL via the
command line (See Section 19.1.4). For example, a hypothetical default Table Access Method
for the tables that pgbench creates called wuzza can be specified with:
PGOPTIONS='-c default_table_access_method=wuzza'
Good Practices
It is very easy to use pgbench to produce completely meaningless numbers. Here are some
guidelines to help you get useful results.
In the first place, never believe any test that runs for only a few seconds. Use the -t or
-T option to make the run last at least a few minutes, so as to average out noise. In some
cases you could need hours to get numbers that are reproducible. It's a good idea to try
the test run a few times, to find out if your numbers are reproducible or not.
For the default TPC-B-like test scenario, the initialization scale factor (-s) should be
at least as large as the largest number of clients you intend to test (-c); else you'll
mostly be measuring update contention. There are only -s rows in the pgbench_branches
table, and every transaction wants to update one of them, so -c values in excess of -s
will undoubtedly result in lots of transactions blocked waiting for other transactions.
The default test scenario is also quite sensitive to how long it's been since the tables
were initialized: accumulation of dead rows and dead space in the tables changes the
results. To understand the results you must keep track of the total number of updates and
when vacuuming happens. If autovacuum is enabled it can result in unpredictable changes in
measured performance.
A limitation of pgbench is that it can itself become the bottleneck when trying to test a
large number of client sessions. This can be alleviated by running pgbench on a different
machine from the database server, although low network latency will be essential. It might
even be useful to run several pgbench instances concurrently, on several client machines,
against the same database server.
Security
If untrusted users have access to a database that has not adopted a secure schema usage
pattern, do not run pgbench in that database. pgbench uses unqualified names and does not
manipulate the search path.