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pgbench(1)               PostgreSQL 12.6 Documentation              pgbench(1)


       pgbench - run a benchmark test on PostgreSQL


       pgbench -i [option...] [dbname]

       pgbench [option...] [dbname]


       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
           number of transactions per client: 1000
           number of transactions actually processed: 10000/10000
           tps = 85.184871 (including connections establishing)
           tps = 85.296346 (excluding connections establishing)

       The first six lines report some of the most important parameter
       settings. The next 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. (In -T mode, only the actual number of
       transactions is printed.) The last two lines report the number of
       transactions per second, figured with and without counting the time to
       start database sessions.

       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.)

           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.


       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:

           Required to invoke initialization mode.

       -I 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

           g (Generate data)
               Generate data and load it into the standard tables, replacing
               any data already present.

           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
           Create the pgbench_accounts, pgbench_tellers and pgbench_branches
           tables with the given fillfactor. Default is 100.

           Perform no vacuuming during initialization. (This option suppresses
           the v initialization step, even if it was specified in -I.)

           Switch logging to quiet mode, producing only one progress message
           per 5 seconds. The default logging prints one message each 100000
           rows, which often outputs many lines per second (especially on good

       -s 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.

           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.)

           Create indexes in the specified tablespace, rather than the default

           Create tables in the specified tablespace, rather than the default

           Create all tables as unlogged tables, rather than permanent tables.

   Benchmarking Options
       pgbench accepts the following command-line benchmarking arguments:

       -b 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
           Number of clients simulated, that is, number of concurrent database
           sessions. Default is 1.

           Establish a new connection for each transaction, rather than doing
           it just once per client session. This is useful to measure the
           connection overhead.

           Print debugging output.

       -D varname=value
           Define a variable for use by a custom script (see below). Multiple
           -D options are allowed.

       -f 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
           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.

           Write information about each transaction to a log file. See below
           for details.

       -L 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.

       -M querymode
           Protocol to use for submitting queries to the server:

           o   simple: use simple query protocol.

           o   extended: use extended query protocol.

           o   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 52 for more

           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.

           Run built-in simple-update script. Shorthand for -b simple-update.

       -P 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 and standard deviation 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.

           Report the average per-statement latency (execution time from the
           perspective of the client) of each command after the benchmark
           finishes. See below for details.

       -R 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
           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.

           Run built-in select-only script. Shorthand for -b select-only.

       -t transactions
           Number of transactions each client runs. Default is 10.

       -T seconds
           Run the test for this many seconds, rather than a fixed number of
           transactions per client.  -t and -T are mutually exclusive.

           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.

           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.

           Set the filename prefix for the log files created by --log. The
           default is pgbench_log.

           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.

           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, 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).

   Common Options
       pgbench accepts the following command-line common arguments:

       -h hostname
           The database server's host name

       -p port
           The database server's port number

       -U login
           The user name to connect as

           Print the pgbench version and exit.

           Show help about pgbench command line arguments, and exit.


       A successful run will exit with status 0. Exit status 1 indicates
       static problems such as invalid command-line options. 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.


           Default connection parameters.

       This utility, like most other PostgreSQL utilities, uses the
       environment variables supported by libpq (see Section 33.14).


   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

       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 =

        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

   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.

           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
           a 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.

       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 258. A value specified for these
       variables using -D takes precedence over the automatic presets. Once
       set, a variable's value can be inserted into a 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 258. Automatic Variables
       |Variable     | Description                |
       |client_id    | unique number identifying  |
       |             | the client session (starts |
       |             | from zero)                 |
       |default_seed | seed used in hash          |
       |             | 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

       \gset [prefix]
           This command may be used to end SQL queries, taking the place of
           the terminating semicolon (;).

           When this 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.

           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.

               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_

       \if expression
       \elif expression
           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

       \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.


               \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.


               \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.


               \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.


               \shell command literal_argument :variable ::literal_starting_with_colon

   Built-in Operators
       The arithmetic, bitwise, comparison and logical operators listed in
       Table 259 are built into pgbench and may be used in expressions
       appearing in \set.

       Table 259. pgbench Operators by Increasing Precedence
       |Operator          | Description      | Example   | Result |
       |OR                | logical or       | 5 or 0    | TRUE   |
       |AND               | logical and      | 3 and 0   | FALSE  |
       |NOT               | logical not      | not false | TRUE   |
       |IS [NOT]          | value tests      | 1 is null | FALSE  |
       |(NULL|TRUE|FALSE) |                  |           |        |
       |ISNULL|NOTNULL    | null tests       | 1 notnull | TRUE   |
       |=                 | is equal         | 5 = 4     | FALSE  |
       |<>                | is not equal     | 5 <> 4    | TRUE   |
       |!=                | is not equal     | 5 != 5    | FALSE  |
       |<                 | lower than       | 5 < 4     | FALSE  |
       |<=                | lower or equal   | 5 <= 4    | FALSE  |
       |>                 | greater than     | 5 > 4     | TRUE   |
       |>=                | greater or equal | 5 >= 4    | TRUE   |
       ||                 | integer bitwise  | 1 | 2     | 3      |
       |                  | OR               |           |        |
       |#                 | integer bitwise  | 1 # 3     | 2      |
       |                  | XOR              |           |        |
       |&                 | integer bitwise  | 1 & 3     | 1      |
       |                  | AND              |           |        |
       |~                 | integer bitwise  | ~ 1       | -2     |
       |                  | NOT              |           |        |
       |<<                | integer bitwise  | 1 << 2    | 4      |
       |                  | shift left       |           |        |
       |>>                | integer bitwise  | 8 >> 2    | 2      |
       |                  | shift right      |           |        |
       |+                 | addition         | 5 + 4     | 9      |
       |-                 | subtraction      | 3 - 2.0   | 1.0    |
       |*                 | multiplication   | 5 * 4     | 20     |
       |/                 | division         | 5 / 3     | 1      |
       |                  | (integer         |           |        |
       |                  | truncates the    |           |        |
       |                  | results)         |           |        |
       |%                 | modulo           | 3 % 2     | 1      |
       |-                 | opposite         | - 2.0     | -2.0   |

   Built-In Functions
       The functions listed in Table 260 are built into pgbench and may be
       used in expressions appearing in \set.

       Table 260. pgbench Functions
       |Function               | Return Type   | Description               | Example               | Result                 |
       |abs(a)                 | same as a     | absolute                  | abs(-17)              | 17                     |
       |                       |               | value                     |                       |                        |
       |debug(a)               | same as a     | print a to                | debug(5432.1)         | 5432.1                 |
       |                       |               | stderr,                   |                       |                        |
       |                       |               |         and               |                       |                        |
       |                       |               | return a                  |                       |                        |
       |double(i)              | double        | cast to                   | double(5432)          | 5432.0                 |
       |                       |               | double                    |                       |                        |
       |exp(x)                 | double        | exponential               | exp(1.0)              | 2.718281828459045      |
       |greatest(a [,          | double if any | largest value             | greatest(5,           | 5                      |
       |... ] )                | a is double,  | among                     | 4, 3, 2)              |                        |
       |                       | else integer  | arguments                 |                       |                        |
       |hash(a [,              | integer       | alias for                 | hash(10,              | -5817877081768721676   |
       |seed ] )               |               | hash_murmur2()            | 5432)                 |                        |
       |hash_fnv1a(a           | integer       | FNV-1a hash               | hash_fnv1a(10,        | -7793829335365542153   |
       |[, seed ] )            |               |                           | 5432)                 |                        |
       |hash_murmur2(a         | integer       | MurmurHash2               | hash_murmur2(10,      | -5817877081768721676   |
       |[, seed ] )            |               | hash                      | 5432)                 |                        |
       |int(x)                 | integer       | cast to int               | int(5.4 + 3.8)        | 9                      |
       |least(a [, ...         | double if any | smallest value            | least(5, 4, 3,        | 2.1                    |
       |] )                    | a is double,  | among                     | 2.1)                  |                        |
       |                       | else integer  | arguments                 |                       |                        |
       |ln(x)                  | double        | natural                   | ln(2.718281828459045) | 1.0                    |
       |                       |               | logarithm                 |                       |                        |
       |mod(i, j)              | integer       | modulo                    | mod(54, 32)           | 22                     |
       |pi()                   | double        | value of the              | pi()                  | 3.14159265358979323846 |
       |                       |               | constant PI               |                       |                        |
       |pow(x, y),             | double        | exponentiation            | pow(2.0, 10),         | 1024.0                 |
       |power(x, y)            |               |                           | power(2.0, 10)        |                        |
       |random(lb, ub)         | integer       | uniformly-distributed     | random(1, 10)         | an integer between 1   |
       |                       |               | random integer            |                       | and 10                 |
       |                       |               | in [lb, ub]               |                       |                        |
       |random_exponential(lb, | integer       | exponentially-distributed | random_exponential(1, | an integer between 1   |
       |ub, parameter)         |               | random integer in         | 10, 3.0)              | and 10                 |
       |                       |               | [lb, ub],                 |                       |                        |
       |                       |               |               see         |                       |                        |
       |                       |               | below                     |                       |                        |
       |random_gaussian(lb,    | integer       | Gaussian-distributed      | random_gaussian(1,    | an integer between 1   |
       |ub, parameter)         |               | random integer in [lb,    | 10, 2.5)              | and 10                 |
       |                       |               | ub],                      |                       |                        |
       |                       |               |               see below   |                       |                        |
       |random_zipfian(lb, ub, | integer       | Zipfian-distributed       | random_zipfian(1, 10, | an integer between 1   |
       |parameter)             |               | random integer in [lb,    | 1.5)                  | and 10                 |
       |                       |               | ub],                      |                       |                        |
       |                       |               |               see below   |                       |                        |
       |sqrt(x)                | double        | square root               | 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.

       o   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.

       o   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.

       o   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].

       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. Hash functions can be used to
       scatter the distribution of random functions such as random_zipfian or
       random_exponential. For instance, the following pgbench script
       simulates possible real world workload typical for social media and
       blogging platforms where few accounts generate excessive load:

           \set r random_zipfian(0, 100000000, 1.07)
           \set k abs(hash(:r)) % 1000000

       In some cases several distinct distributions are needed which don't
       correlate with each other and this is when implicit seed parameter
       comes in handy:

           \set k1 abs(hash(:r, :default_seed + 123)) % 1000000
           \set k2 abs(hash(:r, :default_seed + 321)) % 1000000

       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)
           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);

       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.

       The format of the log is:

           client_id transaction_no time script_no time_epoch time_us [ schedule_lag ]

       where client_id indicates which client session ran the transaction,
       transaction_no counts how many transactions have been run by that
       session, time is the total elapsed transaction time in microseconds,
       script_no identifies which script file was used (useful when multiple
       scripts were specified with -f or -b), and time_epoch/time_us are a
       Unix-epoch time stamp and an offset in microseconds (suitable for
       creating an ISO 8601 time stamp with fractional seconds) showing when
       the transaction completed. The schedule_lag field is the difference
       between the transaction's scheduled start time, and the time it
       actually started, in microseconds. It is only present when the --rate
       option is used. When both --rate and --latency-limit are used, the time
       for a skipped transaction will be reported as skipped.

       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.

       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:

           interval_start num_transactions sum_latency sum_latency_2 min_latency max_latency [ sum_lag sum_lag_2 min_lag max_lag [ skipped ] ]

       where interval_start is the start of the interval (as a Unix epoch time
       stamp), num_transactions is the number of transactions within the
       interval, sum_latency is the sum of the transaction latencies within
       the interval, sum_latency_2 is the sum of squares of the transaction
       latencies within the interval, min_latency is the minimum latency
       within the interval, and max_latency is the maximum latency within the
       interval. The next fields, sum_lag, sum_lag_2, min_lag, and max_lag,
       are only present if the --rate option is used. They provide statistics
       about the time each transaction had to wait for the previous one to
       finish, i.e., the difference between each transaction's scheduled start
       time and the time it actually started. The very last field, skipped, is
       only present if the --latency-limit option is used, too. It counts the
       number of transactions skipped because they would have started too
       late. Each transaction is counted in the interval when it was

       Here is some example output:

           1345828501 5601 1542744 483552416 61 2573
           1345828503 7884 1979812 565806736 60 1479
           1345828505 7208 1979422 567277552 59 1391
           1345828507 7685 1980268 569784714 60 1398
           1345828509 7073 1979779 573489941 236 1411

       Notice that while the plain (unaggregated) log file shows which script
       was used for each transaction, the aggregated log does not. Therefore
       if you need per-script data, you need to aggregate the data on your

   Per-Statement Latencies
       With the -r option, pgbench collects the elapsed transaction time of
       each statement executed by every client. It then reports an average of
       those values, referred to as the latency for each statement, 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
           number of transactions per client: 1000
           number of transactions actually processed: 10000/10000
           latency average = 15.844 ms
           latency stddev = 2.715 ms
           tps = 618.764555 (including connections establishing)
           tps = 622.977698 (excluding connections establishing)
           statement latencies in milliseconds:
                   0.002  \set aid random(1, 100000 * :scale)
                   0.005  \set bid random(1, 1 * :scale)
                   0.002  \set tid random(1, 10 * :scale)
                   0.001  \set delta random(-5000, 5000)
                   0.326  BEGIN;
                   0.603  UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
                   0.454  SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
                   5.528  UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
                   7.335  UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
                   0.371  INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid, :delta, CURRENT_TIMESTAMP);
                   1.212  END;

       If multiple script files are specified, the averages 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.

   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.

       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.

PostgreSQL 12.6                      2021                           pgbench(1)

postgresql 12.6 - Generated Tue Feb 16 08:46:13 CST 2021
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