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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
           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.)

           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:

       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 (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
       --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 100000 rows, which often outputs many lines per second (especially on good
           hardware).

       -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.

       --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
       --debug
           Print debugging output.

       -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.

       -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 52 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 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.

       -r
       --report-latencies
           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
       --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.

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

       --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).

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

       -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. 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.

ENVIRONMENT

       PGDATABASE
       PGHOST
       PGPORT
       PGUSER
           Default connection parameters.

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

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 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
       ┌─────────────┬──────────────────────────────────────┐
       │VariableDescription                          │
       ├─────────────┼──────────────────────────────────────┤
       │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 supported:

       \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
       \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

   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
       ┌──────────────────┬────────────────────────┬───────────┬────────┐
       │OperatorDescriptionExampleResult │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │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 OR     │ 1 | 2     │ 3      │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │#                 │ integer bitwise XOR    │ 1 # 3     │ 2      │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │&                 │ integer bitwise AND    │ 1 & 3     │ 1      │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │~                 │ integer bitwise NOT    │ ~ 1       │ -2     │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │<<                │ integer bitwise shift  │ 1 << 2    │ 4      │
       │                  │ left                   │           │        │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │>>                │ integer bitwise shift  │ 8 >> 2    │ 2      │
       │                  │ right                  │           │        │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │+                 │ addition               │ 5 + 4     │ 9      │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │-                 │ subtraction            │ 3 - 2.0   │ 1.0    │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │*                 │ multiplication         │ 5 * 4     │ 20     │
       ├──────────────────┼────────────────────────┼───────────┼────────┤
       │/                 │ division (integer      │ 5 / 3     │ 1      │
       │                  │ 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
       ┌───────────────────────┬────────────────────┬───────────────────────────┬───────────────────────┬────────────────────────┐
       │FunctionReturn TypeDescriptionExampleResult                 │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │abs(a)                 │ same as a          │ absolute value            │ abs(-17)              │ 17                     │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │debug(a)               │ same as a          │ print a to stderr,        │ debug(5432.1)         │ 5432.1                 │
       │                       │                    │         and return        │                       │                        │
       │                       │                    │ a                         │                       │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │double(i)              │ double             │ cast to double            │ double(5432)          │ 5432.0                 │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │exp(x)                 │ double             │ exponential               │ exp(1.0)              │ 2.718281828459045      │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │greatest(a [, ... ]    │ double if any a is │ largest value among       │ greatest(5, 4, 3,     │ 5                      │
       │)                      │ double, else       │ arguments                 │ 2)                    │                        │
       │                       │ integer            │                           │                       │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │hash(a [, seed ] )     │ integer            │ alias for                 │ hash(10, 5432)        │ -5817877081768721676   │
       │                       │                    │ hash_murmur2()            │                       │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │hash_fnv1a(a [,        │ integer            │ FNV-1a hash               │ hash_fnv1a(10,        │ -7793829335365542153   │
       │seed ] )               │                    │                           │ 5432)                 │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │hash_murmur2(a [,      │ integer            │ MurmurHash2 hash          │ hash_murmur2(10,      │ -5817877081768721676   │
       │seed ] )               │                    │                           │ 5432)                 │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │int(x)                 │ integer            │ cast to int               │ int(5.4 + 3.8)        │ 9                      │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │least(a [, ... ] )     │ double if any a is │ smallest value            │ least(5, 4, 3, 2.1)   │ 2.1                    │
       │                       │ double, else       │ among arguments           │                       │                        │
       │                       │ integer            │                           │                       │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │ln(x)                  │ double             │ natural logarithm         │ ln(2.718281828459045) │ 1.0                    │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │mod(i, j)              │ integer            │ modulo                    │ mod(54, 32)           │ 22                     │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │pi()                   │ double             │ value of the              │ pi()                  │ 3.14159265358979323846 │
       │                       │                    │ constant PI               │                       │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │pow(x, y), power(x,    │ double             │ exponentiation            │ pow(2.0, 10),         │ 1024.0                 │
       │y)                     │                    │                           │ power(2.0, 10)        │                        │
       ├───────────────────────┼────────────────────┼───────────────────────────┼───────────────────────┼────────────────────────┤
       │random(lb, ub)         │ integer            │ uniformly-distributed     │ random(1, 10)         │ an integer between 1   │
       │                       │                    │ random integer in         │                       │ and 10                 │
       │                       │                    │ [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.

       •   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].

       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)
           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.

       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 committed.

       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
       own.

   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.

   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.