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PGBENCH(1)		PostgreSQL 9.5.0 Documentation		    PGBENCH(1)

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: 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, some
       options are useful in both cases.

   Initialization Options
       pgbench accepts the following command-line initialization arguments:

       -i
       --initialize
	   Required to invoke initialization mode.

       -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 after initialization.

       -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.

       --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:

       -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
       --file=filename
	   Read transaction script from filename. See below for details.  -N,
	   -S, and -f are mutually exclusive.

       -j threads
       --jobs=threads
	   Number of worker threads within pgbench. Using more than one thread
	   can be helpful on multi-CPU machines. The number of clients must be
	   a multiple of the number of threads, since each thread is given the
	   same number of client sessions to manage. Default is 1.

       -l
       --log
	   Write the time taken by each transaction to a log file. See below
	   for details.

       -L limit
       --latency-limit=limit
	   Transaction which 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.

	   The default is simple query protocol. (See Chapter 50,
	   Frontend/Backend Protocol, in the documentation 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
	   Do not update pgbench_tellers and pgbench_branches. This will avoid
	   update contention on these tables, but it makes the test case even
	   less like TPC-B.

       -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 custom benchmarks (-f
	   option), the scale factor will be reported as 1 unless this option
	   is used.

       -S
       --select-only
	   Perform select-only transactions instead of TPC-B-like test.

       -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
	   together with -l - with this option, the log contains per-interval
	   summary (number of transactions, min/max latency and two additional
	   fields useful for variance estimation).

	   This option is not currently supported on Windows.

       --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.

NOTES
   What is the “Transaction” Actually Performed in pgbench?
       The default transaction script issues seven commands per transaction:

	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 specify -N, steps 4 and 5 aren't included in the transaction. If
       you specify -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. You can even specify multiple
       scripts (multiple -f options), in which case a random one of the
       scripts is chosen each time a client session starts a new transaction.

       The format of a script file is one SQL command per line; multiline SQL
       commands are not supported. Empty lines and lines beginning with -- are
       ignored. Script file lines can also be “meta commands”, which are
       interpreted by pgbench itself, as described below.

       There is a simple variable-substitution facility for script files.
       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 219, “Automatic variables”. 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.

       Table 219. Automatic variables
       ┌──────────┬────────────────────────────┐
       │Variable  │ Description		       │
       ├──────────┼────────────────────────────┤
       │scale	  │ current scale factor       │
       ├──────────┼────────────────────────────┤
       │client_id │ unique number identifying  │
       │	  │ the client session (starts │
       │	  │ from zero)		       │
       └──────────┴────────────────────────────┘

       Script file meta commands begin with a backslash (\). Arguments to a
       meta command are separated by white space. These meta commands are
       supported:

       \set varname expression
	   Sets variable varname to an integer value calculated from
	   expression. The expression may contain integer constants such as
	   5432, references to variables :variablename, and expressions
	   composed of unary (-) or binary operators (+, -, *, /, %) with
	   their usual associativity, and parentheses.

	   Examples:

	       \set ntellers 10 * :scale
	       \set aid (1021 * :aid) % (100000 * :scale) + 1

       \setrandom varname min max [ uniform | { gaussian | exponential }
       parameter ]
	   Sets variable varname to a random integer value between the limits
	   min and max inclusive. Each limit can be either an integer constant
	   or a :variablename reference to a variable having an integer value.

	   By default, or when uniform is specified, all values in the range
	   are drawn with equal probability. Specifying gaussian or
	   exponential options modifies this behavior; each requires a
	   mandatory parameter which determines the precise shape of the
	   distribution.

	   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) - 1.0)

	   then value i between min and max inclusive is drawn with
	   probability: f(i + 0.5) - f(i - 0.5). Intuitively, the larger
	   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 parameter is 2.0 for performance of the Box-Muller
	   transform.

	   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)) / (1.0 - exp(-parameter))

	   Then value i between min and max inclusive is drawn with
	   probability: f(x) - f(x + 1). Intuitively, the larger 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, 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.  parameter value must be strictly positive.

	   Example:

	       \setrandom aid 1 :naccounts gaussian 5.0

       \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.
	   The command must return an integer value through its standard
	   output.

	   argument can be either a text constant or a :variablename reference
	   to a variable of any types. If you want to use argument starting
	   with colons, you need to add 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 is ignored.

	   Example:

	       \shell command literal_argument :variable ::literal_starting_with_colon

       As an example, the full definition of the built-in TPC-B-like
       transaction is:

	   \set nbranches :scale
	   \set ntellers 10 * :scale
	   \set naccounts 100000 * :scale
	   \setrandom aid 1 :naccounts
	   \setrandom bid 1 :nbranches
	   \setrandom tid 1 :ntellers
	   \setrandom delta -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, pgbench writes
       the time taken by each transaction to a log file. The log file will be
       named pgbench_log.nnn, where nnn is the PID of the pgbench process. If
       the -j option is 2 or higher, creating 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 pgbench_log.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 file_no time_epoch time_us [schedule_lag]

       where time is the total elapsed transaction time in microseconds,
       file_no identifies which script file was used (useful when multiple
       scripts were specified with -f), and time_epoch/time_us are a Unix
       epoch format time stamp and an offset in microseconds (suitable for
       creating an ISO 8601 time stamp with fractional seconds) showing when
       the transaction completed. Field schedule_lag 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. The last field skipped_transactions reports the number of
       transactions skipped because they were too far behind schedule. It is
       only present when both options --rate and --latency-limit are used.

       Here is a snippet of the log file generated:

	    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 it's 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, the logs use a bit different
       format:

	   interval_start num_of_transactions latency_sum latency_2_sum min_latency max_latency [lag_sum lag_2_sum min_lag max_lag [skipped_transactions]]

       where interval_start is the start of the interval (Unix epoch format
       time stamp), num_of_transactions is the number of transactions within
       the interval, latency_sum is a sum of latencies (so you can compute
       average latency easily). The following two fields are useful for
       variance estimation - latency_sum is a sum of latencies and
       latency_2_sum is a sum of 2nd powers of latencies. The last two fields
       are min_latency - a minimum latency within the interval, and
       max_latency - maximum latency within the interval. A transaction is
       counted into the interval when it was committed. The fields in the end,
       lag_sum, lag_2_sum, min_lag, and max_lag, are only present if the
       --rate option is used. The very last one, skipped_transactions, is only
       present if the option --latency-limit is present, too. They are
       calculated from 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.

       Here is example outputs:

	   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 contains index of
       the custom script files, 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: 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
	   tps = 618.764555 (including connections establishing)
	   tps = 622.977698 (excluding connections establishing)
	   statement latencies in milliseconds:
		   0.004386	   \set nbranches 1 * :scale
		   0.001343	   \set ntellers 10 * :scale
		   0.001212	   \set naccounts 100000 * :scale
		   0.001310	   \setrandom aid 1 :naccounts
		   0.001073	   \setrandom bid 1 :nbranches
		   0.001005	   \setrandom tid 1 :ntellers
		   0.001078	   \setrandom delta -5000 5000
		   0.326152	   BEGIN;
		   0.603376	   UPDATE pgbench_accounts SET abalance = abalance + :delta WHERE aid = :aid;
		   0.454643	   SELECT abalance FROM pgbench_accounts WHERE aid = :aid;
		   5.528491	   UPDATE pgbench_tellers SET tbalance = tbalance + :delta WHERE tid = :tid;
		   7.335435	   UPDATE pgbench_branches SET bbalance = bbalance + :delta WHERE bid = :bid;
		   0.371851	   INSERT INTO pgbench_history (tid, bid, aid, delta, mtime) VALUES (:tid, :bid, :aid, :delta, CURRENT_TIMESTAMP);
		   1.212976	   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.

PostgreSQL 9.5.0		     2016			    PGBENCH(1)
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