NAME

       Algorithm::Backoff::MILD - Multiplicative Increment, Linear Decrement (MILD) backoff

VERSION

       This document describes version 0.010 of Algorithm::Backoff::MILD (from Perl distribution
       Algorithm-Backoff), released on 2024-02-24.

SYNOPSIS

        use Algorithm::Backoff::MILD;

        # 1. instantiate

        my $ab = Algorithm::Backoff::MILD->new(
            #consider_actual_delay => 1, # optional, default 0
            #max_actual_duration   => 0, # optional, default 0 (retry endlessly)
            #max_attempts          => 0, # optional, default 0 (retry endlessly)
            #jitter_factor         => 0.25, # optional, default 0
            #min_delay             => 2, # optional, default 0
            #max_delay             => 100, # optional
            initial_delay              => 1,   # required
            delay_multiple_on_failure  => 1.5, # required
            delay_increment_on_success => -2,  # required
        );

        # 2. log success/failure and get a new number of seconds to delay, timestamp is
        # optional but must be monotonically increasing.

        # for example, using the parameters initial_delay=1,
        # delay_multiple_on_failure=1.5, delay_increment_on_success=-2, min_delay=0.5:

        my $secs;
        $secs = $ab->failure();   # => 1    (= initial_delay)
        $secs = $ab->failure();   # => 1.5  (1 * 1.5)
        $secs = $ab->failure();   # => 2.25 (1.5 * 1.5)
        $secs = $ab->success();   # => 0.25 (2.25 - 2)
        $secs = $ab->success();   # => 1 (max(0.25 - 2, 0.5, 1))
        $secs = $ab->failure();   # => 1.5 (1 * 1.5)

       Illustration using CLI show-backoff-delays (4 failures followed by 5 successes, followed
       by 3 failures):

        % show-backoff-delays -a MILD --initial-delay 3 --min-delay 1 \
            --delay-multiple-on-failure 2 --delay-increment-on-success -5 \
            0 0 0 0   1 1 1 1 1   0 0 0
        3
        6
        12
        24
        19
        14
        9
        4
        1
        2
        4

DESCRIPTION

       Upon failure, this backoff algorithm calculates the next delay as:

        D1 = initial_delay
        D2 = max(min(D1 * delay_multiple_on_failure, max_delay), min_delay)
        ...

       Upon success, the next delay is calculated as:

        D1 = initial_delay
        D2 = max(D1 + delay_increment_on_success, min_delay, initial_delay)
        ...

       "initial_delay", "delay_multiple_on_failure", and "delay_increment_on_success" are
       required. "initial_delay" and "min_delay" should be larger than zero; otherwise the next
       delays will all be zero.

       There are limits on the number of attempts (`max_attempts`) and total duration
       (`max_actual_duration`).

       It is recommended to add a jitter factor, e.g. 0.25 to add some randomness to avoid
       "thundering herd problem".

METHODS

   new
       Usage:

        new(%args) -> obj

       This function is not exported.

       Arguments ('*' denotes required arguments):

       •   consider_actual_delay => bool (default: 0)

           Whether to consider actual delay.

           If set to true, will take into account the actual delay (timestamp difference).  For
           example, when using the Constant strategy of delay=2, you log failure() again right
           after the previous failure() (i.e. specify the same timestamp).  failure() will then
           return ~2+2 = 4 seconds. On the other hand, if you waited 2 seconds before calling
           failure() again (i.e. specify the timestamp that is 2 seconds larger than the previous
           timestamp), failure() will return 2 seconds.  And if you waited 4 seconds or more,
           failure() will return 0.

       •   delay_increment_on_success* => float

           How much to add to previous delay, in seconds, upon success (e.g. -5).

       •   delay_multiple_on_failure* => ufloat

           How much to multiple previous delay, upon failure (e.g. 1.5).

       •   initial_delay* => ufloat

           Initial delay for the first attempt after failure, in seconds.

       •   jitter_factor => float

           How much to add randomness.

           If you set this to a value larger than 0, the actual delay will be between a random
           number between original_delay * (1-jitter_factor) and original_delay *
           (1+jitter_factor). Jitters are usually added to avoid so-called "thundering herd"
           problem.

           The jitter will be applied to delay on failure as well as on success.

       •   max_actual_duration => ufloat (default: 0)

           Maximum number of seconds for all of the attempts (0 means unlimited).

           If set to a positive number, will limit the number of seconds for all of the attempts.
           This setting is used to limit the amount of time you are willing to spend on a task.
           For example, when using the Exponential strategy of initial_delay=3 and
           max_attempts=10, the delays will be 3, 6, 12, 24, ... If failures are logged according
           to the suggested delays, and max_actual_duration is set to 21 seconds, then the third
           failure() will return -1 instead of 24 because 3+6+12 >= 21, even though max_attempts
           has not been exceeded.

       •   max_attempts => uint (default: 0)

           Maximum number consecutive failures before giving up.

           0 means to retry endlessly without ever giving up. 1 means to give up after a single
           failure (i.e. no retry attempts). 2 means to retry once after a failure.  Note that
           after a success, the number of attempts is reset (as expected). So if max_attempts is
           3, and if you fail twice then succeed, then on the next failure the algorithm will
           retry again for a maximum of 3 times.

       •   max_delay => ufloat

           Maximum delay time, in seconds.

       •   min_delay => ufloat (default: 0)

           Maximum delay time, in seconds.

       Return value:  (obj)

HOMEPAGE

       Please visit the project's homepage at <https://metacpan.org/release/Algorithm-Backoff>.

SOURCE

       Source repository is at <https://github.com/perlancar/perl-Algorithm-Backoff>.

SEE ALSO

       Algorithm::Backoff::LILD

       Algorithm::Backoff::LIMD

       Algorithm::Backoff::MIMD

       Algorithm::Backoff

       Other "Algorithm::Backoff::*" classes.

AUTHOR

       perlancar <perlancar@cpan.org>

CONTRIBUTING

       To contribute, you can send patches by email/via RT, or send pull requests on GitHub.

       Most of the time, you don't need to build the distribution yourself. You can simply modify
       the code, then test via:

        % prove -l

       If you want to build the distribution (e.g. to try to install it locally on your system),
       you can install Dist::Zilla, Dist::Zilla::PluginBundle::Author::PERLANCAR,
       Pod::Weaver::PluginBundle::Author::PERLANCAR, and sometimes one or two other Dist::Zilla-
       and/or Pod::Weaver plugins. Any additional steps required beyond that are considered a bug
       and can be reported to me.

COPYRIGHT AND LICENSE

       This software is copyright (c) 2024, 2019 by perlancar <perlancar@cpan.org>.

       This is free software; you can redistribute it and/or modify it under the same terms as
       the Perl 5 programming language system itself.

BUGS

       Please report any bugs or feature requests on the bugtracker website
       <https://rt.cpan.org/Public/Dist/Display.html?Name=Algorithm-Backoff>

       When submitting a bug or request, please include a test-file or a patch to an existing
       test-file that illustrates the bug or desired feature.