Skip to content

petr-klinger/pg_timetable

 
 

Repository files navigation

License: MIT Coverage Status Documentation Status Release Github All Releases Docker Pulls Go Report Card Mentioned in Awesome Go

pg_timetable: Advanced scheduling for PostgreSQL

pg_timetable is an advanced standalone job scheduler for PostgreSQL, offering many advantages over traditional schedulers such as cron and others. It is completely database driven and provides a couple of advanced concepts. It allows you to schedule PostgreSQL commands, system programs and built-in operations:

-- Run public.my_func() at 00:05 every day in August:
SELECT timetable.add_job('execute-func', '5 0 * 8 *', 'SELECT public.my_func()');

-- Run VACUUM at minute 23 past every 2nd hour from 0 through 20 every day:
SELECT timetable.add_job('run-vacuum', '23 0-20/2 * * *', 'VACUUM');

-- Refresh materialized view every 2 hours:
SELECT timetable.add_job('refresh-matview', '@every 2 hours', 
  'REFRESH MATERIALIZED VIEW public.mat_view');

-- Clear log table after pg_timetable restart:
SELECT timetable.add_job('clear-log', '@reboot', 'TRUNCATE public.log');

-- Reindex at midnight on Sundays with reindexdb utility:

--  using default database under default user (no command line arguments)
SELECT timetable.add_job('reindex-job', '0 0 * * 7', 'reindexdb', job_kind := 'PROGRAM');

--  specifying target database and tables, and be verbose
SELECT timetable.add_job('reindex-job', '0 0 * * 7', 'reindexdb',
          '["--table=foo", "--dbname=postgres", "--verbose"]'::jsonb, 'PROGRAM');

--  passing password using environment variable through bash shell
SELECT timetable.add_job('reindex-job', '0 0 * * 7', 'bash',
    '["-c", "PGPASSWORD=5m3R7K4754p4m reindexdb -U postgres -h 192.168.0.221 -v'::jsonb,
    'PROGRAM');    

Documentation

https://pg-timetable.readthedocs.io/

Main features

  • Tasks can be arranged in chains
  • Each task executes SQL, built-in or executable command
  • Parameters can be passed to tasks
  • Missed chains (possibly due to downtime) can be retried automatically
  • Support for configurable repetitions
  • Builtin tasks such as sending emails, downloading, importing files, etc.
  • Fully database driven configuration
  • Full support for database driven logging
  • Enhanced cron-style scheduling
  • Optional concurrency protection

Complete installation guide can be found in the documentation.

Possible choices are:

Complete usage guide can be found in the documentation.

  1. Download pg_timetable executable

  2. Make sure your PostgreSQL server is up and running and has a role with CREATE privilege for a target database, e.g.

    my_database=> CREATE ROLE scheduler PASSWORD 'somestrong';
    my_database=> GRANT CREATE ON DATABASE my_database TO scheduler;
  1. Create a new job, e.g. run VACUUM each night at 00:30
    my_database=> SELECT timetable.add_job('frequent-vacuum', '30 0 * * *', 'VACUUM');
    add_job
    ---------
          3
    (1 row)
  1. Run the pg_timetable
    # pg_timetable postgresql://scheduler:somestrong@localhost/my_database --clientname=vacuumer
  1. PROFIT!

Supported Environments

Cloud Service Supported PostgreSQL Version Supported OS Supported
Alibaba Cloud 15 (devel) Linux
Amazon RDS 14 (current) Darwin
Amazon Aurora 13 Windows
Azure 12 FreeBSD*
Citus Cloud 11 NetBSD*
Crunchy Bridge 10 OpenBSD*
DigitalOcean Solaris*
Google Cloud
Heroku
Supabase

* - there are no official release binaries made for these OSes. One would need to build them from sources.

** - previous PostgreSQL versions may and should work smoothly. Only officially supported PostgreSQL versions are listed in this table.

Contributing

Open in Gitpod

If you want to contribute to pg_timetable and help make it better, feel free to open an issue or even consider submitting a pull request.

Support

For professional support, please contact Cybertec.

Authors

About

pg_timetable: Advanced scheduling for PostgreSQL

Resources

License

Code of conduct

Security policy

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Go 60.6%
  • PLpgSQL 38.6%
  • Dockerfile 0.8%