![]() ![]() It also needs to be efficient, controllable, and scale with the installation.Īnd we make all this power available to you as an end user. For our own benefit, the job scheduler needs to be internal to the database. This makes the product much more responsive to the caller and results in more efficient processing of these tasks. We extensively use the advantage of this internal scheduler for our core features, enabling us to defer compression, retention, and refreshing of continuous aggregates to a background process (among other things). These were extended to prevent overlapping job executions, provide predictable job timing, and provide better forensics. And by “better visibility” of the job logs, we mean that they are also being logged to a table where they can be queried internally. The flexible intervals enable you to determine whether the next run of the job occurs based on the scheduled clock time or the end of the last job run. And in our latest release (2.9.1), we extended it to allow you to schedule jobs with flexible intervals and provide you with better visibility of error logs. So being the PostgreSQL lovers we are at Timescale, we decided to build such a feature so that our users and customers can benefit from a job scheduler in PostgreSQL. ![]() Even after the addition of background processes that would support the feature ( all the way back in 9.6), background job scheduling is unfortunately not a part of core PostgreSQL. ![]() The PostgreSQL Global Development Group has been debating for years about including a built-in job scheduler. It is one of the most requested features in the history of ever. The benefits of having a scheduler built into the database are obvious: no dependencies, no inherent security leaks, fits in your existing high availability plan, and takes part in your data recovery plan, too.Īs a PostgreSQL guy, it really makes you wonder why a built-in job scheduler is not a part of the core PostgreSQL project. What is a database job scheduler? Essentially, a job scheduler is a process that kicks off in-database functions and procedures at specified times and runs them independently of user sessions. ![]()
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