Create a data retention policy

Automatically drop data once its time value ages past a certain interval. When you create a data retention policy, TimescaleDB automatically schedules a background job to drop old chunks.

Add a data retention policy

Add a data retention policy by using the add_retention_policy function.

Adding a data retention policy

  1. Choose which hypertable you want to add the policy to. Decide how long want you want to keep data before dropping it. In this example, the hypertable name is conditions, and data is kept for 24 hours.
  2. Call add_retention_policy:
    SELECT add_retention_policy('conditions', INTERVAL '24 hours');

note

A data retention poilcy only allows you to drop chunks based on how far they are in the past. To drop chunks based on how far they are in the future, manually drop chunks.

Remove a data retention policy

Remove an existing data retention policy by using the remove_retention_policy function. Pass it the name of the hypertable to remove the policy from.

SELECT remove_retention_policy('conditions');

See scheduled data retention jobs

To see your scheduled data retention jobs and their job statistics, query the timescaledb_information.jobs and timescaledb_information.job_stats tables. For example:

SELECT j.hypertable_name,
j.job_id,
config,
schedule_interval,
job_status,
last_run_status,
last_run_started_at,
js.next_start,
total_runs,
total_successes,
total_failures
FROM timescaledb_information.jobs j
JOIN timescaledb_information.job_stats js
ON j.job_id = js.job_id
WHERE j.proc_name = 'policy_retention';

The results look like this:

-[ RECORD 1 ]-------+-----------------------------------------------
hypertable_name | conditions
job_id | 1000
config | {"drop_after": "5 years", "hypertable_id": 14}
schedule_interval | 1 day
job_status | Scheduled
last_run_status | Success
last_run_started_at | 2022-05-19 16:15:11.200109+00
next_start | 2022-05-20 16:15:11.243531+00
total_runs | 1
total_successes | 1
total_failures | 0

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