Dropping data

When you are working with continuous aggregates, you can drop a view, or you can drop raw data from the underlying hypertable or from the continuous aggregate itself. A combination of refresh and data retention policies can help you downsample your data. This lets you keep historical data at a lower granularity than recent data.

However, you should be aware if a retention policy is likely to drop raw data from your hypertable that you need in your continuous aggregate.

To simplify the process of setting up downsampling, you can use the visualizer and code generator.

You can drop a continuous aggregate view using the DROP MATERIALIZED VIEW command. This command also removes refresh policies defined on the continuous aggregate. It does not drop the data from the underlying hypertable.

If you drop data from a hypertable used in a continuous aggregate it can lead to problems with your continuous aggregate view. In many cases, dropping underlying data replaces the aggregate with NULL values, which can lead to unexpected results in your view.

You can drop data from a hypertable using drop_chunks in the usual way, but before you do so, always check that the chunk is not within the refresh window of a continuous aggregate that still needs the data. This is also important if you are manually refreshing a continuous aggregate. Calling refresh_continuous_aggregate on a region containing dropped chunks recalculates the aggregate without the dropped data.

If a continuous aggregate is refreshing when data is dropped because of a retention policy, the aggregate is updated to reflect the loss of data. If you need to retain the continuous aggregate after dropping the underlying data, set the start_offset value of the aggregate policy to a smaller interval than the drop_after parameter of the retention policy.

For more information, see the data retention documentation.

Set up downsampling and data retention

Maximize your storage by keeping downsampled historical data and dropping raw data.

Once you've created a continuous aggregate, you can automatically downsample your data. Enter the time bucket from your continuous aggregate definition. Then, adjust the sliders to select how you want to update your continuous aggregate, and how long you want to keep your raw and downsampled data.

Time bucket interval

Time bucket interval

Units for time bucket interval

Units for time bucket intervalSecond(s)Minute(s)Hour(s)Day(s)Week(s)Month(s)

Second(s)

Refresh

Automatically keep downsampled data up to date with new data from 30 minutes to 12 hours ago.

Drop raw data

Drop raw data older than 1 year.

Drop downsampled data

Drop downsampled data older than 5 years.

Hypertable name

Continuous aggregate name

SELECT add_retention_policy('hypertable_name', INTERVAL '1 year');

SELECT add_continuous_aggregate_policy('continuous_aggregate_name',
  start_offset => INTERVAL '12 hours',
  end_offset => INTERVAL '30 minutes',
  schedule_interval => INTERVAL '10 seconds'
);

SELECT add_retention_policy('continuous_aggregate_name', INTERVAL '5 years');

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