Rollup Jobs

A rollup job is a periodic task that aggregates data from indices specified by an index pattern, and then rolls it into a new index. Rollup indices are a good way to compactly store months or years of historical data for use in visualizations and reports.

To get started, open the main menu, then click Stack Management > Rollup Jobs.

Before using this feature, you should be familiar with how rollups work. Rolling up historical data is a good source for more detailed information.

The manage_rollup cluster privilege is required to access Rollup jobs.

To add the privilege, open the main menu, then click Stack Management > Roles.

Kibana makes it easy for you to create a rollup job by walking you through the process. You fill in the name, data flow, and how often you want to roll up the data. Then you define a date histogram aggregation for the rollup job and optionally define terms, histogram, and metrics aggregations.

When defining the index pattern, you must enter a name that is different than the output rollup index. Otherwise, the job will attempt to capture the data in the rollup index. For example, if your index pattern is metricbeat-*, you can name your rollup index rollup-metricbeat, but not metricbeat-rollup.

Once you’ve saved a rollup job, you’ll see it the Rollup Jobs overview page, where you can drill down for further investigation. The Manage menu enables you to start, stop, and delete the rollup job. You must first stop a rollup job before deleting it.

You can’t change a rollup job after you’ve created it. To select additional fields or redefine terms, you must delete the existing job, and then create a new one with the updated specifications. Be sure to use a different name for the new rollup job—reusing the same name can lead to problems with mismatched job configurations. You can read more at rollup job configuration.

This example creates a rollup job to capture log data from sample web logs. Before you start, add the web logs sample data set.

In this example, you want data that is older than 7 days in the target index pattern kibana_sample_data_logs to roll up into the rollup_logstash index. You’ll bucket the rolled up data on an hourly basis, using 60m for the time bucket configuration. This allows for more granular queries, such as 2h and 12h.

For this example, the job will perform the rollup every minute. However, you’d typically roll up less frequently in production.

As you walk through the Create rollup job UI, enter the data:

On the Review and save page, click Start job now and Save.

The terms, histogram, and metrics fields reflect the key information to retain in the rolled up data: where visitors are from (geo.src), what operating system they are using (machine.os.keyword), and how much data is being sent (bytes).

You can now use the rolled up data for analysis at a fraction of the storage cost of the original index. The original data can live side by side with the new rollup index, or you can remove or archive it using Index Lifecycle Management.

Your next step is to visualize your rolled up data in a vertical bar chart. Most visualizations support rolled up data, with the exception of Timelion and Vega visualizations.