This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
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.
manage_rollup cluster privilege is required to access Rollup jobs.
To add the privilege, open the main menu, then click Stack Management > Roles.
Create a rollup jobedit
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
you can name your rollup index
rollup-metricbeat, but not
Start, stop, and delete rollup jobsedit
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.
Try it: Create and visualize rolled up dataedit
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
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.
Create the rollup jobedit
As you walk through the Create rollup job UI, enter the data:
Rollup index name
Time bucket size
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.
Visualize the rolled up dataedit
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.
- Open the main menu, then click Stack Management > Index Patterns.
Click Create index pattern, and select Rollup index pattern from the dropdown.
Enter rollup_logstash,kibana_sample_logs as your Index Pattern and
@timestampas the Time Filter field name.
The notation for a combination index pattern with both raw and rolled up data is
rollup_logstash,kibana_sample_data_logs. In this index pattern,
rollup_logstashmatches the rolled up index pattern and
kibana_sample_data_logsmatches the index pattern for raw data.
- Open the main menu, click Dashboard, then Create dashboard.
- Set the time filter to Last 90 days.
- On the dashboard, click Create visualization.
rollup_logstash,kibana_sample_data_logsas your source to see both the raw and rolled up data.
- Select Bar vertical stacked in the chart type dropdown.
@timestampfield to the Horizontal axis.
bytesfield to the Vertical axis, defaulting to an
Average of bytes.
Kibana creates a vertical bar chart of your data. Select a section of the chart to zoom in.