Create rollup jobs APIedit

Creates a rollup job.

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.


PUT _rollup/job/<job_id>


  • If the Elasticsearch security features are enabled, you must have manage or manage_rollup cluster privileges to use this API. For more information, see Security privileges.


The rollup job configuration contains all the details about how the job should run, when it indexes documents, and what future queries will be able to execute against the rollup index.

There are three main sections to the job configuration: the logistical details about the job (cron schedule, etc), the fields that are used for grouping, and what metrics to collect for each group.

Jobs are created in a STOPPED state. You can start them with the start rollup jobs API.

Path parametersedit

(Required, string) Identifier for the rollup job. This can be any alphanumeric string and uniquely identifies the data that is associated with the rollup job. The ID is persistent; it is stored with the rolled up data. If you create a job, let it run for a while, then delete the job, the data that the job rolled up is still be associated with this job ID. You cannot create a new job with the same ID since that could lead to problems with mismatched job configurations.

Request bodyedit

(Required, string) A cron string which defines the intervals when the rollup job should be executed. When the interval triggers, the indexer attempts to rollup the data in the index pattern. The cron pattern is unrelated to the time interval of the data being rolled up. For example, you may wish to create hourly rollups of your document but to only run the indexer on a daily basis at midnight, as defined by the cron. The cron pattern is defined just like a Watcher cron schedule.

(Required, object) Defines the grouping fields and aggregations that are defined for this rollup job. These fields will then be available later for aggregating into buckets.

These aggs and fields can be used in any combination. Think of the groups configuration as defining a set of tools that can later be used in aggregations to partition the data. Unlike raw data, we have to think ahead to which fields and aggregations might be used. Rollups provide enough flexibility that you simply need to determine which fields are needed, not in what order they are needed.

There are three types of groupings currently available: date_histogram, histogram, and terms.

Properties of groups

(Required, object) A date histogram group aggregates a date field into time-based buckets. This group is mandatory; you currently cannot rollup documents without a timestamp and a date_histogram group. The date_histogram group has several parameters:

Properties of date_histogram
calendar_interval or fixed_interval

(Required, time units) The interval of time buckets to be generated when rolling up. For example, 60m produces 60 minute (hourly) rollups. This follows standard time formatting syntax as used elsewhere in Elasticsearch. The interval defines the minimum interval that can be aggregated only. If hourly (60m) intervals are configured, rollup search can execute aggregations with 60m or greater (weekly, monthly, etc) intervals. So define the interval as the smallest unit that you wish to later query. For more information about the difference between calendar and fixed time intervals, see Calendar and fixed intervals.

Smaller, more granular intervals take up proportionally more space.


(Optional,time units) How long to wait before rolling up new documents. By default, the indexer attempts to roll up all data that is available. However, it is not uncommon for data to arrive out of order, sometimes even a few days late. The indexer is unable to deal with data that arrives after a time-span has been rolled up. That is to say, there is no provision to update already-existing rollups.

Instead, you should specify a delay that matches the longest period of time you expect out-of-order data to arrive. For example, a delay of 1d instructs the indexer to roll up documents up to now - 1d, which provides a day of buffer time for out-of-order documents to arrive.

(Required, string) The date field that is to be rolled up.
(Optional, string) Defines what time_zone the rollup documents are stored as. Unlike raw data, which can shift timezones on the fly, rolled documents have to be stored with a specific timezone. By default, rollup documents are stored in UTC.

(Optional, object) The histogram group aggregates one or more numeric fields into numeric histogram intervals.

Properties of histogram
(Required, array) The set of fields that you wish to build histograms for. All fields specified must be some kind of numeric. Order does not matter.
(Required, integer) The interval of histogram buckets to be generated when rolling up. For example, a value of 5 creates buckets that are five units wide (0-5, 5-10, etc). Note that only one interval can be specified in the histogram group, meaning that all fields being grouped via the histogram must share the same interval.

(Optional, object) The terms group can be used on keyword or numeric fields to allow bucketing via the terms aggregation at a later point. The indexer enumerates and stores all values of a field for each time-period. This can be potentially costly for high-cardinality groups such as IP addresses, especially if the time-bucket is particularly sparse.

While it is unlikely that a rollup will ever be larger in size than the raw data, defining terms groups on multiple high-cardinality fields can effectively reduce the compression of a rollup to a large extent. You should be judicious which high-cardinality fields are included for that reason.

Properties of terms
(Required, string) The set of fields that you wish to collect terms for. This array can contain fields that are both keyword and numerics. Order does not matter.

(Required, string) The index or index pattern to roll up. Supports wildcard-style patterns (logstash-*). The job attempts to rollup the entire index or index-pattern.

The index_pattern cannot be a pattern that would also match the destination rollup_index. For example, the pattern foo-* would match the rollup index foo-rollup. This situation would cause problems because the rollup job would attempt to rollup its own data at runtime. If you attempt to configure a pattern that matches the rollup_index, an exception occurs to prevent this behavior.


(Optional, object) Defines the metrics to collect for each grouping tuple. By default, only the doc_counts are collected for each group. To make rollup useful, you will often add metrics like averages, mins, maxes, etc. Metrics are defined on a per-field basis and for each field you configure which metric should be collected.

The metrics configuration accepts an array of objects, where each object has two parameters.

Properties of metric objects
(Required, string) The field to collect metrics for. This must be a numeric of some kind.
(Required, array) An array of metrics to collect for the field. At least one metric must be configured. Acceptable metrics are min,max,sum,avg, and value_count.
(Required, integer) The number of bucket results that are processed on each iteration of the rollup indexer. A larger value tends to execute faster, but requires more memory during processing. This value has no effect on how the data is rolled up; it is merely used for tweaking the speed or memory cost of the indexer.
(Required, string) The index that contains the rollup results. The index can be shared with other rollup jobs. The data is stored so that it doesn’t interfere with unrelated jobs.
(Optional, time value) Time to wait for the request to complete. Defaults to 20s (20 seconds).


The following example creates a rollup job named sensor, targeting the sensor-* index pattern:

PUT _rollup/job/sensor
  "index_pattern": "sensor-*",
  "rollup_index": "sensor_rollup",
  "cron": "*/30 * * * * ?",
  "page_size": 1000,
  "groups": { 
    "date_histogram": {
      "field": "timestamp",
      "fixed_interval": "1h",
      "delay": "7d"
    "terms": {
      "fields": [ "node" ]
  "metrics": [ 
      "field": "temperature",
      "metrics": [ "min", "max", "sum" ]
      "field": "voltage",
      "metrics": [ "avg" ]

This configuration enables date histograms to be used on the timestamp field and terms aggregations to be used on the node field.

This configuration defines metrics over two fields: temperature and voltage. For the temperature field, we are collecting the min, max, and sum of the temperature. For voltage, we are collecting the average.

When the job is created, you receive the following results:

  "acknowledged": true