elasticsearch/docs/reference/rollup/apis/put-job.asciidoc

[role="xpack"]
[[rollup-put-job]]
=== Create {rollup-jobs} API
[subs="attributes"]
++++
<titleabbrev>Create {rollup-jobs}</titleabbrev>
++++

Creates a {rollup-job}.

experimental[]

NOTE: For version 8.5 and above we recommend <<downsampling,downsampling>> over
rollups as a way to reduce your storage costs for time series data.

[[rollup-put-job-api-request]]
==== {api-request-title}

`PUT _rollup/job/<job_id>`

[[rollup-put-job-api-prereqs]]
==== {api-prereq-title}

* If the {es} {security-features} are enabled, you must have `manage` or
`manage_rollup` cluster privileges to use this API. For more information, see
<<security-privileges>>.

[[rollup-put-job-api-desc]]
==== {api-description-title}

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
<<rollup-start-job,start {rollup-jobs} API>>.

[[rollup-put-job-api-path-params]]
==== {api-path-parms-title}

`<job_id>`::
  (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.

[role="child_attributes"]
[[rollup-put-job-api-request-body]]
==== {api-request-body-title}

`cron`::
(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.

//Begin groups
[[rollup-groups-config]]
`groups`::
(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`
[%collapsible%open]
====
//Begin date_histogram
`date_histogram`:::
(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`
[%collapsible%open]
===== 
`calendar_interval` or `fixed_interval`::::
(Required, <<time-units,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 {es}.
The interval defines the _minimum_ interval that can be aggregated only. If
hourly (`60m`) intervals are configured, <<rollup-search,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>>.
+
--
NOTE: Smaller, more granular intervals take up proportionally more space.

--

`delay`::::
(Optional,<<time-units,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.
--

`field`::::
(Required, string) The date field that is to be rolled up.

`time_zone`::::
(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`.
=====
//End date_histogram

//Begin histogram
`histogram`:::
(Optional, object) The histogram group aggregates one or more numeric fields
into numeric histogram intervals. 
+
.Properties of `histogram`
[%collapsible%open]
===== 
`fields`::::
(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.

`interval`::::
(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.
=====
//End histogram

//Begin terms
`terms`:::
(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.
+
--
TIP: 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`
[%collapsible%open]
===== 

`fields`::::
(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.
=====
//End terms
====
//End groups

`index_pattern`::
(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.
+
--
NOTE: 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.

--

//Begin metrics
[[rollup-metrics-config]]
`metrics`::
(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
[%collapsible%open]
====
`field`:::
(Required, string) The field to collect metrics for. This must be a numeric of
some kind.

`metrics`:::
(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`.
====
//End metrics

`page_size`::
(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.

`rollup_index`::
(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.

`timeout`::
(Optional, <<time-units,time value>>)
Time to wait for the request to complete. Defaults to `20s` (20 seconds).

[[rollup-put-job-api-example]]
==== {api-example-title}

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

[source,console]
--------------------------------------------------
PUT _rollup/job/sensor
{
  "index_pattern": "sensor-*",
  "rollup_index": "sensor_rollup",
  "cron": "*/30 * * * * ?",
  "page_size": 1000,
  "groups": { <1>
    "date_histogram": {
      "field": "timestamp",
      "fixed_interval": "1h",
      "delay": "7d"
    },
    "terms": {
      "fields": [ "node" ]
    }
  },
  "metrics": [ <2>
      {
      "field": "temperature",
      "metrics": [ "min", "max", "sum" ]
    },
    {
      "field": "voltage",
      "metrics": [ "avg" ]
    }
  ]
}
--------------------------------------------------
// TEST[setup:sensor_index]
<1> This configuration enables date histograms to be used on the `timestamp`
field and `terms` aggregations to be used on the `node` field.
<2> 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:

[source,console-result]
----
{
  "acknowledged": true
}
----