OpenSearch/docs/reference/data-frames/apis/update-transform.asciidoc

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[role="xpack"]
[testenv="basic"]
[[update-data-frame-transform]]
=== Update {dataframe-transforms} API
[subs="attributes"]
++++
<titleabbrev>Update {dataframe-transforms}</titleabbrev>
++++
Updates an existing {dataframe-transform}.
beta[]
[[update-data-frame-transform-request]]
==== {api-request-title}
`POST _data_frame/transforms/<data_frame_transform_id>/_update`
[[update-data-frame-transform-prereqs]]
==== {api-prereq-title}
* If the {es} {security-features} are enabled, you must have
`manage_data_frame_transforms` cluster privileges to use this API. The built-in
`data_frame_transforms_admin` role has these privileges. You must also
have `read` and `view_index_metadata` privileges on the source index and `read`,
`create_index`, and `index` privileges on the destination index. For more
information, see {stack-ov}/security-privileges.html[Security privileges] and
{stack-ov}/built-in-roles.html[Built-in roles].
[[update-data-frame-transform-desc]]
==== {api-description-title}
This API updates an existing {dataframe-transform}. All settings except description do not
take effect until after the {dataframe-transform} starts the next checkpoint. This is
so there is consistency with the pivoted data in each checkpoint.
IMPORTANT: When {es} {security-features} are enabled, your {dataframe-transform}
remembers which roles the user who updated it had at the time of update and
runs with those privileges.
IMPORTANT: You must use {kib} or this API to update a {dataframe-transform}.
Do not update a {dataframe-transform} directly via
`.data-frame-internal*` indices using the Elasticsearch index API.
If {es} {security-features} are enabled, do not give users any
privileges on `.data-frame-internal*` indices.
[[update-data-frame-transform-path-parms]]
==== {api-path-parms-title}
`<data_frame_transform_id>`::
(Required, string) Identifier for the {dataframe-transform}. This identifier
can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and
underscores. It must start and end with alphanumeric characters.
[[update-data-frame-transform-query-parms]]
==== {api-query-parms-title}
`defer_validation`::
(Optional, boolean) When `true`, deferrable validations are not run. This
behavior may be desired if the source index does not exist until after the
{dataframe-transform} is updated.
[[update-data-frame-transform-request-body]]
==== {api-request-body-title}
`description`::
(Optional, string) Free text description of the {dataframe-transform}.
`dest`::
(Optional, object) The destination configuration, which has the
following properties:
`index`:::
(Required, string) The _destination index_ for the {dataframe-transform}.
`pipeline`:::
(Optional, string) The unique identifier for a <<pipeline,pipeline>>.
`frequency`::
(Optional, <<time-units, time units>>) The interval between checks for changes
in the source indices when the {dataframe-transform} is running continuously.
Also determines the retry interval in the event of transient failures while
the {dataframe-transform} is searching or indexing. The minimum value is `1s`
and the maximum is `1h`. The default value is `1m`.
`source`::
(Optional, object) The source configuration, which has the following
properties:
`index`:::
(Required, string or array) The _source indices_ for the
{dataframe-transform}. It can be a single index, an index pattern (for
example, `"myindex*"`), or an array of indices (for example,
`["index1", "index2"]`).
`query`:::
(Optional, object) A query clause that retrieves a subset of data from the
source index. See <<query-dsl>>.
`sync`::
(Optional, object) Defines the properties required to run continuously.
`time`:::
(Required, object) Specifies that the {dataframe-transform} uses a time
field to synchronize the source and destination indices.
`field`::::
(Required, string) The date field that is used to identify new documents
in the source.
+
--
TIP: In general, its a good idea to use a field that contains the
<<accessing-ingest-metadata,ingest timestamp>>. If you use a different field,
you might need to set the `delay` such that it accounts for data transmission
delays.
--
`delay`::::
(Optional, <<time-units, time units>>) The time delay between the current
time and the latest input data time. The default value is `60s`.
[[update-data-frame-transform-example]]
==== {api-examples-title}
[source,console]
--------------------------------------------------
POST _data_frame/transforms/simple-kibana-ecomm-pivot/_update
{
"source": {
"index": "kibana_sample_data_ecommerce",
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"dest": {
"index": "kibana_sample_data_ecommerce_transform_v2",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "15m",
"sync": {
"time": {
"field": "order_date",
"delay": "120s"
}
}
}
--------------------------------------------------
// TEST[setup:simple_kibana_continuous_pivot]
When the transform is updated, you receive the updated configuration:
[source,console-result]
----
{
"id": "simple-kibana-ecomm-pivot",
"source": {
"index": ["kibana_sample_data_ecommerce"],
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"pivot": {
"group_by": {
"customer_id": {
"terms": {
"field": "customer_id"
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"dest": {
"index": "kibana_sample_data_ecommerce_transform_v2",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "15m",
"sync": {
"time": {
"field": "order_date",
"delay": "120s"
}
},
"version": "7.4.0",
"create_time": 1518808660505
}
----
// TESTRESPONSE[s/"version": "7.4.0"/"version": $body.version/]
// TESTRESPONSE[s/"create_time": 1518808660505/"create_time": $body.create_time/]