OpenSearch/docs/reference/data-frames/apis/transformresource.asciidoc

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[role="xpack"]
[testenv="basic"]
[[data-frame-transform-resource]]
=== {dataframe-transform-cap} resources
{dataframe-transform-cap} resources relate to the <<data-frame-apis>>.
For more information, see
{stack-ov}/ecommerce-dataframes.html[Transforming your data with {dataframes}].
[discrete]
[[data-frame-transform-properties]]
==== {api-definitions-title}
`description`::
(string) A description of the {dataframe-transform}.
`dest`::
(object) The destination for the {dataframe-transform}. See
<<data-frame-transform-dest>>.
`frequency`::
(time units) The interval between checks for changes in the source indices
when the {dataframe-transform} is running continuously. The minimum value is
`1s` and the maximum is `1h`. The default value is `1m`.
`id`::
(string) A unique identifier for the {dataframe-transform}.
`pivot`::
(object) The method for transforming the data. See
<<data-frame-transform-pivot>>.
`source`::
(object) The source of the data for the {dataframe-transform}. See
<<data-frame-transform-source>>.
[[data-frame-transform-dest]]
==== Dest objects
{dataframe-transform-cap} resources contain `dest` objects. For example, when
you create a {dataframe-transform}, you must define its destination.
[discrete]
[[data-frame-transform-dest-properties]]
===== {api-definitions-title}
`index`::
(string) The _destination index_ for the {dataframe-transform}.
`pipeline`::
(string) The unique identifier for a <<pipeline,pipeline>>.
[[data-frame-transform-source]]
==== Source objects
{dataframe-transform-cap} resources contain `source` objects. For example, when
you create a {dataframe-transform}, you must define its source.
[discrete]
[[data-frame-transform-source-properties]]
===== {api-definitions-title}
`index`::
(array) The _source index_ for the {dataframe-transform}.
`query`::
(object) A query clause that retrieves a subset of data from the source index.
See <<query-dsl>>.
[[data-frame-transform-pivot]]
==== Pivot objects
{dataframe-transform-cap} resources contain `pivot` objects, which define the
pivot function `group by` fields and the aggregation to reduce the data.
[discrete]
[[data-frame-transform-pivot-properties]]
===== {api-definitions-title}
`aggregations` or `aggs`::
(object) Defines how to aggregate the grouped data. The following composite
aggregations are supported:
+
--
* {ref}/search-aggregations-metrics-avg-aggregation.html[Average]
* {ref}/search-aggregations-metrics-weight-avg-aggregation.html[Weighted Average]
* {ref}/search-aggregations-metrics-cardinality-aggregation.html[Cardinality]
* {ref}/search-aggregations-metrics-geocentroid-aggregation.html[Geo Centroid]
* {ref}/search-aggregations-metrics-max-aggregation.html[Max]
* {ref}/search-aggregations-metrics-min-aggregation.html[Min]
* {ref}/search-aggregations-metrics-scripted-metric-aggregation.html[Scripted Metric]
* {ref}/search-aggregations-metrics-sum-aggregation.html[Sum]
* {ref}/search-aggregations-metrics-valuecount-aggregation.html[Value Count]
* {ref}/search-aggregations-pipeline-bucket-script-aggregation.html[Bucket Script]
IMPORTANT: {dataframe-transforms-cap} support a subset of the functionality in
composite aggregations. See
{stack-ov}/dataframe-limitations.html[{dataframe-cap} limitations].
--
`group_by`::
(object) Defines how to group the data. More than one grouping can be defined
per pivot. The following groupings are supported:
+
--
* {ref}/search-aggregations-bucket-composite-aggregation.html#_terms[Terms]
* {ref}/search-aggregations-bucket-composite-aggregation.html#_histogram[Histogram]
* {ref}/search-aggregations-bucket-composite-aggregation.html#_date_histogram[Date Histogram]
--
`max_page_search_size`::
(integer) Defines the initial page size to use for the composite aggregation
for each checkpoint. If circuit breaker exceptions occur, the page size is
dynamically adjusted to a lower value. The minimum value is `10` and the
maximum is `10,000`. The default value is `500`.
[[data-frame-transform-example]]
==== {api-examples-title}
See the
<<put-data-frame-transform-example,create {dataframe-transforms} API examples>>.