[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>>.