| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196 | [role="xpack"][testenv="basic"][[put-data-frame-transform]]=== Create {dataframe-transforms} API[subs="attributes"]++++<titleabbrev>Create {dataframe-transforms}</titleabbrev>++++Instantiates a {dataframe-transform}.beta[][[put-data-frame-transform-request]]==== {api-request-title}`PUT _data_frame/transforms/<data_frame_transform_id>`[[put-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 alsohave `read` and `view_index_metadata` privileges on the source index and `read`,`create_index`, and `index` privileges on the destination index. For moreinformation, see {stack-ov}/security-privileges.html[Security privileges] and{stack-ov}/built-in-roles.html[Built-in roles].[[put-data-frame-transform-desc]]==== {api-description-title}This API defines a {dataframe-transform}, which copies data from source indices,transforms it, and persists it into an entity-centric destination index. Theentities are defined by the set of `group_by` fields in the `pivot` object. Youcan also think of the destination index as a two-dimensional tabular datastructure (known as a {dataframe}). The ID for each document in the{dataframe} is generated from a hash of the entity, so there is a unique rowper entity. For more information, see{stack-ov}/ml-dataframes.html[{dataframe-transforms-cap}].When the {dataframe-transform} is created, a series of validations occur toensure its success. For example, there is a check for the existence of thesource indices and a check that the destination index is not part of the sourceindex pattern. You can use the `defer_validation` parameter to skip thesechecks.Deferred validations are always run when the {dataframe-transform} is started,with the exception of privilege checks. When {es} {security-features} areenabled, the {dataframe-transform} remembers which roles the user that createdit had at the time of creation and uses those same roles. If those roles do nothave the required privileges on the source and destination indices, the{dataframe-transform} fails when it attempts unauthorized operations.IMPORTANT:  You must use {kib} or this API to create a {dataframe-transform}.            Do not put a {dataframe-transform} directly into any            `.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.[[put-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.[[put-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 created.[[put-data-frame-transform-request-body]]==== {api-request-body-title}`description`::  (Optional, string) Free text description of the {dataframe-transform}.`dest`::  (Required, object) Required. 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`.`pivot`::  (Required, object) Defines the pivot function `group by` fields and the aggregation to  reduce the data. See <<data-frame-transform-pivot>>.`source`::  (Required, 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, it’s 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 transmissiondelays.--    `delay`::::      (Optional, <<time-units, time units>>) The time delay between the current time and the      latest input data time. The default value is `60s`.[[put-data-frame-transform-example]]==== {api-examples-title}[source,js]--------------------------------------------------PUT _data_frame/transforms/ecommerce_transform{  "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",    "pipeline": "add_timestamp_pipeline"  },  "frequency": "5m",  "sync": {    "time": {      "field": "order_date",      "delay": "60s"    }  }}--------------------------------------------------// CONSOLE// TEST[setup:kibana_sample_data_ecommerce]When the transform is created, you receive the following results:[source,js]----{  "acknowledged" : true}----// TESTRESPONSE
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