Update a transform
Generally available; Added in 7.2.0
Updates certain properties of a transform.
All updated properties except description do not take effect until after the transform starts the next checkpoint,
thus there is data consistency in each checkpoint. To use this API, you must have read and view_index_metadata
privileges for the source indices. You must also have index and read privileges for the destination index. When
Elasticsearch security features are enabled, the transform remembers which roles the user who updated it had at the
time of update and runs with those privileges.
Required authorization
- Index privileges:
read,index,view_index_metadata - Cluster privileges:
manage_transform
Query parameters
-
When true, deferrable validations are not run. This behavior may be desired if the source index does not exist until after the transform is created.
-
Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.
Values are
-1or0.
Body
Required
-
Free text description of the transform.
-
A duration. Units can be
nanos,micros,ms(milliseconds),s(seconds),m(minutes),h(hours) andd(days). Also accepts "0" without a unit and "-1" to indicate an unspecified value. -
The source of the data for the transform.
POST
/_transform/{transform_id}/_update
Console
POST _transform/simple-kibana-ecomm-pivot/_update
{
"source": {
"index": "kibana_sample_data_ecommerce",
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"pivot": {
"group_by": {
"customer_id": {
"terms": {
"field": "customer_id",
"missing_bucket": true
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"dest": {
"index": "kibana_sample_data_ecommerce_transform1",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "5m",
"sync": {
"time": {
"field": "order_date",
"delay": "60s"
}
},
"retention_policy": {
"time": {
"field": "order_date",
"max_age": "30d"
}
}
}resp = client.transform.update_transform(
transform_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",
"missing_bucket": True
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
description="Maximum priced ecommerce data by customer_id in Asia",
dest={
"index": "kibana_sample_data_ecommerce_transform1",
"pipeline": "add_timestamp_pipeline"
},
frequency="5m",
sync={
"time": {
"field": "order_date",
"delay": "60s"
}
},
retention_policy={
"time": {
"field": "order_date",
"max_age": "30d"
}
},
)const response = await client.transform.updateTransform({
transform_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",
missing_bucket: true,
},
},
},
aggregations: {
max_price: {
max: {
field: "taxful_total_price",
},
},
},
},
description: "Maximum priced ecommerce data by customer_id in Asia",
dest: {
index: "kibana_sample_data_ecommerce_transform1",
pipeline: "add_timestamp_pipeline",
},
frequency: "5m",
sync: {
time: {
field: "order_date",
delay: "60s",
},
},
retention_policy: {
time: {
field: "order_date",
max_age: "30d",
},
},
});response = client.transform.update_transform(
transform_id: "simple-kibana-ecomm-pivot",
body: {
"source": {
"index": "kibana_sample_data_ecommerce",
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"pivot": {
"group_by": {
"customer_id": {
"terms": {
"field": "customer_id",
"missing_bucket": true
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"dest": {
"index": "kibana_sample_data_ecommerce_transform1",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "5m",
"sync": {
"time": {
"field": "order_date",
"delay": "60s"
}
},
"retention_policy": {
"time": {
"field": "order_date",
"max_age": "30d"
}
}
}
)$resp = $client->transform()->updateTransform([
"transform_id" => "simple-kibana-ecomm-pivot",
"body" => [
"source" => [
"index" => "kibana_sample_data_ecommerce",
"query" => [
"term" => [
"geoip.continent_name" => [
"value" => "Asia",
],
],
],
],
"pivot" => [
"group_by" => [
"customer_id" => [
"terms" => [
"field" => "customer_id",
"missing_bucket" => true,
],
],
],
"aggregations" => [
"max_price" => [
"max" => [
"field" => "taxful_total_price",
],
],
],
],
"description" => "Maximum priced ecommerce data by customer_id in Asia",
"dest" => [
"index" => "kibana_sample_data_ecommerce_transform1",
"pipeline" => "add_timestamp_pipeline",
],
"frequency" => "5m",
"sync" => [
"time" => [
"field" => "order_date",
"delay" => "60s",
],
],
"retention_policy" => [
"time" => [
"field" => "order_date",
"max_age" => "30d",
],
],
],
]);curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"source":{"index":"kibana_sample_data_ecommerce","query":{"term":{"geoip.continent_name":{"value":"Asia"}}}},"pivot":{"group_by":{"customer_id":{"terms":{"field":"customer_id","missing_bucket":true}}},"aggregations":{"max_price":{"max":{"field":"taxful_total_price"}}}},"description":"Maximum priced ecommerce data by customer_id in Asia","dest":{"index":"kibana_sample_data_ecommerce_transform1","pipeline":"add_timestamp_pipeline"},"frequency":"5m","sync":{"time":{"field":"order_date","delay":"60s"}},"retention_policy":{"time":{"field":"order_date","max_age":"30d"}}}' "$ELASTICSEARCH_URL/_transform/simple-kibana-ecomm-pivot/_update"client.transform().updateTransform(u -> u
.description("Maximum priced ecommerce data by customer_id in Asia")
.dest(d -> d
.index("kibana_sample_data_ecommerce_transform1")
.pipeline("add_timestamp_pipeline")
)
.frequency(f -> f
.time("5m")
)
.retentionPolicy(r -> r
.time(t -> t
.field("order_date")
.maxAge(m -> m
.time("30d")
)
)
)
.source(s -> s
.index("kibana_sample_data_ecommerce")
.query(q -> q
.term(te -> te
.field("geoip.continent_name")
.value(FieldValue.of("Asia"))
)
)
)
.sync(sy -> sy
.time(ti -> ti
.delay(d -> d
.time("60s")
)
.field("order_date")
)
)
.transformId("simple-kibana-ecomm-pivot")
);
Request example
Run `POST _transform/simple-kibana-ecomm-pivot/_update` to update a transform that uses the pivot method.
{
"source": {
"index": "kibana_sample_data_ecommerce",
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"pivot": {
"group_by": {
"customer_id": {
"terms": {
"field": "customer_id",
"missing_bucket": true
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"dest": {
"index": "kibana_sample_data_ecommerce_transform1",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "5m",
"sync": {
"time": {
"field": "order_date",
"delay": "60s"
}
},
"retention_policy": {
"time": {
"field": "order_date",
"max_age": "30d"
}
}
}
Response examples (200)
A successful response when creating a transform.
{
"id": "simple-kibana-ecomm-pivot",
"authorization": {
"roles": [
"superuser"
]
},
"version": "10.0.0",
"create_time": 1712951576767,
"source": {
"index": [
"kibana_sample_data_ecommerce"
],
"query": {
"term": {
"geoip.continent_name": {
"value": "Asia"
}
}
}
},
"dest": {
"index": "kibana_sample_data_ecommerce_transform_v2",
"pipeline": "add_timestamp_pipeline"
},
"frequency": "15m",
"sync": {
"time": {
"field": "order_date",
"delay": "120s"
}
},
"pivot": {
"group_by": {
"customer_id": {
"terms": {
"field": "customer_id",
"missing_bucket": true
}
}
},
"aggregations": {
"max_price": {
"max": {
"field": "taxful_total_price"
}
}
}
},
"description": "Maximum priced ecommerce data by customer_id in Asia",
"settings": {},
"retention_policy": {
"time": {
"field": "order_date",
"max_age": "30d"
}
}
}