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Update connector pipeline API
editUpdate connector pipeline API
editThis functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.
Updates the pipeline
configuration of a connector.
When you create a new connector, the configuration of an ingest pipeline is populated with default settings.
To get started with Connector APIs, check out our tutorial.
Request
editPUT _connector/<connector_id>/_pipeline
Prerequisites
edit- To sync data using self-managed connectors, you need to deploy the Elastic connector service. on your own infrastructure. This service runs automatically on Elastic Cloud for Elastic managed connectors.
-
The
connector_id
parameter should reference an existing connector.
Path parameters
edit-
<connector_id>
- (Required, string)
Request body
edit-
pipeline
- (Required, object) The pipeline configuration of the connector. The pipeline determines how data is processed during ingestion into Elasticsearch.
Pipeline configuration must include the following attributes:
-
extract_binary_content
(Required, boolean) A flag indicating whether to extract binary content during ingestion. -
name
(Required, string) The name of the ingest pipeline. -
reduce_whitespace
(Required, boolean) A flag indicating whether to reduce extra whitespace in the ingested content. -
run_ml_inference
(Required, boolean) A flag indicating whether to run machine learning inference on the ingested content.
Response codes
edit-
200
-
Connector
pipeline
field was successfully updated. -
400
-
The
connector_id
was not provided or the request payload was malformed. -
404
(Missing resources) -
No connector matching
connector_id
could be found.
Examples
editThe following example updates the pipeline
property for the connector with ID my-connector
:
resp = client.connector.update_pipeline( connector_id="my-connector", pipeline={ "extract_binary_content": True, "name": "my-connector-pipeline", "reduce_whitespace": True, "run_ml_inference": True }, ) print(resp)
response = client.connector.update_pipeline( connector_id: 'my-connector', body: { pipeline: { extract_binary_content: true, name: 'my-connector-pipeline', reduce_whitespace: true, run_ml_inference: true } } ) puts response
const response = await client.connector.updatePipeline({ connector_id: "my-connector", pipeline: { extract_binary_content: true, name: "my-connector-pipeline", reduce_whitespace: true, run_ml_inference: true, }, }); console.log(response);
PUT _connector/my-connector/_pipeline { "pipeline": { "extract_binary_content": true, "name": "my-connector-pipeline", "reduce_whitespace": true, "run_ml_inference": true } }
{ "result": "updated" }