Update connector pipeline API
editUpdate connector pipeline APIedit
This 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 the tutorial.
Requestedit
PUT _connector/<connector_id>/_pipeline
Prerequisitesedit
- 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 native connectors.
-
The
connector_idparameter should reference an existing connector.
Path parametersedit
-
<connector_id> - (Required, string)
Request bodyedit
-
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 codesedit
-
200 -
Connector
pipelinefield was successfully updated. -
400 -
The
connector_idwas not provided or the request payload was malformed. -
404(Missing resources) -
No connector matching
connector_idcould be found.
Examplesedit
The following example updates the pipeline property for the connector with ID my-connector:
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
PUT _connector/my-connector/_pipeline
{
"pipeline": {
"extract_binary_content": true,
"name": "my-connector-pipeline",
"reduce_whitespace": true,
"run_ml_inference": true
}
}
{
"result": "updated"
}