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103 lines
2.7 KiB
Text
103 lines
2.7 KiB
Text
[[update-connector-pipeline-api]]
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=== Update connector pipeline API
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preview::[]
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++++
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<titleabbrev>Update connector pipeline</titleabbrev>
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++++
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Updates the `pipeline` configuration of a connector.
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When you create a new connector, the configuration of an <<ingest-pipeline-search-details-generic-reference, ingest pipeline>> is populated with default settings.
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[[update-connector-pipeline-api-request]]
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==== {api-request-title}
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`PUT _connector/<connector_id>/_pipeline`
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[[update-connector-pipeline-api-prereq]]
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==== {api-prereq-title}
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* To sync data using connectors, it's essential to have the Elastic connectors service running.
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* The `connector_id` parameter should reference an existing connector.
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[[update-connector-pipeline-api-path-params]]
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==== {api-path-parms-title}
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`<connector_id>`::
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(Required, string)
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[role="child_attributes"]
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[[update-connector-pipeline-api-request-body]]
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==== {api-request-body-title}
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`pipeline`::
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(Required, object) The pipeline configuration of the connector. The pipeline determines how data is processed during ingestion into Elasticsearch.
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Pipeline configuration must include the following attributes:
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- `extract_binary_content` (Required, boolean) A flag indicating whether to extract binary content during ingestion.
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- `name` (Required, string) The name of the ingest pipeline.
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- `reduce_whitespace` (Required, boolean) A flag indicating whether to reduce extra whitespace in the ingested content.
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- `run_ml_inference` (Required, boolean) A flag indicating whether to run machine learning inference on the ingested content.
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[[update-connector-pipeline-api-response-codes]]
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==== {api-response-codes-title}
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`200`::
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Connector `pipeline` field was successfully updated.
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`400`::
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The `connector_id` was not provided or the request payload was malformed.
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`404` (Missing resources)::
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No connector matching `connector_id` could be found.
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[[update-connector-pipeline-api-example]]
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==== {api-examples-title}
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The following example updates the `pipeline` property for the connector with ID `my-connector`:
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////
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[source, console]
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--------------------------------------------------
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PUT _connector/my-connector
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{
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"index_name": "search-google-drive",
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"name": "My Connector",
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"service_type": "google_drive"
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}
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--------------------------------------------------
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// TESTSETUP
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[source,console]
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--------------------------------------------------
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DELETE _connector/my-connector
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--------------------------------------------------
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// TEARDOWN
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////
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[source,console]
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----
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PUT _connector/my-connector/_pipeline
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{
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"pipeline": {
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"extract_binary_content": true,
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"name": "my-connector-pipeline",
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"reduce_whitespace": true,
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"run_ml_inference": true
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}
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}
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----
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[source,console-result]
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----
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{
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"result": "updated"
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}
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----
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