Bulk load documents into OpenSearch using an Internal Storage file.

yaml
id: opensearch_load
namespace: company.team

inputs:
  - id: file
    type: FILE

tasks:
  - id: load
    type: io.kestra.plugin.opensearch.Load
    connection:
      hosts:
        - "http://localhost:9200"
    from: "{{ inputs.file }}"
    index: "my_index"

The connection properties.

The source file.

Pebble expression referencing an Internal Storage URI e.g. {{ outputs.mytask.uri }}.

The OpenSearch index.

Default 1000

The chunk size for every bulk request.

Use this key as id.

Possible Values

INDEXCREATEUPDATEDELETE

Sets the type of operation to perform.

Default true

Remove idKey from the final document.

Controls the shard routing of the request.

Using this value to hash the shard and not the id.

The size of the rows fetched.

SubType string

List of HTTP OpenSearch servers.

Must be an URI like https://opensearch.com: 9200 with scheme and port.

Basic auth configuration.

SubType string

List of HTTP headers to be send on every request.

Must be a string with key value separated with : , ex: Authorization: Token XYZ.

Sets the path's prefix for every request used by the HTTP client.

For example, if this is set to /my/path, then any client request will become /my/path/ + endpoint. In essence, every request's endpoint is prefixed by this pathPrefix. The path prefix is useful for when OpenSearch is behind a proxy that provides a base path or a proxy that requires all paths to start with '/'; it is not intended for other purposes and it should not be supplied in other scenarios.

Whether the REST client should return any response containing at least one warning header as a failure.

Trust all SSL CA certificates.

Use this if the server is using a self signed SSL certificate.

Basic auth password.

Basic auth username.

​Load

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