OpenMetadata/openmetadata-docs/content/v0.13.3/connectors/pipeline/glue-pipeline/cli.md

title	slug
Run Glue Pipeline Connector using the CLI	/connectors/pipeline/glue-pipeline/cli

Run Glue Pipeline using the metadata CLI

In this section, we provide guides and references to use the Glue connector.

Configure and schedule Glue metadata and profiler workflows from the OpenMetadata UI:

• Requirements
• Metadata Ingestion

Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%} To deploy OpenMetadata, check the Deployment guides. {% /inlineCallout %}

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment.

Python Requirements

To run the Glue ingestion, you will need to install:

pip3 install "openmetadata-ingestion[glue]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Glue.

In order to create and run a Metadata Ingestion workflow, we will follow the steps to create a YAML configuration able to connect to the source, process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following JSON Schema

1. Define the YAML Config

This is a sample config for Glue:

{% codePreview %}

{% codeInfoContainer %}

Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

awsAccessKeyId: Enter your secure access key ID for your Glue connection. The specified key ID should be authorized to read all databases you want to include in the metadata ingestion workflow.

{% /codeInfo %}

{% codeInfo srNumber=2 %}

awsSecretAccessKey: Enter the Secret Access Key (the passcode key pair to the key ID from above).

{% /codeInfo %}

{% codeInfo srNumber=3 %}

awsRegion: Enter the location of the amazon cluster that your data and account are associated with.

{% /codeInfo %}

{% codeInfo srNumber=4 %}

awsSessionToken: The AWS session token is an optional parameter. If you want, enter the details of your temporary session token.

{% /codeInfo %}

{% codeInfo srNumber=5 %}

endPointURL: Your Glue connector will automatically determine the AWS Glue endpoint URL based on the region. You may override this behavior by entering a value to the endpoint URL.

{% /codeInfo %}

Source Configuration - Source Config

{% codeInfo srNumber=6 %}

The sourceConfig is defined here:

dbServiceNames: Database Service Name for the creation of lineage, if the source supports it.

includeTags: Set the Include tags toggle to control whether or not to include tags as part of metadata ingestion.

markDeletedPipelines: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

pipelineFilterPattern and chartFilterPattern: Note that the pipelineFilterPattern and chartFilterPattern both support regex as include or exclude.

{% /codeInfo %}

Sink Configuration

{% codeInfo srNumber=7 %}

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

{% /codeInfo %}

Workflow Configuration

{% codeInfo srNumber=8 %}

The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.

For a simple, local installation using our docker containers, this looks like:

{% /codeInfo %}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

source:
  type: glue
  serviceName: local_glue
  serviceConnection:
    config:
      type: Glue
      awsConfig:

        awsAccessKeyId: KEY

        awsSecretAccessKey: SECRET

        awsRegion: us-east-2

        # awsSessionToken: TOKEN

        # endPointURL: https://glue.us-east-2.amazonaws.com/

  sourceConfig:
    config:
      type: PipelineMetadata
      # markDeletedPipelines: True
      # includeTags: True
      # includeLineage: true
      # pipelineFilterPattern:
      #   includes:
      #     - pipeline1
      #     - pipeline2
      #   excludes:
      #     - pipeline3
      #     - pipeline4

sink:
  type: metadata-rest
  config: {}

workflowConfig:
  openMetadataServerConfig:
    hostPort: "http://localhost:8585/api"
    authProvider: openmetadata
    securityConfig:
      jwtToken: "{bot_jwt_token}"

{% /codeBlock %}

{% /codePreview %}

Workflow Configs for Security Provider

We support different security providers. You can find their definitions here.

Openmetadata JWT Auth

• JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.

workflowConfig:
  openMetadataServerConfig:
    hostPort: "http://localhost:8585/api"
    authProvider: openmetadata
    securityConfig:
      jwtToken: "{bot_jwt_token}"

• You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration. If you need information on configuring the ingestion with other security providers in your bots, you can follow this doc link.

2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

metadata ingest -c <path-to-yaml>

Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.