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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
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%} To deploy OpenMetadata, check the Deployment guides. {% /inlineCallout %}
The Glue connector ingests metadata through AWS Boto3 Client. We will ingest Workflows, its jobs and their run status.
The user must have the following permissions for the ingestion to run successfully:
glue:ListWorkflows
glue:GetWorkflow
glue:GetJobRuns
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 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 %}
{% partial file="workflow-config.md" /%}
{% /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: {}
{% partial file="workflow-config-yaml.md" /%}
{% /codeBlock %}
{% /codePreview %}
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.