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OpenMetadata/openmetadata-docs/content/openmetadata/connectors/database/datalake/cli.md
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Docs - Python requirements & metadata docker (#6790) 
Docs - Python requirements & metadata docker (#6790)
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Run Datalake Connector using the CLI /openmetadata/connectors/database/datalake/cli

Metadata Ingestion

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

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 Datalake using AWS S3:


source:
  type: datalake
  serviceName: local_datalake
  serviceConnection:
    config:
      type: Datalake
      configSource:      
        securityConfig: 
          awsAccessKeyId: aws access key id
          awsSecretAccessKey: aws secret access key
          awsRegion: aws region
      bucketName: bucket name
      prefix: prefix
  sourceConfig:
    config:
      tableFilterPattern:
        includes:
        - ''
sink:
  type: metadata-rest
  config: {}
workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: no-auth

Source Configuration - Source Config using AWS S3

The sourceConfig is defined here.

  • awsAccessKeyId: Enter your secure access key ID for your DynamoDB connection. The specified key ID should be authorized to read all databases you want to include in the metadata ingestion workflow.
  • awsSecretAccessKey: Enter the Secret Access Key (the passcode key pair to the key ID from above).
  • awsRegion: Specify the region in which your DynamoDB is located. This setting is required even if you have configured a local AWS profile.
  • schemaFilterPattern and tableFilternPattern: Note that the schemaFilterPattern and tableFilterPattern both support regex as include or exclude. E.g.,

This is a sample config for Datalake using GCS:



source:
  type: datalake
  serviceName: local_datalake
  serviceConnection:
    config:
      type: Datalake
      configSource:      
        securityConfig: 
          gcsConfig:
            type: type of account
            projectId: project id
            privateKeyId: private key id
            privateKey: private key
            clientEmail: client email
            clientId: client id
            authUri: https://accounts.google.com/o/oauth2/auth
            tokenUri: https://oauth2.googleapis.com/token
            authProviderX509CertUrl: https://www.googleapis.com/oauth2/v1/certs
            clientX509CertUrl:  clientX509 Certificate Url
      bucketName: bucket name
      prefix: prefix
  sourceConfig:
    config:
      tableFilterPattern:
        includes:
        - ''
sink:
  type: metadata-rest
  config: {}
workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: no-auth

Source Configuration - Service Connection using GCS

The sourceConfig is defined here.