--- title: Run Datalake Connector using the CLI slug: /connectors/database/datalake/cli --- # Run Datalake using the metadata CLI In this section, we provide guides and references to use the Datalake connector. Configure and schedule Datalake metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#metadata-ingestion) - [DBT Integration](#dbt-integration) ## Requirements To deploy OpenMetadata, check the Deployment guides. 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. ** S3 Permissions **

To execute metadata extraction AWS account should have enough access to fetch required data. The Bucket Policy in AWS requires at least these permissions:

```json { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:GetObject", "s3:ListBucket" ], "Resource": [ "arn:aws:s3:::", "arn:aws:s3:::/*" ] } ] } ``` ### Python Requirements To run the Datalake ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[datalake]" ``` ## 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: ```yaml 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: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` #### Source Configuration - Source Config using AWS S3 The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json). * **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: ```yaml 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: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` #### Source Configuration - Service Connection using GCS The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json). * **type**: Credentials type, e.g. `service_account`. * **projectId** * **privateKey** * **privateKeyId** * **clientEmail** * **clientId** * **authUri**: [https://accounts.google.com/o/oauth2/auth](https://accounts.google.com/o/oauth2/auth) by default * **tokenUri**: [https://oauth2.googleapis.com/token](https://oauth2.googleapis.com/token) by default * **authProviderX509CertUrl**: [https://www.googleapis.com/oauth2/v1/certs](https://www.googleapis.com/oauth2/v1/certs) by default * **clientX509CertUrl** * **bucketName**: name of the bucket in GCS * **Prefix**: prefix in gcs bucket * **schemaFilterPattern** and **tableFilternPattern**: Note that the `schemaFilterPattern` and `tableFilterPattern` both support regex as `include` or `exclude`. E.g., #### Source Configuration - Source Config The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json): - `markDeletedTables`: To flag tables as soft-deleted if they are not present anymore in the source system. - `includeTables`: true or false, to ingest table data. Default is true. - `includeViews`: true or false, to ingest views definitions. - `databaseFilterPattern`, `schemaFilterPattern`, `tableFilternPattern`: Note that the they support regex as include or exclude. E.g., ```yaml tableFilterPattern: includes: - users - type_test ``` #### Sink Configuration To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. #### Workflow Configuration 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: ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client). You can find the different implementation of the ingestion below. ### Openmetadata JWT Auth ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` ### Auth0 SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: auth0 securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### Azure SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: azure securityConfig: clientSecret: '{your_client_secret}' authority: '{your_authority_url}' clientId: '{your_client_id}' scopes: - your_scopes ``` ### Custom OIDC SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### Google SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: google securityConfig: secretKey: '{path-to-json-creds}' ``` ### Okta SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: http://localhost:8585/api authProvider: okta securityConfig: clientId: "{CLIENT_ID - SPA APP}" orgURL: "{ISSUER_URL}/v1/token" privateKey: "{public/private keypair}" email: "{email}" scopes: - token ``` ### Amazon Cognito SSO The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens) ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: auth0 securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### OneLogin SSO Which uses Custom OIDC for the ingestion ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### KeyCloak SSO Which uses Custom OIDC for the ingestion ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### 2. Run with the CLI First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run: ```bash metadata ingest -c ``` 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. ## DBT Integration You can learn more about how to ingest DBT models' definitions and their lineage [here](https://docs.open-metadata.org/openmetadata/ingestion/workflows/metadata/dbt).