--- title: Run Salesforce Connector using the CLI slug: /connectors/database/salesforce/cli --- # Run Salesforce using the metadata CLI {% multiTablesWrapper %} | Feature | Status | | :----------------- | :--------------------------- | | Stage | PROD | | Metadata | {% icon iconName="check" /%} | | Query Usage | {% icon iconName="cross" /%} | | Data Profiler | {% icon iconName="check" /%} | | Data Quality | {% icon iconName="check" /%} | | Lineage | {% icon iconName="cross" /%} | | DBT | {% icon iconName="cross" /%} | | Supported Versions | -- | | Feature | Status | | :----------- | :--------------------------- | | Lineage | {% icon iconName="cross" /%} | | Table-level | {% icon iconName="cross" /%} | | Column-level | {% icon iconName="cross" /%} | {% /multiTablesWrapper %} In this section, we provide guides and references to use the Salesforce connector. Configure and schedule Salesforce metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#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. Following are the permissions you will require to fetch the metadata from Salesforce. **API Access**: You must have the API Enabled permission in your Salesforce organization. **Object Permissions**: You must have read access to the Salesforce objects that you want to ingest. ### Python Requirements To run the Salesforce ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[salesforce]" ``` ## Metadata Ingestion All connectors are defined as JSON Schemas. [Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/salesforceConnection.json) you can find the structure to create a connection to Salesforce. 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](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json) ### 1. Define the YAML Config This is a sample config for Salesforce: {% codePreview %} {% codeInfoContainer %} #### Source Configuration - Service Connection {% codeInfo srNumber=1 %} **username**: Username to connect to the Salesforce. This user should have the access as defined in requirements. {% /codeInfo %} {% codeInfo srNumber=2 %} **password**: Password to connect to Salesforce. {% /codeInfo %} {% codeInfo srNumber=3 %} **hostPort**: Enter the fully qualified hostname and port number for your Salesforce deployment in the Host and Port field. {% /codeInfo %} {% codeInfo srNumber=4 %} **securityToken**: Salesforce Security Token is required to access the metadata through APIs. You can checkout [this doc](https://help.salesforce.com/s/articleView?id=sf.user_security_token.htm&type=5) on how to get the security token. {% /codeInfo %} {% codeInfo srNumber=5 %} **sobjectName**: Specify the Salesforce Object Name in case you want to ingest a specific object. If left blank, we will ingest all the Objects. {% /codeInfo %} #### Source Configuration - Source Config {% codeInfo srNumber=8 %} 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., {% /codeInfo %} #### Sink Configuration {% codeInfo srNumber=9 %} To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. {% /codeInfo %} #### Workflow Configuration {% codeInfo srNumber=10 %} 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 %} #### Advanced Configuration {% codeInfo srNumber=6 %} **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to Athena during the connection. These details must be added as Key-Value pairs. {% /codeInfo %} {% codeInfo srNumber=7 %} **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to Athena during the connection. These details must be added as Key-Value pairs. - In case you are using Single-Sign-On (SSO) for authentication, add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "sso_login_url"` {% /codeInfo %} {% /codeInfoContainer %} {% codeBlock fileName="filename.yaml" %} ```yaml source: type: salesforce serviceName: local_salesforce serviceConnection: config: type: Salesforce ``` ```yaml {% srNumber=1 %} username: username ``` ```yaml {% srNumber=2 %} password: password ``` ```yaml {% srNumber=3 %} hostPort: hostPort ``` ```yaml {% srNumber=4 %} securityToken: securityToken ``` ```yaml {% srNumber=5 %} sobjectName: sobjectName ``` ```yaml {% srNumber=6 %} # connectionOptions: # key: value ``` ```yaml {% srNumber=7 %} # connectionArguments: # key: value ``` ```yaml {% srNumber=8 %} sourceConfig: config: type: DatabaseMetadata markDeletedTables: true includeTables: true includeViews: true # includeTags: true # databaseFilterPattern: # includes: # - database1 # - database2 # excludes: # - database3 # - database4 # schemaFilterPattern: # includes: # - schema1 # - schema2 # excludes: # - schema3 # - schema4 # tableFilterPattern: # includes: # - users # - type_test # excludes: # - table3 # - table4 ``` ```yaml {% srNumber=9 %} sink: type: metadata-rest config: {} ``` ```yaml {% srNumber=10 %} 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](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client). ## 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](/deployment/security/enable-jwt-tokens). ```yaml workflowConfig: openMetadataServerConfig: hostPort: "http://localhost:8585/api" authProvider: openmetadata securityConfig: jwtToken: "{bot_jwt_token}" ``` - You can refer to the JWT Troubleshooting section [link](/deployment/security/jwt-troubleshooting) 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](/deployment/security/workflow-config-auth). ### 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. ## Related {% tilesContainer %} {% tile title="Ingest with Airflow" description="Configure the ingestion using Airflow SDK" link="/connectors/database/salesforce/airflow" / %} {% /tilesContainer %}