Run Domo Database using the metadata CLI
Feature | Status |
---|---|
Stage | PROD |
Metadata | |
Query Usage | |
Data Profiler | |
Data Quality | |
Lineage | Partially via Views |
DBT | |
Supported Versions | -- |
Feature | Status |
---|---|
Lineage | Partially via Views |
Table-level | |
Column-level |
In this section, we provide guides and references to use the Domo Database connector.
Configure and schedule DomoDatabase metadata and profiler workflows from the OpenMetadata UI:
Requirements
OpenMetadata 0.12 or laterTo 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.
Note:
For metadata ingestion, kindly make sure add alteast data
scopes to the clientId provided. Question related to scopes, click here.
Python Requirements
To run the DomoDatabase ingestion, you will need to install:
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to DomoDatbase.
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 DomoDatabase:
Source Configuration - Service Connection
Client ID: Client ID to Connect to DOMODatabase.
Secret Token: Secret Token to Connect DOMODatabase.
Access Token: Access to Connect to DOMODatabase.
API Host: API Host to Connect to DOMODatabase instance.
SandBox Domain: Connect to SandBox Domain.
database: Optional name to give to the database in OpenMetadata. If left blank, we will use default as the database name
Source Configuration - Source Config
The sourceConfig
is defined here:
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 filter supports regex as include or exclude. You can find examples here
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:
Advanced Configuration
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.
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"
- In case you authenticate with SSO using an external browser popup, then add the
authenticator
details in the Connection Arguments as a Key-Value pair as follows:"authenticator" : "externalbrowser"
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.
- 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:
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.