In this section, we provide guides and references to use the Lightdash connector.
Configure and schedule Lightdash metadata and profiler workflows from the OpenMetadata UI:
How to Run the Connector Externally
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.
If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.
Requirements
To integrate Lightdash, ensure you are using OpenMetadata version 1.2.x or higher.
Python Requirements
We have support for Python versions 3.8-3.11
To run the Lightdash 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 Lightdash.
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 Lightdash:
Source Configuration - Service Connection
- Host and Port: Specify the network location where your Lightdash instance is accessible, combining both hostname and port in a URI format: either
http://hostname:portorhttps://hostname:port, based on your security needs. Example: For a local setup, usehttp://localhost:8080; for a server deployment, it might behttps://lightdash.example.com:3000. Ensure the specified port is open and accessible through network firewall settings.
- API Key: This key authenticates requests to your Lightdash instance. Keep the API Key secure, sharing it only with authorized applications or users.
- Project UUID: This unique identifier links API requests or configurations to a specific project in Lightdash.
- Space UUID: Identifies a specific "Space" in Lightdash, used to organize dashboards, charts, and assets.
- Proxy Authentication: If your Lightdash instance requires authentication through a proxy server, provide proxy credentials. Proxy authentication controls access to external resources and Lightdash.
Source Configuration - Source Config
The sourceConfig is defined here:
- dbServiceNames: Database Service Names for ingesting lineage if the source supports it.
- dashboardFilterPattern, chartFilterPattern, dataModelFilterPattern: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
- projectFilterPattern: Filter the dashboards, charts and data sources by projects. Note that all of them support regex as include or exclude. E.g., "My project, My proj.*, .*Project".
- includeOwners: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.
- includeTags: Set the 'Include Tags' toggle to control whether to include tags in metadata ingestion.
- includeDataModels: Set the 'Include Data Models' toggle to control whether to include tags as part of metadata ingestion.
- markDeletedDashboards: Set the 'Mark Deleted Dashboards' toggle to flag dashboards as soft-deleted if they are not present anymore in the source system.
- Include Draft Dashboard (toogle): Set the 'Include Draft Dashboard' toggle to include draft dashboards. By default it will include draft dashboards.
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.
Logger Level
You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.
JWT Token
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.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
SSL Configuration
If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.
Find more information on how to troubleshoot SSL issues here.
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.