In this section, we provide guides and references to use the Unity Catalog connector.
Configure and schedule Unity Catalog metadata workflow 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
Python Requirements
We have support for Python versions 3.8-3.11
To run the Unity Catalog 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 Databricks.
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 Unity Catalog:
Source Configuration - Service Connection
catalog: Catalog of the data source(Example: hive_metastore). This is optional parameter, if you would like to restrict the metadata reading to a single catalog. When left blank, OpenMetadata Ingestion attempts to scan all the catalog.
databaseSchema: DatabaseSchema of the data source. This is optional parameter, if you would like to restrict the metadata reading to a single databaseSchema. When left blank, OpenMetadata Ingestion attempts to scan all the databaseSchema.
hostPort: Enter the fully qualified hostname and port number for your Databricks deployment in the Host and Port field.
token: Generated Token to connect to Databricks.
httpPath: Databricks compute resources URL.
connectionTimeout: The maximum amount of time (in seconds) to wait for a successful connection to the data source. If the connection attempt takes longer than this timeout period, an error will be returned.
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.
markDeletedStoredProcedures: Optional configuration to soft delete stored procedures in OpenMetadata if the source stored procedures are deleted. Also, if the stored procedures is deleted, all the associated entities like lineage, etc., with that stored procedures will be deleted.
includeTables: true or false, to ingest table data. Default is true.
includeViews: true or false, to ingest views definitions.
includeTags: Optional configuration to toggle the tags ingestion.
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.
includeStoredProcedures: Optional configuration to toggle the Stored Procedures ingestion.
includeDDL: Optional configuration to toggle the DDL Statements ingestion.
queryLogDuration: Configuration to tune how far we want to look back in query logs to process Stored Procedures results.
queryParsingTimeoutLimit: Configuration to set the timeout for parsing the query in seconds.
useFqnForFiltering: Regex will be applied on fully qualified name (e.g service_name.db_name.schema_name.table_name) instead of raw name (e.g. table_name).
databaseFilterPattern, schemaFilterPattern, tableFilterPattern: Note that the filter supports regex as include or exclude. You can find examples here
threads (beta): The number of threads to use when extracting the metadata using multithreading. Please take a look here before configuring this.
incremental (beta): Incremental Extraction configuration. Currently implemented for:
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.
Advanced Configuration
Connection Options (Optional): Enter the details for any additional connection options that can be sent to database 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 database 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
authenticatordetails in the Connection Arguments as a Key-Value pair as follows:"authenticator" : "sso_login_url"
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.
Query Usage
The Query Usage workflow will be using the query-parser processor.
After running a Metadata Ingestion workflow, we can run Query Usage workflow. While the serviceName will be the same to that was used in Metadata Ingestion, so the ingestion bot can get the serviceConnection details from the server.
1. Define the YAML Config
This is a sample config for BigQuery Usage:
Source Configuration - Source Config
You can find all the definitions and types for the sourceConfig here.
queryLogDuration: Configuration to tune how far we want to look back in query logs to process usage data.
stageFileLocation: Temporary file name to store the query logs before processing. Absolute file path required.
resultLimit: Configuration to set the limit for query logs
queryLogFilePath: Configuration to set the file path for query logs
Processor, Stage and Bulk Sink Configuration
To specify where the staging files will be located.
Note that the location is a directory that will be cleaned at the end of the ingestion.
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
After saving the YAML config, we will run the command the same way we did for the metadata ingestion:
Lineage
You can learn more about how to ingest lineage here.
dbt Integration
You can learn more about how to ingest dbt models' definitions and their lineage here.