Run Trino 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 Trino connector.
Configure and schedule Trino 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.
Python Requirements
To run the Trino ingestion, you will need to install:
To ingest metadata from the Trino source, the user must have select privileges for the following tables.
information_schema.schematainformation_schema.columnsinformation_schema.tablesinformation_schema.viewssystem.metadata.table_comments
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Trino.
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 Trino:
Source Configuration - Service Connection
username: Specify the User to connect to Trino. It should have enough privileges to read all the metadata.
password: Password to connect to Trino.
hostPort: Enter the fully qualified hostname and port number for your Trino deployment in the Host and Port field.
catalog: Trino offers a catalog feature where all the databases are stored. (Providing the Catalog is not mandatory from 0.12.2 or greater versions)
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.
proxies: Proxies for the connection to Trino data source
params: URL parameters for connection to the Trino data source
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
authenticatordetails 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
authenticatordetails in the Connection Arguments as a Key-Value pair as follows:"authenticator" : "externalbrowser"
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.
Data Profiler
The Data Profiler workflow will be using the orm-profiler processor.
After running a Metadata Ingestion workflow, we can run Data Profiler 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 the profiler:
Source Configuration - Source Config
You can find all the definitions and types for the sourceConfig here.
generateSampleData: Option to turn on/off generating sample data.
profileSample: Percentage of data or no. of rows we want to execute the profiler and tests on.
threadCount: Number of threads to use during metric computations.
processPiiSensitive: Optional configuration to automatically tag columns that might contain sensitive information.
confidence: Set the Confidence value for which you want the column to be marked
timeoutSeconds: Profiler Timeout in Seconds
databaseFilterPattern: Regex to only fetch databases that matches the pattern.
schemaFilterPattern: Regex to only fetch tables or databases that matches the pattern.
tableFilterPattern: Regex to only fetch tables or databases that matches the pattern.
Processor Configuration
Choose the orm-profiler. Its config can also be updated to define tests from the YAML itself instead of the UI:
tableConfig: tableConfig allows you to set up some configuration at the table level.
- You can learn more about how to configure and run the Profiler Workflow to extract Profiler data and execute the Data Quality from 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:
Note now instead of running ingest, we are using the profile command to select the Profiler workflow.
SSL Configuration
In order to integrate SSL in the Metadata Ingestion Config, the user will have to add the SSL config under connectionArguments which is placed in source.
SSL Modes
There are couple of types of SSL modes that redshift supports which can be added to ConnectionArguments, they are as follows:
- false: In order to disable SSL verification, set the
verifyparameter toFalse. - <path-to-crt>: To use self-signed certificates, specify a path to the certificate in
verifyparameter. More details can be found in the Python requests library documentation.