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Trino
Trino
PROD
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Feature List
Metadata
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Data Profiler
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Stored Procedures

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:

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.

We have support for Python versions 3.8-3.11

To run the Trino ingestion, you will need to install:

To extract metadata, the user needs to be able to have SELECT privilege on all the tables that you would like to ingest in OpenMetadata as well as SELECT privilege system.metadata.table_comments table.

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

This is a sample config for Trino:

username: Specify the User to connect to Trino. It should have enough privileges to read all the metadata.

  • authType: User can authenticate the Trino Instance with auth type as Basic Authentication i.e. Password or by using JWT Authentication.
    • Basic Auth:
      • password: Password to connect to Trino.
    • JWT Auth Config:
      • jwt: JWT can be used to authenticate with trino. Follow the steps in the official trino documentation to setup trino with jwt.
    • Azure:
      • clientId: To get the Client ID (also known as application ID), follow these steps:
        1. Log into Microsoft Azure.
        2. Search for App registrations and select the App registrations link.
        3. Select the Azure AD app you're using for Trino.
        4. From the Overview section, copy the Application (client) ID.
      • clientSecret: To get the client secret, follow these steps:
        1. Log into Microsoft Azure.
        2. Search for App registrations and select the App registrations link.
        3. Select the Azure AD app you're using for Trino.
        4. Under Manage, select Certificates & secrets.
        5. Under Client secrets, select New client secret.
        6. In the Add a client secret pop-up window, provide a description for your application secret. Choose when the application should expire, and select Add.
        7. From the Client secrets section, copy the string in the Value column of the newly created application secret.
      • tenantId: To get the tenant ID, follow these steps:
        1. Log into Microsoft Azure.
        2. Search for App registrations and select the App registrations link.
        3. Select the Azure AD app you're using for Trino.
        4. From the Overview section, copy the Directory (tenant) ID.
      • scopes: To let OM use the Trino Auth APIs using your Azure AD app, you'll need to add the scope
        1. Log into Microsoft Azure.
        2. Search for App registrations and select the App registrations link.
        3. Select the Azure AD app you're using for Trino.
        4. From the Expose an API section, copy the Application ID URI
        5. Make sure the URI ends with /.default in case it does not, you can append the same manually

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.

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

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:

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

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.

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 authenticator details in the Connection Arguments as a Key-Value pair as follows: "authenticator" : "sso_login_url"
filename.yaml

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.

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.

This is a sample config for the profiler:

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.

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.

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

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.

filename.yaml
  • You can learn more about how to configure and run the Profiler Workflow to extract Profiler data and execute the Data Quality from here

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.

When creating a JSON config for a test workflow the source configuration is very simple.

The only sections you need to modify here are the serviceName (this name needs to be unique) and entityFullyQualifiedName (the entity for which we'll be executing tests against) keys.

Once you have defined your source configuration you'll need to define te processor configuration.

The processor type should be set to "orm-test-runner". For accepted test definition names and parameter value names refer to the tests page.

Note that while you can define tests directly in this YAML configuration, running the workflow will execute ALL THE TESTS present in the table, regardless of what you are defining in the YAML.

This makes it easy for any user to contribute tests via the UI, while maintaining the test execution external.

You can keep your YAML config as simple as follows if the table already has tests.

  • forceUpdate: if the test case exists (base on the test case name) for the entity, implements the strategy to follow when running the test (i.e. whether or not to update parameters)
  • testCases: list of test cases to add to the entity referenced. Note that we will execute all the tests present in the Table.
  • name: test case name
  • testDefinitionName: test definition
  • columnName: only applies to column test. The name of the column to run the test against
  • parameterValues: parameter values of the test

The sink and workflowConfig will have the same settings as the ingestion and profiler workflow.

To run the tests from the CLI execute the following command

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.

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 verify parameter to False.
  • <path-to-crt>: To use self-signed certificates, specify a path to the certificate in verify parameter. More details can be found in the Python requests library documentation.
filename.yaml