Trino Connector | Collate Distributed SQL Integration

• Requirements
• Iceberg Table Support
• Metadata Ingestion
• Lineage
• Data Profiler
• Data Quality
• dbt Integration
• Troubleshooting
• Reverse Metadata

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Requirements

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Metadata

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Profiler and Data Quality

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Iceberg Table Support

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How Table Classification Works

• Collate inspects catalog metadata to identify whether the configured catalog is backed by the Iceberg connector.
• Tables from Iceberg-backed catalogs are classified in Collate as Iceberg.

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Access Requirements

• Catalog permissions: Grant access to list catalogs and read system metadata used by Trino for connector discovery.
• File system permissions: Direct object storage write permissions are not required for metadata ingestion. Keep read access aligned with your configured Iceberg catalog and storage policies.

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Metadata Ingestion

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Step 1: Add New Service

1. Navigate to Settings > Services and select Database Services.
2. Click Add New Service.

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Step 2: Select a Service and Connector

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Step 3: Add Service Name and Description

• Enter a unique, descriptive Service Name. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other Trino services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

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Select Ingestion Runner

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Enter Connection Details

password: secret:/my/database/password

• Username: Specify the user to connect to Trino. It should have enough privileges to read all the metadata.
• Auth Config: Authenticate the Trino instance with either Basic Authentication (password) or 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:
    • Client ID: 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.
    • Client Secret: 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.
    • Tenant ID: 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 Collate 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
• Host and Port: 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 an optional parameter. Use it to restrict metadata reading to a single databaseSchema. When left blank, Collate ingestion attempts to scan all schemas.
• proxies: Proxies for the connection to Trino data source
• params: URL parameters for connection to the Trino data source
• Connection Options (Optional): Enter the details for any additional connection options that can be sent to Trino 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 Trino 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"

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SSL Configuration

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SSL Modes

• false: 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. Find more details in the Python requests library documentation.

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Advanced Configuration

• Connection Options (Optional): Enter the details for any additional connection options that can be sent to the 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 during the connection. These details must be added as key-value pairs.

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Test Connection

1. Click Test Connection to verify the credentials.
2. After the test succeeds, click Save.

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Step 5: Configure Ingestion Options

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How Filter Patterns Work

• Include: Add one or more comma-separated values. Each value uses one of the following match types. Collate ingests only assets whose names match at least one rule. Leave blank to include all assets.
• Exclude: Add one or more comma-separated values. Each value uses one of the following match types. Collate skips any asset whose name matches a rule. Leave blank to exclude nothing.

• contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
• starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
• ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
• is exactly: matches the exact name only. For example, analytics matches only analytics.
• matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.

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Filter Options

• Database: Controls which databases Collate ingests from the source.
• Schema: Controls which schemas within the ingested databases are included.
• Table: Controls which tables and views within the ingested schemas are included.

• Scan Mode: Choose between the following scan modes:
  • Scan all: Ingests every asset of that type the connector can access. This is the default.
  • Only specific: Enables include rules so only assets matching at least one rule are ingested.
• Exclude system toggle: Use this toggle to filter out system-reserved names defined by the connector for that asset type.
• Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
• Preview: Shows a real-time summary of what will be in scope based on your current rules.
• Include rules: In Only specific mode, click + Add to define a rule. Added rules appear as chips. An asset is included if it matches any rule.

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Step 6: Create & Deploy

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Configure Metadata Agent and Schedule Ingestion

1. Navigate to Settings > Services and select the Databases service.
2. Select your service and click the Agents tab.
3. Click Add Agent and select Metadata from the dropdown. For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
4. On the Configure Ingestion page, do the following and click Next.
   • Name this Ingestion: Enter a unique, recognizable name for this ingestion pipeline.
   • Agent Setup: Configure core parameters for metadata extraction. The following fields are available:

     Field	Default	Description
     Default Owner	—	Owner applied to any entity that has no owner from a more specific field below. Accepts a user or a team, by name or email.
     Service Owner	—	Not applied during ingestion. This field doesn’t affect the owners of databases, schemas, or tables.
     Database Owner	—	Owner assigned to every database this agent ingests. Accepts either one owner for all of them, or a mapping of specific owners per database.
     Database Schema Owner	—	Owner assigned to every schema this agent ingests. Accepts either one owner for all of them, or a mapping of specific owners per schema.
     Table Owner	—	Owner assigned to every table this agent ingests. Accepts either one owner for all of them, or a mapping of specific owners per table.
     Enable Inheritance	On	When on, a schema or table with no match of its own inherits the owner resolved for its parent. Default Owner still applies when nothing else resolves an owner.
     Query Log Duration	1	How many days of query logs to look back through when processing stored procedure results.
     Query Parsing Timeout Limit	300	How many seconds to spend parsing a single query before giving up on it and moving to the next. Raise this if large or complex queries are being skipped.
     Number of Threads	1	How many tables to ingest in parallel. Raising this can speed up ingestion on databases with many tables, at the cost of more load on the source.
     Incremental Extraction	Off	When on, a run extracts only entities that changed since the last successful run, instead of re-scanning everything every time. Faster on large, mostly-unchanged databases.
     Successful Pipeline Run Lookback Days	7	Only used when Incremental Extraction is on. How many days back to search for a prior successful run to use as the starting point for “what changed since then.”
     Safety Margin Days	1	Only used when Incremental Extraction is on. Extra days added before that starting point, as a buffer so changes that were still in flight when the last run finished aren’t missed.
     Extract JSON Schema	Off	Sample values in JSON columns to infer and ingest their schema, so the individual fields inside a JSON column are visible in Collate rather than just “JSON”. Requires SELECT permission on the sampled tables; if that permission is missing, the JSON column is still ingested, just without a detailed schema.
     JSON Schema Sample Size	10	Only used when Extract JSON Schema is on. Number of rows sampled per JSON column to infer its schema. A larger sample gives more accurate results but takes longer to run.

     For more information, see Hierarchical Owner Configuration.
   • Filter Patterns: Apply include or exclude rules to scope which databases, schemas, tables, and stored procedures this agent ingests. These follow the same filter options described in Step 5.
   • Scope & Behaviour: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:

     Toggle	Default	Description
     Include Tables	On	Ingest tables and their columns. Turn off to skip tables entirely, for example if this agent exists only to pull tags or stored procedures.
     Include Tags	On	Ingest tags already defined on tables/columns in the source system (for example, a classification tag applied in Snowflake) and bring them into Collate as tags on the same assets.
     Include Stored Procedures	On	Ingest stored procedures as their own assets, so they show up in the catalog and can be linked into lineage.
     Include DDL Statements	Off	Also ingest the raw CREATE TABLE / CREATE VIEW statement for each asset, so it’s viewable in Collate alongside the asset’s metadata.
     Include Owners	Off	When an ingested asset’s owner in the source system is an email that matches an existing Collate user, assign that user as the asset’s owner. Never overwrites an owner an asset already has in Collate.
     Include Custom Properties	Off	Ingest source-specific metadata that doesn’t map to a standard Collate field (for example, a database-specific attribute) into custom properties on the asset, if custom properties have been defined for that entity type.
     Mark Deleted Tables	On	If a table this agent previously ingested no longer exists in the source, soft-delete it in Collate too. Only affects tables within schemas this agent actually scans.
     Mark Deleted Stored Procedures	On	Same as Mark Deleted Tables, but for stored procedures.
     Mark Deleted Schemas	Off	If an entire schema this agent previously ingested no longer exists in the source, soft-delete the schema and everything in it.
     Mark Deleted Databases	Off	If an entire database this agent previously ingested no longer exists in the source, soft-delete the database and everything in it.
     Override Metadata	Off	On: values from the source (descriptions, tags, owners, display names) always overwrite what’s currently in Collate, even if someone edited it there. Off: Collate only fills in fields that are still empty, so manual edits in Collate are preserved.
     Enable Debug Log	Off	Run this ingestion at DEBUG log verbosity instead of the normal level. Turn on when troubleshooting a failing or unexpected run; leave off otherwise, since debug logs are much larger.

     Note: Available toggles vary by connector. Stored procedure options only appear for connectors that support stored procedures.
     
   • Advanced Config: Driver-level options (connection arguments, scheme, and timeouts). Most connections never need these, and they vary by connector. This section also has one ingestion-scope toggle:

     Toggle	Default	Description
     Include Views	On	Ingest views in addition to tables. Turn off to skip views entirely. Because view lineage is derived from parsing each view’s SQL definition, turning this off also stops view-based lineage from being generated for this service.

     
5. On the Schedule Interval page, set when the agent runs:
   • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
   • On-Demand: No automatic schedule. Trigger the agent manually when needed.
   
6. Click Add to deploy the agent.

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Reverse Metadata

-- Update table description
COMMENT ON TABLE "{database}"."{schema}"."{table}" IS {description}

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Troubleshooting