StarRocks Connector | Collate Database Guide

This section provides guides and references to use the StarRocks connector. Configure and schedule StarRocks metadata and profiler workflows from the Collate UI:

• Requirements
• Iceberg Table Support
• Metadata Ingestion
• Data Profiler
• Data Quality
• Troubleshooting

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Requirements

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Metadata

To extract metadata from StarRocks, the user needs to have:

• Valid credentials (username and password) with appropriate permissions
• Access to the StarRocks FE (Frontend) host and query port
• Privileges to read all the metadata in StarRocks

The user should be able to:

• Authenticate against the StarRocks FE node
• Query schemas and tables via the MySQL-compatible interface
• Read table definitions, column types, and view definitions

You can find more details about StarRocks authentication in the official StarRocks documentation.

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Profiler and Data Quality

Executing the profiler workflow or data quality tests will require the user to have SELECT permission on the tables where the profiler/tests will be executed. For more information, see Profiler Workflow and Data Quality.

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Iceberg Table Support

StarRocks supports Iceberg table ingestion in Collate through engine metadata mapping.

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How Table Classification Works

• Collate reads table engine metadata from StarRocks system metadata.
• Tables whose engine resolves to ICEBERG are classified in Collate as Iceberg.

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Access Requirements

• Catalog permissions: Grant read access to database, table, and column metadata in the target StarRocks instance.
• File system permissions: Direct object storage write permissions are not required for metadata ingestion. Keep read access aligned with your external table and engine configuration.

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Metadata Ingestion

To ingest metadata from StarRocks, you need to create a service connection. The service connects StarRocks with Collate. Once you create a service, Collate automatically starts ingesting metadata.

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Step 1: Add New Service

Open the Services page and start a 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

From the service type dropdown, select Database Services, then click the StarRocks connector tile.

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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 StarRocks services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

Specify where ingestion runs, provide your source credentials, and verify the connection.

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Select Ingestion Runner

Select an Ingestion Runner: the runner where the ingestion pipeline will execute.

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Enter Connection Details

Enter the connection details for StarRocks. The right-hand panel in the UI displays inline help for each field.

• Scheme: SQLAlchemy driver scheme options. Defaults to mysql+pymysql.
• Username: Username to connect to StarRocks. This user should have privileges to read all the metadata in StarRocks.
• Password: Password to connect to StarRocks.
• Host and Port: Host and port of the StarRocks FE service (for example, localhost:9030).
• Database Name (Optional): Name to give to the database in Collate. If left blank, default will be used.
• Database Schema (Optional): Restrict metadata reading to a single schema. When left blank, Collate scans all schemas.
• SSL Config (Optional): SSL certificate configuration for secure connections.
• Schema Filter Pattern (Optional): Regex to only include/exclude schemas that match the pattern. System schemas (information_schema, _statistics_, sys) are excluded by default.
• Table Filter Pattern (Optional): Regex to only include/exclude tables that match the pattern.
• Database Filter Pattern (Optional): Regex to only include/exclude databases that match the pattern.

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Advanced Configuration

Database Services include an Advanced Configuration section for passing extra arguments to the connector and, if needed, changing the connection scheme. You need this only for advanced connectivity scenarios or customizations.

• 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

In the What to Ingest step, use filter patterns to control which assets Collate ingests from your database service. Filter rules match asset names using the following match types.

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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.

Rules match asset names using one of five match types:

• 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.

When both Include and Exclude are set, Exclude takes priority.

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Filter Options

The Database, Schema, and Table sections each include the following 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.

Each section provides the following controls:

• 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

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. Collate saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Settings > Services and select your service.

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Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts schemas, tables, columns, and other structural metadata from your source and keeps your Collate catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, Collate automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:

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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Troubleshooting