Querying AWS Sagemaker Catalog
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Written by AutoGineer from the skill’s own files, not by the author
This skill provides guidance and SQL patterns for querying SageMaker Catalog asset metadata exported as Apache Iceberg tables in S3 Tables. It enables users to perform governance audits, track asset growth, identify metadata gaps, and conduct historical comparisons of catalog state without requiring custom ETL pipelines. The skill covers configuration, permission management via Lake Formation, and specific SQL query structures for analyzing catalog inventory.
What it does
- Provides SQL templates for analyzing catalog asset inventory and metadata.
- Explains how to enable and configure daily metadata exports from SageMaker Catalog.
- Details the schema and key columns for querying asset metadata tables.
- Demonstrates how to perform time-travel analysis to compare catalog snapshots.
- Outlines required Lake Formation permissions for secure access to catalog data.
- Offers troubleshooting steps for common configuration and query errors.
When to use it
- When you need to perform governance queries on your data catalog.
- When auditing data ownership or identifying assets missing business descriptions.
- When tracking the growth of cataloged assets over time.
- When comparing the state of the catalog across different dates.
- When analyzing catalog metadata for quality or consistency.
Advantages
- Enables SQL-based analytics on catalog metadata without building custom ETL.
- Supports historical trend analysis through daily snapshot partitioning.
- Integrates with standard AWS analytics services like Athena.
- Provides clear patterns for filtering and joining catalog data.
Usage examples
- “How many assets are in my catalog by type?”
- Returns a count of assets grouped by resource type using the current daily snapshot.
- “Find all assets that are missing a business description.”
- Generates a list of assets where the business_description field is NULL.
- “Show me the asset growth over the last 30 days.”
- Provides a daily count of assets for the past month to visualize catalog growth.
- “Compare current catalog descriptions with those from a week ago.”
- Performs a join between two snapshots to identify assets that received new descriptions.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/aws/querying-aws-sagemaker-catalog/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip querying-aws-sagemaker-catalog.zip -d .agents/skills
Documentation by AWS
Query AWS SageMaker Catalog System Tables
Overview
Works best with the AWS MCP server for sandboxed execution and audit logging. All commands below use the AWS CLI and work in any environment with configured AWS credentials.
Amazon SageMaker Unified Studio (whose catalog feature is referred to below as SageMaker Catalog) exports asset metadata as a daily-snapshot
Apache Iceberg table in the AWS-managed aws-sagemaker-catalog table bucket. This
enables SQL queries over your entire data catalog inventory — asset counts, governance
gaps, ownership audits, and historical comparisons — without building custom ETL.
Data is partitioned by snapshot_time and exported once daily (around midnight per
region). The table is read-only.
Decision Tree
| User intent | Use this skill? | Alternative |
|---|---|---|
| SQL analytics on catalog state (counts, governance, trends) | Yes | — |
| Historical comparison ("what changed in catalog last week") | Yes — time travel via snapshot_time | — |
| Find assets without owners or descriptions | Yes | — |
| Find a specific table by name or concept | No | finding-data-lake-assets or Glue Discovery search |
| Browse/enumerate catalog interactively | No | exploring-data-catalog |
| Run a query on a table's data | No | querying-data-lake |
| Manage catalog metadata (add descriptions, tags) | No | Glue Discovery put-form-type / associate-glossary-terms |
Common Tasks
1. Check If Configured
aws datazone get-data-export-configuration \
--domain-identifier <DOMAIN_ID> \
--region <REGION>If no domain exists:
aws datazone list-domains --region <REGION>If export not enabled: guide user to enable.
One domain per account per region.
Verify table bucket exists:
aws s3tables list-table-buckets --region <REGION> \
--query "tableBuckets[?name=='aws-sagemaker-catalog']"2. Enable
With KMS encryption (recommended for production):
aws datazone put-data-export-configuration \
--domain-identifier <DOMAIN_ID> \
--region <REGION> \
--enable-export \
--encryption-configuration kmsKeyArn=<KMS_KEY_ARN>,sseAlgorithm=aws:kmsNote: Encryption cannot be changed after creation. Always specify KMS for sensitive catalog data.
Without encryption (for quick testing only):
aws datazone put-data-export-configuration \
--domain-identifier <DOMAIN_ID> \
--region <REGION> \
--enable-exportFirst data available within 24 hours. See: Exporting asset metadata
3. Verify Permissions for Querying
Requires:
S3 Tables federated catalog registered in Glue (
s3tablescatalog)Lake Formation SELECT + DESCRIBE grants on the table
Grant access:
aws lakeformation grant-permissions \
--principal DataLakePrincipalIdentifier=<ROLE_ARN> \
--resource '{"Table": {"CatalogId": "<ACCOUNT>:s3tablescatalog/aws-sagemaker-catalog", "DatabaseName": "asset_metadata", "Name": "asset"}}' \
--permissions DESCRIBE SELECT \
--region <REGION>4. Query
Query syntax:
"s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"Constraints:
You MUST always filter by
snapshot_time— without it, the query scans all historical snapshots and returns duplicatesYou MUST confirm workgroup and output location before executing
Default to
DATE(snapshot_time) = CURRENT_DATEfor current stateYou SHOULD use the key columns documented in this skill to build queries. If you need the full schema, run
get-tablesonce:aws glue get-tables --catalog-id "<ACCOUNT>:s3tablescatalog/aws-sagemaker-catalog" --database-name "asset_metadata" --region <REGION>
Key columns:
| Column | What it holds | Usage |
|---|---|---|
snapshot_time | Partition key — daily snapshot timestamp | Always filter on this |
asset_id | Unique catalog asset identifier | Primary key for lookups |
resource_type_enum | GlueTable, RedshiftTable, S3Collection, etc. | Filter by asset type |
resource_id | ARN or native identifier | Cross-reference with source systems |
asset_name | Business-friendly name | Display, search |
resource_name | Technical name (table name, prefix) | Filtering |
business_description | Business context (NULL if not provided) | Governance gaps |
extended_metadata | map<string,string> — flexible key-value attributes | Use bracket notation: extended_metadata['owningEntityId'] |
asset_created_time | When asset first appeared in catalog | Growth analysis |
asset_updated_time | Last modification time | Freshness checks |
Current catalog state:
SELECT resource_type_enum, COUNT(*) as count
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
GROUP BY resource_type_enum
ORDER BY count DESC;Assets without business descriptions:
SELECT asset_name, resource_name, resource_type_enum, account_id
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
AND business_description IS NULL;Asset growth over last 30 days:
SELECT DATE(snapshot_time) as date, COUNT(*) as total_assets
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) >= CURRENT_DATE - INTERVAL '30' DAY
GROUP BY DATE(snapshot_time)
ORDER BY date DESC;Time travel — compare current vs 7 days ago (new descriptions added):
SELECT t.asset_id, t.resource_name,
p.business_description as before,
t.business_description as now
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset" t
JOIN "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset" p
ON t.asset_id = p.asset_id
WHERE DATE(t.snapshot_time) = CURRENT_DATE
AND DATE(p.snapshot_time) = CURRENT_DATE - INTERVAL '7' DAY
AND p.business_description IS NULL
AND t.business_description IS NOT NULL;Assets by owner:
SELECT extended_metadata['owningEntityId'] as owner, COUNT(*) as count
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
AND extended_metadata['owningEntityId'] IS NOT NULL
GROUP BY extended_metadata['owningEntityId']
ORDER BY count DESC;Filter by metadata form field:
SELECT *
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
AND extended_metadata['<metadata-form-name>.<field-name>'] = '<field-value>';Key Behaviors
Daily snapshots — exported around midnight per region
Always filter by
snapshot_time— without it you get all history (duplicates, slow)One domain per account per region — to switch domains, delete config first
No additional charge beyond S3 Tables storage + Athena queries
Read-only — to update asset metadata, use Glue Discovery APIs or SageMaker Unified Studio
Troubleshooting
| Error | Cause | Fix |
|---|---|---|
aws-sagemaker-catalog bucket not found | Export not enabled | Run put-data-export-configuration --enable-export |
Empty results with CURRENT_DATE | First export hasn't run yet (takes up to 24h) | Wait; try yesterday's date |
AccessDenied on query | Missing Lake Formation grants | Grant SELECT + DESCRIBE on the table |
CATALOG_NOT_FOUND | S3 Tables not registered in Glue | Enable integration: S3 console > Table buckets > Enable integration |
| Duplicate rows in results | Missing snapshot_time filter | Add WHERE DATE(snapshot_time) = CURRENT_DATE |
extended_metadata key returns NULL | Key doesn't exist for that asset | Check available keys: SELECT DISTINCT key FROM ... CROSS JOIN UNNEST(map_keys(extended_metadata)) AS t(key) WHERE DATE(snapshot_time) = CURRENT_DATE |
| Cannot update export encryption | Encryption set at creation time only | Delete and recreate export config |
Security Considerations
Data sensitivity: Catalog metadata exposes organizational structure including asset names, ownership, account IDs, naming conventions, and internal resource identifiers. Treat query results as sensitive by default.
Encryption at rest: Always enable KMS encryption when creating the export configuration. Encryption cannot be changed after creation. Additionally, configure SSE-KMS on your Athena workgroup output bucket.
Least-privilege access: Grant Lake Formation SELECT + DESCRIBE only on the specific asset_metadata.asset table to roles that need catalog analytics. Avoid granting access to the entire aws-sagemaker-catalog bucket.
Audit trail: Enable CloudTrail logging for DataZone (PutDataExportConfiguration, GetDataExportConfiguration), Athena (StartQueryExecution, GetQueryResults), and S3 Tables API calls to track who queries catalog metadata.
Credential hygiene: Use IAM roles with temporary credentials for querying. Avoid long-lived access keys for users accessing catalog metadata. Scope down or rotate principals when access is no longer needed.
Additional Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer952 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md10.3 KiB
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Requirements and compatibility
Written for: Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Claude Code frontmatter, Needs an MCP server, Needs a command-line tool
Security
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- aws/agent-toolkit-for-aws · skills/specialized-skills/system-table-skills/querying-aws-sagemaker-catalog · commit 0a218f8
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- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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