querying-aws-sagemaker-catalog

name	querying-aws-sagemaker-catalog
description	Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.
version	1
argument-hint	[query|domain-id|'configure'|'status']

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:kms

Note: 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-export

First 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 duplicates

• You MUST confirm workgroup and output location before executing

• Default to DATE(snapshot_time) = CURRENT_DATE for current state

• You SHOULD use the key columns documented in this skill to build queries. If you need the full schema, run get-tables once:

  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

• Exporting asset metadata
• Asset table schema
• Integrating S3 Tables with analytics services
• Lake Formation permissions