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federate-lakehouse-catalog

Configures Google Cloud Lakehouse federated catalogs connecting BigQuery to Databricks Unity and AWS Glue.

Updated Aug 16, 2026
Search Tags:#bigquery#iceberg#federation#lakehouse#cross-cloud#aws glue#databricks unity
One-click install
npx skills add https://github.com/1919114514yasenpai-maker/focus-quest --skill federate-lakehouse-catalog-1919114514yasenpai-maker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: federate-lakehouse-catalog
Source: https://github.com/1919114514yasenpai-maker/focus-quest/tree/main/.gemini/skills/federate-lakehouse-catalog
Command: npx skills add https://github.com/1919114514yasenpai-maker/focus-quest --skill federate-lakehouse-catalog-1919114514yasenpai-maker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Querying data stored in remote catalogs like Databricks Unity or AWS Glue from Google Cloud normally requires complex cross-cloud setup involving IAM roles, secrets, and region alignment. This Skill guides the entire federation workflow so you can query remote Iceberg data directly from BigQuery or Spark on GCP. ## Core Features & Use Cases - Databricks Unity Federation: Creates regional Secret Manager secrets and federated BigLake Iceberg catalogs pointing to Databricks Unity Catalog with OAuth service principal credentials. - AWS Glue Federation: Walks through AWS IAM role creation with trust policies, scoped Glue/S3 permissions, and catalog creation using your AWS Account ID as the Glue warehouse. - Region Pairing Guidance: Recommends optimal GCP regions paired with AWS regions to minimize cross-cloud query latency. - Validation & Troubleshooting: Verifies the federation by listing namespaces via the bq CLI and proposes meaningful analytical queries on the discovered data. - Use Case: You have tables in AWS Glue on S3 and want to run BigQuery analytics against them without migrating data—this Skill sets up the federated catalog end to end. ## Quick Start Ask the assistant to federate your lakehouse catalog to Databricks or AWS Glue so you can query that remote data from BigQuery.

Frequently Asked Questions about federate-lakehouse-catalog

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query Databricks Unity Catalog data from BigQuery?▼

Create a federated BigLake Iceberg catalog of type unity using gcloud alpha biglake iceberg catalogs create, storing your Databricks OAuth client ID and secret in a regional Secret Manager secret. Grant the catalog's service account secretAccessor access, then query tables via BigQuery in the same region.

How to connect AWS Glue Data Catalog to Google Cloud BigQuery?▼

Create an AWS IAM role with a placeholder trust policy, attach Glue and S3 read permissions, then create a federated BigLake catalog with --glue-warehouse set to your 12-digit AWS Account ID. Finally update the trust policy with the catalog's biglake-service-account-id and enable background refresh.

Which GCP region should I pair with my AWS region for lakehouse federation?▼

Choose GCP regions with Low Latency Dedicated or Partner CCI connectivity. For example, AWS us-east-1 pairs with GCP us-east4, us-west-2 with us-west1, eu-west-2 with europe-west2, and eu-central-1 with europe-west3.

Why does my federated catalog validation fail after creation?▼

Common causes include the Secret Manager secret and catalog being in different regions, the AWS trust policy not referencing the correct biglake-service-account-id, or missing secretAccessor permissions. Verify region alignment and IAM bindings, then consult the Cross-Cloud Lakehouse troubleshooting documentation.

When should I not use lakehouse catalog federation?▼

Do not use federation for direct remote database SQL execution such as Databricks SQL, or for managing remote infrastructure like Databricks clusters and AWS Glue jobs. It is designed only for querying remote catalog data from GCP engines like BigQuery and Spark.

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