polaris-catalog

name	polaris-catalog
description	ALWAYS USE when configuring Polaris catalog, managing namespaces, or setting up credentials in floe-platform. Use IMMEDIATELY when integrating DuckDB via dbt-duckdb plugin, configuring PyIceberg REST catalog, or debugging access control issues. Provides research steps for REST API, OAuth2 authentication, and multi-engine coordination with DuckDB, dbt, and Dagster.

Apache Polaris Catalog Management (floe-runtime)

When to Use This Skill

Invoke this skill when working on:

• Polaris catalog configuration in platform.yaml
• Namespace creation and management
• Credential setup (OAuth2, static, IAM role)
• DuckDB ATTACH integration via dbt-duckdb plugin
• PyIceberg catalog operations
• Access control (principals, roles, privileges)
• Helm chart initialization jobs

Core Principles

1. Catalog-as-Control-Plane

NEVER write directly to storage. All table operations MUST flow through Polaris catalog:

Apache Polaris (REST Catalog API)
        ↓
DuckDB (ATTACH) | dbt-duckdb (Plugin) | PyIceberg (Direct)

2. Two-Tier Configuration Architecture

File	Audience	Contains
platform.yaml	Platform Engineers	Polaris endpoints, credentials, storage
floe.yaml	Data Engineers	Logical references (catalog: default)

Data engineers NEVER see credentials.

Pre-Implementation Checklist

Step 1: Discover Existing Patterns (ALWAYS DO FIRST)

# Check floe-polaris client implementation
cat packages/floe-polaris/src/floe_polaris/client.py

# Review platform.yaml examples
cat demo/platform-config/platform/local/platform.yaml | grep -A 20 "catalogs:"

# Check dbt-duckdb plugin ATTACH logic
cat packages/floe-dbt/src/floe_dbt/plugins/polaris.py

# Review Helm initialization
cat demo/platform-config/charts/floe-infrastructure/templates/polaris-init-job.yaml

Step 2: Verify Polaris Runtime State

# Check Polaris availability
curl -s http://localhost:8181/api/catalog/v1/config

# Test OAuth2 authentication
curl -X POST http://localhost:8181/api/catalog/v1/oauth/tokens \
  -d "grant_type=client_credentials" \
  -d "client_id=demo_client" \
  -d "client_secret=demo_secret" \
  -d "scope=PRINCIPAL_ROLE:ALL"

# List catalogs
curl -H "Authorization: Bearer $TOKEN" \
  http://localhost:8181/api/management/v1/catalogs

Step 3: Research When Uncertain (Use WebSearch)

• "Apache Polaris REST catalog API 2025"
• "Apache Polaris namespace hierarchical creation 2025"
• "DuckDB Iceberg REST catalog ATTACH syntax 2025"
• "Apache Polaris OAuth2 client credentials flow 2025"

Official docs: https://polaris.apache.org

Quick Reference: Common Patterns

Pattern 1: Platform Configuration

# platform/local/platform.yaml
catalogs:
  default:
    type: polaris
    uri: "http://floe-infra-polaris:8181/api/catalog"
    warehouse: demo_catalog
    credentials:
      mode: oauth2
      client_id:
        secret_ref: polaris-client-id    # → POLARIS_CLIENT_ID env var
      client_secret:
        secret_ref: polaris-client-secret # → POLARIS_CLIENT_SECRET env var
      scope: "PRINCIPAL_ROLE:service_admin"
    access_delegation: none  # Disable vended credentials for LocalStack
    token_refresh_enabled: true

Pattern 2: floe-polaris Client Usage

from floe_polaris import create_catalog, PolarisCatalogConfig
from pydantic import SecretStr

config = PolarisCatalogConfig(
    uri="http://polaris:8181/api/catalog",
    warehouse="demo_catalog",
    client_id="demo_client",
    client_secret=SecretStr("demo_secret"),
    scope="PRINCIPAL_ROLE:service_admin",
    token_refresh_enabled=True,
)
catalog = create_catalog(config)

# Create namespace with parents
catalog.create_namespace("demo.bronze", create_parents=True)

# Load table
table = catalog.load_table("demo.bronze.raw_events")

Pattern 3: DuckDB ATTACH (dbt-duckdb plugin handles this)

-- Plugin automatically executes on dbt run:
ATTACH 'demo_catalog' AS polaris_catalog (
    TYPE ICEBERG,
    CLIENT_ID 'demo_client',
    CLIENT_SECRET 'demo_secret',
    OAUTH2_SERVER_URI 'http://polaris:8181/api/catalog/v1/oauth/tokens',
    ENDPOINT 'http://polaris:8181/api/catalog'
);

-- Data engineers just write dbt models:
-- models/gold/metrics.sql
{{ config(materialized='table', schema='gold') }}
SELECT customer_id, SUM(amount) as total
FROM {{ ref('silver_orders') }}
GROUP BY 1

Critical Implementation Notes

S3 Storage Config (OpenAPI Spec)

CRITICAL: Use flat keys, NOT nested objects:

# ✅ CORRECT
storage_config = {
    "storageType": "S3",
    "endpoint": "http://localstack:4566",      # Flat key
    "pathStyleAccess": True,                    # CRITICAL for LocalStack/MinIO
    "region": "us-east-1"
}

# ❌ WRONG
storage_config = {
    "s3": {"endpoint": "..."}  # Not accepted by Polaris API
}

Without pathStyleAccess: true:

UnknownHostException: iceberg-data.localstack: Name or service not known

Catalog Storage Config is Immutable

Known limitation: Cannot update storage config after catalog creation.

Workaround: Delete and recreate catalog (Helm init job checks existence first).

Access Control: Three-Tier RBAC

Principal (demo_client)
  ↓
Principal Role (service_admin)
  ↓
Catalog Role (demo_data_admin)
  ↓
Privileges (CATALOG_MANAGE_CONTENT, TABLE_*, NAMESPACE_*)

Common Errors and Solutions

1. Authentication failure (401)

• Verify POLARIS_CLIENT_ID and POLARIS_CLIENT_SECRET env vars
• Check token_refresh_enabled: true
• Test OAuth2 token manually

2. DuckDB ATTACH fails

• Check catalog_uri includes /api/catalog
• Verify environment variables in dbt profiles.yml

3. S3 path resolution fails

• Ensure pathStyleAccess: true in storage config
• Set access_delegation: "" (empty string) for LocalStack

4. Namespace not found

• Use create_parents=True when creating nested namespaces
• Check hierarchical creation order (parent before child)

Detailed Documentation

For comprehensive details, see:

• Integration Patterns: .claude/skills/polaris-skill/docs/integration-patterns.md
• API Reference: .claude/skills/polaris-skill/docs/api-reference.md
• Helm Initialization: demo/platform-config/charts/floe-infrastructure/templates/polaris-init-job.yaml
• floe-polaris Package: packages/floe-polaris/README.md
• Platform Config Guide: docs/platform-config.md
• Apache Polaris Docs: https://polaris.apache.org

Implementation Workflow

1. ✅ Discover existing patterns in packages/floe-polaris
2. ✅ Verify Polaris availability (local or K8s)
3. ✅ Research unfamiliar features (WebSearch)
4. ✅ Use floe-polaris factory functions (create_catalog)
5. ✅ Follow two-tier configuration (credentials in platform.yaml)
6. ✅ Test DuckDB ATTACH (run dbt debug)
7. ✅ Verify table writes via DuckDB native Iceberg
8. ✅ Run integration tests (pytest packages/floe-polaris/tests/integration)

Security Best Practices

• Use SecretStr for all credentials
• Never log secrets or credentials
• Use PRINCIPAL_ROLE:<role_name> (least-privilege scope)
• NEVER use PRINCIPAL_ROLE:ALL in production
• Rotate credentials via K8s secrets
• Enable audit logging in production

---

Remember: This skill provides research guidance. Always discover existing patterns first, verify runtime state, and validate against two-tier architecture.