Workflow [PR], commit [f920a81]

QA Verification

This PR was verified manually using a real Iceberg setup backed by Google Cloud Storage (GCS) and a local Nessie REST catalog.

The verification followed the reproduction steps documented in issue #1199.

Test environment

• ClickHouse binary (not Docker)
• Nessie REST catalog running locally
• Iceberg tables stored on GCS
• Tested with:
  • Private GCS bucket (with credentials)
  • Public GCS bucket (no credentials)

Validation steps

Before running the ClickHouse queries:

• GCS access was configured locally using a GCP Service Account (GOOGLE_APPLICATION_CREDENTIALS pointing to the QA service account JSON)
• The Nessie REST catalog was started via Docker and exposed at http://localhost:19120/iceberg, with the warehouse explicitly configured as:

gs://altinity-qa-test/carlos_test/

This ensures the gs:// storage path is exercised.

• The Iceberg table was populated by running the write_to_iceberg.py script provided in the issue, which creates the namespace and table via Nessie and writes both metadata and data files to GCS

ClickHouse validation

CREATE DATABASE demo_local
ENGINE = DataLakeCatalog('http://localhost:19120/iceberg')
SETTINGS
  catalog_type = 'rest',
  storage_endpoint = 'https://storage.googleapis.com',
  warehouse = 'warehouse';

USE demo_local;

SHOW TABLES;

Result:

┌─name───────────────────────┐
│ local_dataset.taxi_dataset │
└────────────────────────────┘

SELECT count() FROM `local_dataset.taxi_dataset`;

Result:

┌─count()─┐
│ 3475226 │
└─────────┘

Result

• Iceberg tables created via Nessie are correctly discovered by ClickHouse
• Metadata and data stored on GCS are read successfully
• The gs:// warehouse path is handled correctly
• Data is accessible and queryable
• Verified with both private and public GCS buckets

✅ Confirmed working when using Iceberg tables stored on GCS and accessed via the Nessie REST catalog.