Cicd Trigger

CI/CD Trigger

Trigger GitHub Actions workflows for running ClickHouse regression tests on x86 or ARM architectures.

Working Directory

Run from the repository root:

cd clickhouse-regression

Prerequisites

The user must have a GitHub personal access token. Set it via environment variable or pass explicitly:

export GITHUB_TOKEN="ghp_your_token"

The token requires the following permissions:

Create a token at GitHub Settings > Developer settings > Personal access tokens > Tokens (classic).

Command Format

python3 cicd-trigger.py [options]

Required Options

• --token <token> - GitHub personal access token (or set GITHUB_TOKEN env variable)

Common Options

Available Flags

• none - No special flags
• --use-keeper - Use ClickHouse Keeper
• --with-analyzer - Use new query analyzer
• --use-keeper --with-analyzer - Both Keeper and analyzer
• --as-binary - Run as binary
• --thread-fuzzer - Enable thread fuzzer
• Combinations of the above

Available Test Suites

Full regression: all, all_aws, all_gcs

Core suites: aes_encryption, aggregate_functions, atomic_insert, attach, base_58, data_types, datetime64_extended_range, disk_level_encryption, dns, engines, example, extended_precision_data_types, functions, lightweight_delete, memory, selects, session_timezone, settings, version, window_functions

Alter operations: alter_all, alter_replace_partition, alter_attach_partition, alter_move_partition

Authentication/Security: jwt_authentication, kerberos, ldap, oauth, rbac, ssl_server

ClickHouse Keeper: clickhouse_keeper, clickhouse_keeper_failover

S3/Cloud storage: s3_all, s3_aws, s3_azure, s3_gcs, s3_minio, export_part, export_partition

Tiered storage: tiered_storage_all, tiered_storage_aws, tiered_storage_gcs, tiered_storage_local, tiered_storage_minio, tiered_storage_cas

Parquet: parquet_all, parquet, parquet_minio, parquet_s3, parquet_native_v3, parquet_minio_native_v3, parquet_s3_native_v3

Benchmarks: benchmark_all, benchmark_aws, benchmark_gcs, benchmark_minio

Other: iceberg, kafka, key_value, part_moves_between_shards, swarms, hive_partitioning

Examples

Run the example test suite on x86:

python3 cicd-trigger.py --suite example

Run on ARM architecture:

python3 cicd-trigger.py --suite example --arch arm64

Run with ClickHouse Keeper enabled:

python3 cicd-trigger.py --suite s3_minio --flags "--use-keeper"

Run a specific ClickHouse version:

python3 cicd-trigger.py --suite example \
    --package docker://altinity/clickhouse-server:24.8.6.70.altinitystable \
    --version 24.8.6.70.altinitystable

Run on a feature branch and wait for completion:

python3 cicd-trigger.py --suite example --branch my-feature-branch --wait

Debug mode for troubleshooting:

python3 cicd-trigger.py --suite example --debug

List currently running workflows:

python3 cicd-trigger.py --list-running

Run with custom name:

python3 cicd-trigger.py --suite all --custom-run-name "Nightly regression"

Run specific tests with extra arguments:

python3 cicd-trigger.py --suite rbac --extra-args "--only '/rbac/views/*'"

Use explicit token:

python3 cicd-trigger.py --suite example --token "ghp_your_token"

Output

On success, the script displays:

• Workflow trigger confirmation
• Link to GitHub Actions page
• Link to where logs will be uploaded after completion

Notes

• The workflow runs on GitHub Actions self-hosted runners
• Logs are uploaded to altinity-internal-test-reports S3 bucket
• Use --wait to block until the workflow completes
• Use --list-running to check workflow status before triggering new runs