Local ClickHouse

Install, configure, and validate local ClickHouse as an alternative to ClickHouse Cloud for development and backtesting (ADR-0044, ADR-0045).

Purpose

Enable local ClickHouse deployment for:

1. Backtesting: 50-100x faster queries (no network round-trip)
2. Development: Offline work without Cloud credentials
3. Evaluation: Try package before Cloud commitment
4. Cost savings: Avoid Cloud costs during experimentation

When to Use

Use this skill when:

• Local development: Setting up development environment without Cloud
• Backtesting optimization: Need faster query performance
• Offline mode: Working without network access
• Package evaluation: Trying gapless-crypto-clickhouse before Cloud setup

Triggers: User mentions "local ClickHouse", "install clickhouse", "backtesting setup", "offline mode", "GCCH_MODE=local"

Prerequisites

System Requirements:

• macOS (Homebrew) or Linux (apt/installer)
• 2-4GB RAM minimum
• 10GB+ disk space for data

Network: Internet required for installation only (offline after setup)

Workflow

Step 1: Install ClickHouse

macOS (Homebrew):

# Install ClickHouse
brew install clickhouse

# Verify installation
clickhouse --version

Linux (Ubuntu/Debian):

# Quick installer (recommended)
curl https://clickhouse.com/ | sh
./clickhouse --version

# Or via apt
sudo apt-get install -y apt-transport-https ca-certificates
curl -fsSL https://packages.clickhouse.com/deb/lts/clickhouse.gpg | sudo gpg --dearmor -o /usr/share/keyrings/clickhouse-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/clickhouse-keyring.gpg] https://packages.clickhouse.com/deb stable main" | sudo tee /etc/apt/sources.list.d/clickhouse.list
sudo apt-get update
sudo apt-get install -y clickhouse-server clickhouse-client

Step 2: Start ClickHouse Server

macOS (Homebrew):

# Start server in background
clickhouse server --daemon

# Verify server is running
clickhouse client --query "SELECT 1"

Linux (systemd):

# Start and enable service
sudo service clickhouse-server start
sudo systemctl enable clickhouse-server

# Verify server is running
clickhouse-client --query "SELECT 1"

Step 3: Configure Environment

Set Local Mode:

# Explicit local mode (recommended)
export GCCH_MODE=local

# Or rely on auto-detection (localhost triggers local mode)
export CLICKHOUSE_HOST=localhost

Environment Variables:

# Full local configuration
export GCCH_MODE=local
export CLICKHOUSE_HOST=localhost
export CLICKHOUSE_HTTP_PORT=8123
export CLICKHOUSE_DATABASE=default
export CLICKHOUSE_USER=default
export CLICKHOUSE_PASSWORD=

Step 4: Verify Connection

Using Python:

from gapless_crypto_clickhouse import probe

# Check local ClickHouse status
status = probe.check_local_clickhouse()
print(f"Installed: {status['installed']}")
print(f"Running: {status['running']}")
print(f"Version: {status['version']}")

# Get current mode
mode = probe.get_current_mode()
print(f"Mode: {mode}")  # Should be "local"

Using CLI:

# Quick connection test
GCCH_MODE=local python -c "
from gapless_crypto_clickhouse.clickhouse.config import ClickHouseConfig
config = ClickHouseConfig.from_env()
print(f'Host: {config.host}')
print(f'Port: {config.http_port}')
print(f'Secure: {config.secure}')
"

Step 5: Test with Real Data

Query with Auto-Ingestion:

import os
os.environ["GCCH_MODE"] = "local"

from gapless_crypto_clickhouse import query_ohlcv

# First query downloads and ingests data automatically
df = query_ohlcv(
    "BTCUSDT",
    "1h",
    "2024-01-01",
    "2024-01-07"
)
print(f"Rows: {len(df)}")
print(df.head())

Mode Detection Logic

The package auto-detects deployment mode based on environment:

GCCH_MODE=local       → Local mode (explicit)
GCCH_MODE=cloud       → Cloud mode (requires CLICKHOUSE_HOST)
GCCH_MODE=auto        → Auto-detect:
  CLICKHOUSE_HOST=""           → Local mode
  CLICKHOUSE_HOST="localhost"  → Local mode
  CLICKHOUSE_HOST="127.0.0.1"  → Local mode
  CLICKHOUSE_HOST="*.cloud"    → Cloud mode

Introspection:

from gapless_crypto_clickhouse import probe

# Get available modes
modes = probe.get_deployment_modes()
print(modes["available_modes"])  # ["local", "cloud"]

# Get current mode
current = probe.get_current_mode()  # "local" or "cloud"

# Get installation guide
guide = probe.get_local_installation_guide()
print(guide["macos"]["commands"])

Success Criteria

• ClickHouse server running on localhost:8123

• probe.check_local_clickhouse()

  returns

  {"installed": True, "running": True}

• probe.get_current_mode()

  returns

  "local"

• query_ohlcv()

  executes without Cloud credentials

Troubleshooting

Issue: "Connection refused" on port 8123

• Check: Is ClickHouse server running?

  # macOS
  ps aux | grep clickhouse
  
  # Linux
  sudo service clickhouse-server status
  

• Action: Start server with

  clickhouse server --daemon

Issue: "Command not found: clickhouse"

• Check: Was ClickHouse installed correctly?
• macOS: Run

  brew install clickhouse

• Linux: Run

  curl https://clickhouse.com/ | sh

Issue: Mode detected as "cloud" instead of "local"

• Check: Is

  CLICKHOUSE_HOST

  set to a remote hostname?
• Action: Set

  export GCCH_MODE=local

  explicitly

Issue: Server crashes with memory error

• Check: System has 2-4GB RAM available
• Action: Increase available memory or reduce concurrent queries

Issue: Permission denied errors

• Check: ClickHouse data directory permissions
• Action: Ensure user has write access to

  /var/lib/clickhouse

  (Linux)

Port Reference

Performance Comparison

Server Management

Start Server:

# macOS
clickhouse server --daemon

# Linux
sudo service clickhouse-server start

Stop Server:

# macOS
pkill -f clickhouse-server

# Linux
sudo service clickhouse-server stop

Check Logs:

# macOS (Homebrew)
tail -f /opt/homebrew/var/log/clickhouse-server/clickhouse-server.log

# Linux
sudo tail -f /var/log/clickhouse-server/clickhouse-server.log

E2E Validation Workflow (ADR-0045)

This skill includes executable scripts for end-to-end validation of local ClickHouse.

Scripts Directory

scripts/start-clickhouse.sh

scripts/deploy-schema.sh

scripts/ingest-sample-data.py

query_ohlcv()

scripts/take-screenshot.py

scripts/validate-data.py

Running E2E Validation

Full workflow (manual):

# 1. Start ClickHouse
./skills/local-clickhouse/scripts/start-clickhouse.sh

# 2. Deploy schema
./skills/local-clickhouse/scripts/deploy-schema.sh

# 3. Ingest sample data
uv run python skills/local-clickhouse/scripts/ingest-sample-data.py

# 4. Capture screenshot
uv run python skills/local-clickhouse/scripts/take-screenshot.py

# 5. Validate data
uv run python skills/local-clickhouse/scripts/validate-data.py

Via pytest (automated):

# Run E2E tests (requires mise ClickHouse installed)
uv run pytest tests/test_local_clickhouse_e2e.py -v

# Tests will FAIL (not skip) if ClickHouse not available

Evidence Output

Scripts output evidence to

tests/screenshots/

• play-ui-{timestamp}.png

  - Playwright screenshots

• validation-{timestamp}.json

  - Structured validation results

References

• ADR-0044: Local ClickHouse Option
• ADR-0045: Local ClickHouse E2E Validation
• Plan 0044: Implementation Plan
• Plan 0045: E2E Validation Plan
• llms.txt: AI agent documentation with deployment modes
• probe.py:

  get_deployment_modes()

  ,

  check_local_clickhouse()

Next Steps

After successful local setup:

1. Schema Creation: Tables created automatically on first query
2. Data Ingestion: Use

   query_ohlcv()

   with

   auto_ingest=True

3. E2E Validation: Run

   uv run pytest tests/test_local_clickhouse_e2e.py -v

4. Backtesting: Run analysis with 50-100x faster queries
5. Production Migration: Switch to Cloud mode with

   export GCCH_MODE=cloud