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📋 Overview

This repository contains a ClickHouse lab for learning and testing purposes.

🚀 Quick Start

Prerequisites

Before getting started, ensure you have installed:

• Docker
• Docker Compose
• Mise

Note

Mise is optional but highly recommended because some helpers commands and environment variables are managed through it for ease of management.

Setup

First, you need to install the required tools via mise:

mise install

Provisioning

Once the prerequisites are installed, you can simply launch the environment provisioning:

mise start

Finally, you can access the ClickHouse via CLI or the embedded SQL console:

• CLI (ClickHouse Client)

  mise client

• Embedded SQL console

  mise sql

Sample dataset examples

In the datasets folder, there are SQL scripts to load various public datasets referenced on the ClickHouse website.

To import a dataset, simply run the mise load-dataset task with the name of the file without the .sql suffix:

mise load-dataset cell-towers
mise load-dataset ontime

Note

The available datasets are hardcoded in the Mise task to simplify the process (pro-tip: use tab completion to choose a dataset).

Integrations

ClickHouse can be integrated with external systems such as object storage, event streaming platforms (e.g Kafka), or databases (e.g PostgreSQL, MySQL or MongoDB).

In this lab, some of these systems can be optionally enabled with --enable-<integration> flags if available:

$ mise start --help     
Start stack

Usage: start [--enable-pg]

Flags:
  --enable-pg  Enable PostgreSQL integration

# Enable PostgreSQL integration
mise start --enable-pg

Versions management

Stack services versions are managed in the mise.toml file in the env section. These variables are loaded directly in shell environment variables by Mise once entering the stack folder.

[env]
CLICKHOUSE_VERSION = "26.9.8.3"
POSTGRESQL_VERSION = "18.6"

Mise tasks available

All common operations are wrapped in Mise tasks to provide a consistent and convenient interface instead of memorizing long docker-compose or clickhouse commands.

Stack management

• start - Start stack
• stop - Stop stack
• clean - Clean all stack resources (services, volumes, networks)
• reset - Reset stack from scratch
• logs - Get logs from a given stack service

Datasets management

• load-dataset - Load sample dataset into ClickHouse

Misc

• client - Connect to ClickHouse using CLI client (alias: cli)
• dashboard - Open embedded ClickHouse dashboard in browser (alias: dash)
• sql - Open embedded ClickHouse SQL console in browser