Which ClickHouse engines are supported?

It provides detailed implementation patterns for the entire MergeTree family, including ReplacingMergeTree, SummingMergeTree, and AggregatingMergeTree.

How does this skill improve ClickHouse query performance?

It enforces optimal ORDER BY sequences and primary key selection to ensure queries scan less than 1% of total data rather than performing full table scans.

Does it prevent the 'Too Many Parts' error?

Yes, it includes specific diagnostics and solutions for over-partitioning, which is the leading cause of part-count exceptions in ClickHouse.

Can it help reduce ClickHouse storage costs?

Yes, by recommending LowCardinality types, optimal numeric sizes, and TTL-based tiered storage, it typically achieves 10x+ compression ratios compared to raw data.

ClickHouse Schema Design Optimizer

Name: ClickHouse Schema Design Optimizer
Author: obsessiondb

byobsessiondb

•

Database Management

Optimizes ClickHouse table structures using performance-driven schema rules for sub-second queries and superior data compression.

This skill provides an automated framework for designing and auditing ClickHouse schemas, ensuring optimal performance for high-volume analytical workloads. It guides developers through critical decisions regarding MergeTree engine selection, primary key ordering, partitioning strategies, and data type optimization. By enforcing best practices like low-cardinality string handling and TTL-based data lifecycles, it helps achieve 10x compression ratios and sub-second query responses on billion-row tables while preventing common anti-patterns like over-partitioning and high-cardinality index prefixes.

Key Features

01MergeTree engine specialized guidance for deduplication and aggregation

02Data type optimization including LowCardinality and smallest-fit numeric types

0312 GitHub stars

04Performance-first ORDER BY and PRIMARY KEY selection logic

05Automated data lifecycle management via TTL and tiered storage config

06Intelligent partitioning strategies to prevent 'Too Many Parts' errors

Use Cases

01Implementing automated data retention and multi-tier storage policies

02Designing high-performance analytical tables for billion-row datasets

03Refactoring legacy ClickHouse schemas to improve query speed and reduce disk usage

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add obsessiondb/clickhouse-skills clickhouse-schema-design

For use in Claude.ai and ChatGPT

Download Skill