What common analytical patterns are covered?

The skill includes ready-to-use SQL for common BI tasks such as user retention analysis, conversion funnels, and monthly cohort tracking optimized for column-store execution.

Does this include support for data ingestion?

Yes, it includes specialized patterns for high-performance data loading, including TypeScript examples for bulk inserts and streaming ingestion to prevent the 'many small parts' problem.

How does this skill improve ClickHouse performance?

The skill provides expert guidance on indexing strategies, partition pruning, and proper engine selection (like ReplacingMergeTree or AggregatingMergeTree) to ensure sub-second query performance.

Can I use this for real-time analytics?

Absolutely. It provides implementation patterns for Materialized Views and state-based aggregation functions that enable real-time data processing and instant metric reporting.

ClickHouse Analytics & Data Engineering

Name: ClickHouse Analytics & Data Engineering
Author: LuciferDono

byLuciferDono

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データベース管理

Optimizes ClickHouse schema design, high-performance analytical queries, and data engineering workflows for OLAP workloads.

This skill provides specialized guidance for working with ClickHouse, a high-performance column-oriented OLAP database. It assists developers in implementing optimized data patterns including MergeTree engine selection, materialized views for real-time aggregation, and efficient batch data ingestion strategies. Whether you are migrating analytical workloads from traditional RDBMS or building complex time-series dashboards, this skill ensures best practices for data compression, partition pruning, and advanced analytical functions like funnel and retention analysis.

主な機能

01Real-time data processing strategies using Materialized Views

021 GitHub stars

03Performance-tuned SQL templates for complex aggregations and window functions

04Advanced analytical patterns for funnel, cohort, and retention analysis

05Advanced MergeTree engine selection and configuration patterns

06High-throughput batch and streaming ingestion code snippets

ユースケース

01Designing real-time dashboards for high-cardinality time-series data

02Optimizing slow OLAP queries and improving database storage efficiency

03Migrating large-scale analytical workloads from PostgreSQL or MySQL to ClickHouse

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add luciferdono/labs clickhouse-io

For use in Claude.ai and ChatGPT