clickhouse-io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
npx skills add mturac/everything-openai-codex --skill clickhouse-io --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ClickHouse Analytics Patterns ClickHouse-specific patterns for high-performance analytics and data engineering. ## When to Activate - Designing ClickHouse table schemas (MergeTree engine selection) - Writing analytical queries (aggregations, window functions, joins) - Optimizing query performance (partition pruning, projections, materialized views) - Ingesting large volumes of data (batch inserts, Kafka integration) - Migrating from PostgreSQL/MySQL to ClickHouse for analytics - Implementing real-time dashboards or time-series analytics ## Overview ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP). It's optimized for fast analytical queries on large datasets. **Key Features:** - Column-oriented storage - Data compression - Parallel query execution - Distributed queries - Real-time analytics ## Table Design Patterns ### MergeTree Engine (Most Common) ```sql CREATE TABLE markets_analytics ( date Date, market_id String, market_name String, volume UInt64, trades UInt32, unique_traders UInt32, avg_trade_size Float64, created_at DateTime ) ENGINE = MergeTree() PARTITION BY toYYYYMM(date) ORDER BY (date, market_id) SETTINGS index_g
- When to Activate
- Overview
- Table Design Patterns
- MergeTree Engine (Most Common)
- ReplacingMergeTree (Deduplication)
- AggregatingMergeTree (Pre-aggregation)
- Query Optimization Patterns
- Efficient Filtering
- Aggregations
- Window Functions
- Data Insertion Patterns
- Bulk Insert (Recommended)
- Streaming Insert
- Materialized Views
What does the clickhouse-io skill do?
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill clickhouse-io --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.