clickhouse-iolisted
Install: claude install-skill cleodin/antigravity-awesome-skills
# ClickHouse Analytics Patterns
ClickHouse-specific patterns for high-performance analytics and data engineering.
## 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_granularity = 8192;
```
### ReplacingMergeTree (Deduplication)
```sql
-- For data that may have duplicates (e.g., from multiple sources)
CREATE TABLE user_events (
event_id String,
user_id String,
event_type String,
timestamp DateTime,
properties String
) ENGINE = ReplacingMergeTree()
PARTITION BY toYYYYMM(timestamp)
ORDER BY (user_id, event_id, timestamp)
PRIMARY KEY (user_id, event_id);
```
### AggregatingMergeTree (Pre-aggregation)
```sql
-- For maintaining aggregated metrics
CREATE TABLE market_stats_hourly (
hour DateTime,
market_id String,
total_volume AggregateFunction(sum, UInt64),
total_trades AggregateFunction(count, UInt32),
uniqu