clickhouse-io - ClickHouse Analytics & Data Engineering Patterns
ClickHouse database patterns, query optimization, and analytics best practices for high-performance analytical workloads
Tags
Updated: 2026-06-30Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Create tables with MergeTree engine
- Deduplicate data with ReplacingMergeTree
- Pre-aggregate with AggregatingMergeTree
- Optimize query filters
- Aggregate data with functions
- Calculate window functions
- Bulk insert data batches
- Stream data continuously
- Create materialized views
- Monitor query performance
- Check table statistics
- Analyze time series data
- Track user retention
- Analyze conversion funnels
- Perform cohort analysis
- Execute ETL pipelines
- Capture data changes
- Configure partition strategies
- Order optimization keys
- Check query performance logs
Inputs
- ClickHouse connection URL
- Database credentials
- Table schema definitions
- Data sources
- Query requirements
- Target tables
- Source database
- Event data
- Trade data
- Market data
- User activity data
Outputs
- Query result sets
- Inserted records
- Table structures
- Query performance reports
- Aggregated metrics
- Materialized view data
- Time series analysis results
- Retention analysis results
- Funnel analysis results
- Cohort analysis results
- Database statistics
- Optimized query plans