Agent skill · data analytics · davila7
clickhouse-io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Why this skill is useful
Provides specific ClickHouse query optimization patterns and data engineering best practices that enhance analytical performance.
What it needs
About 5k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
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) ReplacingMergeTree (Deduplication) AggregatingMergeTree (Pre-aggregation) Query Optimization Patterns Efficient Filtering Aggregations Window Functions Data Insertion Patterns Bulk Insert (Recommended) Streaming Insert Materialized Views Real-time Aggregations Performance Monitoring Query Performance Table Statistics Common Analytics Queries Time Series Analysis Funnel Analysis Cohort Analysis Data Pipeline Patterns ETL Pattern Change Data Capture (CDC) Best Practices 1. Partitioning Strategy Partition by time (usually month or day) Avoid too many partitions (performance impact) Use DATE type for partition key 2. Ordering Key Put most frequently filtered columns first Consider cardinality (high cardinality first) Order impacts compression 3. Data Types Use smallest appropriate type (UInt32 vs UInt64) Use LowCardinality for repeated strings Use Enum for categorical data 4. Avoid SELECT (specify columns) FINAL (merge data before query instead) Too many JOINs (denormalize for analytics) Small frequent inserts (batch instead) 5. Monitoring Track query performance Monitor disk usage Check merge operations Review slow query log Remember: ClickHouse excels at analytical workloads. Design tables for your query patterns, batch inserts, and leverage materialized views for real-time aggregations.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/cc-skill-clickhouse-io