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altinity-expert-clickhouse-storage

Diagnose ClickHouse storage usage, compression efficiency, and part sizes via checks.sql queries.

16|2|Updated Jan 8, 2026
Search Tags:#diagnostics#compression#storage#clickhouse#disk-usage#part-size
One-click install
npx skills add https://github.com/Altinity/Skills --skill altinity-expert-clickhouse-storage-altinity
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: altinity-expert-clickhouse-storage
Source: https://github.com/Altinity/Skills/tree/main/altinity-expert-clickhouse/skills/altinity-expert-clickhouse-storage
Command: npx skills add https://github.com/Altinity/Skills --skill altinity-expert-clickhouse-storage-altinity

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Diagnose ClickHouse storage usage, compression efficiency, and part sizes to identify bottlenecks that affect IO and query performance.

Core Features & Use Cases

  • Disk usage and path analysis across hosts and disks
  • Compression quality assessment across tables and columns
  • Part size distribution, detection of tiny parts, and wide vs compact parts
  • Guidance for storage policies and data layout to optimize space and IO

Quick Start

Run the storage diagnostics by executing checks.sql against your ClickHouse cluster to surface bottlenecks and compression insights.

Frequently Asked Questions about altinity-expert-clickhouse-storage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I diagnose ClickHouse disk usage and identify bottlenecks across a multi-node cluster?▼

Diagnose ClickHouse disk usage by running checks.sql queries against system tables like system.disks and system.parts to surface disk space pressure, IO bottlenecks, and aggregated storage metrics.

What is the best way to check ClickHouse compression efficiency across tables and columns?▼

Check ClickHouse compression efficiency by querying system.columns and system.parts to return aggregated metrics that assess compression quality and identify tables needing storage optimization.

How do I detect tiny parts and fragmentation in ClickHouse storage?▼

Detect ClickHouse tiny parts and fragmentation by inspecting system.parts to analyze part size distribution, identifying wide versus compact parts that cause high IO and degraded query performance.

Does this ClickHouse storage diagnostics approach work for multi-node deployments experiencing disk space pressure?▼

Yes, this approach applies to ClickHouse multi-node deployments experiencing disk space pressure, high IO, or fragmentation, aggregating storage metrics across hosts and disks to identify bottlenecks.

How do I inspect ClickHouse storage policies to optimize data layout and space utilization?▼

Inspect ClickHouse storage policies by querying system.storage_policies to return guidance on data layout optimization, helping reduce space consumption and improve IO efficiency across disks.

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