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data-analysis

Run read-only SQL recipes against ClickHouse system tables for custom analysis.

255|42|Updated Nov 16, 2023
Search Tags:#sql#data-analysis#performance-tuning#clickhouse#system-tables#query-log#cluster-monitoring
One-click install
npx skills add https://github.com/chmonitor/chmonitor --skill data-analysis-chmonitor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/chmonitor/chmonitor/tree/main/.agents/skills/data-analysis
Command: npx skills add https://github.com/chmonitor/chmonitor --skill data-analysis-chmonitor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill fills gaps in ClickHouse cluster analysis when built-in dedicated tools (like get_slow_queries or get_expensive_queries) do not support the specific aggregations, custom time windows, or metric combinations you need for your use case.

Core Features & Use Cases

  • Custom Query Log Analysis: Run pre-vetted read-only SQL recipes to analyze system.query_log for largest data scans, most expensive queries, query fingerprint patterns, and query volume trends.
  • Table Storage Breakdown: Aggregate system.parts data to rank user tables by disk usage, row count, and compression ratio.
  • Period-over-Period Comparison: Compare query load between two equal-length time windows to spot traffic spikes or performance regressions.
  • Use Case: For example, if you need to identify the top 10 query patterns that consumed the most read bytes over a custom 7-day window, or compare query latency between this week and last week, this skill provides safe, version-aware SQL recipes to get those insights without risking data modification.

Quick Start

Use the data-analysis skill to run a custom read-only SQL query that identifies the top 5 query patterns with the highest average memory usage over a specified time window.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I analyze ClickHouse query logs when built-in tools don't support custom time windows?▼

Analyze ClickHouse query logs by running pre-vetted, read-only SQL recipes against system.query_log to calculate custom aggregations, rank expensive queries, and evaluate historical load trends over specific time windows.

What is the best way to identify the largest data scans in ClickHouse?▼

Identify the largest data scans in ClickHouse by executing custom SQL queries against system.query_log to rank read bytes and group query fingerprints, providing insights built-in dedicated tools cannot aggregate.

How do I check ClickHouse table storage breakdown by disk usage and compression ratio?▼

Check ClickHouse table storage breakdown by aggregating system.parts data with custom SQL, which ranks user tables by disk usage, row count, and compression ratio for detailed storage analysis.

Can I compare ClickHouse query load between two custom time periods?▼

Compare ClickHouse query load between two equal-length time windows using period-over-period SQL recipes to spot traffic spikes or performance regressions without risking data modification.

Does this custom SQL analysis approach modify my ClickHouse database?▼

Custom SQL analysis queries are strictly read-only and target ClickHouse system tables like query_log and parts, ensuring you can safely extract version-aware performance insights without modifying database data.

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