🔵 ByteHouse brand identity
"ByteHouse" — Volcengine cloud-native data warehouse, blazing fast, stable, secure, and easy to use
This Skill is based on ByteHouse MCP Server and provides complete cluster diagnostic and health check capabilities
Description
ByteHouse cluster diagnostic and health check tool.
Use this Skill in the following situations: (1) Need to check ByteHouse cluster health status (2) Need to diagnose cluster problems and anomalies (3) Need to view cluster node status (4) Need to analyze cluster performance metrics (5) User mentions "cluster diagnostic", "health check", "node status", "cluster problem"
Prerequisites
- Python 3.8+
- uv (already installed in
/root/.local/bin/uv) - ByteHouse MCP Server Skill - this skill depends on the ByteHouse access capability provided by the
bytehouse-mcpskill
Dependencies
This skill depends on the bytehouse-mcp skill and uses the MCP Server it provides to access ByteHouse.
Ensure that the bytehouse-mcp skill is correctly configured and can be used normally.
📁 File description
- SKILL.md - This file, the main skill document
- cluster_diagnostics.py - Cluster diagnostic main program
- README.md - Quick start guide
Configuration information
ByteHouse connection configuration
This skill reuses the configuration of the bytehouse-mcp skill. Please ensure that the following has been configured in the bytehouse-mcp skill:
export BYTEHOUSE_HOST="<ByteHouse-host>"
export BYTEHOUSE_PORT="<ByteHouse-port>"
export BYTEHOUSE_USER="<ByteHouse-user>"
export BYTEHOUSE_PASSWORD="<ByteHouse-password>"
export BYTEHOUSE_SECURE="true"
export BYTEHOUSE_VERIFY="true"
🎯 Features
1. Cluster health check
- Check cluster node status
- Check replica synchronization status
- Check data partition status
- Check system table integrity
2. Node status diagnosis
- Get cluster node list
- Check node liveness status
- View node resource usage
- Analyze node performance metrics
3. Query history analysis
- Query execution history statistics
- Slow query identification
- Query error analysis
- Query performance trends
4. System table check
- Check system.parts table
- Check system.replicas table
- Check system.clusters table
- Check system.mutations table
🚀 Quick start
Method 1: Run cluster health check
cd /root/.openclaw/workspace/skills/bytehouse-diagnostics
# 先设置环境变量(复用bytehouse-mcp的配置)
export BYTEHOUSE_HOST="<ByteHouse-host>"
export BYTEHOUSE_PORT="<ByteHouse-port>"
export BYTEHOUSE_USER="<ByteHouse-user>"
export BYTEHOUSE_PASSWORD="<ByteHouse-password>"
export BYTEHOUSE_SECURE="true"
export BYTEHOUSE_VERIFY="true"
# 运行集群诊断
uv run cluster_diagnostics.py
Diagnostic content includes:
- Cluster health status
- Node status check
- Replica synchronization status
- Data partition check
- Query history analysis
- System table integrity check
Output files (saved in the output/ directory):
health_check_{timestamp}.json- Health check reportnode_status_{timestamp}.json- Node status reportquery_stats_{timestamp}.json- Query statistics report
💻 Diagnostic check items
Health check items
| Check item | Description | Status |
|---|---|---|
| Cluster connection | Test ByteHouse connectivity | ✅/❌ |
| System Table Access | Check whether system.* tables are accessible | ✅/❌ |
| Replica Status | Check data replica synchronization status | ✅/⚠️/❌ |
| Partition Status | Check data partition integrity | ✅/⚠️/❌ |
| Node Liveness | Check cluster node liveness status | ✅/❌ |
| Mutation Status | Check mutation execution status | ✅/⚠️/❌ |
Diagnostic Metrics
- Cluster Level: Total nodes, active nodes, replica count, partition count
- Node Level: CPU usage, memory usage, disk usage, query count
- Query Level: Total queries, slow queries, error queries, average query time
📊 Diagnostic Report Example
Health Check Report
{
"cluster_name": "bh_log_boe",
"check_time": "2026-03-12T21:00:00",
"overall_status": "healthy",
"checks": [
{
"name": "cluster_connection",
"status": "pass",
"message": "成功连接到ByteHouse"
}
]
}
📚 More Information
For detailed usage instructions, please refer to bytehouse-mcp skill
Last updated: 2026-03-12