DataMédio

ClickHouse Analytics Patterns

poraffaan-m·affaan-m· v1.0.0 · atualizado em 2026-04-10

Score

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

clickhousedata-analyticsolapquery-optimizationdata-engineeringdatabase

0Stars

0Forks

0Usos

Fork

Documento do Skill

SKILL.mdclickhouse-io/workflow

Assess Requirements: — Determine the specific analytical needs and data characteristics.

Design Table: — Choose the appropriate MergeTree engine and define partitioning and ordering keys.

Optimize Queries: — Implement efficient filtering, aggregations, and window functions.

Insert Data: — Use bulk or streaming inserts for optimal performance.

Monitor Performance: — Track query performance, disk usage, and merge operations.

Refine Strategy: — Adjust partitioning, ordering, and data types based on monitoring results.

Telemetria de Agentes

Execuções

total

Taxa de Sucesso

últimos 30d

Latência Média

0.0s

p50

Alucinação

0.0%

detecção

Tokens Entrada

avg 0/exec

Tokens Saída

avg 0/exec

Uso por Plataforma

Skills Relacionados

Similar aTwelve Data

60%

Similar aTwitter / X Data

60%

Similar atushare

60%

Árvore do Skill

ClickHouse Analytics Patterns

clickhouse-io

Fases Cognitivas5

1.SENSE

2.CONTEXTUALIZE

3.RECOMMEND

4.ACT

5.REFLECT

Triggers5

optimize ClickHouse querydesign ClickHouse tableinsert data into ClickHousemonitor ClickHouse performanceanalyze data with ClickHouse

Avaliar este Skill

Score Breakdown

⭐Avaliação Humana0%

🤖Sucesso de Agentes0%

🕐Atualidade100%

🔗Saúde de Dependências100%

🕸️Centralidade no Grafo0%

🛡️Segurança50%

CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download clickhouse-io

$ synaptic skills detail clickhouse-io

$ synaptic skills live clickhouse-io

Links

GitHub Repository