open-digger-clickhouse-schema

Reference the OpenDigger ClickHouse schema for table purposes, engines, and key columns.

363|99|Updated Aug 18, 2020
One-click install
npx skills add https://github.com/X-lab2017/open-digger --skill open-digger-clickhouse-schema
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: open-digger-clickhouse-schema
Source: https://github.com/X-lab2017/open-digger/tree/main/skills/open-digger-clickhouse-schema
Command: npx skills add https://github.com/X-lab2017/open-digger --skill open-digger-clickhouse-schema

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive reference for the OpenDigger ClickHouse database schema, enabling users to understand and query the database more efficiently.

Core Features & Use Cases

  • Schema Reference: Offers detailed descriptions of all core tables, including their purpose, engine, sort/partition keys, and key columns.
  • Query Optimization: Helps users write correct and performant ClickHouse queries by explaining table relationships and materialized views.
  • Use Case: When writing SQL queries against the OpenDigger backend store, such as querying the events table or global_openrank rankings, this Skill serves as a valuable resource.

Quick Start

Use the open-digger-clickhouse-schema skill to view the schema for the 'events' table.

Frequently Asked Questions about open-digger-clickhouse-schema

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

FAQPage Schema
How do I query the OpenDigger ClickHouse events table?

Query the OpenDigger ClickHouse events table by referencing its schema for table purposes, engines, sort keys, and key columns to construct correct SQL statements. This approach ensures accurate data retrieval from the backend store.

What is the schema structure for OpenRank rankings in ClickHouse?

The schema structure for global_openrank rankings in ClickHouse includes specific table engines, sort keys, and key columns designed for ranking data. Reviewing the schema reference clarifies table relationships and materialized views for these rankings.

How can I optimize SQL queries against the OpenDigger ClickHouse backend store?

Optimize SQL queries against the OpenDigger ClickHouse backend store by understanding table relationships, sort keys, partition keys, and materialized views. The schema reference provides these details to help write performant queries.

Can I use this schema reference to understand ClickHouse materialized views?

Yes, you can use this schema reference to understand ClickHouse materialized views. It explains table relationships and view structures to help you navigate the OpenDigger database schema efficiently for complex queries.

What ClickHouse table engines are used in the OpenDigger database?

The OpenDigger database utilizes specific ClickHouse table engines for core tables like events and global_openrank. The schema reference details these engines alongside sort and partition keys to guide your database interactions.