clickhouse-io
Skill153 starsChanged 8 months agoMITView on GitHub
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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- Rojios/everything-claude-codetheir own version, first seen Nov 8, 2026
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- renepf/claude-skillstheir own version, first seen Oct 25, 2026
- davidanthonyn/claude-skillstheir own version, first seen Oct 20, 2026
- mstuder-slalom/everything-claude-codetheir own version, first seen Oct 20, 2026
- xfstudio/skillstheir own version, first seen Oct 13, 2026
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- loulanyue/awesome-claude-notes★ 272same name
- Fmarzochi/EGC★ 61same name
- FaisalAlqarni/sp-ecc★ 9same name
- xfstudio/skills★ 9same name
- gongyijie85/dsh-ecc★ 8same name
- Lukasbrujula/claude-code-framework★ 4same name
- PatriotAgenticLLC/better_claude_skillz★ 3same name
- ai4brands-design/claude-skills★ 2same name
- ronmkr/PromptBook★ 2same name
- TsinHzl/claude-code-config★ 2same name
16 more not listed
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In this repository15 other files it gives its agents.
- AGENTS.mdAGENTS.md
- rules/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
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The file
Files
ClickHouse Analytics Patterns
ClickHouse is a column-oriented DBMS for OLAP, optimized for fast analytical queries on large datasets. Key strengths: columnar storage, compression, parallel execution, distributed queries, real-time analytics.
Reference Files
| File | Contents |
| references/table-design.md | MergeTree engine types, table creation patterns, partitioning, ordering keys, data type selection |
| references/query-optimization.md | Filtering best practices, aggregations, window functions, materialized views, performance monitoring |
| references/data-pipeline.md | Bulk/streaming insert, ETL/CDC patterns, time series, funnel, cohort, and retention query templates |
Engine Selection Guide
| Engine | Use When | Trade-off |
| MergeTree | Default for most tables | No dedup or pre-aggregation |
| ReplacingMergeTree | Data has duplicates from multiple sources | Dedup only on merge, not query time |
| AggregatingMergeTree | Pre-computed rollups (hourly/daily stats) | Requires *State/*Merge function pairs |
Core Rules
- Batch inserts -- never insert row-by-row
- Specify columns -- avoid
SELECT * - Filter on indexed columns first -- match ORDER BY key order
- Denormalize -- minimize JOINs for analytical tables
- Leverage materialized views -- for real-time aggregations
ClickHouse excels at analytical workloads. Design tables for your query patterns, batch inserts, and leverage materialized views for real-time aggregations.
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