ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
8.1
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0
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Data & Analytics
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Excellent ClickHouse skill with comprehensive coverage of database patterns, query optimization, and data engineering practices. The description accurately reflects the skill's extensive capabilities including table design patterns (MergeTree variants), query optimization techniques, data insertion strategies, materialized views, and analytics patterns. Task knowledge is strong with detailed SQL examples, TypeScript code snippets for data ingestion, and real-world patterns like ETL and CDC. Structure is clear with logical sections, though the single-file format is appropriate given the cohesive nature of the content. Novelty is good—ClickHouse-specific optimizations (AggregatingMergeTree, quantile functions, partitioning strategies) and complex analytical queries (retention, funnel, cohort analysis) would require significant token investment for a CLI agent to derive independently. Minor improvement areas: could benefit from more advanced distributed table patterns and additional performance tuning edge cases, but overall this is a highly useful, well-documented skill for analytical workloads.
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