ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
55
31%
Does it follow best practices?
Impact
100%
1.21xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/clickhouse-io/SKILL.mdTable schema design
MergeTree base engine
100%
100%
ReplacingMergeTree for dedup
100%
100%
Time-based partition key
100%
100%
index_granularity setting
100%
100%
Indexed columns ordered first
100%
100%
LowCardinality for repeated strings
100%
100%
Enum for categorical data
100%
100%
Smallest numeric types
100%
100%
No SELECT * in queries
100%
100%
Avoid FINAL keyword
100%
100%
No excessive JOINs
100%
100%
Query optimization patterns
No SELECT *
100%
100%
Indexed columns filtered first
100%
100%
quantile() for percentiles
100%
100%
toStartOfDay for daily bucketing
100%
100%
Window function for running total
100%
100%
system.query_log usage
100%
100%
query_log type filter
100%
100%
query_log duration field
100%
100%
uniq() for distinct count
100%
100%
Bulk ingestion and materialized views
clickhouse npm package
0%
100%
Batch insert in TypeScript
100%
100%
No per-row insert loop
100%
100%
AggregatingMergeTree for stats table
0%
100%
AggregateFunction column types
0%
100%
Materialized view with State combinators
0%
100%
Merge combinators in query
0%
100%
Time-based partition on events table
100%
100%
toStartOfHour for time bucketing
100%
100%
No SELECT * in queries
100%
100%
79cc4e3
Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.