name: clickhouse-best-practices description: MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 28 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses. license: Apache-2.0 metadata: author: ClickHouse Inc version: "0.3.0"

ClickHouse Best Practices

Comprehensive guidance for ClickHouse covering schema design, query optimization, and data ingestion. Contains 28 rules across 3 main categories (schema, query, insert), prioritized by impact.

Official docs: ClickHouse Best Practices

IMPORTANT: How to Apply This Skill

Before answering ClickHouse questions, follow this priority order:

1. Check for applicable rules in the rules/ directory
2. If rules exist: Apply them and cite them in your response using "Per rule-name..."
3. If no rule exists: Use the LLM's ClickHouse knowledge or search documentation
4. If uncertain: Use web search for current best practices
5. Always cite your source: rule name, "general ClickHouse guidance", or URL

Why rules take priority: ClickHouse has specific behaviors (columnar storage, sparse indexes, merge tree mechanics) where general database intuition can be misleading. The rules encode validated, ClickHouse-specific guidance.

Langfuse-Specific Rules

• Use packages/shared/src/server/queries/clickhouse-sql/event-query-builder.ts for queries against the events table. Do not hand-roll events SQL unless you first confirm the query builder cannot express the query.
• Never use FINAL on the events table; it is designed so FINAL is not required and the keyword hurts performance.
• ClickHouse query attribution is stored in system.query_log.log_comment as JSON from packages/shared/src/server/clickhouse/queryTags.ts. Parse it with JSONExtractString(log_comment, 'surface'), JSONExtractString(log_comment, 'route'), and JSONExtractString(log_comment, 'projectId'). Known surface values are trpc, publicapi, worker, mcp, and unknown; ClickhouseWriter inserts use projectId = "MULTI_PROJECT".
• Query attribution is propagated through OpenTelemetry baggage. Entry points call contextWithLangfuseProps(...) from packages/shared/src/server/headerPropagation.ts, setting ClickHouse surface, optional route, and optional projectId. The ClickHouse repository layer then reads baggage via normalizeClickHouseQueryTags(...) and writes it to log_comment. Prefer setting attribution at entry points rather than passing tags through every repository call.
• Any migration in packages/shared/clickhouse/migrations/clustered/** with more than one ALTER on the same table must end every metadata ALTER (ADD/DROP/MODIFY COLUMN, ADD/DROP INDEX) with SETTINGS alter_sync = 2, and every mutation-creating ALTER (MATERIALIZE …, UPDATE, DELETE) with SETTINGS mutations_sync = 2. The matching unclustered/ file runs against plain MergeTree and does not need (and should not duplicate) these settings.

Review Procedures

For Schema Reviews (CREATE TABLE, ALTER TABLE)

Read these rule files in order:

1. rules/schema-pk-plan-before-creation.md - ORDER BY is immutable
2. rules/schema-pk-cardinality-order.md - Column ordering in keys
3. rules/schema-pk-prioritize-filters.md - Filter column inclusion
4. rules/schema-types-native-types.md - Proper type selection
5. rules/schema-types-minimize-bitwidth.md - Numeric type sizing
6. rules/schema-types-lowcardinality.md - LowCardinality usage
7. rules/schema-types-avoid-nullable.md - Nullable vs DEFAULT
8. rules/schema-partition-low-cardinality.md - Partition count limits
9. rules/schema-partition-lifecycle.md - Partitioning purpose

Check for:

• PRIMARY KEY / ORDER BY column order (low-to-high cardinality)
• Data types match actual data ranges
• LowCardinality applied to appropriate string columns
• Partition key cardinality bounded (100-1,000 values)
• ReplacingMergeTree has version column if used
• Clustered migration files with multiple ALTERs on the same table use SETTINGS alter_sync = 2 (metadata) and SETTINGS mutations_sync = 2 (MATERIALIZE …, UPDATE, DELETE); unclustered mirror has none

For Query Reviews (SELECT, JOIN, aggregations)

Read these rule files:

1. rules/query-join-choose-algorithm.md - Algorithm selection
2. rules/query-join-filter-before.md - Pre-join filtering
3. rules/query-join-use-any.md - ANY vs regular JOIN
4. rules/query-index-skipping-indices.md - Secondary index usage
5. rules/schema-pk-filter-on-orderby.md - Filter alignment with ORDER BY

Check for:

• Filters use ORDER BY prefix columns
• JOINs filter tables before joining (not after)
• Correct JOIN algorithm for table sizes
• Skipping indices for non-ORDER BY filter columns

For Insert Strategy Reviews (data ingestion, updates, deletes)

Read these rule files:

1. rules/insert-batch-size.md - Batch sizing requirements
2. rules/insert-mutation-avoid-update.md - UPDATE alternatives
3. rules/insert-mutation-avoid-delete.md - DELETE alternatives
4. rules/insert-async-small-batches.md - Async insert usage
5. rules/insert-optimize-avoid-final.md - OPTIMIZE TABLE risks

Check for:

• Batch size 10K-100K rows per INSERT
• No ALTER TABLE UPDATE for frequent changes
• ReplacingMergeTree or CollapsingMergeTree for update patterns
• Async inserts enabled for high-frequency small batches

Output Format

Structure your response as follows:

## Rules Checked

- `rule-name-1` - Compliant / Violation found
- `rule-name-2` - Compliant / Violation found
...

## Findings

### Violations
- **`rule-name`**: Description of the issue
  - Current: [what the code does]
  - Required: [what it should do]
  - Fix: [specific correction]

### Compliant
- `rule-name`: Brief note on why it's correct

## Recommendations

[Prioritized list of changes, citing rules]

Rule Categories by Priority

Quick Reference

Schema Design - Primary Key (CRITICAL)

• schema-pk-plan-before-creation - Plan ORDER BY before table creation (immutable)
• schema-pk-cardinality-order - Order columns low-to-high cardinality
• schema-pk-prioritize-filters - Include frequently filtered columns
• schema-pk-filter-on-orderby - Query filters must use ORDER BY prefix

Schema Design - Data Types (CRITICAL)

• schema-types-native-types - Use native types, not String for everything
• schema-types-minimize-bitwidth - Use smallest numeric type that fits
• schema-types-lowcardinality - LowCardinality for <10K unique strings
• schema-types-enum - Enum for finite value sets with validation
• schema-types-avoid-nullable - Avoid Nullable; use DEFAULT instead

Schema Design - Partitioning (HIGH)

• schema-partition-low-cardinality - Keep partition count 100-1,000
• schema-partition-lifecycle - Use partitioning for data lifecycle, not queries
• schema-partition-query-tradeoffs - Understand partition pruning trade-offs
• schema-partition-start-without - Consider starting without partitioning

Schema Design - JSON (MEDIUM)

• schema-json-when-to-use - JSON for dynamic schemas; typed columns for known

Query Optimization - JOINs (CRITICAL)

• query-join-choose-algorithm - Select algorithm based on table sizes
• query-join-use-any - ANY JOIN when only one match needed
• query-join-filter-before - Filter tables before joining
• query-join-consider-alternatives - Dictionaries/denormalization vs JOIN
• query-join-null-handling - join_use_nulls=0 for default values

Query Optimization - Indices (HIGH)

• query-index-skipping-indices - Skipping indices for non-ORDER BY filters

Query Optimization - Materialized Views (HIGH)

• query-mv-incremental - Incremental MVs for real-time aggregations
• query-mv-refreshable - Refreshable MVs for complex joins

Insert Strategy - Batching (CRITICAL)

• insert-batch-size - Batch 10K-100K rows per INSERT

Insert Strategy - Async (HIGH)

• insert-async-small-batches - Async inserts for high-frequency small batches
• insert-format-native - Native format for best performance

Insert Strategy - Mutations (CRITICAL)

• insert-mutation-avoid-update - ReplacingMergeTree instead of ALTER UPDATE
• insert-mutation-avoid-delete - Lightweight DELETE or DROP PARTITION

Insert Strategy - Optimization (HIGH)

• insert-optimize-avoid-final - Let background merges work

When to Apply

This skill activates when you encounter:

• CREATE TABLE statements
• ALTER TABLE modifications
• ORDER BY or PRIMARY KEY discussions
• Data type selection questions
• Slow query troubleshooting
• JOIN optimization requests
• Data ingestion pipeline design
• Update/delete strategy questions
• ReplacingMergeTree or other specialized engine usage
• Partitioning strategy decisions

Rule File Structure

Each rule file in rules/ contains:

• YAML frontmatter: title, impact level, tags
• Brief explanation: Why this rule matters
• Incorrect example: Anti-pattern with explanation
• Correct example: Best practice with explanation
• Additional context: Trade-offs, when to apply, references