ClickHouse Best Practices

Guidance for ClickHouse covering schema design, query optimization, and data ingestion. Contains 28 atomic rules across 3 categories (schema, query, insert), prioritized by impact. Extended with 14 reference files covering cluster management, backups, monitoring, and integrations.

Official docs: ClickHouse Best Practices

Official docs: ClickHouse Best Practices

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⚠️ Security Considerations

Credential Placeholders

Example credentials in documentation (password123, AKIAIOSFODNN7EXAMPLE) are placeholders only. Never use these in production. Use proper secret management:

• Environment variables
• Secret managers (AWS Secrets Manager, HashiCorp Vault, etc.)
• Kubernetes secrets (for K8s deployments)
• ClickHouse named collections with external configuration

Installation & Operations

For installation and operational procedures:

• Follow official documentation links provided in reference files
• Prefer package managers (apt, yum, helm) over direct downloads
• Use versioned artifacts instead of latest in production
• Test procedures in non-production environments first

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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: Check references/ for deeper topic coverage
4. If neither covers it: Use general ClickHouse knowledge or search documentation
5. Always cite your source: rule name, reference file, 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.

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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-pk-filter-on-orderby.md — Query filter alignment
5. rules/schema-types-native-types.md — Proper type selection
6. rules/schema-types-minimize-bitwidth.md — Numeric type sizing
7. rules/schema-types-lowcardinality.md — LowCardinality usage
8. rules/schema-types-avoid-nullable.md — Nullable vs DEFAULT
9. rules/schema-types-enum.md — Enum for finite value sets
10. rules/schema-partition-low-cardinality.md — Partition count limits
11. rules/schema-partition-lifecycle.md — Partitioning purpose
12. rules/schema-partition-query-tradeoffs.md — Partition pruning trade-offs
13. rules/schema-partition-start-without.md — Start without partitioning
14. rules/schema-json-when-to-use.md — JSON type usage

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

For Query Reviews (SELECT, JOIN, aggregations)

Read these rule files:

1. rules/query-join-choose-algorithm.md — Algorithm selection
2. rules/query-join-use-any.md — ANY vs regular JOIN
3. rules/query-join-filter-before.md — Pre-join filtering
4. rules/query-join-consider-alternatives.md — Dictionaries/denormalization
5. rules/query-join-null-handling.md — join_use_nulls setting
6. rules/query-index-skipping-indices.md — Secondary index usage
7. rules/query-mv-incremental.md — Incremental materialized views
8. rules/query-mv-refreshable.md — Refreshable materialized views

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-async-small-batches.md — Async insert usage
3. rules/insert-format-native.md — Native format for performance
4. rules/insert-mutation-avoid-update.md — UPDATE alternatives
5. rules/insert-mutation-avoid-delete.md — DELETE alternatives
6. 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

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Output Format

Structure review responses 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]

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Rule Categories by Priority

Priority	Category	Impact	Prefix	Count
1	Primary Key Selection	CRITICAL	schema-pk-	4
2	Data Type Selection	CRITICAL	schema-types-	5
3	JOIN Optimization	CRITICAL	query-join-	5
4	Insert Batching	CRITICAL	insert-batch-	1
5	Mutation Avoidance	CRITICAL	insert-mutation-	2
6	Partitioning Strategy	HIGH	schema-partition-	4
7	Skipping Indices	HIGH	query-index-	1
8	Materialized Views	HIGH	query-mv-	2
9	Async Inserts	HIGH	insert-async-	2
10	OPTIMIZE Avoidance	HIGH	insert-optimize-	1
11	JSON Usage	MEDIUM	schema-json-	1

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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

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Quick Decision Guides

Which Table Engine?

Need to store data?
├── < 1M rows, dimension → Memory
└── ≥ 1M rows → MergeTree family
    ├── Deduplication? → ReplacingMergeTree(version)
    ├── Changelog? → CollapsingMergeTree(sign)
    ├── Pre-aggregation? → AggregatingMergeTree()
    ├── Replication? → ReplicatedMergeTree(...)
    └── Default → MergeTree()

See references/table-engines.md for complete reference.

Common Issues & Quick Fixes

Issue	Quick Fix
Too many parts	OPTIMIZE TABLE table FINAL (see insert-optimize-avoid-final)
Slow query	EXPLAIN SELECT ... to check index usage
Mutation stuck	Check system.mutations, consider alternatives per insert-mutation-avoid-update
Replication lag	Check system.replication_queue, ZooKeeper
OOM on query	Increase max_memory_usage, optimize query

See references/debugging.md for detailed troubleshooting.

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Deep Reference Files

For topics beyond the 28 rules, see the references/ directory:

Schema & Table Design

• references/core-concepts.md — Architecture, data model, internals
• references/schema-design.md — Database engines, migrations, version control
• references/table-design.md — ORDER BY, partitioning, column selection
• references/table-engines.md — Complete MergeTree family reference

Query & Performance

• references/sql-reference.md — Complete SQL dialect, data types
• references/query-optimization.md — EXPLAIN, JOINs, projections, skip indexes
• references/advanced-features.md — Materialized views, mutations, TTL, dictionaries

Operations & Cluster

• references/debugging.md — Query debugging, merges, mutations, replication
• references/cluster-management.md — Distributed tables, replication, sharding
• references/backup-restore.md — Backup strategies, disaster recovery
• references/monitoring.md — Query monitoring, health checks, system queries

Integration & Best Practices

• references/integrations.md — Kafka, S3, PostgreSQL, MySQL, BI tools
• references/best-practices.md — Complete checklist and anti-patterns
• references/external.md — Altinity KB links, official docs
• references/system-queries.md — Ready-to-use queries for operations

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Version: 1.3.0 Rules: Synced with ClickHouse/agent-skills (Apache-2.0) References: Altinity Knowledge Base (200+ articles) + ClickHouse Official Docs