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ClickHouse Best Practices

ClickHouse Best Practices

v0.4.0
Apache-2.0
Repository Docs
markdown Development
clickhousedatabaseolapanalyticssqlperformance

Summary

ClickHouse's official agent skill: 31 rules for primary keys, data types, JOINs, batching and partitioning that an agent must check and cite before advising on a schema or query.

Features

  • 31 impact-prioritised rules the agent must check before answering
  • Requires the agent to cite the rule it applied
  • Critical rules for primary keys, data types, JOINs, batching and mutations
  • Partitioning, skipping indices, materialized views and async inserts
  • Applies to open-source ClickHouse and ClickHouse Cloud
  • Ships with an architecture advisor and chDB skills in the same repo

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  1. Copy the skill content with the button below.
  2. Paste it into your agent's instruction file or system prompt (for example AGENTS.md, .cursorrules, or a custom instructions field).
  3. Ask the agent to apply the skill whenever the task matches.

Skill Content

Markdown Content

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---
name: clickhouse-best-practices
description: MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 31 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: "0.4.0"
---

# ClickHouse Best Practices

Comprehensive guidance for ClickHouse covering schema design, query optimization, data ingestion, and AI agent connectivity. Contains 31 rules across 4 main categories (schema, query, insert, agent), prioritized by impact.

> **Official docs:** [ClickHouse Best Practices](https://clickhouse.com/docs/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.

---

## Agent Connectivity & Query Workflow

Before querying ClickHouse, agents must establish a connection and follow the discovery workflow:

1. `rules/agent-connect-mcp.md` - Connection setup (MCP + CLI), credential discovery, output format selection
2. `rules/agent-discovery-schema.md` - **CRITICAL**: 7-step schema discovery workflow
3. `rules/agent-query-safety.md` - **CRITICAL**: LIMIT, timeouts, progressive exploration

**Every agent session should follow this sequence:**

1. **Connect** — establish connection via MCP or CLI (see `agent-connect-mcp`)
2. **Discover** — databases → tables → columns + comments → sort keys → skip indexes → sample → EXPLAIN
3. **Plan** — use sort key and skip index knowledge to write efficient WHERE clauses
4. **Execute** — run queries with LIMIT and timeouts
5. **Recover** — on timeout/memory errors, narrow filters and retry (see `agent-query-safety`)

### Subagent architecture notes

If your system dispatches ClickHouse tasks to specialized subagents:
- **Schema discovery + query execution**: any model — the steps are procedural
- **EXPLAIN analysis + query optimization**: benefits from mid-tier reasoning
- **Schema design review against all 28 rules**: benefits from mid-tier reasoning

---

## 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

### 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

| Priority | Category | Impact | Prefix | Rule 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 |
| 12 | Agent Schema Discovery | CRITICAL | `agent-discovery-` | 1 |
| 13 | Agent Query Safety | CRITICAL | `agent-query-` | 1 |
| 14 | Agent Connectivity + Formats | HIGH | `agent-connect-` | 1 |

---

## 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

### Agent Integration - Discovery (CRITICAL)

- `agent-discovery-schema` - Always discover schema before querying

### Agent Integration - Safety (CRITICAL)

- `agent-query-safety` - LIMIT, timeouts, progressive exploration

### Agent Integration - Connectivity + Formats (HIGH)

- `agent-connect-mcp` - MCP + CLI setup, credential discovery, output format selection

---

## When to Apply

This skill activates when you encounter:

- AI agent connecting to ClickHouse (MCP, CLI, HTTP)
- Agent workflow design for ClickHouse
- Schema discovery or exploration requests

- `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

---

## Full Compiled Document

For the complete guide with all rules expanded inline: `AGENTS.md`

Use `AGENTS.md` when you need to check multiple rules quickly without reading individual files.

Usage Instructions

Learn how to use this skill with different AI agents.

Generic Instructions
npx skills add clickhouse/agent-skills
# or, with the ClickHouse CLI
clickhousectl skills

Example Usage

Review this events table DDL and the slow aggregation query against it, citing the ClickHouse rules that apply.

Description

ClickHouse punishes schema mistakes at a scale other databases do not. A poorly ordered primary key or a Nullable(String) where a LowCardinality(String) belonged does not cost you a few milliseconds — it costs you an order of magnitude once the table is large, and it is expensive to undo. This official skill from ClickHouse Inc encodes the fixes as a rule set the agent is required to consult.

The structure is what makes it work. Rather than prose the model can skim, the skill is 31 numbered rules in a rules/ directory, prioritised by impact, and the instructions tell the agent to check applicable rules first, apply them, and cite them by name in its answer ("Per primary-key-ordering…"). If no rule covers the question, it is told to say so and fall back to general knowledge or documentation. That makes recommendations auditable rather than plausible.

Rules are grouped by where the damage happens:

  • Critical — primary key selection (4 rules), data type selection (5), JOIN optimisation (5), insert batching (1) and mutation avoidance (2). These are the ones that decide whether a table performs at all.
  • High — partitioning strategy (4), skipping indices (1), materialized views (2), async inserts (2) and avoiding OPTIMIZE (1).
  • Medium — JSON column usage.

Later versions add rules for agent connectivity, covering how an agent should query a ClickHouse instance in the first place.

The guidance applies equally to open-source ClickHouse and to ClickHouse Cloud. It is one of several official skills in the same repository, alongside an architecture advisor for real-time deployment decisions, clickhousectl skills for cloud deploy and local development, and chDB skills for in-process analytics in Python.

Install: npx skills add clickhouse/agent-skills, or clickhousectl skills if you already have the ClickHouse CLI. Apache-2.0, version 0.4.0, and it follows the open Agent Skills specification at agentskills.io.

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