---
name: altinity-expert-clickhouse-schema
description: Analyze ClickHouse table structure, partitioning, ORDER BY keys, materialized views, and identify schema design anti-patterns. Use for table design issues and optimization.
---

# Table Schema and Design Analysis

Analyze table structure, partitioning, ORDER BY, materialized views, and identify design anti-patterns.

---

## Diagnostics

Run all queries from the file checks.sql and analyze the results.

---

## Deep Dive Queries (Placeholder-Based)

### Partition Distribution for Specific Table

```sql
select
    database,
    table,
    count() as partitions,
    sum(rows) as total_rows,
    formatReadableSize(sum(bytes_on_disk)) as total_size,
    formatReadableSize(median(bytes_on_disk)) as median_partition_size,
    min(partition) as oldest_partition,
    max(partition) as newest_partition
from system.parts
where active and database = '{database}' and table = '{table}'
group by database, table, partition
order by partition desc
limit 100
```

### Column Compression Analysis for Specific Table

```sql
select
    name,
    type,
    formatReadableSize(data_compressed_bytes) as compressed,
    formatReadableSize(data_uncompressed_bytes) as uncompressed,
    round(data_uncompressed_bytes / nullIf(data_compressed_bytes, 0), 2) as ratio,
    compression_codec
from system.columns
where database = '{database}' and table = '{table}'
order by data_compressed_bytes desc
limit 50
```

**Look for:**
- Columns with ratio < 2 → consider better codec or data transformation
- Large columns without codec → add CODEC(ZSTD) or LZ4HC
- String columns with low cardinality → consider LowCardinality(String)

### Index Usage Analysis for Specific Database

```sql
select
    database,
    table,
    name as index_name,
    type,
    expr,
    granularity
from system.data_skipping_indices
where database = '{database}'
order by database, table
```

---

## Schema Design Recommendations

### Partition Key Guidelines

| Data Volume | Recommended Granularity | Example |
|-------------|------------------------|---------|
| < 10GB/month | No partitioning or yearly | `toYear(ts)` |
| 10-100GB/month | Monthly | `toYYYYMM(ts)` |
| 100GB-1TB/month | Weekly or daily | `toMonday(ts)` |
| > 1TB/month | Daily | `toDate(ts)` |

### ORDER BY Guidelines

1. **First column**: Low cardinality, frequently filtered (e.g., `tenant_id`, `region`)
2. **Second column**: Time-based if range queries common
3. **Subsequent**: Other filter columns by selectivity (most selective last)

**Anti-patterns:**
- UUID/hash as first column
- High-cardinality ID without tenant prefix
- DateTime64 with microseconds as first column

### Compression Codec Recommendations

| Data Type | Recommended Codec |
|-----------|-------------------|
| Integers (sequential) | `Delta, ZSTD` |
| Integers (random) | `ZSTD` or `LZ4HC` |
| Floats | `Gorilla, ZSTD` |
| Timestamps | `DoubleDelta, ZSTD` |
| Strings (long) | `ZSTD(3)` |
| Strings (repetitive) | `LowCardinality` + `ZSTD` |

---

## Cross-Module Triggers

| Finding | Load Module | Reason |
|---------|-------------|--------|
| Many small partitions | `altinity-expert-clickhouse-ingestion` | Check batch sizing |
| Oversized partitions | `altinity-expert-clickhouse-merges` | Merge can't complete |
| High PK memory | `altinity-expert-clickhouse-memory` | Memory pressure |
| MV performance issues | `altinity-expert-clickhouse-reporting` | Query analysis |
| Too many parts per partition | `altinity-expert-clickhouse-merges` | Merge backlog |

---

## Settings Reference

| Setting | Default | Recommendation |
|---------|---------|----------------|
| `index_granularity` | 8192 | Lower for point lookups, higher for scans |
| `ttl_only_drop_parts` | 0 | Set to 1 if TTL deletes entire partitions |
| `min_bytes_for_wide_part` | 10MB | Increase if many small parts |