Aitozi commented on PR #7877:
URL: https://github.com/apache/paimon/pull/7877#issuecomment-4469405541
Benchmark command:
```bash
mvn -s ~/.m2/apache-community.xml -pl paimon-format -am -Pfast-build \
-DfailIfNoTests=false -Dtest=MapShreddingStorageBenchmark test
```
Benchmark file: [MapShreddingStorageBenchmark.java]
**Common Setup**
- Schema: `id INT, headers MAP<STRING, STRING>`
- Rows: `100,000`
- Hot keys: `32`
- Value length: `16`
- Compression: `snappy`
- Compared layouts:
- regular: normal Parquet map encoding
- mapShredding: promotes 32 hot keys from `headers` into sidecar columns
- Map shredding options:
- `map.shredding.columns=headers`
- `map.shredding.maxKeys=32`
- `map.shredding.maxInferBufferRow=10000`
- `map.shredding.maxInferBufferMemory=64 mb`
**Results**
| Scenario | Regular | Map Shredding | Saved | Saving |
|---|---:|---:|---:|---:|
| Columnar value storage | 708,012 bytes | 431,637 bytes | 276,375 bytes |
39.04% |
| Long hot key storage | 40,845,943 bytes | 16,365,106 bytes | 24,480,837
bytes | 59.93% |
**Scenario Details**
- **Columnar value storage**: key names are short, values follow a repeated
pattern with `valueRunLength=128` and `valueCardinality=4`, dictionary encoding
enabled. This measures whether promoted hot-key values benefit from columnar
and dictionary encoding.
- **Long hot key storage**: hot key names include `128` bytes of padding,
dictionary encoding disabled. This measures the benefit of avoiding repeated
long map-key strings in every row.
Conclusion: in this synthetic storage benchmark, map shredding reduces file
size in both cases. The biggest gain appears when hot map keys are long and
repeated across many rows, saving about `59.93%`.
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