Apache Parquet Java Performance Improvements

Targeted performance optimizations to parquet-java's encoding, decoding, and compression layers. Each PR addresses an independent codec or subsystem, replacing stream-wrapper abstractions with direct ByteBuffer I/O, eliminating per-value allocations, and adding JMH benchmarks to validate the improvements.

All benchmarks: JDK 25.0.3 (Temurin), JMH 1.37, Linux x86_64, 100K values/iteration.

## Pull requests

| PR | Status | Scope | Headline result |
|----|--------|-------|-----------------|
| #3565 | Merged | PLAIN encoding/decoding | Decode 2.6–13x, encode 2–3.8x |
| #3566 | Open | DICTIONARY encoding/decoding | Encode 1.5–100x (high-card / long binary) |
| #3567 | Open | DELTA_BINARY_PACKED, DELTA_LENGTH_BYTE_ARRAY, DELTA_BYTE_ARRAY | Decode +22–31%, encode +3–7% |
| #3568 | Open | RLE/Bit-Packing hybrid codec | Decode +30%, encode +5% |
| #3569 | Merged | BYTE_STREAM_SPLIT | Decode 1.4–5.1x, encode 1.6–6.9x |
| #3570 | Open | Compression (Snappy, ZSTD, LZ4, GZIP, LZO, Brotli) | Isolated decompress +15–25% (Snappy/Zstd/Gzip), Snappy compress up to ~2.9x; enables LZ4/Brotli/LZO without native libs |
| #3571 | Merged | Row group flush buffer lifecycle | Correct resource management (not a perf win) |

PRs 1–6 and 8 are independent and can be reviewed/merged in parallel. Additional PRs for column I/O (par7) and level write batching (par9) will follow once their dependencies (#3565, #3568) land.

## Common optimization patterns

- **InputStream → ByteBuffer**: Direct `ByteBuffer` (LITTLE_ENDIAN) access for `getInt()`/`getLong()`/`getFloat()`/`getDouble()` JVM intrinsics instead of per-byte stream reads.
- **Buffer reuse**: Allocate once, grow lazily — no fresh allocation per page or per run.
- **pack32/unpack32 fast paths**: Batch 32 values per packer/unpacker call (4x fewer invocations).
- **Eliminate intermediate copies**: Write directly to output buffers, bypass stream wrappers.

## Benchmark highlights

### PLAIN (#3565)

| Benchmark | Master | Optimized | Speedup |
|---|---:|---:|---:|
| decodeInt | 425 M ops/s | 5,427 M ops/s | **12.8x** |
| decodeBoolean | 639 | 1,642 | **2.6x** |
| encodeInt | 148 | 559 | **3.8x** |
| encodeBoolean | 850 | 1,692 | **2.0x** |

### DICTIONARY (#3566)

| Benchmark | Master | Optimized | Speedup |
|---|---:|---:|---:|
| encodeBinary LOW len=1000 | 1.5 M ops/s | 148.3 M ops/s | **~100x** |
| encodeBinary LOW len=100 | 13.2 | 107.8 | **8.2x** |
| encodeFlba HIGH len=12 | 6.3 | 15.4 | **2.4x** |
| encodeInt HIGH_CARD | 14.9 | 23.5 | **1.58x** |

### DELTA (#3567)

| Component | Avg improvement |
|---|---:|
| DELTA_BINARY_PACKED decode | **+27%** |
| DELTA_BYTE_ARRAY decode | **+31%** |
| Long delta decode (TIMESTAMP_MILLIS pattern) | **+28%** |
| Encoding (all delta variants) | **+3–7%** |

### RLE (#3568)

| Category | Avg improvement |
|---|---:|
| Direct decoder (packed data) | **+30%** |
| Boolean decode (packed patterns) | **+14%** |
| Encoder | **+5%** |

### BYTE_STREAM_SPLIT (#3569)

| Benchmark | Master | Optimized | Speedup |
|---|---:|---:|---:|
| decodeInt | 203 M ops/s | 1,034 M ops/s | **5.1x** |
| encodeDouble | 53 | 365 | **6.9x** |
| encodeLong | 52 | 356 | **6.9x** |
| encodeInt | 99 | 515 | **5.2x** |

### Compression (#3570)

Isolated `CompressionBenchmark`, ours/master geomean over 16 realistic encoding shapes (>1 = faster):

| Codec | compress | decompress |
|---|---:|---:|
| Snappy | 1.38x | 1.25x |
| Zstd | 1.00x | 1.18x |
| Gzip | 1.00x | 1.15x |
| LZ4_RAW | 0.96x | 1.06x |

Snappy peaks near 2.9x compress / 1.8x decompress on small, highly compressible pages. Compression is ~1–10% of end-to-end write for the fast codecs (up to ~46% for Gzip), so file-level impact scales with codec weight. Also migrates LZO from GPL to Apache 2.0 (aircompressor) and Brotli from abandoned jbrotli to brotli4j (adds aarch64 support); LZ4/Brotli/LZO now work without native Hadoop codecs.

### Row group flush (#3571)

Correct resource management — releases column buffers during flush rather than after. Peak memory unchanged (peak occurs during page compression, not flush). Makes buffers GC-eligible sooner.

## How to run the benchmarks

```bash
# Build the benchmark jar
./mvnw --projects parquet-benchmarks -amd -DskipTests -Denforcer.skip=true clean package

# Quick single-iteration smoke test
./parquet-benchmarks/run.sh all -wi 0 -i 1 -f 1

# Full statistical run
./parquet-benchmarks/run.sh all -wi 5 -i 5 -f 3 -rff /tmp/benchmark-results.json

# Specific benchmark
./parquet-benchmarks/run.sh all "PlainEncodingBenchmark|PlainDecodingBenchmark"
```

## Test validation

Each PR passes the full module test suite:

```bash
./mvnw --projects parquet-column,parquet-common,parquet-hadoop -amd verify
```

Bắt đầu bằng cách xem xét các PR đang mở #3566, #3567, #3568 và #3570, vì công việc tối ưu hóa đã được chia thành các hệ thống con độc lập. Chạy các lệnh benchmark trong issue cho khu vực codec hoặc nén tương ứng, sau đó xác thực việc hoàn tất bằng bộ kiểm thử của các module parquet-column, parquet-common và parquet-hadoop.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.