JingsongLi opened a new pull request, #20:
URL: https://github.com/apache/paimon-vector-index/pull/20

   ## Summary
   
   Add an IVF_HNSW_SQ core index variant that combines IVF partitioning, 
per-partition HNSW graph search, and 8-bit scalar quantization for compressed 
vector storage.
   
   ## Changes
   
   - Add a reusable 8-bit `ScalarQuantizer` with batch encode/decode and 
zero-allocation distance calculation for L2, inner product, and cosine.
   - Add in-memory `IVFHNSWSQIndex` with train/add/build_graphs/search APIs, 
filter support, and SQ scan fallback when graphs are absent or filters are 
selective.
   - Add an `IVFHNSWSQIndexReader` file format and reader with single-query, 
batch-query, and Roaring filter search helpers.
   - Reuse IVF_HNSW_FLAT graph serialization and checked IO helpers for 
consistent HNSW graph validation.
   - Extend the recall benchmark to include IVF-HNSW-SQ alongside IVF-PQ, 
IVF-FLAT, and IVF-HNSW-FLAT.
   
   ## Testing
   
   - `cargo fmt --check`
   - `cargo test -p paimon-vindex-core`
   - `cargo clippy -p paimon-vindex-core --all-targets -- -D warnings`
   - `cargo check -p paimon-vindex-jni`
   - `cargo bench -p paimon-vindex-core --bench recall_bench --no-run`
   - `cargo test --manifest-path python/Cargo.toml --features auto-initialize 
--no-default-features`
   - `javac -d /tmp/paimon-vindex-java-test $(find jni/java jni/java-test -name 
'*.java')`
   
   ## Notes
   
   This PR intentionally keeps JNI/Python public APIs unchanged and adds the 
new index at the core layer first. The SQ implementation stores one byte per 
dimension and reconstructs approximate vectors for HNSW graph storage/search.
   


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