Dan RammerandClaude Opus 5
fe34eb3549
## What Renames the MemWAL surface in two passes, across Rust, Python, TypeScript, and Java, including the wire format. ### 1. MemWAL APIs drop "LSM" The write path these APIs drive is Lance's MemWAL; "LSM" described its shape rather than naming it. Turning it on and off now reads as enabling a feature rather than installing a spec. | Before | After | |---|---| | `set_lsm_write_spec` | `enable_memwal` | | `unset_lsm_write_spec` | `disable_memwal` | | `get_lsm_write_spec` | `get_memwal_spec` | | `flush_lsm` / `compact_lsm` / `checkpoint_lsm` | `flush_memwal` / `compact_memwal` / `checkpoint_memwal` | | `get_lsm_stats` | `get_memwal_stats` | | `close_lsm_writers` | `close_memwal_writers` | | `use_lsm` (query, merge insert) | `use_memwal` | | `LsmWriteSpec` / `LsmStats` | `MemWalWriteSpec` / `MemWalStats` | | Java `LanceDbTableLsm` | `LanceDbTableMemWal` | TypeScript and Java use camelCase (`enableMemWal`, `getMemWalStats`, ...); the napi methods set `js_name` so the generated names keep the `MemWal` casing. flush/compact/checkpoint keep a `_memwal` suffix so `compact_memwal` is not confused with `compact_files` / `optimize`, which compact the base table. Internal names (`LsmMode`, `LsmScanner`, the `merge::lsm` / `query::lsm` modules) are unchanged. ### 2. Stats use SSTable and table shard Aligns the stats surface with the MemWAL naming settled upstream in lance-format/lance#7943 and #7957, where the persisted unit became an **SSTable**. **Generation → SSTable.** A `GenerationStats` describes one flushed MemTable, which is an SSTable. The generation *number* is kept — an SSTable is identified by its generation — so only the noun moved. **Bucket → table shard.** Each entry is one MemWAL shard. "Bucket" names only the hash sharding *transform*, so it was already wrong for `identity` and `year` sharding, which produce shards and no buckets at all. | Before | After | |---|---| | `GenerationStats` | `SsTableStats` | | `BucketStats` | `TableShardStats` | | `stats.buckets` | `stats.table_shards` | | `BucketStats.generations` | `TableShardStats.sstables` | | `include_generation_rows` | `include_sstable_rows` | | `newest_generation` | `newest_sstable_generation` | | `outstanding_generations` | `outstanding_sstables` | Docs and comments follow suit: "seal" → "freeze", "L0" / "flushed generations" → SSTables, "bucket" (meaning a shard) → table shard. `MemWalWriteSpec::bucket`, `num_buckets`, and the `"Sealed"` shard status value are **unchanged** — those name the sharding transform or a server value, not the shard. ## Compatibility Breaking, for an experimental API. The wire format changes with the SDKs, so this must roll out together with the matching server change: - Routes: `/set_lsm_write_spec/` → `/enable_memwal/`, `/unset_lsm_write_spec/` → `/disable_memwal/`, `/get_lsm_write_spec/` → `/get_memwal_spec/`, `/flush_lsm/` → `/flush_memwal/`, `/compact_lsm/` → `/compact_memwal/`, `/get_lsm_stats/` → `/get_memwal_stats/` - Response keys: `lsm_write_spec` → `memwal_spec`, `lsm_stats` → `memwal_stats`, `buckets` → `table_shards`, `generations` → `sstables` - Request fields: `include_generation_rows` → `include_sstable_rows`; `use_lsm` → `use_memwal` on query and merge-insert bodies ## Validation - Rust: `cargo test --features remote -p lancedb --lib --tests` — 1467 lib tests and all integration test targets pass; `cargo clippy` clean - Python: rebuilt the extension; `test_remote_db`, `test_memwal_spec`, `test_merge_insert_lsm`, `test_query`, `test_permutation`, `test_table` — 655 passed; `ruff format` / `ruff check` clean - TypeScript: `pnpm build`; `table`, `merge`, `query` tests — 593 passed; `biome check` clean; `docs/src/js` regenerated with `npm run docs` - Java: `mvn test` — 37 passed (Spotless applied with JDK 11; the pinned google-java-format does not run on JDK 21) 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
Pre-Haswell x86_64 hosts: lancedb-compat
The default lancedb wheel targets x86-64-haswell (AVX2 + FMA + F16C) for full performance on modern hardware. Pre-Haswell hosts — Intel Sandy Bridge / Ivy Bridge / Westmere; AMD Bulldozer / Piledriver / Steamroller — don't have AVX2 and crash with Illegal instruction at import lancedb.
For those hosts, install the lancedb-compat package instead:
pip install lancedb-compat
Same Python API (import lancedb works as usual). The compat wheel is compiled at the x86-64-v2 baseline (Nehalem-class) and uses runtime SIMD dispatch in the embedded lance crate to pick the right kernel tier (scalar / AVX / AVX+FMA / AVX2+FMA / AVX-512) at load time, so it still goes fast on modern hardware while running cleanly on the pre-Haswell silicon. Use lance.simd_info() from Python to verify which tier was selected.
lancedb and lancedb-compat install to the same lancedb/ namespace and conflict at install time. Pick one. To switch, pip uninstall lancedb first, then pip install lancedb-compat (or vice-versa).
If you need a custom baseline (or lancedb-compat isn't yet published for your platform), build from source with the override:
RUSTFLAGS="-C target-cpu=x86-64-v2" maturin build --release
pip install ./target/wheels/lancedb-*.whl
Preview Releases
Stable releases are created about every 2 weeks. For the latest features and bug fixes, you can install the preview release. These releases receive the same level of testing as stable releases, but are not guaranteed to be available for more than 6 months after they are released. Once your application is stable, we recommend switching to stable releases.
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
Threading in CPU-limited containers
LanceDB uses separate pools for compute work and storage I/O. On a container with two visible CPUs, current releases intentionally use one compute worker by default; no manual configuration is needed. If every query logs an I/O core reservation warning on a two-CPU container, upgrade from LanceDB 0.21.1 or earlier.
The two commonly tuned environment variables control different resources:
LANCE_CPU_THREADSoverrides the number of compute workers. One worker is the appropriate setting for a two-CPU container when an explicit override is needed.LANCE_IO_THREADScontrols concurrent storage operations, not reserved CPU cores. Its default can be greater than the number of CPUs because I/O workers spend much of their time waiting for storage.
Keep the defaults unless measurements show that the workload benefits from an override. See the Lance threading model for the current defaults and tuning guidance.
Usage
Basic Example
import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()
print(results)
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.