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Dan Rammer
f1c4967eeb
## Why Four of the eight LSM methods are **remote-only in the core**. `impl BaseTable for NativeTable` implements only `set`/`unset`/`get_lsm_write_spec` and `close_lsm_writers`; `flush_lsm`, `compact_lsm` and `get_lsm_stats` fall through to trait defaults returning `NotSupported` (`rust/lancedb/src/table.rs:679,687,696`), and `checkpoint_lsm` is built on all three. That explains the state of the bindings: Node had bound the four that work against a local table and stopped, so a Cloud user could install an LSM write spec but had no way to observe fresh-tier state or drive a checkpoint. Java had none of it at all. | SDK | set/unset/get spec | closeWriters | flush | compact | getStats | checkpoint | |---|---|---|---|---|---|---| | Rust core | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Python | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Node *(before)* | ✅ | ✅ | — | — | — | — | | **Node (after)** | ✅ | ✅ | **new** | **new** | **new** | **new** | | Java *(before)* | — | — | — | — | — | — | | **Java (after)** | **new** | n/a | **new** | **new** | **new** | **new** | Go and C are separate repos and are out of scope here. `closeLsmWriters` drains cached in-process shard writers, so it has no meaning for Java, which is a pure REST client. ## Node Adds napi bindings for `flushLsm`, `compactLsm`, `checkpointLsm` and `getLsmStats`, plus typed `LsmStats` / `BucketStats` / `GenerationStats` / `MemtableStats` objects — typed rather than a JSON blob, matching the existing `LsmWriteSpec` object in the same file, with `u64` cast to `i64` per that file's convention. Because these four are remote-only, the new tests assert each binding reaches the core and surfaces `NotSupported` against a local table. That covers the wiring; behavior against a real endpoint stays covered by the mocked-endpoint tests in `rust/lancedb/src/remote/table.rs`. ## Python No new methods. All eight are on `LanceTable`, `AsyncTable` and `RemoteTable` — the last four landed on the sync `RemoteTable` in #3961, which is merged into this branch. What was missing here was reachability. `LsmWriteSpec` was importable only from the private `lancedb._lancedb`, appearing in `table.py` solely under `if TYPE_CHECKING:`, and `docs/src/python/python.md` had no mention of it, which per the repo's docs guidance means it rendered nowhere in the API reference. It is now `lancedb.LsmWriteSpec`, in `__all__`, and documented. ## Java Java reaches LanceDB purely over REST through the generated Lance Namespace client, and these routes are not in that spec, so they are issued through a small dedicated client rather than added to the spec. That call is revisitable — LSM is one of four unspecified route families alongside `multipart_write`, `page_cache/prewarm` and `branches/diff|merge`. If those are ever regularized into the spec as a group, `LanceDbTableLsm` is one file that gets deleted. `LsmWriteSpec` here is deliberately **not** `org.lance.memwal.InitializeMemWalParams`. That type defaults to maintaining *no* indexes where a spec here defaults to maintaining *every* index, and it cannot express the `null` that asks the server to resolve the set: | Value | On the wire | Meaning | |---|---|---| | unset (null) | `null` | Server resolves **every** maintainable index | | `Collections.emptyList()` | `[]` | Maintain **none** | | `Arrays.asList("id_idx")` | `["id_idx"]` | Exactly those | A dedicated test pins null and `[]` as distinct on the wire, since collapsing them is the failure mode that motivated a LanceDB-owned type. `checkpointLsm` is ported from `rust/lancedb/src/table/checkpoint.rs` with its constants and status semantics intact: 429/503 retried in place against an 8-budget, 421 restarting from flush against a 3-budget, 5s poll, and a target watermark fixed after the seal so it terminates under write load. `getLsmStats` returns typed `LsmStats` / `BucketStats` / `GenerationStats` / `MemtableStats`, mirroring the Rust structs in `rust/lancedb/src/table/lsm_stats.rs` and the objects Node exposes. Decoding is strict — see below. ## Review feedback Both gatekeeper findings were real. Each was reproduced against the scripted test server first, and each fix ships with the reproducer as a regression test. **The transport was doubling every checkpoint retry budget.** `HttpClients.createDefault()` installs Apache's default response retry strategy, whose retryable-status list is exactly 429 and 503 — the two statuses `isRetryable` owns. A 429 held against `flush_lsm` issued **18** wire requests where the loop intends 9, and `compact_lsm` was retried in place despite the loop being built to fall through to a fresh stats poll instead. Timing confirmed the mechanism: that run took 25.4s ≈ 16.3s of the loop's own backoff plus 9 × the transport's 1s retry interval. Automatic retries are now disabled, so the checkpoint loop is the sole owner of the 421/429/503 transitions. A side effect worth noting: `testCheckpointRetriesRetryableStatusInPlace` was passing on a transport-absorbed 429 and never reaching `issue()`'s retry branch at all. It now exercises the real path. **Stats decoding failed open.** `getLsmStats` read the response with Jackson's `path()`, which yields a missing node that iterates as an empty array — making "malformed" indistinguishable from "no buckets", which is indistinguishable from "drained". Four separate payloads made `checkpointLsm()` report convergence for a checkpoint that never ran: | Response | Before | Now | |---|---|---| | `{"lsm_stats": null}` or absent key | disabled ✓ | disabled ✓ | | `{"lsm_stats": {}}` | **reported success** | `IllegalStateException` | | empty response body | **reported success** | `IllegalStateException` | | bucket missing required fields | **reported success** | `IllegalStateException` | The empty-body row is the one to weight: a proxy 200 with no body is a realistic production event, and it silently reported a checkpoint that never happened. Decoding is now strict and fails closed, matching the serde contract on the Rust side exactly. One deliberate deviation from the review comment, which asked that *only* explicit JSON `null` count as disabled: Rust has `#[serde(default)]` on `lsm_stats`, so an **absent key** decodes to `None` there too. Java now matches that. It is an absent-or-malformed **`buckets`** that fails closed, which is the case the comment was actually protecting. ## Testing - Java: **33 passing** (8 existing + 25 LSM) against a scripted `com.sun.net.httpserver.HttpServer` — no new test dependency. Wire assertions mirror `rust/lancedb/src/remote/table.rs:6581-6748`; checkpoint tests cover convergence, not piling onto a latched bucket, 421 restart-from-flush, 429 retry-in-place, terminal-status propagation, reissue exhaustion, the exact wire-request count against the retry budget, and five malformed stats payloads. - Node: **19 LSM tests passing**; `cargo check`, `npm run build`, `npm run tsc`, `npm run lint`, `npm run docs` all clean. - Python: `ruff format --check` and `ruff check` clean. - Java formatting: `./mvnw -pl lancedb-core spotless:apply` and `spotless:check` both clean under a JDK 11 toolchain. ## Note: spotless needs a pre-16 JDK `./mvnw spotless:apply` fails on JDK 16+ with `JCTree$JCImport.getQualifiedIdentifier()` — google-java-format 1.7, pinned at `java/pom.xml:34`, predates JDK 16's compiler API change. **This is pre-existing** and reproduces on a pristine `main` checkout. It is not a blocker, just a toolchain requirement. Spotless was run against these sources under JDK 11 and both `spotless:apply` and `spotless:check` pass on the whole module: ```shell JAVA_HOME=/path/to/jdk11 ./mvnw -pl lancedb-core spotless:apply ``` Bumping the plugin so it works on modern JDKs is still worth doing, but separately from this PR. 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
The Multimodal AI Lakehouse
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors
The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
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Key Features:
- Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
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- Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
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- Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
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- Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
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- Rich Ecosystem: Integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
How to Install:
Follow the Quickstart doc to set up LanceDB locally.
API & SDK: We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|---|---|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/rest |
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