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Author SHA1 Message Date
lancedb-gatefixer[bot] 2fbf6d6211 test(python): cover concurrent S3 table opens (#3833)
## Summary

- add regression coverage for the reported synchronous Python workload
with 32 simultaneous `open_table` calls
- verify every independently opened S3-backed table handle can read
through the connection's shared session and object-store client

## Root cause

In Python v0.13.0, each synchronous table handle lazily constructed its
own Lance dataset. Opening many handles in parallel therefore triggered
independent S3 client construction and bucket-region resolution, which
failed under thread pressure. The current Rust-backed connection path
owns a shared Lance session and retains its object-store handle, so
table opens reuse the existing S3 client; these tests lock in that
behavior through the public Python API and a causal Session-registry
invariant.

## Validation

- `uvx --from 'ruff==0.15.20' ruff format --check
python/tests/test_s3.py`
- `uvx --from 'ruff==0.15.20' ruff check .`
- `cargo fmt --all`
- `cargo test --quiet --features remote -p lancedb
test_concurrent_open_table_reuses_connection_object_store`
- `cargo check --quiet --features remote --tests --examples`
- equivalent 32-thread `open_table(...).count_rows()` workload against a
local database
- targeted S3 test collected successfully locally; execution requires
the CI LocalStack service, which is unavailable in this runner

Fixes #1786

<!-- lance-gatekeeper-fix:v1 agent=d311f3c7151f77ae22b4997702e7b7db
generation=1 -->

---------

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 14:56:57 +08:00
Jack Ye 391cac9034 fix(remote): centralize timeline consistency (#4053)
Centralizes remote table freshness fencing and response-version tracking
in the default transport path.

Covers schema and blob bypass paths, keeps explicit time-travel and
cross-timeline operations unfenced, and advances freshness after refresh
and index job completion.
2026-08-26 12:54:36 +08:00
LanceDB Robot 21530432a0 chore: update lance dependency to v12.0.0-beta.2 (#4056)
Updates the Rust workspace Lance crates and Java lance-core dependency
to
[v12.0.0-beta.2](https://github.com/lance-format/lance/releases/tag/v12.0.0-beta.2).
No compatibility fixes were required; full-workspace Clippy passes with
all features and warnings denied.
2026-08-25 21:56:26 -05:00
lancedb-gatefixer[bot] 9b825c5f29 fix(node): route auto search using table embeddings (#3832)
## Summary

- Resolve automatic string-search routing from the active table schema
whenever the query executes.
- Defer embedding-provider construction while leaving explicit vector
and FTS routes unchanged.
- Cover unrelated global registrations and metadata transitions across
repeated executions of one query builder.

## Root cause

LocalTable.search used the number of globally registered embedding
providers to choose between vector and full-text search. A provider
registered for any other table therefore sent a plain FTS table down the
vector path. A wrapper-lifetime metadata snapshot avoided that
contamination but became stale after time travel or read-consistency
refreshes. The query now records fluent builder operations and creates
the appropriate native vector or FTS query from the active schema on
each execution.

## Validation

- pnpm build
- pnpm tsc
- pnpm lint
- pnpm run docs
- pnpm test --runInBand (681 passed, 5 skipped)

Fixes #1557

<!-- lance-gatekeeper-fix:v1 agent=b6183df8296db4aabdc5d19a2256b029
generation=1 -->

---------

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 10:08:48 +08:00
LanceDB Robot 8083232dd5 chore: update lance dependency to v12.0.0-beta.1 (#4055)
Updates the Lance Rust workspace dependencies and Java lance-core
dependency to
[v12.0.0-beta.1](https://github.com/lance-format/lance/releases/tag/v12.0.0-beta.1).

Includes compatibility updates for the renamed shard-manifest API and
paginated object-store wrappers.
2026-08-25 16:49:17 -07:00
lancedb-gatefixer[bot] 302b21aa94 test(node): cover nested PDF metadata queries (#3827)
## Summary

- add an end-to-end Node regression matching LangChain PDFLoader
metadata
- verify create/query round trips rich nested `loc` and `pdf.info`
fields against the currently configured Apache Arrow peer

## Root cause

LanceDB v0.14 delegated nested object inference to Apache Arrow. Nested
strings were dictionary-encoded with colliding dictionary IDs, so
serializing query results as an IPC file failed with a
dictionary-replacement error. Current `main` recursively infers nested
fields and avoids those invalid dictionaries, but the reported LangChain
path had no end-to-end regression coverage.

## Validation

- `pnpm build`
- `pnpm lint`
- `pnpm run docs`
- `pnpm test --runInBand` (678 passed, 5 skipped)

Fixes #1963

<!-- lance-gatekeeper-fix:v1 agent=bf8d489db7db2e17678b143f9f0a36d2
generation=1 -->

---------

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 06:42:29 +08:00
lancedb-gatefixer[bot] 35b5d015ac fix(node): preserve embedding registration in server bundles (#3806)
## Summary

- lazily initialize built-in OpenAI and Hugging Face providers when
consumers call the public embedding registry API
- choose automatic vector versus FTS search from embedding metadata on a
fresh pinned table revision for every execution
- expose automatic string searches as an `AutoQuery` with only
operations common to both native query families
- keep the registry shared and built-in registration safe across
duplicated module graphs

## Root cause

Nitro treats dependency modules as side-effect-free and removes the bare
OpenAI provider import from its generated route. Registration therefore
never runs, so `getRegistry().get("openai")` remains undefined even when
the registry itself is shared globally. Bundlers may also duplicate the
provider and registry module graphs.

The public embedding entry point now initializes built-in providers only
when `getRegistry()` is explicitly called, keeping initialization on a
live path that Nitro retains. Each terminal automatic-search execution
pins the exact table revision visible at dispatch, reads embedding
metadata and computes an embedding from that snapshot, replays the
builder operations, and constructs and executes the selected native
query against the same snapshot. Pinned native snapshots execute locally
when namespace pushdown cannot carry their revision, while remote
snapshots are seeded directly from one version-and-schema response. The
public `AutoQuery` builder exposes only the operations shared by FTS and
vector search, so runtime class narrowing cannot expose invalid
vector-only methods. Repeated built-in registration replaces stale
constructors from duplicated module graphs while public `register()`
retains its duplicate-alias error.

## Validation

- `cargo fmt --all`
- `cargo check --quiet --features remote --tests --examples`
- `cargo clippy --quiet --features remote --tests --examples`
- `pnpm build`
- `pnpm lint`
- `pnpm run docs`
- `pnpm test --runInBand` (783 passed, 5 skipped)
- serial examples suite with a local OpenAI mock (11 passed), including
`sentence-transformers.test.ts`
- packaged Nitro 2.13.4 server route using the reported imports returned
`{"registered":true}`
- fresh-process FTS fixture initialized both public built-ins and
confirmed automatic string search still returned the indexed row
- schema-consistency regressions cover read-consistency refresh,
checkout, checkoutLatest, restore, runtime class narrowing, concurrent
overwrite during embedding computation, and reused automatic-search
builders
- focused regressions confirm pinned native snapshots bypass unversioned
namespace pushdown and remote snapshots use one describe request

Fixes #2429

<!-- lance-gatekeeper-fix:v1 agent=2adf0f21b8bfb634606ed8897a849e30
generation=1 -->

---------

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 04:17:32 +08:00
lancedb-gatefixer[bot] a57fb68891 docs(python): fix Azure storage options examples (#3899)
## Summary

- document that Azure Blob Storage credentials can be passed directly
through `storage_options`
- provide valid quoted `account_name` and `account_key` examples for
both sync and async Python connections
- execute the option dictionaries during doctests so the original
unquoted-key mistake is caught

## Root cause

The historical Python storage guide used `account_name` and
`account_key` as bare identifiers in dictionary literals. Following that
example either raised `NameError` or, when those names were predefined,
produced incorrect option keys. The runtime already accepts direct Azure
credentials, but the current Python API reference did not contain a
corrected Azure example.

## Validation

- `python/.venv/bin/ruff format --check
python/python/lancedb/__init__.py`
- `python/.venv/bin/ruff check .`
- `cd python && uv run --no-sync pytest --doctest-modules
python/lancedb/__init__.py -q`
- `cd python && uv run --no-sync pytest python/tests/test_import.py -q`

Fixes #2236

<!-- lance-gatekeeper-fix:v1 agent=7a7a9e009eb2ebe52ac9b1adf2e8afb2
generation=1 -->

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 00:31:14 +08:00
Drew a614400755 feat: accept blob URI writes (#3954)
#3528 added blob declarations and binary coercion. String values were
still rejected. They now coerce to the blob `uri` child.

```python
table.add([{"id": 1, "image": "s3://bucket/media/cat.jpg"}])

payload = table.fetch_blobs("image", table.search().to_arrow())
```

A URI under a registered base writes with no extra options. An
unregistered URI fails. `allow_external_blob_outside_bases` is a local
escape hatch that stores an absolute URI. It does not register a base.
Remote `add` rejects that flag before making a request. String input
still coerces and is sent as a `uri` struct.

`add_bases` is a follow-up. `merge_insert` does not coerce string blob
input.

### Testing

- `cargo test -p lancedb --test blob_integration`
- `cargo test -p lancedb blob_coerce`
- `cargo test -p lancedb --features remote --lib
add_rejects_external_blob_flag add_string_blob_becomes_uri_struct`
- `cd python && uv run --extra tests pytest python/tests/test_blob.py -k
uri -q`

Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-25 22:59:53 +08:00
Xuanwo 1d880f11ff fix(python): use dev profile for editable builds (#4049)
## Problem

`uv run ... maturin develop` synchronizes the project as an editable
package before running the command. Maturin's editable build otherwise
uses the release profile, which enables the repository's fat LTO
configuration during local bootstrap.

## Behavior

Editable Python builds now explicitly use Cargo's dev profile. The
minimum maturin version is raised to 1.10, where `editable-profile`
support was introduced.
2026-08-25 19:51:40 +08:00
Lance Release ec4ad54ba2 Bump version: 0.38.0-beta.9 → 0.38.0-beta.10 2026-08-25 10:37:09 +00:00
Xuanwo d0bcc6c6fe fix: remove unsupported Function secrets contract (#4047)
## Problem

The unreleased First-Class Function authoring API exposed
`secrets=[...]` and serialized `required_secrets`, promising runtime
resolution and injection that Sophon does not implement.

## Behavior

Remove the secrets dimension from the public Python decorator, Python
and Rust registration/version models, and shared wire fixtures. Existing
successfully registered Functions retain stable identity: the field
could only be empty and empty values were already omitted from canonical
serialization.

A stable LanceDB release has not shipped this Function API, so this
contracts the surface before it becomes a published compatibility
commitment.

## Validation gap

The Rust shared-golden Function suites and Python formatting/lint checks
pass locally. Python pytest was not run because the local environment
lacks its runtime dependencies and the frozen native editable build did
not complete in practical time.
2026-08-25 18:35:27 +08:00
Lance Release 81c3f108ce Bump version: 0.38.0-beta.8 → 0.38.0-beta.9 2026-08-25 10:32:12 +00:00
66 changed files with 3874 additions and 738 deletions
+1 -1
View File
@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.38.0-beta.8"
current_version = "0.38.0-beta.10"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
Generated
+45 -45
View File
@@ -3455,8 +3455,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"
[[package]]
name = "fsst"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"rand 0.9.5",
@@ -4815,8 +4815,8 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"
[[package]]
name = "lance"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arc-swap",
"arrow",
@@ -4888,8 +4888,8 @@ dependencies = [
[[package]]
name = "lance-arrow"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4911,7 +4911,7 @@ dependencies = [
[[package]]
name = "lance-arrow-scalar"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4925,7 +4925,7 @@ dependencies = [
[[package]]
name = "lance-arrow-stats"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -4934,8 +4934,8 @@ dependencies = [
[[package]]
name = "lance-bitpacking"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrayref",
"crunchy",
@@ -4945,8 +4945,8 @@ dependencies = [
[[package]]
name = "lance-core"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4983,8 +4983,8 @@ dependencies = [
[[package]]
name = "lance-datafusion"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5013,8 +5013,8 @@ dependencies = [
[[package]]
name = "lance-datagen"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5031,8 +5031,8 @@ dependencies = [
[[package]]
name = "lance-derive"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"proc-macro2",
"quote",
@@ -5041,8 +5041,8 @@ dependencies = [
[[package]]
name = "lance-encoding"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-arith",
"arrow-array",
@@ -5075,8 +5075,8 @@ dependencies = [
[[package]]
name = "lance-file"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-arith",
"arrow-array",
@@ -5107,8 +5107,8 @@ dependencies = [
[[package]]
name = "lance-index"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arc-swap",
"arrow",
@@ -5172,8 +5172,8 @@ dependencies = [
[[package]]
name = "lance-index-core"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5195,8 +5195,8 @@ dependencies = [
[[package]]
name = "lance-io"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5236,8 +5236,8 @@ dependencies = [
[[package]]
name = "lance-linalg"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5251,8 +5251,8 @@ dependencies = [
[[package]]
name = "lance-namespace"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"async-trait",
@@ -5264,8 +5264,8 @@ dependencies = [
[[package]]
name = "lance-namespace-impls"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-ipc",
@@ -5318,8 +5318,8 @@ dependencies = [
[[package]]
name = "lance-select"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -5333,8 +5333,8 @@ dependencies = [
[[package]]
name = "lance-table"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5374,8 +5374,8 @@ dependencies = [
[[package]]
name = "lance-testing"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5388,8 +5388,8 @@ dependencies = [
[[package]]
name = "lance-tokenizer"
version = "11.0.0-beta.22"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"frostem",
"icu_segmenter",
@@ -5402,7 +5402,7 @@ dependencies = [
[[package]]
name = "lancedb"
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
dependencies = [
"ahash",
"anyhow",
@@ -5490,7 +5490,7 @@ dependencies = [
[[package]]
name = "lancedb-nodejs"
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -5515,7 +5515,7 @@ dependencies = [
[[package]]
name = "lancedb-python"
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
dependencies = [
"arrow",
"async-trait",
+14 -14
View File
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
rust-version = "1.91.0"
[workspace.dependencies]
lance = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
lance = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lancedb = { path = "rust/lancedb", default-features = false }
ahash = "0.8"
# Note that this one does not include pyarrow
+1 -1
View File
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.38.0-beta.8</version>
<version>0.38.0-beta.10</version>
</dependency>
```
+518
View File
@@ -0,0 +1,518 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / AutoQuery
# Class: AutoQuery
A builder for automatic string searches.
Automatic search determines whether to use full-text or vector search from
the table revision selected for each execution. This builder exposes the
common operations supported by both query families.
## Extends
- `StandardQueryBase`&lt;`NativeQuery` \| `NativeVectorQuery`&gt;
## Properties
### inner
```ts
protected inner: Query | VectorQuery | Promise<Query | VectorQuery>;
```
#### Inherited from
`StandardQueryBase.inner`
## Methods
### analyzePlan()
```ts
analyzePlan(distributedMetrics?): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Parameters
* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
How distributed worker metrics are displayed for remote query plans.
Defaults to `"aggregate"`.
#### Returns
`Promise`&lt;`string`&gt;
A query execution plan with runtime metrics for each step.
#### Example
```ts
import * as lancedb from "@lancedb/lancedb"
const db = await lancedb.connect("./.lancedb");
const table = await db.createTable("my_table", [
{ vector: [1.1, 0.9], id: "1" },
]);
const plan = await table.query().nearestTo([0.5, 0.2]).analyzePlan();
Example output (with runtime metrics inlined):
AnalyzeExec verbose=true, metrics=[]
ProjectionExec: expr=[id@3 as id, vector@0 as vector, _distance@2 as _distance], metrics=[output_rows=1, elapsed_compute=3.292µs]
Take: columns="vector, _rowid, _distance, (id)", metrics=[output_rows=1, elapsed_compute=66.001µs, batches_processed=1, bytes_read=8, iops=1, requests=1]
CoalesceBatchesExec: target_batch_size=1024, metrics=[output_rows=1, elapsed_compute=3.333µs]
GlobalLimitExec: skip=0, fetch=10, metrics=[output_rows=1, elapsed_compute=167ns]
FilterExec: _distance@2 IS NOT NULL, metrics=[output_rows=1, elapsed_compute=8.542µs]
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], metrics=[output_rows=1, elapsed_compute=63.25µs, row_replacements=1]
KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
```
#### Inherited from
`StandardQueryBase.analyzePlan`
***
### execute()
```ts
protected execute(options?): AsyncGenerator<RecordBatch<any>, void, unknown>
```
Execute the query and return the results as an
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
`AsyncGenerator`&lt;`RecordBatch`&lt;`any`&gt;, `void`, `unknown`&gt;
#### See
- AsyncIterator
of
- RecordBatch.
By default, LanceDb will use many threads to calculate results and, when
the result set is large, multiple batches will be processed at one time.
This readahead is limited however and backpressure will be applied if this
stream is consumed slowly (this constrains the maximum memory used by a
single query)
#### Inherited from
`StandardQueryBase.execute`
***
### explainPlan()
```ts
explainPlan(verbose): Promise<string>
```
Generates an explanation of the query execution plan.
#### Parameters
* **verbose**: `boolean` = `false`
If true, provides a more detailed explanation. Defaults to false.
#### Returns
`Promise`&lt;`string`&gt;
A Promise that resolves to a string containing the query execution plan explanation.
#### Example
```ts
import * as lancedb from "@lancedb/lancedb"
const db = await lancedb.connect("./.lancedb");
const table = await db.createTable("my_table", [
{ vector: [1.1, 0.9], id: "1" },
]);
const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
```
#### Inherited from
`StandardQueryBase.explainPlan`
***
### fastSearch()
```ts
fastSearch(): this
```
Skip searching un-indexed data. This can make search faster, but will miss
any data that is not yet indexed.
Use [Table#optimize](Table.md#optimize) to index all un-indexed data.
#### Returns
`this`
#### Inherited from
`StandardQueryBase.fastSearch`
***
### ~~filter()~~
```ts
filter(predicate): this
```
A filter statement to be applied to this query.
#### Parameters
* **predicate**: `string`
#### Returns
`this`
#### See
where
#### Deprecated
Use `where` instead
#### Inherited from
`StandardQueryBase.filter`
***
### fullTextSearch()
```ts
fullTextSearch(query, options?): this
```
#### Parameters
* **query**: `string` \| [`FullTextQuery`](../interfaces/FullTextQuery.md)
* **options?**: `Partial`&lt;[`FullTextSearchOptions`](../interfaces/FullTextSearchOptions.md)&gt;
#### Returns
`this`
#### Inherited from
`StandardQueryBase.fullTextSearch`
***
### limit()
```ts
limit(limit): this
```
Set the maximum number of results to return.
By default, a plain search has no limit. If this method is not
called then every valid row from the table will be returned.
#### Parameters
* **limit**: `number`
#### Returns
`this`
#### Inherited from
`StandardQueryBase.limit`
***
### offset()
```ts
offset(offset): this
```
Set the number of rows to skip before returning results.
This is useful for pagination.
#### Parameters
* **offset**: `number`
#### Returns
`this`
#### Inherited from
`StandardQueryBase.offset`
***
### orderBy()
```ts
orderBy(ordering): this
```
Sort the results by the specified column(s).
#### Parameters
* **ordering**: [`ColumnOrdering`](../interfaces/ColumnOrdering.md) \| [`ColumnOrdering`](../interfaces/ColumnOrdering.md)[]
#### Returns
`this`
This query builder.
#### Inherited from
`StandardQueryBase.orderBy`
***
### outputSchema()
```ts
outputSchema(): Promise<Schema<any>>
```
Returns the schema of the output that will be returned by this query.
This can be used to inspect the types and names of the columns that will be
returned by the query before executing it.
#### Returns
`Promise`&lt;`Schema`&lt;`any`&gt;&gt;
An Arrow Schema describing the output columns.
#### Inherited from
`StandardQueryBase.outputSchema`
***
### select()
```ts
select(columns): this
```
Return only the specified columns.
By default a query will return all columns from the table. However, this can have
a very significant impact on latency. LanceDb stores data in a columnar fashion. This
means we can finely tune our I/O to select exactly the columns we need.
As a best practice you should always limit queries to the columns that you need. If you
pass in an array of column names then only those columns will be returned.
You can also use this method to create new "dynamic" columns based on your existing columns.
For example, you may not care about "a" or "b" but instead simply want "a + b". This is often
seen in the SELECT clause of an SQL query (e.g. `SELECT a+b FROM my_table`).
To create dynamic columns you can pass in a Map<string, string>. A column will be returned
for each entry in the map. The key provides the name of the column. The value is
an SQL string used to specify how the column is calculated.
For example, an SQL query might state `SELECT a + b AS combined, c`. The equivalent
input to this method would be:
#### Parameters
* **columns**: `string` \| `string`[] \| `Record`&lt;`string`, `string`&gt; \| `Map`&lt;`string`, `string`&gt;
#### Returns
`this`
#### Example
```ts
new Map([["combined", "a + b"], ["c", "c"]])
Columns will always be returned in the order given, even if that order is different than
the order used when adding the data.
Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
uses `Object.entries` which should preserve the insertion order of the object. However,
object insertion order is easy to get wrong and `Map` is more foolproof.
```
#### Inherited from
`StandardQueryBase.select`
***
### toArray()
```ts
toArray(options?): Promise<any[]>
```
Collect the results as an array of objects.
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
`Promise`&lt;`any`[]&gt;
#### Inherited from
`StandardQueryBase.toArray`
***
### toArrow()
```ts
toArrow(options?): Promise<Table<any>>
```
Collect the results as an Arrow
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
`Promise`&lt;`Table`&lt;`any`&gt;&gt;
#### See
ArrowTable.
#### Inherited from
`StandardQueryBase.toArrow`
***
### useLsm()
```ts
useLsm(enable): this
```
Control MemWAL read routing for this query.
By default (unset), when the table carries a MemWAL write spec (see
[Table#setLsmWriteSpec](Table.md#setlsmwritespec)), reads are routed through the LSM scanner so
they also return data written via the `mergeInsert` LSM path that has not yet
been compacted into the base table (the active/frozen in-memory memtables and
the flushed generations), deduplicated by primary key; a table without a spec
reads the base table.
#### Parameters
* **enable**: `boolean`
`true` forces the LSM scanner and errors if the table has no
MemWAL write spec. `false` bypasses the MemWAL and reads the base table only,
even when a spec is present.
Note: the LSM scanner does not support every query shape (e.g. reranking,
hybrid search, `orderBy`). On a MemWAL table those shapes error unless
`useLsm(false)` is set, because a base-only read would silently exclude
un-compacted MemWAL data.
#### Returns
`this`
#### Inherited from
`StandardQueryBase.useLsm`
***
### where()
```ts
where(predicate): this
```
A filter statement to be applied to this query.
The filter should be supplied as an SQL query string. For example:
#### Parameters
* **predicate**: `string`
#### Returns
`this`
#### Example
```ts
x > 10
y > 0 AND y < 100
x > 5 OR y = 'test'
Filtering performance can often be improved by creating a scalar index
on the filter column(s).
Calling this multiple times combines the filters with a logical AND rather
than replacing the previous filter.
```
#### Inherited from
`StandardQueryBase.where`
***
### withRowId()
```ts
withRowId(): this
```
Whether to return the row id in the results.
This column can be used to match results between different queries. For
example, to match results from a full text search and a vector search in
order to perform hybrid search.
#### Returns
`this`
#### Inherited from
`StandardQueryBase.withRowId`
+2 -2
View File
@@ -942,7 +942,7 @@ Get the schema of the table.
abstract search(
query,
queryType?,
ftsColumns?): Query | VectorQuery
ftsColumns?): Query | VectorQuery | AutoQuery
```
Create a search query to find the nearest neighbors
@@ -964,7 +964,7 @@ of the given query
#### Returns
[`Query`](Query.md) \| [`VectorQuery`](VectorQuery.md)
[`Query`](Query.md) \| [`VectorQuery`](VectorQuery.md) \| [`AutoQuery`](AutoQuery.md)
***
+1
View File
@@ -18,6 +18,7 @@
## Classes
- [AutoQuery](classes/AutoQuery.md)
- [BooleanQuery](classes/BooleanQuery.md)
- [BoostQuery](classes/BoostQuery.md)
- [BranchContents](classes/BranchContents.md)
@@ -10,16 +10,12 @@
function getRegistry(): EmbeddingFunctionRegistry
```
Utility function to get the global instance of the registry
Get the global embedding function registry.
LanceDB built-in providers are initialized when this public API is first
used, so importing the root package does not change automatic search
selection for tables without embedding metadata.
## Returns
[`EmbeddingFunctionRegistry`](../classes/EmbeddingFunctionRegistry.md)
`EmbeddingFunctionRegistry` The global instance of the registry
## Example
```ts
const registry = getRegistry();
const openai = registry.get("openai").create();
+1 -1
View File
@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-beta.8</version>
<version>0.38.0-beta.10</version>
<relativePath>../pom.xml</relativePath>
</parent>
+2 -2
View File
@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-beta.8</version>
<version>0.38.0-beta.10</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<arrow.version>15.0.0</arrow.version>
<lance-core.version>11.0.0-beta.22</lance-core.version>
<lance-core.version>12.0.0-beta.2</lance-core.version>
<spotless.skip>false</spotless.skip>
<spotless.version>2.30.0</spotless.version>
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
+1 -1
View File
@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
publish = false
license.workspace = true
description.workspace = true
@@ -0,0 +1,95 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
import { execFileSync } from "node:child_process";
import { resolve } from "node:path";
import type { OpenAIEmbeddingFunction } from "../lancedb/embedding/openai";
import type { EmbeddingFunctionRegistry } from "../lancedb/embedding/registry";
type EmbeddingModule = typeof import("../lancedb/embedding");
type OpenAIModule = typeof import("../lancedb/embedding/openai");
type RegistryModule = typeof import("../lancedb/embedding/registry");
describe("embedding function registry", () => {
const registries: EmbeddingFunctionRegistry[] = [];
afterEach(() => {
for (const registry of registries) {
registry.reset();
}
registries.length = 0;
});
it("defers built-in providers until the public registry API is used", () => {
jest.isolateModules(() => {
const embedding = require("../lancedb/embedding") as EmbeddingModule;
const { getRegistry: getInternalRegistry } =
require("../lancedb/embedding/registry") as RegistryModule;
const registry = getInternalRegistry();
registries.push(registry);
expect(registry.length()).toBe(0);
expect(embedding.getRegistry()).toBe(registry);
expect(registry.get("openai")).toBeDefined();
expect(registry.get("huggingface")).toBeDefined();
});
});
it("preserves automatic FTS search in a fresh process", () => {
execFileSync(
process.execPath,
[resolve(__dirname, "fixtures", "auto_fts_search.cjs")],
{ stdio: "pipe" },
);
});
it("shares registrations across duplicated provider module graphs", () => {
let registeringRegistry: EmbeddingFunctionRegistry | undefined;
let latestOpenAIConstructor: typeof OpenAIEmbeddingFunction | undefined;
jest.isolateModules(() => {
require("../lancedb/embedding/openai");
const { getRegistry } =
require("../lancedb/embedding/registry") as RegistryModule;
registeringRegistry = getRegistry();
registries.push(registeringRegistry);
expect(registeringRegistry.get("openai")).toBeDefined();
});
expect(() => {
jest.isolateModules(() => {
const { OpenAIEmbeddingFunction } =
require("../lancedb/embedding/openai") as OpenAIModule;
latestOpenAIConstructor = OpenAIEmbeddingFunction;
const { getRegistry } =
require("../lancedb/embedding/registry") as RegistryModule;
registries.push(getRegistry());
});
}).not.toThrow();
const previousApiKey = process.env.OPENAI_API_KEY;
process.env.OPENAI_API_KEY = "test";
try {
const latestOpenAI = registeringRegistry!
.get<OpenAIEmbeddingFunction>("openai")!
.create();
expect(latestOpenAI).toBeInstanceOf(latestOpenAIConstructor!);
} finally {
if (previousApiKey === undefined) {
delete process.env.OPENAI_API_KEY;
} else {
process.env.OPENAI_API_KEY = previousApiKey;
}
}
jest.isolateModules(() => {
const { getRegistry } =
require("../lancedb/embedding") as EmbeddingModule;
const publicRegistry = getRegistry();
registries.push(publicRegistry);
expect(publicRegistry).toBe(registeringRegistry);
expect(publicRegistry.get("openai")).toBeDefined();
});
});
});
@@ -0,0 +1,33 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
const assert = require("node:assert/strict");
const tmp = require("tmp");
const { connect, embedding, Index } = require("../../dist");
const { getRegistry } = require("../../dist/embedding/registry");
async function main() {
assert.equal(typeof embedding.getRegistry, "function");
assert.equal(getRegistry().length(), 0);
assert.equal(embedding.getRegistry(), getRegistry());
assert.equal(getRegistry().length(), 2);
const dir = tmp.dirSync({ unsafeCleanup: true });
let db;
try {
db = await connect(dir.name);
const table = await db.createTable("docs", [{ text: "hello world" }]);
await table.createIndex("text", { config: Index.fts() });
const rows = await table.search("hello").toArray();
assert.equal(rows[0].text, "hello world");
} finally {
db?.close();
dir.removeCallback();
}
}
main().catch((error) => {
console.error(error);
process.exitCode = 1;
});
+583 -1
View File
@@ -11,10 +11,13 @@ import * as arrow17 from "apache-arrow-17";
import * as arrow18 from "apache-arrow-18";
import {
AutoQuery,
Connection,
MatchQuery,
PhraseQuery,
Query,
Table,
VectorQuery,
connect,
tokenize,
} from "../lancedb";
@@ -682,6 +685,56 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
},
);
// https://github.com/lancedb/lancedb/issues/1963
it("should query documents with LangChain PDF metadata", async () => {
const tmpDir = tmp.dirSync({ unsafeCleanup: true });
try {
const db = await connect(tmpDir.name);
const documents = [
{
text: "first page",
vector: [1, 0],
source: "first.pdf",
loc: { pageNumber: 1, lines: { from: 1, to: 12 } },
pdf: {
version: "1.10.100",
info: {
format: "PDF 1.7",
producer: "pdf.js",
creator: "Writer",
},
totalPages: 2,
},
},
{
text: "second page",
vector: [0, 1],
source: "second.pdf",
loc: { pageNumber: 2, lines: { from: 13, to: 24 } },
pdf: {
version: "1.10.100",
info: {
format: "PDF 1.7",
producer: "pdf.js",
creator: "Writer",
},
totalPages: 2,
},
},
];
const documentsTable = await db.createTable("documents", documents);
const results = await documentsTable.query().toArray();
expect(results).toHaveLength(2);
expect(results[0].source).toBe("first.pdf");
expect(results[0].pdf.info.producer).toBe("pdf.js");
expect(results[1].loc.pageNumber).toBe(2);
} finally {
tmpDir.removeCallback();
}
});
describe("merge insert", () => {
let tmpDir: tmp.DirResult;
let table: Table;
@@ -1777,6 +1830,194 @@ describe("Read consistency interval", () => {
});
});
describe("automatic search schema consistency", () => {
let tmpDir: tmp.DirResult;
class SchemaRefreshEmbedding extends EmbeddingFunction<string> {
ndims() {
return 2;
}
embeddingDataType() {
return new Float32();
}
async computeSourceEmbeddings(data: string[]) {
return data.map((value) => [value.length, 1]);
}
async computeQueryEmbeddings(value: string) {
return [value.length, 1];
}
}
function embeddingSchema() {
const func = new SchemaRefreshEmbedding();
return LanceSchema({
text: func.sourceField(new Utf8()),
vector: func.vectorField(),
});
}
beforeEach(() => {
getRegistry().reset();
register("schema-refresh")(SchemaRefreshEmbedding);
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => {
getRegistry().reset();
tmpDir.removeCallback();
});
it("uses the schema refreshed from another connection", async () => {
const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
try {
const stale = await first.createTable("docs", [{ text: "before" }], {
schema: embeddingSchema(),
});
const replacement = await second.createTable(
"docs",
[{ text: "after hello" }],
{ mode: "overwrite" },
);
await replacement.createIndex("text", { config: Index.fts() });
const search = stale.search("hello");
expect(search).toBeInstanceOf(AutoQuery);
expect(search).not.toBeInstanceOf(Query);
expect(search).not.toBeInstanceOf(VectorQuery);
expect("nprobes" in search).toBe(false);
const rows = await search.toArray();
expect(rows[0].text).toBe("after hello");
expect((await stale.schema()).metadata.has("embedding_functions")).toBe(
false,
);
} finally {
first.close();
second.close();
}
});
it("tracks embedding metadata across checkout and restore", async () => {
const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
try {
await first.createTable("docs", [{ text: "before" }], {
schema: embeddingSchema(),
});
const table = await second.createTable(
"docs",
[{ text: "after hello" }],
{ mode: "overwrite" },
);
await table.createIndex("text", { config: Index.fts() });
await table.checkout(1);
expect((await table.search("before").toArray())[0].text).toBe("before");
await table.checkoutLatest();
expect((await table.search("hello").toArray())[0].text).toBe(
"after hello",
);
await table.checkout(1);
await table.restore();
expect((await table.search("before").toArray())[0].text).toBe("before");
} finally {
first.close();
second.close();
}
});
it("pins automatic search while computing an embedding", async () => {
let markStarted!: () => void;
let releaseEmbedding!: () => void;
const started = new Promise<void>((resolve) => {
markStarted = resolve;
});
const released = new Promise<void>((resolve) => {
releaseEmbedding = resolve;
});
class BlockingEmbedding extends SchemaRefreshEmbedding {
async computeQueryEmbeddings(value: string) {
markStarted();
await released;
return [value.length, 1];
}
}
register("schema-refresh-blocking")(BlockingEmbedding);
const func = new BlockingEmbedding();
const schema = LanceSchema({
text: func.sourceField(new Utf8()),
vector: func.vectorField(),
});
const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
try {
const table = await first.createTable(
"docs",
[{ text: "hello before" }],
{ schema },
);
const pending = table.search("hello").toArray();
await started;
const replacement = await second.createTable(
"docs",
[{ text: "hello after" }],
{ mode: "overwrite" },
);
await replacement.createIndex("text", { config: Index.fts() });
releaseEmbedding();
expect((await pending)[0].text).toBe("hello before");
} finally {
releaseEmbedding();
first.close();
second.close();
}
});
it("refreshes a reused automatic search for every execution", async () => {
const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
try {
const table = await first.createTable("docs", [
{ text: "hello before", marker: "before" },
]);
await table.createIndex("text", { config: Index.fts() });
const search = table.search("hello").select(["text"]);
const before = (await search.toArray())[0];
expect(before.text).toBe("hello before");
expect(before.marker).toBeUndefined();
const replacement = await second.createTable(
"docs",
[{ text: "hello after", marker: "after" }],
{ mode: "overwrite" },
);
await replacement.createIndex("text", { config: Index.fts() });
const after = (await search.toArray())[0];
expect(after.text).toBe("hello after");
expect(after.marker).toBeUndefined();
} finally {
first.close();
second.close();
}
});
});
describe("schema evolution", function () {
let tmpDir: tmp.DirResult;
beforeEach(() => {
@@ -2344,7 +2585,24 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
);
});
test("full text search if no embedding function provided", async () => {
test("full text search if only an unrelated embedding function is registered", async () => {
register("unused")(
class extends EmbeddingFunction<string> {
ndims() {
return 3;
}
embeddingDataType() {
return new Float32();
}
async computeQueryEmbeddings(_data: string) {
return [1, 2, 3];
}
async computeSourceEmbeddings(data: string[]) {
return data.map(() => [1, 2, 3]);
}
},
);
const db = await connect(tmpDir.name);
const data = [
{ text: "hello world", vector: [0.1, 0.2, 0.3] },
@@ -2366,6 +2624,306 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(results2[0].text).toBe(data[1].text);
});
test("auto search stays consistent with the active revision", async () => {
let initCalls = 0;
let queryCalls = 0;
let markStarted!: () => void;
const started = new Promise<void>((resolve) => {
markStarted = resolve;
});
let releaseEmbedding!: () => void;
const embeddingReleased = new Promise<void>((resolve) => {
releaseEmbedding = resolve;
});
@register("refresh-test")
class TestEmbedding extends EmbeddingFunction<string> {
async init() {
initCalls += 1;
}
ndims() {
return 1;
}
embeddingDataType() {
return new arrow.Float32();
}
async computeQueryEmbeddings(value: string) {
queryCalls += 1;
if (value === "blocked") {
markStarted();
await embeddingReleased;
}
return value === "greetings" ? [0.1] : [0.2];
}
async computeSourceEmbeddings(values: string[]) {
return values.map((value) =>
value === "hello world" ? [0.1] : [0.2],
);
}
}
const writer = await connect(tmpDir.name);
await writer.createTable("test", [{ text: "plain", vector: [0.0] }]);
const reader = await connect(tmpDir.name, {
readConsistencyInterval: 0,
});
const tracked = await reader.openTable("test");
type SnapshotCountingNative = {
querySnapshot: () => Promise<unknown>;
};
const native = (tracked as unknown as { inner: SnapshotCountingNative })
.inner;
const querySnapshot = native.querySnapshot.bind(native);
let snapshotCalls = 0;
native.querySnapshot = async () => {
snapshotCalls += 1;
return await querySnapshot();
};
const autoQuery = tracked.search("greetings").select(["text"]).limit(1);
const func = new TestEmbedding();
const schema = LanceSchema({
text: func.sourceField(new arrow.Utf8()),
vector: func.vectorField(),
});
const data = [{ text: "hello world" }, { text: "goodbye world" }];
await writer.createTable("test", data, { mode: "overwrite", schema });
const baselineInitCalls = initCalls;
expect(
(await tracked.schema()).metadata.get("embedding_functions"),
).toBeDefined();
const results = await autoQuery.toArray();
expect(results[0].text).toBe(data[0].text);
expect(initCalls).toBe(baselineInitCalls + 1);
expect(queryCalls).toBe(1);
expect(snapshotCalls).toBe(1);
const repeatedResults = await autoQuery.toArray();
expect(repeatedResults[0].text).toBe(data[0].text);
expect(initCalls).toBe(baselineInitCalls + 1);
expect(queryCalls).toBe(1);
expect(snapshotCalls).toBe(2);
const pending = tracked
.search("blocked")
.select(["text"])
.limit(1)
.toArray();
await started;
const ftsData = [
{ text: "greetings from full text", vector: [0.0] },
{ text: "blocked from full text", vector: [0.0] },
];
const ftsTable = await writer.createTable("test", ftsData, {
mode: "overwrite",
});
await ftsTable.createIndex("text", { config: Index.fts() });
releaseEmbedding();
const pendingResults = await pending;
expect(pendingResults[0].text).toBe(data[1].text);
expect(
(await tracked.schema()).metadata.get("embedding_functions"),
).toBeUndefined();
const ftsResults = await autoQuery.toArray();
expect(ftsResults[0].text).toBe(ftsData[0].text);
});
test("auto search keeps newer preparation during a revision race", async () => {
let aCalls = 0;
let bCalls = 0;
let markAStarted!: () => void;
const aStarted = new Promise<void>((resolve) => {
markAStarted = resolve;
});
let releaseA!: () => void;
const aReleased = new Promise<void>((resolve) => {
releaseA = resolve;
});
let markBStarted!: () => void;
const bStarted = new Promise<void>((resolve) => {
markBStarted = resolve;
});
let releaseB!: () => void;
const bReleased = new Promise<void>((resolve) => {
releaseB = resolve;
});
@register("race-a")
class EmbeddingA extends EmbeddingFunction<string> {
ndims() {
return 1;
}
embeddingDataType() {
return new arrow.Float32();
}
async computeQueryEmbeddings() {
aCalls += 1;
markAStarted();
await aReleased;
return [0.1];
}
async computeSourceEmbeddings(values: string[]) {
return values.map(() => [0.1]);
}
}
@register("race-b")
class EmbeddingB extends EmbeddingFunction<string> {
ndims() {
return 1;
}
embeddingDataType() {
return new arrow.Float32();
}
async computeQueryEmbeddings() {
bCalls += 1;
markBStarted();
await bReleased;
return [0.2];
}
async computeSourceEmbeddings(values: string[]) {
return values.map(() => [0.2]);
}
}
const writer = await connect(tmpDir.name);
const embeddingA = new EmbeddingA();
const schemaA = LanceSchema({
text: embeddingA.sourceField(new arrow.Utf8()),
vector: embeddingA.vectorField(),
});
await writer.createTable("race", [{ text: "revision a" }], {
schema: schemaA,
});
const reader = await connect(tmpDir.name, {
readConsistencyInterval: 0,
});
const tracked = await reader.openTable("race");
const query = tracked.search("query");
const first = query.toArray();
await aStarted;
const embeddingB = new EmbeddingB();
const schemaB = LanceSchema({
text: embeddingB.sourceField(new arrow.Utf8()),
vector: embeddingB.vectorField(),
});
await writer.createTable("race", [{ text: "revision b" }], {
mode: "overwrite",
schema: schemaB,
});
const second = query.toArray();
await bStarted;
releaseA();
releaseB();
await Promise.all([first, second]);
expect(aCalls).toBe(1);
expect(bCalls).toBe(1);
});
test("stale FTS routing keeps newer vector preparation", async () => {
let vectorCalls = 0;
let markVectorStarted!: () => void;
const vectorStarted = new Promise<void>((resolve) => {
markVectorStarted = resolve;
});
let releaseVector!: () => void;
const vectorReleased = new Promise<void>((resolve) => {
releaseVector = resolve;
});
@register("stale-fts-race")
class RaceEmbedding extends EmbeddingFunction<string> {
ndims() {
return 1;
}
embeddingDataType() {
return new arrow.Float32();
}
async computeQueryEmbeddings() {
vectorCalls += 1;
markVectorStarted();
await vectorReleased;
return [0.1];
}
async computeSourceEmbeddings(values: string[]) {
return values.map(() => [0.1]);
}
}
const writer = await connect(tmpDir.name);
const ftsTable = await writer.createTable("stale_fts", [
{ text: "hello", vector: [0.0] },
]);
await ftsTable.createIndex("text", { config: Index.fts() });
const reader = await connect(tmpDir.name, {
readConsistencyInterval: 0,
});
const tracked = await reader.openTable("stale_fts");
type Snapshot = {
schema: () => Promise<Buffer>;
};
type NativeWithSnapshot = {
querySnapshot: () => Promise<Snapshot>;
};
const native = (tracked as unknown as { inner: NativeWithSnapshot })
.inner;
const querySnapshot = native.querySnapshot.bind(native);
let snapshotCalls = 0;
let markStaleSchemaStarted!: () => void;
const staleSchemaStarted = new Promise<void>((resolve) => {
markStaleSchemaStarted = resolve;
});
let releaseStaleSchema!: () => void;
const staleSchemaReleased = new Promise<void>((resolve) => {
releaseStaleSchema = resolve;
});
native.querySnapshot = async () => {
const snapshot = await querySnapshot();
snapshotCalls += 1;
if (snapshotCalls === 1) {
const schema = snapshot.schema.bind(snapshot);
snapshot.schema = async () => {
markStaleSchemaStarted();
await staleSchemaReleased;
return await schema();
};
}
return snapshot;
};
const query = tracked.search("hello");
const staleFtsExecution = query.toArray();
await staleSchemaStarted;
const embedding = new RaceEmbedding();
const vectorSchema = LanceSchema({
text: embedding.sourceField(new arrow.Utf8()),
vector: embedding.vectorField(),
});
await writer.createTable("stale_fts", [{ text: "hello" }], {
mode: "overwrite",
schema: vectorSchema,
});
const vectorExecution = query.toArray();
await vectorStarted;
releaseStaleSchema();
await staleFtsExecution;
releaseVector();
await vectorExecution;
await query.toArray();
expect(vectorCalls).toBe(1);
});
test("tokenizes FTS queries by column or index name", async () => {
const db = await connect(tmpDir.name);
const data = [
@@ -2916,6 +3474,30 @@ describe("column name options", () => {
expect(results[1].query_index).toBe(1);
});
test("observes promised additional vectors while the query is pending", async () => {
const initialVector = new Promise<number[]>(() => undefined);
const query = table.query().nearestTo(initialVector);
const unhandled: unknown[] = [];
const onUnhandled = (reason: unknown) => unhandled.push(reason);
process.on("unhandledRejection", onUnhandled);
try {
query.addQueryVector(Promise.reject(new Error("extra vector failed")));
await new Promise<void>((resolve) => setImmediate(resolve));
expect(unhandled).toEqual([]);
const rejectedQuery = table
.query()
.nearestTo([0.1, 0.2])
.addQueryVector(Promise.reject(new Error("consumed vector failed")));
await expect(rejectedQuery.toArray()).rejects.toThrow(
"consumed vector failed",
);
} finally {
process.off("unhandledRejection", onUnhandled);
}
});
test("index and search multivectors", async () => {
const db = await connect(tmpDir.name);
const data = [];
+42 -2
View File
@@ -4,7 +4,15 @@
import { Field, Schema } from "../arrow";
import { sanitizeType } from "../sanitize";
import { EmbeddingFunction } from "./embedding_function";
import { EmbeddingFunctionConfig, getRegistry } from "./registry";
import {
EmbeddingFunctionConfig,
EmbeddingFunctionRegistry,
getRegistry as getGlobalRegistry,
registerBuiltIn,
} from "./registry";
type OpenAIModule = typeof import("./openai");
type TransformersModule = typeof import("./transformers");
export {
FieldOptions,
@@ -14,7 +22,39 @@ export {
EmbeddingFunctionConstructor,
} from "./embedding_function";
export * from "./registry";
export {
EmbeddingFunctionRegistry,
parseEmbeddingMetadata,
register,
} from "./registry";
export type {
CreateReturnType,
EmbeddingFunctionConfig,
EmbeddingFunctionCreate,
EmbeddingMetadataEntry,
ResolvedEmbeddingFunctionConfig,
} from "./registry";
function initializeBuiltInProviders() {
const { OpenAIEmbeddingFunction } = require("./openai") as OpenAIModule;
const { TransformersEmbeddingFunction } =
require("./transformers") as TransformersModule;
registerBuiltIn("openai", OpenAIEmbeddingFunction);
registerBuiltIn("huggingface", TransformersEmbeddingFunction);
}
/**
* Get the global embedding function registry.
*
* LanceDB built-in providers are initialized when this public API is first
* used, so importing the root package does not change automatic search
* selection for tables without embedding metadata.
*/
export function getRegistry(): EmbeddingFunctionRegistry {
initializeBuiltInProviders();
return getGlobalRegistry();
}
/**
* Create a schema with embedding functions.
+3 -2
View File
@@ -5,14 +5,13 @@ import type OpenAI from "openai";
import type { EmbeddingCreateParams } from "openai/resources/index";
import { Float, Float32 } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
import { register } from "./registry";
import { registerBuiltIn } from "./registry";
export type OpenAIOptions = {
apiKey: string;
model: EmbeddingCreateParams["model"];
};
@register("openai")
export class OpenAIEmbeddingFunction extends EmbeddingFunction<
string,
Partial<OpenAIOptions>
@@ -100,3 +99,5 @@ export class OpenAIEmbeddingFunction extends EmbeddingFunction<
return response.data[0].embedding;
}
}
registerBuiltIn("openai", OpenAIEmbeddingFunction);
+59 -1
View File
@@ -7,6 +7,10 @@ import {
} from "./embedding_function";
import "reflect-metadata";
const builtInFunctionsKey = Symbol.for(
"@lancedb/lancedb::embedding-built-in-functions::v1",
);
export type CreateReturnType<T> = T extends { init: () => Promise<void> }
? Promise<T>
: T;
@@ -59,6 +63,15 @@ export class EmbeddingFunctionRegistry {
};
}
/** @ignore */
setBuiltIn<
T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor,
>(name: string, ctor: T): T {
this.#functions.set(name, ctor);
Reflect.defineMetadata("lancedb::embedding::name", name, ctor);
return ctor;
}
get<T extends EmbeddingFunction<unknown>>(
name: string,
): EmbeddingFunctionCreate<T> | undefined;
@@ -96,6 +109,7 @@ export class EmbeddingFunctionRegistry {
*/
reset(this: EmbeddingFunctionRegistry) {
this.#functions.clear();
getBuiltInFunctions(this).clear();
}
/**
@@ -183,12 +197,56 @@ export class EmbeddingFunctionRegistry {
}
}
const _REGISTRY = new EmbeddingFunctionRegistry();
function getBuiltInFunctions(registry: EmbeddingFunctionRegistry): Set<string> {
const registryWithBuiltIns = registry as EmbeddingFunctionRegistry & {
[key: symbol]: Set<string> | undefined;
};
let builtInFunctions = registryWithBuiltIns[builtInFunctionsKey];
if (builtInFunctions === undefined) {
builtInFunctions = new Set<string>();
registryWithBuiltIns[builtInFunctionsKey] = builtInFunctions;
}
return builtInFunctions;
}
// Server bundlers can load the side-effect embedding entry points and the public
// embedding API from separate module graphs. Keep their registry shared.
const registryKey = Symbol.for(
"@lancedb/lancedb::embedding-function-registry::v1",
);
const registryGlobal = globalThis as typeof globalThis & {
[key: symbol]: EmbeddingFunctionRegistry | undefined;
};
function getGlobalRegistry(): EmbeddingFunctionRegistry {
const existingRegistry = registryGlobal[registryKey];
if (existingRegistry !== undefined) {
return existingRegistry;
}
const registry = new EmbeddingFunctionRegistry();
registryGlobal[registryKey] = registry;
return registry;
}
const _REGISTRY = getGlobalRegistry();
export function register(name?: string) {
return _REGISTRY.register(name);
}
/** @ignore */
export function registerBuiltIn<
T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor,
>(name: string, ctor: T): T {
const builtInFunctions = getBuiltInFunctions(_REGISTRY);
if (builtInFunctions.has(name)) {
return _REGISTRY.setBuiltIn(name, ctor);
}
_REGISTRY.register(name)(ctor);
builtInFunctions.add(name);
return ctor;
}
/**
* Utility function to get the global instance of the registry
* @returns `EmbeddingFunctionRegistry` The global instance of the registry
+3 -2
View File
@@ -3,7 +3,7 @@
import { Float, Float32 } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
import { register } from "./registry";
import { registerBuiltIn } from "./registry";
export type XenovaTransformerOptions = {
/** The wasm compatible model to use */
@@ -31,7 +31,6 @@ export type XenovaTransformerOptions = {
};
};
@register("huggingface")
export class TransformersEmbeddingFunction extends EmbeddingFunction<
string,
Partial<XenovaTransformerOptions>
@@ -158,6 +157,8 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction<
}
}
registerBuiltIn("huggingface", TransformersEmbeddingFunction);
const tensorDiv = (
src: import("@huggingface/transformers").Tensor,
divBy: number,
+1
View File
@@ -103,6 +103,7 @@ export {
} from "./native.js";
export {
AutoQuery,
ExecutableQuery,
Query,
QueryBase,
+200 -101
View File
@@ -100,6 +100,29 @@ export interface FullTextSearchOptions {
columns?: string | string[];
}
function nearestToNative(
inner: NativeQuery,
vector: Awaited<IntoVector>,
): NativeVectorQuery {
const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
if (raw) {
return inner.nearestToRaw(raw.data, raw.dtype);
}
return inner.nearestTo(Float32Array.from(vector as number[]));
}
function addQueryVectorToNative(
inner: NativeVectorQuery,
vector: Awaited<IntoVector>,
) {
const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
if (raw) {
inner.addQueryVectorRaw(raw.data, raw.dtype);
} else {
inner.addQueryVector(Float32Array.from(vector as number[]));
}
}
/** Common methods supported by all query types
*
* @see {@link Query}
@@ -111,13 +134,15 @@ export class QueryBase<
NativeQueryType extends NativeQuery | NativeVectorQuery | NativeTakeQuery,
> implements AsyncIterable<RecordBatch>
{
protected inner!: NativeQueryType | Promise<NativeQueryType>;
/**
* @hidden
*/
protected constructor(
protected inner: NativeQueryType | Promise<NativeQueryType>,
) {
// intentionally empty
protected constructor(inner?: NativeQueryType | Promise<NativeQueryType>) {
if (inner !== undefined) {
this.inner = inner;
}
}
// call a function on the inner (either a promise or the actual object)
@@ -135,6 +160,15 @@ export class QueryBase<
}
}
/**
* Return the native query used by the next terminal operation.
*
* @hidden
*/
protected async getInner(): Promise<NativeQueryType> {
return this.inner;
}
/**
* Return only the specified columns.
*
@@ -207,16 +241,11 @@ export class QueryBase<
/**
* @hidden
*/
protected nativeExecute(
protected async nativeExecute(
options?: Partial<QueryExecutionOptions>,
): Promise<NativeBatchIterator> {
if (this.inner instanceof Promise) {
return this.inner.then((inner) =>
inner.execute(options?.maxBatchLength, options?.timeoutMs),
);
} else {
return this.inner.execute(options?.maxBatchLength, options?.timeoutMs);
}
const inner = await this.getInner();
return inner.execute(options?.maxBatchLength, options?.timeoutMs);
}
/**
@@ -245,12 +274,7 @@ export class QueryBase<
/** Collect the results as an Arrow @see {@link ArrowTable}. */
async toArrow(options?: Partial<QueryExecutionOptions>): Promise<ArrowTable> {
const batches = [];
let inner;
if (this.inner instanceof Promise) {
inner = await this.inner;
} else {
inner = this.inner;
}
const inner = await this.getInner();
for await (const batch of new RecordBatchIterable(inner, options)) {
batches.push(batch);
}
@@ -279,11 +303,8 @@ export class QueryBase<
* @returns A Promise that resolves to a string containing the query execution plan explanation.
*/
async explainPlan(verbose = false): Promise<string> {
if (this.inner instanceof Promise) {
return this.inner.then((inner) => inner.explainPlan(verbose));
} else {
return this.inner.explainPlan(verbose);
}
const inner = await this.getInner();
return inner.explainPlan(verbose);
}
/**
@@ -321,13 +342,8 @@ export class QueryBase<
distributedMetrics?: AnalyzePlanDistributedMetrics,
): Promise<string> {
const distributedMetricsMode = distributedMetrics ?? "aggregate";
if (this.inner instanceof Promise) {
return this.inner.then((inner) =>
inner.analyzePlan(distributedMetricsMode),
);
} else {
return this.inner.analyzePlan(distributedMetricsMode);
}
const inner = await this.getInner();
return inner.analyzePlan(distributedMetricsMode);
}
/**
@@ -339,12 +355,8 @@ export class QueryBase<
* @returns An Arrow Schema describing the output columns.
*/
async outputSchema(): Promise<import("./arrow").Schema> {
let schemaBuffer: Buffer;
if (this.inner instanceof Promise) {
schemaBuffer = await this.inner.then((inner) => inner.outputSchema());
} else {
schemaBuffer = await this.inner.outputSchema();
}
const inner = await this.getInner();
const schemaBuffer = await inner.outputSchema();
const schema = tableFromIPC(schemaBuffer).schema;
return schema;
}
@@ -356,7 +368,7 @@ export class StandardQueryBase<
extends QueryBase<NativeQueryType>
implements ExecutableQuery
{
constructor(inner: NativeQueryType | Promise<NativeQueryType>) {
constructor(inner?: NativeQueryType | Promise<NativeQueryType>) {
super(inner);
}
@@ -510,6 +522,13 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
super(inner);
}
/**
* @hidden
*/
protected doVectorCall(fn: (inner: NativeVectorQuery) => void) {
super.doCall(fn);
}
/**
* Set the number of partitions to search (probe)
*
@@ -537,7 +556,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* the minimum and maximum to the same value.
*/
nprobes(nprobes: number): VectorQuery {
super.doCall((inner) => inner.nprobes(nprobes));
this.doVectorCall((inner) => inner.nprobes(nprobes));
return this;
}
@@ -551,7 +570,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* but will also increase latency.
*/
minimumNprobes(minimumNprobes: number): VectorQuery {
super.doCall((inner) => inner.minimumNprobes(minimumNprobes));
this.doVectorCall((inner) => inner.minimumNprobes(minimumNprobes));
return this;
}
@@ -565,7 +584,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* potential false negatives.
*/
maximumNprobes(maximumNprobes: number): VectorQuery {
super.doCall((inner) => inner.maximumNprobes(maximumNprobes));
this.doVectorCall((inner) => inner.maximumNprobes(maximumNprobes));
return this;
}
@@ -578,7 +597,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* `undefined` means no lower or upper bound.
*/
distanceRange(lowerBound?: number, upperBound?: number): VectorQuery {
super.doCall((inner) => inner.distanceRange(lowerBound, upperBound));
this.doVectorCall((inner) => inner.distanceRange(lowerBound, upperBound));
return this;
}
@@ -592,7 +611,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* also increase the latency of your query. The default value is 1.5*limit.
*/
ef(ef: number): VectorQuery {
super.doCall((inner) => inner.ef(ef));
this.doVectorCall((inner) => inner.ef(ef));
return this;
}
@@ -606,7 +625,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* whose data type is a fixed-size-list of floats.
*/
column(column: string): VectorQuery {
super.doCall((inner) => inner.column(column));
this.doVectorCall((inner) => inner.column(column));
return this;
}
@@ -627,7 +646,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
distanceType(
distanceType: Required<IvfPqOptions>["distanceType"],
): VectorQuery {
super.doCall((inner) => inner.distanceType(distanceType));
this.doVectorCall((inner) => inner.distanceType(distanceType));
return this;
}
@@ -661,7 +680,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* distance between the query vector and the actual uncompressed vector.
*/
refineFactor(refineFactor: number): VectorQuery {
super.doCall((inner) => inner.refineFactor(refineFactor));
this.doVectorCall((inner) => inner.refineFactor(refineFactor));
return this;
}
@@ -686,7 +705,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* factor can often help restore some of the results lost by post filtering.
*/
postfilter(): VectorQuery {
super.doCall((inner) => inner.postfilter());
this.doVectorCall((inner) => inner.postfilter());
return this;
}
@@ -700,7 +719,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
* calculate your recall to select an appropriate value for nprobes.
*/
bypassVectorIndex(): VectorQuery {
super.doCall((inner) => inner.bypassVectorIndex());
this.doVectorCall((inner) => inner.bypassVectorIndex());
return this;
}
@@ -716,35 +735,31 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
*/
addQueryVector(vector: IntoVector): VectorQuery {
if (vector instanceof Promise) {
// Observe the promise as soon as it is accepted. The existing native
// query may still be pending, and delaying observation until it resolves
// can otherwise surface a fast rejection as unhandled.
const settledVector = vector.then(
(value) => ({ status: "fulfilled" as const, value }),
(reason) => ({ status: "rejected" as const, reason }),
);
const res = (async () => {
try {
const v = await vector;
// biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
const value: any = this.addQueryVector(v);
const inner = value.inner as
| NativeVectorQuery
| Promise<NativeVectorQuery>;
return inner;
} catch (e) {
return Promise.reject(e);
const inner = await this.getInner();
const outcome = await settledVector;
if (outcome.status === "rejected") {
throw outcome.reason;
}
addQueryVectorToNative(inner, outcome.value);
return inner;
})();
return new VectorQuery(res);
} else {
super.doCall((inner) => {
const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
if (raw) {
inner.addQueryVectorRaw(raw.data, raw.dtype);
} else {
inner.addQueryVector(Float32Array.from(vector as number[]));
}
});
this.doVectorCall((inner) => addQueryVectorToNative(inner, vector));
return this;
}
}
rerank(reranker: Reranker): VectorQuery {
super.doCall((inner) =>
this.doVectorCall((inner) =>
inner.rerank(async (args) => {
const vecResults = await fromBufferToRecordBatch(args.vecResults);
const ftsResults = await fromBufferToRecordBatch(args.ftsResults);
@@ -763,6 +778,71 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
}
}
/**
* Create a string query whose vector/FTS routing is resolved against the active
* table schema when the query executes.
*
* @hidden
*/
export function createAutoQuery(
table: NativeTable,
query: string,
columns: string[] | null,
getVector: (metadata: string) => Promise<Awaited<IntoVector>>,
): AutoQuery {
type RouteSnapshot = {
table: NativeTable;
embeddingMetadata: string | undefined;
};
type CachedPreparation = {
metadata: string;
vector: Promise<Awaited<IntoVector>>;
};
let cachedPreparation: CachedPreparation | undefined;
const snapshotRoute = async (): Promise<RouteSnapshot> => {
const snapshot = await table.querySnapshot();
const schema = tableFromIPC(await snapshot.schema()).schema;
return {
table: snapshot,
embeddingMetadata: schema.metadata.get("embedding_functions"),
};
};
const createInner = async (): Promise<NativeQuery | NativeVectorQuery> => {
const route = await snapshotRoute();
if (route.embeddingMetadata === undefined) {
const inner = route.table.query();
inner.fullTextSearch({ query, columns });
return inner;
}
const metadata = route.embeddingMetadata;
if (cachedPreparation?.metadata !== metadata) {
cachedPreparation = {
metadata,
vector: Promise.resolve().then(() => getVector(metadata)),
};
}
const preparation = cachedPreparation;
let vector: Awaited<IntoVector>;
try {
vector = await preparation.vector;
} catch (error) {
if (cachedPreparation === preparation) {
cachedPreparation = undefined;
}
throw error;
}
return nearestToNative(route.table.query(), vector);
};
return new AutoQuery(createInner);
}
/**
* A query that returns a subset of the rows in the table.
*
@@ -788,6 +868,51 @@ export class TakeQuery extends QueryBase<NativeTakeQuery> {
}
}
/**
* A builder for automatic string searches.
*
* Automatic search determines whether to use full-text or vector search from
* the table revision selected for each execution. This builder exposes the
* common operations supported by both query families.
*
* @hideconstructor
*/
export class AutoQuery extends StandardQueryBase<
NativeQuery | NativeVectorQuery
> {
private readonly calls: Array<
(inner: NativeQuery | NativeVectorQuery) => void
> = [];
/** @hidden */
constructor(
private readonly createInner: () => Promise<
NativeQuery | NativeVectorQuery
>,
) {
super();
}
/** @hidden */
protected override doCall(
fn: (inner: NativeQuery | NativeVectorQuery) => void,
) {
this.calls.push(fn);
}
/** @hidden */
protected override async getInner(): Promise<
NativeQuery | NativeVectorQuery
> {
const calls = [...this.calls];
const inner = await this.createInner();
for (const call of calls) {
call(inner);
}
return inner;
}
}
/** A builder for LanceDB queries.
*
* @see {@link Table#query}, {@link Table#search}
@@ -840,45 +965,19 @@ export class Query extends StandardQueryBase<NativeQuery> {
* a default `limit` of 10 will be used. @see {@link Query#limit}
*/
nearestTo(vector: IntoVector): VectorQuery {
const callNearestTo = (
inner: NativeQuery,
resolved: Float32Array | Float64Array | Uint8Array | number[],
): NativeVectorQuery => {
const raw = Array.isArray(resolved)
? null
: extractVectorBuffer(resolved);
if (raw) {
return inner.nearestToRaw(raw.data, raw.dtype);
}
return inner.nearestTo(Float32Array.from(resolved as number[]));
};
if (this.inner instanceof Promise) {
const nativeQuery = this.inner.then(async (inner) => {
const resolved = vector instanceof Promise ? await vector : vector;
return callNearestTo(inner, resolved);
});
const inner = this.inner;
if (inner instanceof Promise) {
const nativeQuery = inner.then(async (resolvedInner) =>
nearestToNative(resolvedInner, await vector),
);
return new VectorQuery(nativeQuery);
}
if (vector instanceof Promise) {
const res = (async () => {
try {
const v = await vector;
// biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
const value: any = this.nearestTo(v);
const inner = value.inner as
| NativeVectorQuery
| Promise<NativeVectorQuery>;
return inner;
} catch (e) {
return Promise.reject(e);
}
})();
return new VectorQuery(res);
} else {
const vectorQuery = callNearestTo(this.inner, vector);
return new VectorQuery(vectorQuery);
return new VectorQuery(
vector.then((resolvedVector) => nearestToNative(inner, resolvedVector)),
);
}
return new VectorQuery(nearestToNative(inner, vector));
}
nearestToText(query: string | FullTextQuery, columns?: string[]): Query {
+31 -14
View File
@@ -43,10 +43,12 @@ import {
Table as _NativeTable,
} from "./native";
import {
AutoQuery,
FullTextQuery,
Query,
TakeQuery,
VectorQuery,
createAutoQuery,
instanceOfFullTextQuery,
} from "./query";
import { sanitizeType } from "./sanitize";
@@ -523,7 +525,7 @@ export abstract class Table {
query: string | IntoVector | MultiVector | FullTextQuery,
queryType?: string,
ftsColumns?: string | string[],
): VectorQuery | Query;
): VectorQuery | Query | AutoQuery;
/**
* Search the table with a given query vector.
*
@@ -975,10 +977,11 @@ export class LocalTable extends Table {
return this.inner.display();
}
private async getEmbeddingFunctions(): Promise<
Map<string, EmbeddingFunctionConfig>
> {
const schema = await this.schema();
private async getEmbeddingFunctions(
inner: _NativeTable = this.inner,
): Promise<Map<string, EmbeddingFunctionConfig>> {
const schemaBuf = await inner.schema();
const schema = tableFromIPC(schemaBuf).schema;
const registry = getRegistry();
return registry.parseFunctions(schema.metadata);
}
@@ -1160,7 +1163,7 @@ export class LocalTable extends Table {
query: string | IntoVector | MultiVector | FullTextQuery,
queryType: string = "auto",
ftsColumns?: string | string[],
): VectorQuery | Query {
): VectorQuery | Query | AutoQuery {
if (typeof query !== "string" && !instanceOfFullTextQuery(query)) {
if (queryType === "fts") {
throw new Error("Cannot perform full text search on a vector query");
@@ -1175,14 +1178,28 @@ export class LocalTable extends Table {
});
}
// The query type is auto or vector
// fall back to full text search if no embedding functions are defined and the query is a string
if (
queryType === "auto" &&
(getRegistry().length() === 0 || instanceOfFullTextQuery(query))
) {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
if (queryType === "auto") {
if (instanceOfFullTextQuery(query)) {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
});
}
const columns =
typeof ftsColumns === "string" ? [ftsColumns] : (ftsColumns ?? null);
return createAutoQuery(this.inner, query, columns, async (metadata) => {
const functions = await getRegistry().parseFunctions(
new Map([["embedding_functions", metadata]]),
);
// TODO: Support multiple embedding functions
const embeddingFunc: EmbeddingFunctionConfig | undefined = functions
.values()
.next().value;
// The route only calls this callback when embedding metadata exists.
// parseFunctions either yields a provider or reports malformed metadata.
if (!embeddingFunc)
throw new Error("Invalid embedding function metadata");
return await embeddingFunc.function.computeQueryEmbeddings(query);
});
}
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": [
"win32"
],
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",
+2 -2
View File
@@ -1,12 +1,12 @@
{
"name": "@lancedb/lancedb",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@lancedb/lancedb",
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"cpu": [
"x64",
"arm64"
+1 -1
View File
@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.38.0-beta.8",
"version": "0.38.0-beta.10",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
+13
View File
@@ -278,6 +278,13 @@ impl Table {
Ok(Query::new(self.inner_ref()?.query()))
}
/// Return a read-only table handle pinned to the current query revision.
#[napi(catch_unwind)]
pub async fn query_snapshot(&self) -> napi::Result<Self> {
let snapshot = self.inner_ref()?.query_snapshot().await.default_error()?;
Ok(Self::new(snapshot))
}
#[napi(catch_unwind)]
pub fn take_offsets(&self, offsets: Vec<i64>) -> napi::Result<TakeQuery> {
Ok(TakeQuery::new(
@@ -554,6 +561,12 @@ impl Table {
.default_error()
}
#[napi(catch_unwind)]
pub async fn checkout_current(&self) -> napi::Result<Self> {
let table = self.inner_ref()?.checkout_current().await.default_error()?;
Ok(Self::new(table))
}
#[napi(catch_unwind)]
pub async fn checkout(&self, version: i64) -> napi::Result<()> {
self.inner_ref()?
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
publish = false
edition.workspace = true
description = "Python bindings for LanceDB"
+4 -1
View File
@@ -101,9 +101,12 @@ azure = ["adlfs>=2024.2.0"]
[tool.maturin]
python-source = "python"
module-name = "lancedb._lancedb"
# uv installs the project as an editable package before `uv run`, so keep that
# bootstrap build consistent with `maturin develop`.
editable-profile = "dev"
[build-system]
requires = ["maturin>=1.9.4"]
requires = ["maturin>=1.10"]
build-backend = "maturin"
[tool.ruff.lint]
+21
View File
@@ -179,6 +179,18 @@ def connect(
... },
... )
For Azure Blob Storage, credentials can be passed directly without setting
environment variables:
>>> azure_storage_options = {
... "account_name": "some-account",
... "account_key": "some-key",
... }
>>> db = lancedb.connect( # doctest: +SKIP
... "az://my-container/my-database",
... storage_options=azure_storage_options,
... )
For tests and temporary data, use an in-memory database:
>>> db = lancedb.connect("memory://")
@@ -465,6 +477,10 @@ async def connect_async(
--------
>>> import lancedb
>>> azure_storage_options = {
... "account_name": "some-account",
... "account_key": "some-key",
... }
>>> async def doctest_example():
... # For a local directory, provide a path to the database
... db = await lancedb.connect_async("~/.lancedb")
@@ -472,6 +488,11 @@ async def connect_async(
... db = await lancedb.connect_async("s3://my-bucket/lancedb",
... storage_options={
... "aws_access_key_id": "***"})
... # Azure credentials can also be passed directly
... db = await lancedb.connect_async(
... "az://my-container/my-database",
... storage_options=azure_storage_options,
... )
... # For tests and temporary data, use an in-memory database
... db = await lancedb.connect_async("memory://")
... # Connect to LanceDB cloud
+1
View File
@@ -283,6 +283,7 @@ class Table:
mode: Literal["append", "overwrite"],
progress: Optional[Any] = None,
write_parallelism: Optional[int] = None,
allow_external_blob_outside_bases: bool = False,
) -> AddResult: ...
async def update(
self, updates: Dict[str, str], where: Optional[str]
+5 -32
View File
@@ -4,7 +4,7 @@
"""Canonical Function values exchanged with LanceDB Enterprise services.
These immutable models contain client/wire state only. Catalog persistence,
environment bake, secret resolution, and execution are owned by Sophon.
environment bake, and execution are owned by Sophon.
``RefreshColumnResult`` is also the backend-neutral result of a local
expression-backed refresh job.
"""
@@ -228,7 +228,7 @@ class PythonEnvironmentSpec(_RemoteValue):
class PythonRuntimeSpec(_RemoteValue):
"""Remote runtime definition with non-secret environment values.
"""Remote runtime definition with environment values.
V1 supports ``kind="python"``. Newer runtime kinds remain readable, while
their unknown payload fields are intentionally not retained by the client.
@@ -267,7 +267,6 @@ class FunctionVersion(_RemoteValue):
runtime: PythonRuntimeSpec
runtime_digest: str
environment_digest: str
required_secrets: tuple[str, ...] = ()
created_at: str
def __call__(self, **inputs: Any) -> FunctionApplication:
@@ -329,17 +328,12 @@ class FunctionVersion(_RemoteValue):
class FunctionRegistrationRequest(_RemoteValue):
"""Stable remote registration envelope produced by :func:`udf`.
Only secret names are represented. Secret values are resolved inside the
remote service and have no client request field.
"""
"""Stable remote registration envelope produced by :func:`udf`."""
name: str
artifact: FunctionArtifactRequest
signature: FunctionSignature
runtime: PythonRuntimeSpec
required_secrets: tuple[str, ...] = ()
class FunctionVersionRef(_OpenRemoteValue):
@@ -484,7 +478,6 @@ class RefreshColumnResult(_RemoteValue):
_FUNCTION_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_.-]*$")
_SECRET_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
_GRAMMAR_PRIMITIVES = (
@@ -915,7 +908,6 @@ class UdfDefinition:
output_schema: Optional[pa.DataType | pa.Field | pa.Schema],
pip: tuple[str, ...],
env: Mapping[str, str],
secrets: tuple[str, ...],
python_version: Optional[str],
):
function_name = name or function.__name__
@@ -930,18 +922,6 @@ class UdfDefinition:
for key, value in environment.items()
):
raise TypeError("Function env keys and values must be strings")
required_secrets = tuple(sorted(set(secrets)))
invalid_secrets = [
secret for secret in required_secrets if not _SECRET_NAME.fullmatch(secret)
]
if invalid_secrets:
raise ValueError(f"invalid Function secret names: {invalid_secrets!r}")
overlap = set(environment) & set(required_secrets)
if overlap:
raise ValueError(
f"Function env and secret names must be disjoint: {sorted(overlap)!r}"
)
signature = _infer_signature(function, input_schema, output_schema)
source = _package_source(function)
digest = f"sha256:{hashlib.sha256(source).hexdigest()}"
@@ -970,7 +950,6 @@ class UdfDefinition:
),
signature=signature,
runtime=runtime,
required_secrets=required_secrets,
)
functools.update_wrapper(self, function)
@@ -996,7 +975,6 @@ def udf(
output_schema: Optional[pa.DataType | pa.Field | pa.Schema] = None,
pip: tuple[str, ...] | list[str] = (),
env: Optional[Mapping[str, str]] = None,
secrets: tuple[str, ...] | list[str] = (),
python_version: Optional[str] = None,
) -> Callable[[Callable[..., Any]], UdfDefinition]: ...
@@ -1009,7 +987,6 @@ def udf(
output_schema: Optional[pa.DataType | pa.Field | pa.Schema] = None,
pip: tuple[str, ...] | list[str] = (),
env: Optional[Mapping[str, str]] = None,
secrets: tuple[str, ...] | list[str] = (),
python_version: Optional[str] = None,
):
"""Prepare a scalar Python callable for remote Function registration.
@@ -1034,10 +1011,7 @@ def udf(
pip : sequence of str, optional
Pip requirements for the remote environment.
env : mapping of str to str, optional
Non-secret environment variables. Use ``secrets`` for credentials.
secrets : sequence of str, optional
Names of secrets resolved by the remote service. Secret values are not
accepted by this API or included in the registration request.
Environment variables included in the Function definition.
python_version : str, optional
Remote Python major/minor version. Defaults to the client version.
@@ -1059,7 +1033,7 @@ def udf(
Examples
--------
>>> from lancedb import udf
>>> @udf(pip=["numpy==2.2.0"], secrets=["MODEL_TOKEN"])
>>> @udf(pip=["numpy==2.2.0"])
... def score(value: float) -> float:
... return value * 2
>>> score(1.5)
@@ -1074,7 +1048,6 @@ def udf(
output_schema=output_schema,
pip=tuple(pip),
env={} if env is None else env,
secrets=tuple(secrets),
python_version=python_version,
)
+4
View File
@@ -610,6 +610,7 @@ class RemoteTable(Table):
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
write_parallelism: Optional[int] = None,
allow_external_blob_outside_bases: bool = False,
) -> AddResult:
"""Add more data to the [Table][lancedb.table.Table].
@@ -642,6 +643,8 @@ class RemoteTable(Table):
data in flight. Defaults to an estimate based on the data size,
capped at the number of CPU cores. Lower this if bulk ingestion is
using too much memory.
allow_external_blob_outside_bases: bool, default False
Not supported on LanceDB Cloud. Setting this raises.
Returns
-------
@@ -658,6 +661,7 @@ class RemoteTable(Table):
fill_value=fill_value,
progress=progress,
write_parallelism=write_parallelism,
allow_external_blob_outside_bases=allow_external_blob_outside_bases,
)
)
finally:
+15
View File
@@ -1269,6 +1269,7 @@ class Table(ABC):
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
write_parallelism: Optional[int] = None,
allow_external_blob_outside_bases: bool = False,
) -> AddResult:
"""Add more data to the [Table][lancedb.table.Table].
@@ -1320,6 +1321,10 @@ class Table(ABC):
data in flight. Defaults to an estimate based on the data size,
capped at the number of CPU cores. Lower this if bulk ingestion is
using too much memory.
allow_external_blob_outside_bases: bool, default False
Store blob URIs that sit outside registered blob bases. The row
keeps a reference, so the object has to stay readable. Local
tables only.
Returns
-------
@@ -3409,6 +3414,7 @@ class LanceTable(Table):
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
write_parallelism: Optional[int] = None,
allow_external_blob_outside_bases: bool = False,
) -> AddResult:
"""Add data to the table.
If vector columns are missing and the table
@@ -3436,6 +3442,9 @@ class LanceTable(Table):
data in flight. Defaults to an estimate based on the data size,
capped at the number of CPU cores. Lower this if bulk ingestion is
using too much memory.
allow_external_blob_outside_bases: bool, default False
Allow blob URIs outside registered bases. See :meth:`Table.add`.
Local tables only.
Returns
-------
@@ -3452,6 +3461,7 @@ class LanceTable(Table):
fill_value=fill_value,
progress=progress,
write_parallelism=write_parallelism,
allow_external_blob_outside_bases=allow_external_blob_outside_bases,
)
)
finally:
@@ -5365,6 +5375,7 @@ class AsyncTable:
fill_value: Optional[float] = None,
progress: Optional[Union[bool, Callable, Any]] = None,
write_parallelism: Optional[int] = None,
allow_external_blob_outside_bases: bool = False,
) -> AddResult:
"""Add more data to the [AsyncTable][lancedb.table.AsyncTable].
@@ -5395,6 +5406,9 @@ class AsyncTable:
data in flight. Defaults to an estimate based on the data size,
capped at the number of CPU cores. Lower this if bulk ingestion is
using too much memory.
allow_external_blob_outside_bases: bool, default False
Allow blob URIs outside registered bases. See :meth:`Table.add`.
Local tables only.
"""
schema = await self.schema()
@@ -5431,6 +5445,7 @@ class AsyncTable:
mode or "append",
progress=progress,
write_parallelism=write_parallelism,
allow_external_blob_outside_bases=allow_external_blob_outside_bases,
)
except RuntimeError as e:
if "Cast error" in str(e):
+68
View File
@@ -617,3 +617,71 @@ def test_fetch_blobs_nested_path_survives_sort_after_query():
def _identifiable_payload(size: int) -> bytes:
block = 256
return b"".join(bytes([i % 256]) * block for i in range(size // block))
def _external_uri_blob_array(uris):
blob_type = lancedb.blob("image").type
storage_type = blob_type.storage_type
child_names = [field.name for field in storage_type]
assert "uri" in child_names, "blob layout no longer has a uri child"
children = [
pa.array(uris if field.name == "uri" else [None] * len(uris), type=field.type)
for field in storage_type
]
storage = pa.StructArray.from_arrays(children, fields=list(storage_type))
return pa.ExtensionArray.from_storage(blob_type, storage)
def _external_uri_table_and_rows(name, uris):
db = lancedb.connect("memory:///")
schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
table = db.create_table(name, schema=schema)
rows = pa.Table.from_arrays(
[
pa.array(range(len(uris)), type=pa.int64()),
_external_uri_blob_array(uris),
],
schema=schema,
)
return table, rows
def test_add_external_uri_struct_round_trips_with_flag(tmp_path):
payload = b"external-uri-bytes"
blob_path = tmp_path / "payload.bin"
blob_path.write_bytes(payload)
table, rows = _external_uri_table_and_rows("external_struct", [blob_path.as_uri()])
table.add(rows, allow_external_blob_outside_bases=True)
hits = table.search().to_arrow()
blobs = table.fetch_blobs("image", hits)
assert blobs[0].as_py() == payload
def test_add_external_uri_without_flag_raises(tmp_path):
blob_path = tmp_path / "payload.bin"
blob_path.write_bytes(b"unreachable")
table, rows = _external_uri_table_and_rows("external_no_flag", [blob_path.as_uri()])
with pytest.raises(ValueError, match="allow_external_blob_outside_bases"):
table.add(rows)
assert table.count_rows() == 0
def test_add_external_uri_string_round_trips_with_flag(tmp_path):
payload = b"external-uri-bytes"
blob_path = tmp_path / "payload.bin"
blob_path.write_bytes(payload)
db = lancedb.connect("memory:///")
schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
table = db.create_table("external_string", schema=schema)
table.add(
[{"id": 1, "image": blob_path.as_uri()}],
allow_external_blob_outside_bases=True,
)
hits = table.search().to_arrow()
blobs = table.fetch_blobs("image", hits)
assert blobs[0].as_py() == payload
@@ -37,21 +37,6 @@ def job_result(name: str) -> dict:
return json.loads(fixture(name))["result"]
def assert_no_secret_values(value):
if isinstance(value, dict):
for key, child in value.items():
assert key not in {
"secret_value",
"secret_values",
"resolved_secret",
"resolved_secrets",
}
assert_no_secret_values(child)
elif isinstance(value, list):
for child in value:
assert_no_secret_values(child)
def test_public_function_values_are_in_api_reference():
docs = Path(__file__).parents[3] / "docs" / "src" / "python" / "python.md"
rendered = docs.read_text()
@@ -109,7 +94,6 @@ def test_function_version_identity_is_immutable_and_exact():
version = FunctionVersion.from_json(json.dumps(value))
assert version.name == "embed"
assert version.version == "fv_01K3EXACT"
assert version.required_secrets == ("HF_TOKEN",)
with pytest.raises((TypeError, ValueError)):
version.version = "fv_changed"
@@ -292,15 +276,6 @@ def test_refresh_result_rejects_non_u64_values(field):
RefreshColumnResult.from_json(json.dumps(value))
def test_canonical_client_values_contain_secret_names_only():
version = FunctionVersion.from_json(
json.dumps(job_result("remote_function_job.json"))
)
canonical = json.loads(version.to_canonical_json())
assert canonical["required_secrets"] == ["HF_TOKEN"]
assert_no_secret_values(canonical)
class _FunctionDeclarationInner:
def __init__(self):
self.calls = []
@@ -39,28 +39,12 @@ FIXTURES = (
@udf(
pip=["numpy>=2"],
env={"MODE": "test"},
secrets=["API_TOKEN"],
python_version="3.12",
)
def normalize_score(value: float) -> float:
return value / 100.0
def _assert_no_secret_values(value):
if isinstance(value, dict):
for key, child in value.items():
assert key not in {
"secret_value",
"secret_values",
"resolved_secret",
"resolved_secrets",
}
_assert_no_secret_values(child)
elif isinstance(value, list):
for child in value:
_assert_no_secret_values(child)
def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
assert isinstance(normalize_score, UdfDefinition)
assert normalize_score(25.0) == 0.25
@@ -75,8 +59,6 @@ def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
"kind": "scalar_to_arrow_batch",
"version": 1,
}
assert request["required_secrets"] == ["API_TOKEN"]
_assert_no_secret_values(request)
def _run_packaged(definition, *args):
@@ -370,7 +352,6 @@ def test_udf_recursion_versus_a_rebound_module_name(tmp_path):
output_schema=None,
pip=(),
env={},
secrets=(),
python_version=None,
)
with pytest.raises(ValueError, match="binds that name to another value"):
@@ -525,14 +506,6 @@ def test_annotation_and_explicit_schema_validation_fail_closed():
return value
def test_environment_rejects_secret_value_overlap():
with pytest.raises(ValueError, match="must be disjoint"):
@udf(env={"TOKEN": "plaintext"}, secrets=["TOKEN"])
def overlapping(value: int) -> int:
return value
def test_local_function_catalog_operations_are_not_supported(tmp_path):
db = lancedb.connect(tmp_path)
message = "Function catalog operations are not supported by this database"
@@ -569,7 +542,6 @@ def _mock_remote_function_catalog():
"runtime": body["runtime"],
"runtime_digest": "sha256:runtime",
"environment_digest": "sha256:environment",
"required_secrets": body.get("required_secrets", []),
"created_at": "2026-08-21T00:00:00Z",
}
response = {"job_id": "job-register"}
@@ -628,7 +600,6 @@ def test_remote_registration_job_and_exact_version_reopen_round_trip():
assert create_request == json.loads(
normalize_score.registration_request.to_canonical_json()
)
_assert_no_secret_values(create_request)
def test_blocking_remote_registration_returns_function_version():
+20
View File
@@ -4,6 +4,7 @@
import asyncio
import copy
from concurrent.futures import ThreadPoolExecutor
from datetime import timedelta
import threading
@@ -86,6 +87,25 @@ def test_s3_lifecycle(s3_bucket: str):
asyncio.run(test())
@pytest.mark.s3_test
def test_concurrent_open_table(s3_bucket: str):
uri = f"s3://{s3_bucket}/test_concurrent_open_table"
db = lancedb.connect(uri, storage_options=copy.copy(CONFIG))
db.create_table("test", pa.table({"x": [1, 2, 3]}))
num_workers = 32
barrier = threading.Barrier(num_workers)
def open_and_count(_):
barrier.wait()
return db.open_table("test").count_rows()
with ThreadPoolExecutor(max_workers=num_workers) as pool:
row_counts = list(pool.map(open_and_count, range(num_workers)))
assert row_counts == [3] * num_workers
@pytest.fixture()
def kms_key():
kms = get_boto3_client("kms", endpoint_url=CONFIG["aws_endpoint"])
+6 -2
View File
@@ -780,15 +780,19 @@ impl Table {
})
}
#[pyo3(signature = (data, mode, progress=None, write_parallelism=None))]
#[pyo3(signature = (data, mode, progress=None, write_parallelism=None, allow_external_blob_outside_bases=false))]
pub fn add<'a>(
self_: PyRef<'a, Self>,
data: PyScannable,
mode: String,
progress: Option<Py<PyAny>>,
write_parallelism: Option<usize>,
allow_external_blob_outside_bases: bool,
) -> PyResult<Bound<'a, PyAny>> {
let mut op = self_.inner_ref()?.add(data);
let mut op = self_
.inner_ref()?
.add(data)
.allow_external_blob_outside_bases(allow_external_blob_outside_bases);
if mode == "append" {
op = op.mode(AddDataMode::Append);
} else if mode == "overwrite" {
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb"
version = "0.38.0-beta.8"
version = "0.38.0-beta.10"
edition.workspace = true
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license.workspace = true
+54 -1
View File
@@ -1476,7 +1476,7 @@ mod tests {
use crate::table::{AnyQuery, WriteOptions};
use arrow_array::{Int32Array, RecordBatch, StringArray};
use arrow_schema::{DataType, Field, Schema, SchemaRef};
use futures::{TryStreamExt, stream::once};
use futures::{TryStreamExt, future::try_join_all, stream::once};
use std::path::PathBuf;
use std::sync::Arc;
use std::time::Duration;
@@ -1614,6 +1614,59 @@ mod tests {
);
}
#[tokio::test]
async fn test_concurrent_open_table_reuses_connection_object_store() {
let tempdir = tempdir().unwrap();
let uri = tempdir.path().to_str().unwrap();
let session = Arc::new(lance::session::Session::default());
let request = ConnectRequest {
uri: uri.to_string(),
#[cfg(feature = "remote")]
client_config: Default::default(),
options: Default::default(),
namespace_client_properties: Default::default(),
manifest_enabled: false,
read_consistency_interval: None,
session: Some(session.clone()),
};
let db = ListingDatabase::connect_with_options(&request)
.await
.unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
db.create_table(CreateTableRequest {
name: "test".to_string(),
namespace_path: vec![],
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
mode: CreateTableMode::Create,
write_options: Default::default(),
location: None,
namespace_client: None,
})
.await
.unwrap();
let before = session.store_registry().stats();
let opened_tables = try_join_all((0..32).map(|_| {
db.open_table(OpenTableRequest {
name: "test".to_string(),
namespace_path: vec![],
index_cache_size: None,
lance_read_params: None,
location: None,
namespace_client: None,
managed_versioning: None,
})
}))
.await
.unwrap();
let after = session.store_registry().stats();
assert_eq!(opened_tables.len(), 32);
assert_eq!(after.misses, before.misses);
assert_eq!(after.active_stores, before.active_stores);
assert!(after.hits >= before.hits + 32);
}
#[tokio::test]
async fn test_listing_database_root_ops_do_not_create_manifest() {
let tempdir = tempdir().unwrap();
+2 -18
View File
@@ -5,7 +5,7 @@
//! backend-neutral terminal result of a computed-column refresh.
//!
//! This module contains client/wire values only. Catalog persistence,
//! environment bake, secret resolution, and execution are owned by Sophon.
//! environment bake, and execution are owned by Sophon.
use std::collections::BTreeMap;
@@ -195,9 +195,6 @@ pub struct PythonEnvironmentSpec {
}
/// Reproducible Python runtime definition understood by Sophon.
///
/// `env` contains non-secret values. Secret values have no client model;
/// [`FunctionVersion::required_secrets`] contains names only.
#[derive(Debug, Clone, PartialEq, Eq)]
#[non_exhaustive]
pub enum PythonRuntimeSpec {
@@ -239,7 +236,7 @@ impl PythonRuntimeSpec {
}
}
/// Non-secret environment variables, or `None` for an unknown kind.
/// Environment variables, or `None` for an unknown kind.
pub fn env(&self) -> Option<&BTreeMap<String, String>> {
match self {
Self::Python { env, .. } => Some(env),
@@ -324,8 +321,6 @@ pub struct FunctionVersion {
runtime: PythonRuntimeSpec,
runtime_digest: String,
environment_digest: String,
#[serde(default, skip_serializing_if = "Vec::is_empty")]
required_secrets: Vec<String>,
created_at: String,
}
@@ -358,11 +353,6 @@ impl FunctionVersion {
&self.environment_digest
}
/// Required secret names. Resolved values exist only inside Sophon.
pub fn required_secrets(&self) -> &[String] {
&self.required_secrets
}
pub fn created_at(&self) -> &str {
&self.created_at
}
@@ -404,18 +394,12 @@ pub struct FunctionArtifactRequest {
}
/// Stable request envelope for remote immutable Function registration.
///
/// Secret values deliberately have no field in this model. The only secret
/// material the client may send is the ordered set of names Sophon resolves
/// inside the remote runtime.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct FunctionRegistrationRequest {
pub name: String,
pub artifact: FunctionArtifactRequest,
pub signature: FunctionSignature,
pub runtime: PythonRuntimeSpec,
#[serde(default, skip_serializing_if = "Vec::is_empty")]
pub required_secrets: Vec<String>,
}
impl_json!(FunctionRegistrationRequest);
+9 -1
View File
@@ -10,7 +10,7 @@ use lance::io::WrappingObjectStore;
use object_store::{
CopyOptions, Error, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta,
ObjectStore, ObjectStoreExt, PutMultipartOptions, PutOptions, PutPayload, PutResult, Result,
UploadPart, path::Path,
UploadPart, list::PaginatedListStore, path::Path,
};
use async_trait::async_trait;
@@ -187,6 +187,14 @@ impl WrappingObjectStore for MirroringObjectStoreWrapper {
secondary: self.secondary.clone(),
})
}
fn wrap_paginated(
&self,
_store_prefix: &str,
original: Arc<dyn PaginatedListStore>,
) -> Option<Arc<dyn PaginatedListStore>> {
Some(original)
}
}
// windows pathing can't be simply concatenated
@@ -12,7 +12,7 @@ use lance::io::WrappingObjectStore;
use object_store::{
CopyOptions, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
PutMultipartOptions, PutOptions, PutPayload, PutResult, RenameOptions, Result as OSResult,
UploadPart, path::Path,
UploadPart, list::PaginatedListStore, path::Path,
};
#[derive(Debug, Default)]
@@ -57,6 +57,14 @@ impl WrappingObjectStore for IoStatsHolder {
stats: self.0.clone(),
})
}
fn wrap_paginated(
&self,
_store_prefix: &str,
original: Arc<dyn PaginatedListStore>,
) -> Option<Arc<dyn PaginatedListStore>> {
Some(original)
}
}
impl IoTrackingStore {
+4
View File
@@ -47,6 +47,10 @@ impl TerminalResult {
}
}
pub(crate) fn value(&self) -> Option<&Value> {
self.value.as_ref()
}
fn decode<T: DeserializeOwned>(self) -> Result<T> {
let value = self.value.ok_or_else(|| match &self.request_id {
Some(request_id) => Error::Http {
File diff suppressed because it is too large Load Diff
+65 -12
View File
@@ -6,6 +6,7 @@
use std::ops::Range;
use std::sync::Arc;
use std::sync::atomic::{AtomicBool, Ordering};
use std::time::Duration;
use arrow_array::{Array, LargeBinaryArray};
use arrow_schema::DataType;
@@ -20,7 +21,7 @@ use crate::error::Result;
use crate::remote::client::{HttpSend, RequestResultExt, RestfulLanceDbClient};
use crate::table::BaseTable;
use super::{FreshnessHeaders, RemoteTable};
use super::{FreshnessHeaders, FreshnessState, RemoteTable, freshness_headers_snapshot};
#[derive(Debug, Clone, Copy)]
enum RangeRequestMode {
@@ -43,7 +44,10 @@ struct TableBlobRangeRequester<S: HttpSend> {
path: String,
version: Option<u64>,
branch: Option<String>,
freshness: FreshnessHeaders,
freshness: Arc<std::sync::Mutex<FreshnessState>>,
parent_freshness: Arc<std::sync::Mutex<FreshnessState>>,
parent_freshness_request: FreshnessHeaders,
read_consistency_interval: Option<Duration>,
}
#[async_trait::async_trait]
@@ -53,8 +57,9 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
range_header: &str,
mode: RangeRequestMode,
) -> Result<(String, Response)> {
let mut request = self
.freshness
let freshness_request =
freshness_headers_snapshot(&self.freshness, self.read_consistency_interval);
let mut request = freshness_request
.apply(self.client.get(&self.path))
.header(header::RANGE, range_header);
if let Some(version) = self.version {
@@ -71,6 +76,9 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
return Ok((request_id, response));
}
let response = self.client.check_response(&request_id, response).await?;
freshness_request.observe_headers(&self.freshness, response.headers());
self.parent_freshness_request
.observe_headers(&self.parent_freshness, response.headers());
Ok((request_id, response))
}
}
@@ -361,18 +369,21 @@ impl<S: HttpSend> RemoteTable<S> {
message: "fetch_blobs is not supported on this LanceDB Cloud server".into(),
});
}
let version = self.current_version().await;
let read_snapshot = self.snapshot_read_state().await;
let mut body = serde_json::json!({
"version": version,
"version": read_snapshot.version,
"column": column,
"row_ids": row_ids,
});
self.apply_branch_body(&mut body);
let request = self
.post_read(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
.client
.post(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
.json(&body);
let (request_id, response) = self.send(request, true).await?;
let (request_id, response) = self
.send_with_freshness(request, true, read_snapshot.freshness)
.await?;
let mut stream = self.read_arrow_response(&request_id, response).await?;
let mut blob_chunks: Vec<Arc<dyn Array>> = Vec::new();
@@ -448,8 +459,7 @@ impl<S: HttpSend> RemoteTable<S> {
});
}
let version = self.current_version().await;
let freshness = self.snapshot_freshness_headers();
let read_snapshot = self.snapshot_read_state().await;
let encoded_column = urlencoding::encode(column);
let requesters = row_ids
.iter()
@@ -461,9 +471,12 @@ impl<S: HttpSend> RemoteTable<S> {
let requester: Arc<dyn BlobRangeRequester> = Arc::new(TableBlobRangeRequester {
client: self.client.clone(),
path,
version,
version: read_snapshot.version,
branch: self.branch.clone(),
freshness,
freshness: Arc::new(std::sync::Mutex::new(read_snapshot.freshness_state)),
parent_freshness: self.freshness.clone(),
parent_freshness_request: read_snapshot.freshness,
read_consistency_interval: self.client.read_consistency_interval,
});
requester
})
@@ -685,6 +698,46 @@ mod tests {
assert!(requests.lock().unwrap().contains(&"bytes=5-11".to_string()));
}
#[tokio::test]
async fn remote_blob_file_keeps_the_open_timeline_after_parent_checkout() {
let range_requests = Arc::new(StdMutex::new(Vec::new()));
let captured = range_requests.clone();
let table = RemoteTable::new_mock(
"my_table".to_string(),
move |request| match request.url().path() {
"/v1/table/my_table/describe/" => http::Response::builder()
.status(200)
.body(r#"{"version":5,"schema":{"fields":[]}}"#.as_bytes().to_vec())
.unwrap(),
"/v1/table/my_table/blob/image/10/bytes" => {
captured.lock().unwrap().push((
request.url().query().unwrap_or_default().to_string(),
request.headers().clone(),
));
range_response(&request, PAYLOAD)
}
path => panic!("unexpected path: {path}"),
},
Some(Version::new(0, 5, 0)),
);
table.checkout(5).await.unwrap();
let file = table
.fetch_blob_files_impl("image", &[10])
.await
.unwrap()
.pop()
.flatten()
.unwrap();
table.checkout_latest().await.unwrap();
file.read_range(5..12).await.unwrap();
let requests = range_requests.lock().unwrap();
let (query, headers) = requests.last().unwrap();
assert!(query.contains("version=5"));
assert!(!headers.contains_key("x-lancedb-min-timestamp"));
}
#[tokio::test]
async fn remote_blob_file_reuses_sequential_response_until_seek() {
let requests = Arc::new(StdMutex::new(Vec::new()));
+74 -9
View File
@@ -24,7 +24,10 @@ use lance::io::exec::utils::InstrumentedRecordBatchStreamAdapter;
use crate::Error;
use crate::remote::ARROW_STREAM_CONTENT_TYPE;
use crate::remote::client::{HttpSend, RestfulLanceDbClient, Sender};
use crate::remote::table::{MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable};
use crate::remote::table::{
FreshnessHeaders, FreshnessState, MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable,
freshness_headers_snapshot,
};
use crate::table::datafusion::insert::COUNT_SCHEMA;
use crate::table::write_progress::WriteProgressTracker;
use crate::table::{AddResult, MergeResult};
@@ -54,6 +57,38 @@ pub enum WriteResult {
Merge(MergeResult),
}
#[derive(Debug, Clone, Default)]
struct WriteFreshness {
state: Option<Arc<Mutex<FreshnessState>>>,
read_consistency_interval: Option<Duration>,
}
impl WriteFreshness {
fn prepare(
&self,
request: reqwest::RequestBuilder,
) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
match &self.state {
Some(state) => {
let freshness_request =
freshness_headers_snapshot(state, self.read_consistency_interval);
(freshness_request.apply(request), Some(freshness_request))
}
None => (request, None),
}
}
fn observe(
&self,
freshness_request: Option<FreshnessHeaders>,
headers: &reqwest::header::HeaderMap,
) {
if let (Some(state), Some(freshness_request)) = (&self.state, freshness_request) {
freshness_request.observe_headers(state, headers);
}
}
}
/// ExecutionPlan for streaming a write (add or merge_insert) to a remote
/// LanceDB table.
///
@@ -71,6 +106,7 @@ pub struct RemoteWriteExec<S: HttpSend = Sender> {
table_name: String,
identifier: String,
client: RestfulLanceDbClient<S>,
freshness: WriteFreshness,
input: Arc<dyn ExecutionPlan>,
op: WriteOp,
properties: Arc<PlanProperties>,
@@ -170,6 +206,7 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
table_name,
identifier,
client,
freshness: WriteFreshness::default(),
input,
op,
properties: Arc::new(properties),
@@ -183,6 +220,18 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
}
}
pub(super) fn with_freshness(
mut self,
state: Arc<Mutex<FreshnessState>>,
read_consistency_interval: Option<Duration>,
) -> Self {
self.freshness = WriteFreshness {
state: Some(state),
read_consistency_interval,
};
self
}
/// Get the add result after execution, if this exec ran an insert.
pub fn add_result(&self) -> Option<AddResult> {
match self
@@ -285,6 +334,7 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
/// each threading the same handful of arguments.
struct PartRequestCtx<'a, S: HttpSend> {
client: &'a RestfulLanceDbClient<S>,
freshness: &'a WriteFreshness,
identifier: &'a str,
table_name: &'a str,
upload_id: &'a str,
@@ -352,7 +402,11 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
}
/// Build the `/insert` request for a single multipart part.
fn build_part_request(&self, part_id: &str, body: reqwest::Body) -> reqwest::RequestBuilder {
fn build_part_request(
&self,
part_id: &str,
body: reqwest::Body,
) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
let mut request = self
.client
.post(&format!("/v1/table/{}/insert/", self.identifier))
@@ -368,12 +422,16 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
if let Some(b) = self.branch {
request = request.query(&[("branch", b)]);
}
request.body(body)
self.freshness.prepare(request.body(body))
}
/// Send a single part's request and drain the response, mapping HTTP and
/// table-not-found errors into `DataFusionError`.
async fn send_part_request(&self, request: reqwest::RequestBuilder) -> DataFusionResult<()> {
async fn send_part_request(
&self,
request: reqwest::RequestBuilder,
freshness_request: Option<FreshnessHeaders>,
) -> DataFusionResult<()> {
let (request_id, response) = self
.client
.send(request)
@@ -388,6 +446,8 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
.check_response(&request_id, response)
.await
.map_err(|e| DataFusionError::External(Box::new(e)))?;
self.freshness
.observe(freshness_request, response.headers());
response.bytes().await.map_err(|e| {
DataFusionError::External(Box::new(Error::Http {
source: Box::new(e),
@@ -419,7 +479,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
let body = reqwest::Body::wrap_stream(chunk_rx);
let part_id = uuid::Uuid::new_v4().to_string();
let request = self.build_part_request(&part_id, body);
let (request, freshness_request) = self.build_part_request(&part_id, body);
// Measured from just before the request is sent, matching the window the
// client read timeout applies to the upload.
@@ -495,7 +555,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
Ok::<bool, DataFusionError>(input_ended)
};
let send = self.send_part_request(request);
let send = self.send_part_request(request, freshness_request);
// `join!` rather than `tokio::spawn`: the producer borrows `input` (and
// `schema`), so it cannot satisfy the `'static` bound a spawned task
@@ -569,7 +629,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
// Building a fresh exec (with a new, empty `result`) is what makes the
// outer rescannable retry loop work: `reset_state()` clears the captured
// result so a re-execution starts clean.
Ok(Arc::new(Self::new_inner(
let mut exec = Self::new_inner(
self.table_name.clone(),
self.identifier.clone(),
self.client.clone(),
@@ -580,7 +640,9 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
self.branch.clone(),
self.max_bytes_per_request,
self.max_request_duration,
)))
);
exec.freshness = self.freshness.clone();
Ok(Arc::new(exec))
}
fn execute(
@@ -613,6 +675,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
&self.metrics,
));
let client = self.client.clone();
let freshness = self.freshness.clone();
let identifier = self.identifier.clone();
let op = self.op.clone();
let result_slot = self.result.clone();
@@ -634,6 +697,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
let overwrite = matches!(op, WriteOp::Insert { overwrite: true });
let ctx = PartRequestCtx {
client: &client,
freshness: &freshness,
identifier: &identifier,
table_name: &table_name,
upload_id,
@@ -688,7 +752,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
let (error_tx, mut error_rx) = tokio::sync::oneshot::channel();
let body = Self::stream_as_http_body(input_stream, error_tx, tracker)?;
let request = request.body(body);
let (request, freshness_request) = freshness.prepare(request.body(body));
let result: DataFusionResult<(String, _)> = async {
let (request_id, response) = client
@@ -708,6 +772,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
.check_response(&request_id, response)
.await
.map_err(|e| DataFusionError::External(Box::new(e)))?;
freshness.observe(freshness_request, response.headers());
Ok((request_id, response))
}
+80 -1
View File
@@ -560,6 +560,13 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
fn id(&self) -> &str;
/// Get the arrow [Schema] of the table.
async fn schema(&self) -> Result<SchemaRef>;
/// Create a read-only handle pinned to the table's current active revision.
///
/// The returned handle is independent from later refreshes or checkouts on
/// this handle. This is used by bindings that must prepare client-side
/// query state from the same revision that the query will execute against.
#[doc(hidden)]
async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>>;
/// Count the number of rows in this table.
async fn count_rows(&self, filter: Option<Filter>) -> Result<usize>;
/// Create a physical plan for the query.
@@ -785,6 +792,12 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
async fn drop_columns(&self, columns: &[&str]) -> Result<DropColumnsResult>;
/// Get the version of the table.
async fn version(&self) -> Result<u64>;
/// Return a new table handle pinned to the exact revision currently visible.
async fn checkout_current(&self) -> Result<Arc<dyn BaseTable>> {
Err(Error::NotSupported {
message: "checkout_current is not supported on this table type".into(),
})
}
/// Checkout a specific version of the table.
async fn checkout(&self, version: u64) -> Result<()>;
/// Checkout a table version referenced by a tag.
@@ -1133,6 +1146,16 @@ impl Table {
self.inner.schema().await
}
/// Create a read-only handle pinned to the current active revision.
#[doc(hidden)]
pub async fn query_snapshot(&self) -> Result<Self> {
Ok(Self {
inner: self.inner.query_snapshot().await?,
database: self.database.clone(),
embedding_registry: self.embedding_registry.clone(),
})
}
/// Count the number of rows in this dataset.
///
/// # Arguments
@@ -1944,6 +1967,20 @@ impl Table {
self.inner.version().await
}
/// Return a new table handle pinned to the exact revision currently visible.
///
/// This is used when asynchronous preparation must remain consistent with
/// the revision used for a later read.
#[doc(hidden)]
pub async fn checkout_current(&self) -> Result<Self> {
let inner = self.inner.checkout_current().await?;
Ok(Self {
inner,
database: self.database.clone(),
embedding_registry: self.embedding_registry.clone(),
})
}
/// Checks out a specific version of the Table
///
/// Any read operation on the table will now access the data at the checked out version.
@@ -3039,10 +3076,33 @@ impl BaseTable for NativeTable {
&self.id
}
async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>> {
let snapshot = self.dataset.new_query_snapshot().await?;
let mut table = self.with_dataset(snapshot);
// QueryTable requests do not carry a revision. A pinned snapshot must
// execute locally until the namespace API can accept that revision.
table
.pushdown_operations
.remove(&NamespaceClientPushdownOperation::QueryTable);
Ok(Arc::new(table))
}
async fn version(&self) -> Result<u64> {
Ok(self.dataset.get().await?.version().version)
}
async fn checkout_current(&self) -> Result<Arc<dyn BaseTable>> {
let current = self.dataset.get().await?;
let dataset = dataset::DatasetConsistencyWrapper::new_time_travel(
current.as_ref().clone(),
self.read_consistency_interval,
);
Ok(Arc::new(Self {
dataset,
..self.clone()
}))
}
async fn checkout(&self, version: u64) -> Result<()> {
self.dataset.as_time_travel(version).await
}
@@ -3208,7 +3268,7 @@ impl BaseTable for NativeTable {
let output = add.into_plan(&table_schema, &table_def)?;
let lance_params = output
let mut lance_params = output
.write_options
.lance_write_params
.unwrap_or(WriteParams {
@@ -3218,6 +3278,9 @@ impl BaseTable for NativeTable {
},
..Default::default()
});
if output.allow_external_blob_outside_bases {
lance_params.allow_external_blob_outside_bases = true;
}
// Repartition for write parallelism if beneficial.
let plan = if num_partitions > 1 {
@@ -4083,6 +4146,14 @@ mod tests {
parent_list_calls: self.parent_list_calls.clone(),
})
}
fn wrap_paginated(
&self,
_store_prefix: &str,
_original: Arc<dyn object_store::list::PaginatedListStore>,
) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
None
}
}
#[tokio::test]
@@ -4186,6 +4257,14 @@ mod tests {
self.called.store(true, Ordering::Relaxed);
original
}
fn wrap_paginated(
&self,
_store_prefix: &str,
original: Arc<dyn object_store::list::PaginatedListStore>,
) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
Some(original)
}
}
#[tokio::test]
+14
View File
@@ -60,6 +60,7 @@ pub struct AddDataBuilder {
pub(crate) embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
pub(crate) progress_callback: Option<ProgressCallback>,
pub(crate) write_parallelism: Option<usize>,
pub(crate) allow_external_blob_outside_bases: bool,
}
impl std::fmt::Debug for AddDataBuilder {
@@ -87,6 +88,7 @@ impl AddDataBuilder {
embedding_registry,
progress_callback: None,
write_parallelism: None,
allow_external_blob_outside_bases: false,
}
}
@@ -141,6 +143,16 @@ impl AddDataBuilder {
self
}
/// Store blob URIs that sit outside registered blob bases.
///
/// The row keeps a reference, so the object has to stay readable.
/// [`crate::table::Table::fetch_blobs`] reads from that location.
/// Defaults to `false`. Local tables only.
pub fn allow_external_blob_outside_bases(mut self, allow: bool) -> Self {
self.allow_external_blob_outside_bases = allow;
self
}
pub async fn execute(self) -> Result<AddResult> {
if self.write_parallelism.map(|p| p == 0).unwrap_or(false) {
return Err(Error::InvalidInput {
@@ -199,6 +211,7 @@ impl AddDataBuilder {
write_options: self.write_options,
mode: self.mode,
tracker,
allow_external_blob_outside_bases: self.allow_external_blob_outside_bases,
})
}
}
@@ -212,6 +225,7 @@ pub struct PreprocessingOutput {
pub write_options: WriteOptions,
pub mode: AddDataMode,
pub tracker: Option<Arc<WriteProgressTracker>>,
pub allow_external_blob_outside_bases: bool,
}
/// Check that the input schema is valid for insert.
+119 -34
View File
@@ -7,7 +7,7 @@
use std::sync::Arc;
use arrow_schema::{DataType, Field, FieldRef};
use arrow_schema::{DataType, Field, FieldRef, Fields};
use datafusion::functions::core::{get_field, named_struct};
use datafusion_common::ScalarValue;
use datafusion_common::config::ConfigOptions;
@@ -35,8 +35,9 @@ pub(super) fn coerce_blob_expr(
});
};
let input_struct_children = match input_field.data_type() {
DataType::Binary | DataType::LargeBinary | DataType::BinaryView => None,
let input_shape = match input_field.data_type() {
DataType::Binary | DataType::LargeBinary | DataType::BinaryView => BlobInputShape::Bytes,
DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => BlobInputShape::String,
DataType::Struct(children) => {
if !children
.iter()
@@ -49,13 +50,15 @@ pub(super) fn coerce_blob_expr(
),
});
}
Some(children)
BlobInputShape::Struct(children)
}
other => {
return Err(Error::InvalidInput {
message: format!(
"cannot coerce column '{}' with type {} into a blob v2 struct. \
expected Binary, LargeBinary, BinaryView, or a Struct with a 'data' or 'uri' child",
expected binary bytes (Binary, LargeBinary, BinaryView), \
strings (Utf8, LargeUtf8, Utf8View), \
or a Struct with a 'data' or 'uri' child",
table_field.name(),
other,
),
@@ -69,9 +72,8 @@ pub(super) fn coerce_blob_expr(
declared.name().as_str(),
))));
let value: Arc<dyn PhysicalExpr> = match input_struct_children {
// Raw binary lands in `data` and everything else is a typed null.
None => {
let value: Arc<dyn PhysicalExpr> = match &input_shape {
BlobInputShape::Bytes => {
if declared.name() == "data" {
Arc::new(CastExpr::new(
input_expr.clone(),
@@ -82,30 +84,43 @@ pub(super) fn coerce_blob_expr(
typed_null(declared.data_type())?
}
}
Some(children) => match children.iter().find(|c| c.name() == declared.name()) {
Some(child) => {
let field_expr: Arc<dyn PhysicalExpr> = Arc::new(ScalarFunctionExpr::new(
&format!("get_field({})", declared.name()),
get_field(),
vec![
input_expr.clone(),
Arc::new(Literal::new(ScalarValue::from(declared.name().as_str()))),
],
Arc::new(child.as_ref().clone()),
config.clone(),
));
if child.data_type() == declared.data_type() {
field_expr
} else {
Arc::new(CastExpr::new(
field_expr,
declared.data_type().clone(),
None,
))
}
BlobInputShape::String => {
if declared.name() == "uri" {
Arc::new(CastExpr::new(
input_expr.clone(),
declared.data_type().clone(),
None,
))
} else {
typed_null(declared.data_type())?
}
None => typed_null(declared.data_type())?,
},
}
BlobInputShape::Struct(children) => {
match children.iter().find(|c| c.name() == declared.name()) {
Some(child) => {
let field_expr: Arc<dyn PhysicalExpr> = Arc::new(ScalarFunctionExpr::new(
&format!("get_field({})", declared.name()),
get_field(),
vec![
input_expr.clone(),
Arc::new(Literal::new(ScalarValue::from(declared.name().as_str()))),
],
Arc::new(child.as_ref().clone()),
config.clone(),
));
if child.data_type() == declared.data_type() {
field_expr
} else {
Arc::new(CastExpr::new(
field_expr,
declared.data_type().clone(),
None,
))
}
}
None => typed_null(declared.data_type())?,
}
}
};
ns_args.push(value);
}
@@ -120,6 +135,12 @@ pub(super) fn coerce_blob_expr(
Ok((expr, table_field.clone()))
}
enum BlobInputShape<'a> {
Bytes,
String,
Struct(&'a Fields),
}
fn typed_null(data_type: &DataType) -> Result<Arc<dyn PhysicalExpr>> {
let scalar = ScalarValue::try_from(data_type).map_err(|e| Error::InvalidInput {
message: format!("cannot build null literal for blob child type {data_type}: {e}"),
@@ -134,7 +155,7 @@ mod tests {
use crate::blob::blob;
use arrow_array::{
Array, ArrayRef, BinaryArray, BinaryViewArray, Int32Array, Int64Array, LargeBinaryArray,
RecordBatch, StringArray, StructArray, UInt8Array, UInt64Array,
RecordBatch, StringArray, StringViewArray, StructArray, UInt8Array, UInt64Array,
};
use arrow_schema::Schema;
use datafusion::prelude::SessionContext;
@@ -436,14 +457,78 @@ mod tests {
#[tokio::test]
async fn unsupported_input_type_is_rejected_with_column_name() {
let batch = batch_with_image(
Field::new("image", DataType::Utf8, true),
Arc::new(StringArray::from(vec!["not bytes"])),
Field::new("image", DataType::Int64, true),
Arc::new(Int64Array::from(vec![42])),
);
let err = coerce_err(batch, &blob_table_schema()).await;
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
assert!(err.to_string().contains("image"));
}
#[tokio::test]
async fn utf8_string_coerces_to_uri_child() {
let batch = batch_with_image(
Field::new("image", DataType::Utf8, true),
Arc::new(StringArray::from(vec![Some("s3://bucket/key"), None])),
);
let coerced = coerce(batch, &blob_table_schema()).await;
let image = image_struct(&coerced);
let uri: &StringArray = image
.column_by_name("uri")
.unwrap()
.as_any()
.downcast_ref()
.unwrap();
assert_eq!(uri.value(0), "s3://bucket/key");
assert!(image.column_by_name("data").unwrap().is_null(0));
assert!(uri.is_null(1));
}
#[tokio::test]
async fn large_utf8_string_coerces_into_four_child_blob_layout() {
use arrow_array::LargeStringArray;
let table_schema = Schema::new(vec![
Field::new("id", DataType::Int64, false),
wide_blob_field("image"),
]);
let batch = batch_with_image(
Field::new("image", DataType::LargeUtf8, true),
Arc::new(LargeStringArray::from(vec!["file:///tmp/blob.bin"])),
);
let coerced = coerce(batch, &table_schema).await;
let image = image_struct(&coerced);
assert_eq!(image.num_columns(), 4);
let uri: &StringArray = image
.column_by_name("uri")
.unwrap()
.as_any()
.downcast_ref()
.unwrap();
assert_eq!(uri.value(0), "file:///tmp/blob.bin");
assert!(image.column_by_name("data").unwrap().is_null(0));
assert!(image.column_by_name("position").unwrap().is_null(0));
assert!(image.column_by_name("size").unwrap().is_null(0));
}
#[tokio::test]
async fn utf8_view_string_coerces_to_uri_child() {
let batch = batch_with_image(
Field::new("image", DataType::Utf8View, true),
Arc::new(StringViewArray::from(vec![Some("s3://bucket/view-key")])),
);
let coerced = coerce(batch, &blob_table_schema()).await;
let image = image_struct(&coerced);
let uri: &StringArray = image
.column_by_name("uri")
.unwrap()
.as_any()
.downcast_ref()
.unwrap();
assert_eq!(uri.value(0), "s3://bucket/view-key");
assert!(image.column_by_name("data").unwrap().is_null(0));
}
#[tokio::test]
async fn blob_metadata_survives_cast_of_sibling_column() {
let batch = RecordBatch::try_new(
+65 -4
View File
@@ -32,6 +32,10 @@ struct DatasetState {
/// `Some(version)` = pinned to a specific version (time travel),
/// `None` = tracking latest.
pinned_version: Option<u64>,
/// Whether the pin is an internal query snapshot rather than user-visible
/// time travel. Query snapshots remain read-only but preserve MemWAL read
/// semantics.
query_snapshot: bool,
}
#[derive(Debug, Clone)]
@@ -70,6 +74,7 @@ impl DatasetConsistencyWrapper {
state: Arc::new(Mutex::new(DatasetState {
dataset,
pinned_version: None,
query_snapshot: false,
})),
consistency,
shard_writer: Arc::new(ShardWriterCache::default()),
@@ -93,6 +98,36 @@ impl DatasetConsistencyWrapper {
wrapper
}
/// Create an independent read-only wrapper pinned to the current dataset
/// while retaining this wrapper's live MemWAL read context.
pub async fn new_query_snapshot(&self) -> Result<Self> {
// Apply the configured consistency policy before taking the snapshot.
// The returned dataset is intentionally discarded: a checkout may race
// after this await, so the dataset and its pin provenance must instead
// be cloned together from one authoritative state sample below.
self.get().await?;
let (dataset, query_snapshot) = {
let state = self.state.lock()?;
// Preserve user time travel so the MemWAL safety guard still sees
// it. Latest and already-internal snapshots remain internal pins.
(
state.dataset.clone(),
state.query_snapshot || state.pinned_version.is_none(),
)
};
let version = dataset.version().version;
Ok(Self {
state: Arc::new(Mutex::new(DatasetState {
dataset,
pinned_version: Some(version),
query_snapshot,
})),
consistency: ConsistencyMode::Lazy,
shard_writer: self.shard_writer.clone(),
})
}
/// The MemWAL `ShardWriter` cache co-located with this dataset.
pub(crate) fn shard_writer(&self) -> &Arc<ShardWriterCache> {
&self.shard_writer
@@ -169,6 +204,7 @@ impl DatasetConsistencyWrapper {
let mut state = self.state.lock()?;
state.dataset = Arc::new(new_dataset);
state.pinned_version = None;
state.query_snapshot = false;
drop(state);
if let ConsistencyMode::Eventual(bg_cache) = &self.consistency {
bg_cache.invalidate();
@@ -202,10 +238,10 @@ impl DatasetConsistencyWrapper {
/// Returns the version, if in time travel mode, or None otherwise.
pub fn time_travel_version(&self) -> Option<u64> {
self.state
.lock()
.unwrap_or_else(|e| e.into_inner())
.pinned_version
let state = self.state.lock().unwrap_or_else(|e| e.into_inner());
(!state.query_snapshot)
.then_some(state.pinned_version)
.flatten()
}
/// Convert into a wrapper in latest version mode.
@@ -225,6 +261,7 @@ impl DatasetConsistencyWrapper {
if state.pinned_version.is_some() {
state.dataset = Arc::new(new_dataset);
state.pinned_version = None;
state.query_snapshot = false;
}
drop(state);
if let ConsistencyMode::Eventual(bg_cache) = &self.consistency {
@@ -260,6 +297,7 @@ impl DatasetConsistencyWrapper {
let mut state = self.state.lock()?;
state.dataset = Arc::new(new_dataset);
state.pinned_version = Some(version_value);
state.query_snapshot = false;
Ok(())
}
@@ -461,6 +499,29 @@ mod tests {
assert_eq!(wrapper.time_travel_version(), Some(1));
}
#[tokio::test]
async fn test_query_snapshot_samples_dataset_and_pin_together() {
let dir = tempfile::tempdir().unwrap();
let uri = dir.path().to_str().unwrap();
let ds = create_test_dataset(uri).await;
let wrapper = DatasetConsistencyWrapper::new_latest(ds, None);
wrapper.as_time_travel(1u64).await.unwrap();
let stale_time_travel_dataset = wrapper.get().await.unwrap();
append_to_dataset(uri).await;
wrapper.as_latest().await.unwrap();
let snapshot = wrapper.new_query_snapshot().await.unwrap();
let snapshot_dataset = snapshot.get().await.unwrap();
assert_eq!(snapshot_dataset.version().version, 2);
assert_ne!(
snapshot_dataset.version().version,
stale_time_travel_dataset.version().version
);
assert_eq!(snapshot.time_travel_version(), None);
}
#[tokio::test]
async fn test_as_latest_from_time_travel() {
let dir = tempfile::tempdir().unwrap();
+38
View File
@@ -1056,6 +1056,44 @@ mod lsm_tests {
);
}
#[tokio::test]
async fn query_snapshot_preserves_lsm_read_semantics() {
let dir = tempdir().unwrap();
let table = id_value_table(&dir).await;
table
.set_lsm_write_spec(LsmWriteSpec::unsharded())
.await
.unwrap();
lsm_upsert(&table, vec![4, 5]).await;
let snapshot = table.query_snapshot().await.unwrap();
let rows = collect_id_value(snapshot.query().execute().await.unwrap()).await;
assert_eq!(
rows.iter().map(|(id, _)| *id).collect::<Vec<_>>(),
vec![1, 2, 3, 4, 5]
);
}
#[tokio::test]
async fn query_snapshot_preserves_time_travel_lsm_guard() {
let dir = tempdir().unwrap();
let table = id_value_table(&dir).await;
table
.set_lsm_write_spec(LsmWriteSpec::unsharded())
.await
.unwrap();
lsm_upsert(&table, vec![4]).await;
let version = table.version().await.unwrap();
table.checkout(version).await.unwrap();
let direct_error = table.query().execute().await.err().unwrap();
assert!(matches!(direct_error, Error::NotSupported { .. }));
let snapshot = table.query_snapshot().await.unwrap();
let snapshot_error = snapshot.query().execute().await.err().unwrap();
assert!(matches!(snapshot_error, Error::NotSupported { .. }));
}
#[tokio::test]
async fn lsm_read_dedup_newest_wins() {
let dir = tempdir().unwrap();
+79 -1
View File
@@ -697,6 +697,7 @@ mod tests {
use super::*;
use crate::query::{QueryExecutionOptions, QueryRequest};
use crate::table::BaseTable;
fn fixed_size_list_array(values: Vec<f32>, dimension: i32) -> FixedSizeListArray {
FixedSizeListArray::try_new_from_values(Float32Array::from(values), dimension).unwrap()
@@ -889,10 +890,56 @@ mod tests {
async fn query_table(&self, _request: NsQueryTableRequest) -> lance::Result<bytes::Bytes> {
self.query_table_calls.fetch_add(1, Ordering::SeqCst);
panic!("approx_mode queries must not be pushed down to namespace query_table");
panic!("query must not be pushed down to namespace query_table");
}
}
#[tokio::test]
async fn test_execute_query_pinned_snapshot_with_namespace_pushdown_runs_locally() {
use crate::connect;
use arrow_array::{Int32Array, RecordBatch};
use arrow_schema::{DataType, Field, Schema};
let conn = connect("memory://").execute().await.unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
let batch = RecordBatch::try_new(
schema,
vec![Arc::new(Int32Array::from(vec![1, 2, 3, 4, 5]))],
)
.unwrap();
let table = conn
.create_table("test_pinned_namespace_fallback", vec![batch])
.execute()
.await
.unwrap();
let namespace_client = Arc::new(CountingNamespaceClient::default());
let mut native_table = table.as_native().unwrap().clone();
native_table.namespace_client = Some(namespace_client.clone());
native_table
.pushdown_operations
.insert(NamespaceClientPushdownOperation::QueryTable);
let snapshot = native_table.checkout_current().await.unwrap();
let snapshot = snapshot.as_any().downcast_ref::<NativeTable>().unwrap();
assert!(snapshot.dataset.time_travel_version().is_some());
let query = AnyQuery::Query(QueryRequest {
filter: Some(QueryFilter::Sql("id > 3".to_string())),
..Default::default()
});
let stream = execute_query(snapshot, &query, QueryExecutionOptions::default())
.await
.unwrap();
let batches = stream.try_collect::<Vec<_>>().await.unwrap();
assert_eq!(
batches.iter().map(|batch| batch.num_rows()).sum::<usize>(),
2
);
assert_eq!(namespace_client.query_table_calls.load(Ordering::SeqCst), 0);
}
#[tokio::test]
async fn test_execute_query_approx_mode_with_namespace_pushdown_runs_locally() {
use crate::connect;
@@ -1009,6 +1056,37 @@ mod tests {
assert_eq!(namespace_client.query_table_calls.load(Ordering::SeqCst), 0);
}
#[tokio::test]
async fn test_query_snapshot_disables_namespace_pushdown() {
use crate::connect;
use crate::table::BaseTable;
use arrow_array::{Int32Array, RecordBatch};
use arrow_schema::{DataType, Field, Schema};
let conn = connect("memory://").execute().await.unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
let batch =
RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1, 2, 3]))]).unwrap();
let table = conn
.create_table("test_snapshot_namespace_fallback", vec![batch])
.execute()
.await
.unwrap();
let mut native_table = table.as_native().unwrap().clone();
native_table.namespace_client = Some(Arc::new(CountingNamespaceClient::default()));
native_table
.pushdown_operations
.insert(NamespaceClientPushdownOperation::QueryTable);
let snapshot = BaseTable::query_snapshot(&native_table).await.unwrap();
let snapshot = snapshot.as_any().downcast_ref::<NativeTable>().unwrap();
assert!(
!can_execute_namespace_query(snapshot, &AnyQuery::Query(QueryRequest::default()),)
.await
.unwrap()
);
}
#[tokio::test]
async fn test_create_plan_multivector_structure() {
use arrow_array::{Float32Array, RecordBatch};
+1 -1
View File
@@ -298,7 +298,7 @@ async fn build_read_context(
for shard_id in shard_ids {
let manifest_store =
ShardManifestStore::new(store.clone(), &base_path, shard_id, scan_batch_size);
if let Some(manifest) = manifest_store.read_latest().await? {
if let Some(manifest) = manifest_store.latest().await? {
snapshots.push(snapshot_from_manifest(shard_id, &manifest, &exclude));
}
}
+226 -4
View File
@@ -5,12 +5,14 @@ use std::sync::Arc;
use arrow_array::{
Array, ArrayRef, BinaryArray, Int64Array, LargeBinaryArray, RecordBatch, StringArray,
StructArray, UInt64Array,
StructArray, UInt64Array, new_null_array,
};
use arrow_schema::{DataType, Field, Fields, Schema};
use futures::TryStreamExt;
use lance::Dataset;
use lance::dataset::WriteParams;
use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
use lance_table::format::BasePath;
use lancedb::{
Connection, Error, Result, Table,
blob::{BlobRangeRequest, blob},
@@ -19,7 +21,7 @@ use lancedb::{
ListingDatabaseOptions, NewTableConfig, OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS,
},
query::{ExecutableQuery, QueryBase},
table::{AddDataMode, CompactionOptions, OptimizeAction, OptimizeStats},
table::{AddDataMode, CompactionOptions, OptimizeAction, OptimizeStats, WriteOptions},
};
use tempfile::tempdir;
@@ -261,11 +263,11 @@ async fn add_rejects_uncoercible_blob_input() -> Result<()> {
let batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int64, false),
Field::new("image", DataType::Utf8, true),
Field::new("image", DataType::Int64, true),
])),
vec![
Arc::new(Int64Array::from(vec![1])),
Arc::new(StringArray::from(vec!["not bytes"])),
Arc::new(Int64Array::from(vec![42])),
],
)
.unwrap();
@@ -1332,3 +1334,223 @@ async fn optimize_preserves_blob_v2_null_and_empty_distinction() -> Result<()> {
);
Ok(())
}
fn uri_struct_batch(id: i64, uri: &str) -> RecordBatch {
let image_field = blob("image", true);
let DataType::Struct(child_fields) = image_field.data_type().clone() else {
unreachable!("blob field is a struct");
};
let children: Vec<ArrayRef> = child_fields
.iter()
.map(|field| match field.name().as_str() {
"uri" => Arc::new(StringArray::from(vec![Some(uri)])) as ArrayRef,
_ => new_null_array(field.data_type(), 1),
})
.collect();
let image = StructArray::new(child_fields, children, None);
RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int64, false),
image_field,
])),
vec![Arc::new(Int64Array::from(vec![id])), Arc::new(image)],
)
.unwrap()
}
fn uri_string_batch(id: i64, uri: &str) -> RecordBatch {
RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int64, false),
Field::new("image", DataType::Utf8, true),
])),
vec![
Arc::new(Int64Array::from(vec![id])),
Arc::new(StringArray::from(vec![Some(uri)])),
],
)
.unwrap()
}
fn write_payload_file_uri(dir: &std::path::Path, name: &str, payload: &[u8]) -> String {
let path = dir.join(name);
std::fs::write(&path, payload).unwrap();
url::Url::from_file_path(&path).unwrap().to_string()
}
#[tokio::test]
async fn external_uri_struct_round_trips_with_flag() -> Result<()> {
let tmp = tempdir().unwrap();
let db = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await?;
let payload: &[u8] = b"external-struct-payload";
let uri = write_payload_file_uri(tmp.path(), "payload.bin", payload);
let table = db
.create_empty_table("t", blob_table_schema())
.execute()
.await?;
table
.add(uri_struct_batch(1, &uri))
.allow_external_blob_outside_bases(true)
.execute()
.await?;
let ids = collect_row_ids(&table).await?;
let bytes = table.fetch_blobs("image", &ids).await?;
assert_eq!(bytes.value(0), payload);
Ok(())
}
#[tokio::test]
async fn external_uri_add_requires_opt_in() -> Result<()> {
let tmp = tempdir().unwrap();
let db = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await?;
let uri = write_payload_file_uri(tmp.path(), "payload.bin", b"unreachable");
let table = db
.create_empty_table("t", blob_table_schema())
.execute()
.await?;
let err = table
.add(uri_struct_batch(1, &uri))
.execute()
.await
.unwrap_err();
assert!(
err.to_string()
.contains("allow_external_blob_outside_bases"),
"got: {err}"
);
assert_eq!(table.count_rows(None).await?, 0);
Ok(())
}
#[tokio::test]
async fn string_uri_input_round_trips_as_external_reference() -> Result<()> {
let tmp = tempdir().unwrap();
let db = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await?;
let payload: &[u8] = b"external-string-payload";
let uri = write_payload_file_uri(tmp.path(), "payload.bin", payload);
let table = db
.create_empty_table("t", blob_table_schema())
.execute()
.await?;
table
.add(uri_string_batch(1, &uri))
.allow_external_blob_outside_bases(true)
.execute()
.await?;
let ids = collect_row_ids(&table).await?;
let bytes = table.fetch_blobs("image", &ids).await?;
assert_eq!(bytes.value(0), payload);
let files = table.fetch_blob_files("image", &ids).await?;
let file = files[0].as_ref().expect("missing blob file");
assert_eq!(file.uri(), Some(uri.as_str()));
Ok(())
}
#[tokio::test]
async fn string_uri_inside_registered_base_does_not_need_the_flag() -> Result<()> {
let tmp = tempdir().unwrap();
let db_path = tmp.path().join("db");
let external_base = tmp.path().join("external_base");
let object_dir = external_base.join("objects");
std::fs::create_dir_all(&object_dir).unwrap();
let payload: &[u8] = b"mapped-in-base";
let object_path = object_dir.join("mapped.bin");
std::fs::write(&object_path, payload).unwrap();
let object_uri = url::Url::from_file_path(&object_path).unwrap().to_string();
let base_uri = url::Url::from_file_path(&external_base)
.unwrap()
.to_string();
let db = connect(db_path.to_str().unwrap()).execute().await?;
let table = db
.create_empty_table("t", blob_table_schema())
.write_options(WriteOptions {
lance_write_params: Some(WriteParams {
initial_bases: Some(vec![BasePath {
id: 1,
name: Some("external".to_string()),
path: base_uri,
is_dataset_root: false,
}]),
..Default::default()
}),
})
.execute()
.await?;
table
.add(uri_string_batch(1, &object_uri))
.execute()
.await?;
let ids = collect_row_ids(&table).await?;
let bytes = table.fetch_blobs("image", &ids).await?;
assert_eq!(bytes.value(0), payload);
Ok(())
}
#[tokio::test]
async fn external_uri_rows_mix_with_inline_rows() -> Result<()> {
let tmp = tempdir().unwrap();
let db = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await?;
let external_payload: &[u8] = b"external-bytes";
let uri = write_payload_file_uri(tmp.path(), "payload.bin", external_payload);
let table =
create_inline_blob_table(&db, "t", &[1], &[Some(b"inline-bytes".as_slice())]).await?;
table
.add(uri_string_batch(2, &uri))
.allow_external_blob_outside_bases(true)
.execute()
.await?;
let pairs = collect_id_rowid(&table).await?;
let row_ids: Vec<u64> = pairs.iter().map(|(_, r)| *r).collect();
let bytes = table.fetch_blobs("image", &row_ids).await?;
for (i, (id, _)) in pairs.iter().enumerate() {
match id {
1 => assert_eq!(bytes.value(i), b"inline-bytes"),
2 => assert_eq!(bytes.value(i), external_payload),
_ => unreachable!(),
}
}
Ok(())
}
#[tokio::test]
async fn malformed_string_uri_is_rejected_at_write() -> Result<()> {
let tmp = tempdir().unwrap();
let db = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await?;
let table = db
.create_empty_table("t", blob_table_schema())
.execute()
.await?;
let err = table
.add(uri_string_batch(1, "not a uri"))
.allow_external_blob_outside_bases(true)
.execute()
.await
.unwrap_err();
assert!(err.to_string().contains("not a uri"), "got: {err}");
assert_eq!(table.count_rows(None).await?, 0);
Ok(())
}
@@ -20,25 +20,6 @@ fn job_result(name: &str) -> Value {
serde_json::from_str::<Value>(&fixture(name)).expect("remote Job fixture")["result"].clone()
}
fn assert_no_secret_values(value: &Value) {
match value {
Value::Object(values) => {
for (key, value) in values {
assert!(
!matches!(
key.as_str(),
"secret_value" | "secret_values" | "resolved_secret" | "resolved_secrets"
),
"client canonical value must not model resolved secret material"
);
assert_no_secret_values(value);
}
}
Value::Array(values) => values.iter().for_each(assert_no_secret_values),
_ => {}
}
}
#[test]
fn function_version_job_result_matches_shared_canonical_golden() {
let result = job_result("remote_function_job.json");
@@ -47,7 +28,6 @@ fn function_version_job_result_matches_shared_canonical_golden() {
assert_eq!(version.name(), "embed");
assert_eq!(version.version(), "fv_01K3EXACT");
assert_eq!(version.runtime_digest(), "sha256:runtime");
assert_eq!(version.required_secrets(), &["HF_TOKEN"]);
assert_eq!(
version.to_canonical_json().expect("canonical JSON"),
fixture("remote_function_version.canonical.json").trim()
@@ -162,21 +142,3 @@ fn floating_point_application_literals_are_rejected_consistently() {
.contains("floating-point Function literals")
);
}
#[test]
fn canonical_client_values_contain_secret_names_only() {
let result = job_result("remote_function_job.json");
let version = FunctionVersion::from_json(&result.to_string()).expect("FunctionVersion result");
let canonical: Value = serde_json::from_str(
&version
.to_canonical_json()
.expect("canonical FunctionVersion"),
)
.expect("canonical JSON");
assert_eq!(
canonical["required_secrets"],
serde_json::json!(["HF_TOKEN"])
);
assert_no_secret_values(&canonical);
}
@@ -6,7 +6,6 @@ use std::path::PathBuf;
use lancedb::Error;
use lancedb::function::FunctionRegistrationRequest;
use serde_json::Value;
fn fixture(name: &str) -> String {
let path = PathBuf::from(env!("CARGO_MANIFEST_DIR"))
@@ -15,25 +14,6 @@ fn fixture(name: &str) -> String {
fs::read_to_string(path).expect("fixture must be readable")
}
fn assert_no_secret_values(value: &Value) {
match value {
Value::Object(values) => {
for (key, value) in values {
assert!(
!matches!(
key.as_str(),
"secret_value" | "secret_values" | "resolved_secret" | "resolved_secrets"
),
"registration requests must not model resolved secret material"
);
assert_no_secret_values(value);
}
}
Value::Array(values) => values.iter().for_each(assert_no_secret_values),
_ => {}
}
}
#[test]
fn registration_request_matches_shared_canonical_golden() {
let request = FunctionRegistrationRequest::from_json(&fixture(
@@ -42,16 +22,10 @@ fn registration_request_matches_shared_canonical_golden() {
.expect("registration request");
assert_eq!(request.name, "normalize_score");
assert_eq!(request.artifact.adapter.kind, "scalar_to_arrow_batch");
assert_eq!(request.required_secrets, ["API_TOKEN"]);
assert_eq!(
request.to_canonical_json().expect("canonical request"),
fixture("remote_function_registration_request.canonical.json").trim()
);
let value: Value =
serde_json::from_str(&request.to_canonical_json().expect("canonical request"))
.expect("request JSON");
assert_no_secret_values(&value);
}
#[tokio::test]
@@ -24,7 +24,6 @@
},
"runtime_digest": "sha256:runtime",
"environment_digest": "sha256:environment",
"required_secrets": ["HF_TOKEN"],
"created_at": "2026-08-21T00:00:00Z"
},
"future_job": {"trace_id": "trace-1"}
@@ -1 +1 @@
{"artifact":{"adapter":{"kind":"scalar_to_arrow_batch","version":1},"content":{"data":"ZnJvbSBfX2Z1dHVyZV9fIGltcG9ydCBhbm5vdGF0aW9ucwoKZGVmIG5vcm1hbGl6ZV9zY29yZSh2YWx1ZTogZmxvYXQpIC0+IGZsb2F0OgogICAgcmV0dXJuIHZhbHVlIC8gMTAwLjAK","encoding":"base64"},"digest":"sha256:760784bdcef57b802f389b97804cc0b618aae39e86044733451bcd0b13089a7f","entrypoint":"normalize_score","kind":"python_callable"},"name":"normalize_score","required_secrets":["API_TOKEN"],"runtime":{"env":{"MODE":"test"},"environment":{"kind":"pip","packages":["numpy>=2"]},"kind":"python","python_version":"3.12"},"signature":{"inputs":[{"arrow_type":"float64","name":"value","nullable":false}],"output":{"arrow_type":"float64","kind":"scalar","nullable":false}}}
{"artifact":{"adapter":{"kind":"scalar_to_arrow_batch","version":1},"content":{"data":"ZnJvbSBfX2Z1dHVyZV9fIGltcG9ydCBhbm5vdGF0aW9ucwoKZGVmIG5vcm1hbGl6ZV9zY29yZSh2YWx1ZTogZmxvYXQpIC0+IGZsb2F0OgogICAgcmV0dXJuIHZhbHVlIC8gMTAwLjAK","encoding":"base64"},"digest":"sha256:760784bdcef57b802f389b97804cc0b618aae39e86044733451bcd0b13089a7f","entrypoint":"normalize_score","kind":"python_callable"},"name":"normalize_score","runtime":{"env":{"MODE":"test"},"environment":{"kind":"pip","packages":["numpy>=2"]},"kind":"python","python_version":"3.12"},"signature":{"inputs":[{"arrow_type":"float64","name":"value","nullable":false}],"output":{"arrow_type":"float64","kind":"scalar","nullable":false}}}
@@ -39,8 +39,5 @@
"env": {
"MODE": "test"
}
},
"required_secrets": [
"API_TOKEN"
]
}
}
@@ -1 +1 @@
{"artifact":{"digest":"sha256:code","entrypoint":"embed","kind":"python_callable"},"created_at":"2026-08-21T00:00:00Z","environment_digest":"sha256:environment","name":"embed","required_secrets":["HF_TOKEN"],"runtime":{"env":{"TOKENIZERS_PARALLELISM":"false"},"environment":{"kind":"pip","packages":["sentence-transformers>=3"]},"kind":"python","python_version":"3.12"},"runtime_digest":"sha256:runtime","signature":{"inputs":[{"arrow_type":"utf8","name":"text","nullable":true}],"output":{"arrow_type":"list<float32>","kind":"scalar","nullable":false}},"version":"fv_01K3EXACT"}
{"artifact":{"digest":"sha256:code","entrypoint":"embed","kind":"python_callable"},"created_at":"2026-08-21T00:00:00Z","environment_digest":"sha256:environment","name":"embed","runtime":{"env":{"TOKENIZERS_PARALLELISM":"false"},"environment":{"kind":"pip","packages":["sentence-transformers>=3"]},"kind":"python","python_version":"3.12"},"runtime_digest":"sha256:runtime","signature":{"inputs":[{"arrow_type":"utf8","name":"text","nullable":true}],"output":{"arrow_type":"list<float32>","kind":"scalar","nullable":false}},"version":"fv_01K3EXACT"}