## Cause
Remote `fetch_blobs` sent every row ID in one Cloud request, exceeding
the server's 1024-row or 64 MiB byte cap. A single blob over the byte
cap could not be read through this method.
## Fix
- Send at most 1024 row IDs per request and split batches further when
the server reports the blob-byte cap, preserving input order and nulls.
- Resolve one exact dataset version before multi-request reads. If an
initial single request hits the byte cap, resolve the version before any
successful split or Range read; use that version for every resulting
request.
- Read an individual oversized blob through the existing Range route.
- Document the per-request caps and transparent handling in the Rust,
Python, and TypeScript APIs and generated JS docs.
## Validation
- Focused Rust `fetch_blobs` tests: 26 passed, including row-count,
byte-cap, Range fallback, and exact-version assertions.
- Rust clippy and formatting passed.
- Focused Python blob tests: 13 passed; Ruff lint and formatting passed.
- Node build, lint, docs generation, and focused `fetchBlobs` test
passed.
Fixes#4275
<!-- lance-gatekeeper-fix:v1 agent=6ae94d49bf1d4cae057bba72584e7b90
generation=1 -->
---------
Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
## Summary
Materialize a source-preserving dedup result from an indexed, pinned
snapshot with a short declaration. The default greedy policy keeps the
smallest unassigned snapshot row ID and removes only its directly
matching neighbors: For A < B < C, an A–B–C chain without an A–C edge
keeps A and C.
```python
from lancedb import vector_dedup
view = db.create_materialized_view(
"images_clean",
vector_dedup("images", column="phash", distance_threshold=4),
)
cleaned = view.table
```
The Python source expression captures the source version once at
creation and
waits for the materialized result by default. Use `dataset_version=...`
for an
explicit snapshot, `with_no_data=True` for declaration only, or
`create_materialized_view_async(...)` for a job handle. AsyncConnection
supports
the same expression. It uses the existing MV REST endpoints and registry
jobs,
without opening a SQL query connection. Source names are exact
root-namespace
table names. Additional select/where/limit options are rejected for this
source.
The SQL declaration remains available:
```sql
CREATE MATERIALIZED VIEW images_clean AS
SELECT * FROM vector_dedup('images', 7, 'phash', 4);
REFRESH MATERIALIZED VIEW images_clean;
```
This is the host-facing SQL entry point. The MV builder now accepts a
typed native vector source; the Rust SDK also supports the same
definition through `MaterializedViewDefinition::from_sql` and
`prepare_definition`; `view.refresh().execute()` executes it locally.
Hosts distribute its units using their existing job infrastructure. The
raw `vector_duplicate_pairs` source remains available separately when
callers want the pair relation.
## Implementation and contract
- Use actual Rust Lance `13.0.0-beta.15` (`db53dcf367`); the native
partition primitive computes pairs from index representations without
source-vector aggregation or a Python pair loop.
- Extend partitioned MV refresh with two dependent waves. Physical
segment/partition tasks stream pairs through a bounded external sort,
select direct representatives and write per-source-fragment bitmap
artifacts. Source-fragment tasks start after every selection receipt
completes and stream retained original rows, including blob payloads,
into uncommitted output fragments.
- Reuse normal blob write coercion and row-mask scans, including stable
row-ID translation after compaction. Null vectors, isolated rows and
source deletions are preserved correctly. Conflicting representative
decisions across overlapping index scopes fail before publication.
- Expose `dependency_units()` and `write_refresh_partition_with_inputs`
alongside the existing plan/commit API. Receipts bind
snapshot/configuration/policy/destination generation. Only a complete
accepted set can publish; unfinished units restart, completed units can
be reused. There is no pair-position checkpoint.
- Use MV format 4 for dedup results and format 3 for native pairs;
Python and TypeScript metadata readers recognize both. No source
deletion or source row-ID migration occurs.
Only same-segment/same-partition edges are covered. Quantized scores use
symmetric represented-vector distances. Result materialization requires
V2 data storage and is initially a native MV source, not an ordinary
SELECT table function. Compressed vertex masks stay in memory; edge
sorting spills to local disk. Unreferenced artifacts use normal Lance
retention/cleanup and must be retained for the job's recovery window.
## Validation
AWS Linux validation:
- Native pair/result integration matrix passed: multiple
segments/partitions, exact thresholds, empty output, cross-batch data,
single-process pair parity, source preservation, lost receipts and
publication guards.
- Blob/null-vector/pinned-deletion tests passed with both row-ID modes,
including compaction that changes physical row addresses.
- Representative policy, forced external-sort spill and
conflicting/corrupt artifact tests passed.
- Full MV regression suite: 153 passed, 2 pre-existing ignored. Rust
formatting and Clippy passed.
- Python MV suite: 47 passed; TypeScript MV suite: 11 passed. Native
bindings were rebuilt in project-local environments; formatting, lint
and TypeScript docs passed.
- Rust declaration doctests: 3 passed, including the complete local
dedup example.
- Companion host validation: 41 MV job tests passed (1 pre-existing
ignored), full workspace Clippy passed, and the complete process-level
CLI E2E suite passed (3 tests). Recovery exercises both selection and
materialization waves.
- A real CIFAR-10 pHash run used five actual registry-worker owners,
completed 32 selection + 24 materialization tasks, and retained 49,846
of 50,000 rows with identical original values and image payloads.
Host workflow performance measurements are recorded in the companion
host PR. Cross-platform CI is still running. The previous remote-test
bootstrap failed before Cargo tests with `401 Bad credentials`; the
workflow fix described below is being validated by CI. No deployment or
merge is performed.
## Python source validation
AWS tests cover automatic and explicit snapshots, physical/stable row
IDs, local
and remote creation, sync/job/async-connection APIs, delayed refresh,
strict
options and identifier quoting. The native Python extension was rebuilt
through
the project's uv/maturin backend. Ruff, Pyright and the full MkDocs
API-reference
build passed; both new public symbols are rendered.
A real 50,000-image FEv2 run disabled both Python SQL entry points and
supplied an
unreachable SQL endpoint. The new API still materialized the same 49,846
retained
rows and original image payloads. Three recorded creation/refresh jobs
completed
56 tasks each on all five registry-worker owners, and remained on source
snapshot
3 after source latest advanced to 4. No worker or server wire-protocol
changes
were needed for this client entry point.
Previous CI authentication failure:
https://github.com/lancedb/lancedb/actions/runs/36334679276/job/108663151265.
## Review and CI fixes
- Validate all JSON merge source fields before projection, rejecting
unknown and duplicate names at every struct level. Missing/reordered
fields and ordinary JSON merges remain supported. A checked-in 12-case
integration matrix covers root fields, structs, lists, large lists,
fixed-size lists and map values; rejected writes leave the table version
and row count unchanged.
- Match namespace connection MV method signatures to
`MaterializedViewSource` in all four sync/async methods, fixing the
Python 3.10 import failure from runtime override checks.
- Restore the remote-test script's encrypted-CLI path: use the Actions
token for artifact download and pass `SOPHON_READ_TOKEN` under the
variable the decryption script consumes. The previous workflow omitted
that variable and attempted the private release path, failing with HTTP
401. On the final head, remote CI passes: 1,464 Rust unit tests, the
integration targets and doctests pass (3 unit tests ignored).
AWS validation for these fixes: both review reproducers failed before
their fixes and pass afterward; 55 merge tests, 29 cast tests and the
standalone 7-case admission regression pass. Python 3.10.21 imports
successfully; 90 MV/namespace tests, 14 JSON tests and four real
namespace dedup cases pass. After `794b97a0`, the native binding was
rebuilt again and the JSON suite rerun. Rust formatting/Clippy, Ruff and
Pyright pass. Sophon's locked test compilation passes against the final
SDK source for all seven affected crates. Extended runners, logs and
benchmark artifacts remain local.
Gatekeeper recommends approval on `794b97a0`, and the `breaking-change`
label is set. Final CI: **49 checks passed, 3 expected skips, no
failures or pending checks**, including remote tests, Python 3.10,
minimum dependencies and Windows ARM Rust tests. All wheel builds pass
after retrying the Linux matrix affected by transient AlmaLinux
repository-metadata 404s. All code-review threads are resolved. The PR
remains open for maintainer review and merge.
---------
Co-authored-by: Yang Cen <yangcen@Yangs-Mac-mini.local>
Co-authored-by: Lance Release <lance-dev@lancedb.com>
Cancellation is the only job control the SDK exposes, and it is
terminal, so a long-running server-side job cannot be parked and picked
up again. This adds `pause_job` and `resume_job` to the Rust core
connection and the Python bindings (sync and async), posting to the
server's `/v1/jobs/pause` and `/v1/jobs/resume` endpoints.
A pause parks the job until it is resumed: its workers drain and stop.
The outcome strings mirror the server's answers — a job finalizing its
results reports `"committing"` and cannot be parked, and a resume before
the drain is confirmed reports `"still_pausing"`; both are retried
rather than failed. Resuming re-queues the job and its workers pick
their work back up from checkpoints. Local connections report the
operations as unsupported, like the rest of the jobs API.
Adds opt-in `batch_size=40`: 80 non-null candidates use **2 requests
instead of 80**. Default `batch_size=1` preserves the existing payload.
Each batched question sees only its document and the shared query;
instructions/criteria stay unchanged. Prompts referencing
`state.document` need adaptation. Concurrency still limits requests;
retries remain SDK-managed. Batch-local IDs and ordered results preserve
duplicate documents; invalid IDs/probabilities raise without fallback.
Validation: **124 automated tests passed**, plus live search
integrations in both modes. A **100-query live subset test of the
initial implementation** (6,851 candidate pairs; `jev-1.13.0`, SDK
0.7.1, concurrency 32) passed: unbatched/batched calls **6,851/199**,
median **877/351 ms**, p95 **9,446/598 ms**. Hybrid Hit@5/Hit@10 was
**83%/89% vs 84%/90%**; vector/FTS results and exact configuration are
in the [test
report](https://github.com/lancedb/lancedb/blob/typesafe-request-batching/python/benchmarks/typesafe_batching.md).
Ruff and MkDocs passed. The simplified batching flow also passed a fresh
four-query live check: 292 candidate pairs, with 292 unbatched versus 8
batched calls.
Builds on #4209; motivated by [research
#7](https://github.com/lancedb/research/pull/7).
Dropping a view unbinds its name and leaves the definition dataset to a
server-side cleanup job, so the two are separate events a caller may
want to wait on.
`drop_view_async` returns that job — the same shape
`drop_materialized_view_async` and `drop_function_async` already use: a
`202` carries the job id, a `200` (nothing was bound to the name) yields
an already-finished job with no id, and any other success status is an
error rather than a silent no-op.
## `drop_view` waits
`drop_view` now awaits the job before returning, so a caller who does
not want to think about cleanup gets the stronger guarantee: when it
returns, the definition really is deleted.
That is deliberately **different** from `drop_materialized_view` and
`drop_function`, which return as soon as the name is unbound and
document that content may still be deleting. The view API is the newer
one, and waiting is the semantic worth having; the other two are left
alone rather than changing behaviour already released.
## Surfaces
`Database` trait, the remote client, `Connection`, and the Python and
Node bindings — matching where `drop_materialized_view_async` is already
exposed.
Four client tests cover the accepted case reporting its job id, the
nothing-bound case reporting a finished job, a `202` without a usable
`job_id`, and an unexpected success status.
A view is a named query a database stores and plans on every read. It
holds no rows, which is the whole difference from a materialized view.
## API
| Verb | Route |
| --- | --- |
| `create_view(name, query, namespace_path)` | `POST
/v1/view/{id}/create` |
| `describe_view(name, namespace_path)` | `POST /v1/view/{id}/describe`
|
| `drop_view(name, namespace_path)` | `POST /v1/view/{id}/drop` |
| `list_views(namespace_path)` | `GET /v1/namespace/{id}/view/list` |
On `Connection` and the `Database` trait, with the remote client, Python
(sync and async) and Node bindings. Local databases return
`NotSupported`: the server side is Sophon's, where a view is an object
of the database manifest.
`ViewDescription` carries the defining query, the database *and
namespace path* unqualified names in it resolve against, and the schema
the query resolved to. `create_view` returns one, so a caller has the
schema without a second call.
Both defaults travel with the view because it outlives the session that
declared it: the server re-plans the stored query on every read, so a
reader resolving an unqualified name against its own defaults would read
a different table. `default_namespace_path` crosses the wire as
`default_namespace`, a path like `namespace`, absent for the root.
There is no replace: a name already taken is an error, and changing a
view is a drop followed by a create, each authorized against what it
actually touches.
Querying a view stays SQL's job. There are no rows behind a view, so
there is no `open_view` returning a `Table`.
A view could only map source rows one to one, or one to many through a
FROM-position item, so nothing could see all the rows sharing a key.
A view query now takes `GROUP BY expr, ...` with aggregate projections,
planned and executed by DataFusion over the lance scan. A group spans
fragments, so a grouped view is recomputed in full whenever its source
changes; each row's provenance is its group's smallest source row id.
Such a query is stored as definition format 2, so a reader that predates
grouping reports the view as unrefreshable instead of failing to parse
it.
Stacked on #4190.
A view definition was a structured record under a `kind` tag, one kind
per query shape, and a Function returning `list<struct>` was about to
add a third. That names shapes instead of describing a relation.
A materialized view is now a relation defined by a query, stored as one
canonical SQL string under a format number:
```sql
SELECT columns FROM [ns.]table [, function(args) AS alias | , UNNEST(column) AS alias]
[WHERE predicate] [LIMIT n]
```
Any other clause is refused at parse time. Older readers report the view
as unrefreshable, the pre-format layouts still read, and a legacy view
is rewritten on its next refresh that commits, rebuilt only where its
raw text meant something else under lance's parser.
A Function in FROM position yields one row per element it returns, as a
table function does in any dialect. The server stages its list output in
a hidden table and records that binding beside the query, which stays as
the user wrote it; refresh scans the staging and unnests the column, the
same operator as UNNEST over a list column the table already holds. Row
ids repeat per element, so eviction and incremental append are
unchanged. A local database refuses a Function in FROM position, since
it has no executor.
A refresh running under a skip policy records each row it skipped, with
the failing input and the error, but the client could not read that
store: the server exposes it over SQL and, since recently, a REST route.
A user who hit per-row failures still had to open a SQL session.
`Table::function_errors` calls the route. The listing is table-addressed
with optional job and column filters, the same addressing the SQL
surface uses, so the two cannot disagree about what a table's errors
are. The two non-record signals come back as their own fields rather
than as rows: capped-fragment summaries, and whether the listing stopped
at its limit. Local tables refuse rather than answer with an empty list.
Python and Node expose the same call, with the same optional filters.
Adds the client half of database-scoped named Secrets: a Secret is a
name and
an opaque value stored by the service, and a Function binds one to the
environment variable its library already reads. Secrets are addressed by
a
namespace path plus a name.
The UDF body is unchanged and stays portable — it reads `OPENAI_API_KEY`
the
way it always did, and the binding is what puts a value there:
```python
db.create_secret("openai-prod", os.environ["OPENAI_API_KEY"])
function = db.create_function(
analyze_caption,
secrets=[
EnvVarSecret(secret_name="openai-prod", env_variable="OPENAI_API_KEY")
],
)
function.secret_bindings # the Secret's name, never its value
```
- `create_secret` / `alter_secret` / `list_secrets` / `describe_secret`
/
`drop_secret` on sync, async and remote connections, with the pyo3
binding
and the Rust client behind them. Each takes `namespace_path`
keyword-only,
defaulting to the root.
- **There is no read API, by construction rather than by policy** — no
code
path returns a stored credential, and `describe_secret` answers with
metadata only.
- `EnvVarSecret` is a pure local constructor: it contacts no server, so
it
cannot fail on a Secret that does not exist. It exists so that a bare
string
in that position — which would be a credential — is a `TypeError` rather
than a plausible-looking mistake that reads identically in a diff.
- `create_function(..., secrets=[...])` carries the bindings as
`secret_bindings`: a list of `SecretBinding` tagged by `kind`, so a
later
delivery mode is a variant rather than a sibling field. The value never
travels — it is resolved by the service when the Function runs, which is
what
lets a rotation reach columns already pinned to an older
FunctionVersion.
- A binding names its Secret as a `SecretReference` of `{name,
namespace_path}`
rather than one joined string, so no delimiter has to be excluded from
every
name and segment forever, and `ClientConfig.id_delimiter` cannot
contradict
an identity built on a fixed separator.
- A root namespace is omitted from the request body rather than sent
empty, so
a root request is byte-identical to one from a client that predates
namespaces. Tests pin it.
This is the client surface the design's §4 describes; the service side
lives in
sophon.
**Previously split across two PRs.** Namespace addressing was #4151,
stacked on
this one; it is folded in here so the Secret identity contract — name,
namespace path, and the binding that carries both — is reviewable as one
piece
rather than as a shape introduced and then replaced.
## Identifier safety, merged from #4189
**#4189 is merged into this branch**, so the client half of Secrets and
the
guards on the identity it puts in the URL are one PR. What it added:
- Components are checked where the identifier is built, before a request
is
constructed. `create_secret("../jobs", value)` no longer resolves to
`/v1/jobs/create` and delivers a credential-bearing body to a route with
none
of this one's body suppression.
- Each component is percent-encoded and joined by the delimiter, so
nothing
inside a component can end the path segment or add one.
- A component may not be empty, a relative segment (`.`, `..`, and their
`%2e`
spellings), or the delimiter itself — the three ways a component erases
a
boundary the split has to recover. `["prod", ""]` joined to `prod$`,
which
reads back as `["prod"]`.
- `$` is the only accepted `id_delimiter`, refused at client
construction.
`ClientConfig.id_delimiter` remains, since the identifier grammar comes
from
the Lance REST catalog standard, but a value that would produce
identifiers no
service splits the caller's way is now an error where it was written.
- One `build_object_identifier` and one character set serve tables,
namespaces,
Secrets, Functions and materialized views.
Components are checked for *addressability*, not a character set: the
name's
own grammar stays each object's own, so a catalog database keeps the `/`
that
`RemoteCatalog::validate_name` allows.
## Known shortcoming
`secret_bindings` is omitted from a registration body when empty, so a
client
that binds nothing sends what a client without bindings sends. When a
client
does bind a Secret and the service does not know the field, the field is
ignored: registration succeeds, the returned version carries no
bindings, and
the Function fails at execution with the variable unset, far from the
call that
asked for it.
`ServerVersion` is how this codebase refuses a feature the service is
too old
for, and it gates five features already. It does not gate this one: it
is held
per table, and registering a Function is a database-level call. Noted at
the
field in `remote/db.rs`; wiring the gate is follow-up work.
**Tests:** lancedb lib 1340 passed, `first_class_function_slice1` 9,
`first_class_function_slice2` 3, plus Python tests across both slices.
Rebased onto `main` after #4176 (OCI Function identity), #4191 (`.`/`..`
table
names) and #4195 (remote catalogs).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
https://claude.ai/code/session_01UfmeJ533rQDnPBkMtjerV6
---------
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add a `Catalog` trait and `RemoteCatalog` for managing databases,
exposed through Rust, synchronous/asynchronous Python, and TypeScript. A
remote catalog represents the server's root namespace, and each database
is one child namespace. Create/connect return ordinary LanceDB
connections, so existing table APIs work unchanged.
## Rust API
`Catalog` is an object-safe async trait with `create_database`,
`connect_database`, `list_databases`, and `drop_database`. Backend
create/connect methods return `Arc<dyn Database>`; the public
`CatalogConnection` wraps them as `Connection` values and shares its
embedding registry with those connections. `RemoteCatalog` implements
the trait; `connect_catalog` is the convenience builder, available with
the `remote` feature.
```rust
use lancedb::catalog::{
CreateDatabaseRequest, DropDatabaseRequest, ListDatabasesRequest,
};
let catalog = lancedb::connect_catalog("https://my-server.example")
.api_key("my-api-key")
.execute()
.await?;
let db = catalog.create_database(
CreateDatabaseRequest::new("analytics").exist_ok(true),
).await?;
let connected = catalog.connect_database("analytics").await?;
let page = catalog.list_databases(
ListDatabasesRequest::default().limit(20),
).await?;
// page.databases: Vec<String>; page.page_token: Option<String>
catalog.drop_database(
DropDatabaseRequest::new("analytics").ignore_missing(true),
).await?;
```
Create/drop also accept a plain name for default behavior, e.g.
`catalog.create_database("analytics").await?`. Existing names fail
creation unless `exist_ok` is enabled; missing names fail drop unless
`ignore_missing` is enabled. Drop always requires an empty database.
## Python API
```python
import lancedb
catalog = lancedb.connect_catalog(
"https://my-server.example", api_key="my-api-key"
)
db = catalog.create_database("analytics", exist_ok=True)
connected = catalog.connect_database("analytics")
page = catalog.list_databases(limit=20)
# page.databases: list[str]; page.page_token: Optional[str]
if page.page_token is not None:
next_page = catalog.list_databases(limit=20, page_token=page.page_token)
catalog.drop_database("analytics", ignore_missing=True)
```
`connect_catalog` returns `Catalog`; create/connect return the existing
`DBConnection` API. The async equivalent is `catalog = await
lancedb.connect_catalog_async(...)`, returning `AsyncCatalog`; await
each of the same four methods, with create/connect returning
`AsyncConnection`.
## TypeScript API
```typescript
import { connectCatalog } from "@lancedb/lancedb";
const catalog = await connectCatalog("https://my-server.example", {
apiKey: "my-api-key",
});
const db = await catalog.createDatabase("analytics", { existOk: true });
const connected = await catalog.connectDatabase("analytics");
const page = await catalog.listDatabases({ limit: 20 });
// page.databases: string[]; page.pageToken?: string
if (page.pageToken !== undefined) {
const nextPage = await catalog.listDatabases({
limit: 20, pageToken: page.pageToken,
});
}
await catalog.dropDatabase("analytics", { ignoreMissing: true });
```
Create/connect return the existing `Connection` API. All four methods
are asynchronous.
## REST mapping
All paths below are relative to the catalog endpoint. `{name}` is the
logical database name encoded as one URL path component. The default
namespace delimiter is `$`, so the root identifier is encoded as `%24`.
| Catalog operation | Existing REST route | Request |
| --- | --- | --- |
| `create_database(name)` | `POST /v1/namespace/{name}/create` |
`{"mode":"Create"}`; `exist_ok=true` sends `{"mode":"ExistOk"}` |
| `connect_database(name)` | `POST /v1/namespace/{name}/describe` |
`{}`; verifies existence before returning a scoped connection |
| `list_databases(...)` | `GET /v1/namespace/%24/list` | Optional
`limit` and `page_token` query parameters |
| `drop_database(name)` | `POST /v1/namespace/{name}/drop` |
`{"mode":"Fail","behavior":"Restrict"}`; `ignore_missing=true` changes
mode to `"Skip"` |
For example, database `team/search` uses
`/v1/namespace/team%2Fsearch/create`. A paginated root listing can use
`/v1/namespace/%24/list?limit=20&page_token=a%2Fb`. The list response
retains the existing namespace wire shape,
`{"namespaces":["analytics"],"page_token":"next"}`; the SDK exposes
`namespaces` as `databases` and preserves the opaque continuation token.
An absent or empty token ends pagination. Page limits must be between 1
and 2147483647. Create/drop accept a namespace JSON response or HTTP
204.
Catalog management requests omit both `x-lancedb-database` and
`x-lancedb-database-prefix`, including values supplied through static or
dynamic headers. Returned database connections set `x-lancedb-database`
to the exact logical name and keep independent scope. API keys, OAuth or
dynamic authentication, client settings, table read consistency
settings, and an optional SQL endpoint override carry over to those
connections. OAuth cannot be combined with an API key or a custom header
provider.
For SQL through an HTTPS catalog, configure the existing SQL endpoint
contract with Rust
`.sql_host_override("grpc+tls://sql.example.com:10026")` or Python
`sql_host_override="grpc+tls://sql.example.com:10026"`. TypeScript
catalog options expose the same setting as `sqlHostOverride`. It is
inherited by created/connected databases, retained by Python connection
serialization, and initialized lazily when SQL is executed.
Create HTTP 409 maps to `DatabaseAlreadyExists`; connect/drop HTTP 404
maps to `DatabaseNotFound`, except that `ignore_missing` suppresses a
missing-database drop. Other server errors propagate. The server
enforces restricted deletion; the client never requests cascading
deletion.
Database names preserve literal slashes as part of one name. They must
be nonempty ASCII, with no control characters, surrounding whitespace,
or configured namespace delimiter, and cannot be `.` or `..`. Endpoints
must be HTTP(S) URLs without embedded credentials, query parameters, or
fragments.
## Scope
This PR adds the client API and reuses existing namespace endpoints.
Local catalogs, `__catalog` storage, location generation/sanitization,
and `__manifest` lifecycle support remain deferred; the Lance dependency
is unchanged.
The PR also runs macOS Node tests serially to avoid existing
resource-contention timeouts reproduced across recent main runs.
---------
Co-authored-by: Xuanwo <github@xuanwo.io>
Stacked on #4173 (`jack/restore-oidc-flows`, base branch mirrored to
this repo so the diff shows only this change); context from review:
https://github.com/lancedb/lancedb/pull/4173#issuecomment-5674048100.
Rebase to `main` once #4173 and #4179 merge.
## What moved to the `oauth2` crate (5.0, no default features)
- Authorization URL generation and CSRF state (`authorize_url`,
`CsrfToken`)
- PKCE S256 challenge/verifier generation and code exchange
- Client-credentials, authorization-code, refresh-token, and device-code
grant request construction
- Device authorization request and the device token polling loop
(`authorization_pending`, `slow_down` +5s, expiry deadline, denial,
network backoff capped at 10s)
- Standard success/error response parsing (`RequestTokenError`)
- Token-endpoint client authentication and standards-compliant parameter
encoding (RFC 6749 2.3.1 Basic encoding)
LanceDB keeps ownership of OIDC discovery (compared `openidconnect`: no
measurable win for our 3-field metadata + strict validation, at real
dependency cost), HTTPS-or-loopback endpoint enforcement, the loopback
callback server, browser/stderr prompts, token caching and refresh
orchestration, and the dedicated hardened Azure IMDS source, which is
unchanged.
## Client authentication methods
New `ClientAuthMethod` enum (`none` | `client_secret_basic` |
`client_secret_post`), exposed in Rust, Python, and Node. Unset resolves
to `client_secret_basic` when a secret is present (RFC 6749 2.3.1
recommendation and the normal Okta confidential-app default, so a
default Okta app works without weakening its configuration) and to
`none` for public clients (PKCE/device). Explicit `none` with a secret,
or basic/post without one, is rejected. The method applies to client
credentials, code exchange, refresh, and device requests. Deliberate
behavior change: confidential clients previously always sent the secret
in the POST body; they now default to Basic (Keycloak accepts both).
No `audience`/`resource` parameters were added: the supported target is
an Okta custom authorization server with the API audience configured
server-side, so client-provided audience parameters are unnecessary;
`add_extra_param` support exists if a concrete provider contract ever
needs them.
## Device polling behavior changes (deliberate, tested)
- The first token poll now happens immediately rather than after one
interval (RFC 8628 allows both).
- Transient failures (HTTP 429, 5xx, `temporarily_unavailable`, network
errors) now retry with exponential backoff capped at 10s instead of
retrying at the fixed interval; polling never spins faster than once per
second even if a server reports a zero interval.
## Security and compatibility
- Issuer and discovered endpoints (and device verification URIs) still
require HTTPS except explicit loopback HTTP, enforced before any crate
URL type is built
- Token HTTP client keeps the hardened redirect policy that refuses
insecure redirect targets; regression test added
- Errors never embed raw response bodies (avoids leaking tokens through
parse failures); all credential types stay redacted in Debug
- Transient conditions (429/5xx/`temporarily_unavailable`) remain
retryable in device polling and hard errors elsewhere; refresh keeps
rotation and reauthentication semantics
- Existing public APIs stay source-compatible except the added
`OAuthConfig.client_auth_method` field
## Tests
Rust: client-auth methods across code
exchange/refresh/client-credentials/device (none/basic/post),
auth-method resolution and validation, transient device retries,
denial/expiry, redirect rejection, malformed-response leak check, PKCE
URL assertions, redaction. Python and Node: enum values, conversion,
unknown-method errors, config defaults.
Manual Okta validation recipe (no automated Okta credentials): create a
custom authorization server with an API audience, one confidential web
app (Basic) for authorization-code, one native app (PKCE, no secret),
one native device app; point `issuer_url` at the custom server, set
`client_auth_method` only for the POST-required case; verify token
acquisition, refresh after expiry, and `x-lancedb-credential-type: oidc`
against a LanceDB deployment. Never commit tenant URLs or secrets.
Co-authored-by: Xuanwo <github@xuanwo.io>
Function versions identify independent Function objects and their
numeric revisions. Rust and Python expose the object ID, location,
canonical decimal version, metadata, and availability separately from
the OCI image digest. Computed-column applications carry the complete
object reference, so existing bindings retain their identity after a
name is removed and reused.
Source authoring keeps the existing
create_function/create_function_async, job wait, and column-binding
APIs. The server coordinates baking followed by registration; users do
not have to manage manifest digests to create a Function. The previous
stored Function representation is intentionally unsupported. Existing
contract tests and shared wire fixtures are migrated to the new model.
This SDK change accompanies the final integration layer
https://github.com/lancedb/sophon/pull/7887 in the Sophon stack:
https://github.com/lancedb/sophon/pull/7885 →
https://github.com/lancedb/sophon/pull/7886 →
https://github.com/lancedb/sophon/pull/7887. A metadata-only revision
can retain the same executable image; Function version numbers must not
be used as image cache keys.
---------
Co-authored-by: lancedb automation <robot@lancedb.com>
Co-authored-by: Yang Cen <bubble-cal@outlook.com>
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
## Issue
Fixes#4063
## Background
The Node.js SDK currently requires callers to know the Arrow extension
metadata needed to represent JSON fields. This makes a common LanceDB
schema type unnecessarily verbose and easy to get wrong.
## Changes
- Add `makeJsonField(name, nullable = true)` to create a UTF-8 Arrow
field with the `arrow.json` extension metadata.
- Re-export the helper from the public Node.js entry point.
- Add coverage for the default nullable behavior, explicit non-nullable
fields, and the extension metadata.
- Add the generated TypeDoc function page and public globals entry,
including a usage example.
## Implementation
The helper uses the existing Apache Arrow `Field` type and sets
`ARROW:extension:name` to `arrow.json`, matching the metadata convention
already used by LanceDB.
## Compatibility
This is an additive Node.js API. Existing schema construction and Arrow
behavior are unchanged.
## Verification
- `pnpm test -- arrow.test.ts --runInBand` — 236 tests passed.
- `pnpm exec biome ci lancedb/arrow.ts lancedb/index.ts
__test__/arrow.test.ts` — passed.
- `git diff --check` — passed.
## Not run / known limitations
- `pnpm build` and `pnpm run docs` were attempted after expanding the
checkout. Both are blocked locally by the native binding build/type
declarations: Cargo did not complete, and TypeDoc reported the missing
generated `nodejs/lancedb/native` module. The docs files were generated
from the updated TypeScript comments; full build and docs validation are
left to CI.
## Summary
Align the experimental materialized-view HTTP transport with the
equivalent Table API shape and add remote materialized-view support
across Rust, Python, and TypeScript. This is an intentional breaking
change to the experimental materialized-view surface.
Materialized-view creation performs an initial refresh by default. The
create endpoint returns `202 Accepted` with `{ "job_id": "..." }`;
blocking SDK creation waits for that job before returning a populated
view. `with_no_data` / `withNoData` explicitly creates only the
definition and empty backing table.
## Route comparison
| Operation | Materialized-view API | Equivalent Table API |
| --- | --- | --- |
| Create | `POST /v1/materialized_view/{id}/create` | `POST
/v1/table/{id}/create` |
| Describe/open | `POST /v1/materialized_view/{id}/describe` | `POST
/v1/table/{id}/describe` |
| List | `GET /v1/namespace/{id}/materialized_view/list` | `GET
/v1/namespace/{id}/table/list` |
| Refresh | `POST /v1/materialized_view/{id}/refresh` | asynchronous
Table mutation pattern |
| Drop | `POST /v1/materialized_view/{id}/drop` | `POST
/v1/table/{id}/drop` |
Create, describe, refresh, and drop identify the target in the singular
item path instead of duplicating it in the request body. Create and drop
require `202 Accepted` with a valid job ID. List is a namespace-scoped
GET with opaque pagination tokens. The Rust list API now returns view
names, matching Table listing and the existing Python and TypeScript
APIs.
## Python API changes
| Operation | Synchronous API | Asynchronous API | Table/job pattern |
| --- | --- | --- | --- |
| Create and wait | `DBConnection.create_materialized_view(...)` |
`await AsyncConnection.create_materialized_view(...)` | Returns a
materialized-view handle after its initial-population job finishes |
| Submit create | `DBConnection.create_materialized_view_async(...) ->
Job[None]` | `await AsyncConnection.create_materialized_view_async(...)
-> AsyncJob[None]` | Matches job-returning Table mutations such as
`create_index_async` |
| Open | `DBConnection.open_materialized_view(...)` | `await
AsyncConnection.open_materialized_view(...)` | Opens the backing Table
plus its definition |
| List | `DBConnection.list_materialized_views()` | `await
AsyncConnection.list_materialized_views()` | Returns names like Table
listing |
| Refresh and wait | `MaterializedView.refresh(...)` | `await
AsyncMaterializedView.refresh(...)` | Returns the typed refresh result
after the job finishes |
| Submit refresh | `MaterializedView.refresh_async(...) ->
Job[RefreshMaterializedViewResult]` | `await
AsyncMaterializedView.refresh_async(...) ->
AsyncJob[RefreshMaterializedViewResult]` | Matches
`Table.refresh_column_async`; remote job handles expose the server job
ID |
| Drop | `DBConnection.drop_materialized_view(...)` | `await
AsyncConnection.drop_materialized_view(...)` | Matches blocking
`drop_table` |
| Submit drop | `DBConnection.drop_materialized_view_async(...) ->
Job[None]` | `await AsyncConnection.drop_materialized_view_async(...) ->
AsyncJob[None]` | Matches `drop_table_async`; remote handles expose the
server cleanup job ID |
The materialized-view handle exposes its backing Table through `.table`,
so normal Table query, search, and index APIs apply. Definition lookup
and refresh are backend-aware rather than depending on local schema
metadata. TypeScript exposes the equivalent blocking/job drop pair as
`dropMaterializedView` and `dropMaterializedViewAsync`.
Stacked on #4173 (diff includes it until that merges; will rebase
after). Addresses the token-cache part of [Colin's
review](https://github.com/lancedb/lancedb/pull/4173#issuecomment-5674048100).
Adds an explicit, opt-in persistent OAuth token cache shared by Rust,
Python, and Node clients, plus `login` / `status` / `logout` session
APIs, so short-lived processes (CLIs, scripts, notebooks) reuse one
session instead of restarting a browser or device flow on every start.
- **Opt-in and minimal**: existing callers stay memory-only and lazy.
Only refresh tokens are persisted (never access tokens, never client
secrets), so there are no local token-expiry decisions to get wrong when
clocks move. Each process start performs one silent refresh grant.
- **Hardened file backend**: private directory (`0700`), per-record
files (`0600`), owner validation, symlink rejection, and atomic `rename`
replacement. Corrupt, truncated, unknown-version, or permission-invalid
records fail with actionable errors naming the file. Native keyring
backends were evaluated (keyring crate routes Linux through D-Bus/zbus:
heavy deps, headless/CI flakiness) and are deferred; the file store is
the explicit opt-in, not a downgrade from a keyring.
- **Cache key**: SHA-256 of the canonical identity (issuer, client ID,
sorted/de-duplicated scopes, flow, public/confidential), so no secret
appears in a filename and distinct identities never collide. Versioned
record schema (`version: 1`). One record per identity: last login wins,
documented.
- **Cross-process rotation locking**: per-key `fs4` file lock (`flock` /
`LockFileEx`) around the refresh critical section — acquire, reread the
durable record, refresh exactly once, atomically store the rotated
refresh token, release. The OS releases locks on process death, so
crashes cannot strand stale locks. Only confirmed
`invalid_grant`/`invalid_token` deletes a record and reauthenticates;
transport, 5xx, 429, and parse failures retain it.
- **Session APIs**: `OAuthSession::login/status/logout` in Rust,
`lancedb.remote.OAuthSession` (async) in Python, `OAuthSession` class in
Node. `status` returns non-secret metadata only. `logout` removes only
the local credential — provider revocation (RFC 7009) is a deliberate
follow-up, and local logout never terminates browser SSO. Azure managed
identity is rejected for persistence (machine identity stays in memory);
client credentials have nothing refreshable to persist and stay
memory-only.
- No CLI binary exists in this repo, so this ships library APIs plus doc
examples in all three languages.
Tests: Rust unit + mock-IdP integration (cache-key
canonicalization/separation, record
versioning/corruption/truncation/symlink/owner/perms, lock serialization
+ release, two concurrent providers proving no `invalid_grant` and
correct rotation, transient-failure retention, `invalid_grant` delete +
reauthenticate, login/status/logout lifecycle, client-credentials no-op,
IMDS rejection, secret redaction); Python lifecycle + a true
two-subprocess cross-process reuse test (second process refreshes once,
never hits the device endpoint); Node lifecycle + device-flow login
test. Local builds were skipped in development; CI validates all
bindings.
---------
Co-authored-by: Xuanwo <github@xuanwo.io>
<!-- lance-gatekeeper-fix:v1 agent=278cb095b2e5d69051442bc254d803a6
generation=1 -->
## Summary
- pass the TypeScript `cleanupOlderThan` date to the native binding as
an unchanged epoch timestamp
- prune with Lance's absolute `before_timestamp` policy so dispatch and
compaction time cannot move the cutoff
- retain versions created after the supplied cutoff and document that
behavior
- add boundary and end-to-end regression coverage
## Root cause
The TypeScript layer converted the absolute date into an elapsed
duration before calling native optimize. Lance converted that duration
back into a timestamp only after compaction, which silently advanced the
requested cutoff and made the cleanup count depend on a millisecond
timing boundary.
## Validation
- `cargo fmt --all`
- `cargo clippy --quiet --features remote --tests --examples -p lancedb
-p lancedb-nodejs`
- `pnpm build`
- `pnpm lint`
- `pnpm run docs`
- `pnpm test __test__/table.test.ts --runInBand` (309 passed)
Fixes#4159
---------
Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
refresh_column fills nulls, so once a row has a value nothing revisits
it: an update to one of its inputs, or a definition change, leaves the
computed value stale for good.
This stamps the column's field metadata with the definition it was
computed under and a per-fragment signature of the input storage it was
read from (input data files and overlays; not the deletion file, since a
delete changes no surviving value). A refresh recomputes every live row
of a fragment whose stamp disagrees with the manifest, then records what
it computed from in a second commit after the fill. A compacted fragment
inherits freshness through the Rewrite lineage when every fragment it
was built from was signed, or was appended since the stamp, never had an
input moved, and left its rows of the product unfilled (a raw append may
supply a value; the product's data is the evidence, and the null fill
covers those rows); otherwise it recomputes. A column declared before
the stamps existed keeps the null-fill contract on its first refresh,
which enrolls it as it stood.
The map is one entry per fragment per column, so it is kept out of the
manifest: each stamp writes an immutable sidecar under `_computed/`,
named by its content digest, and the field metadata holds the digest.
Pruning old versions also drops the sidecars no remaining version
references, keeping any younger than seven days as lance keeps
unverified files, since a sidecar is put before the commit that
references it. The stamp commit is metadata-only, so a materialized
view's drift check treats it like the fill. The core lives in
`table::freshness` so a remote refresh can share the contract.
this PR blob v2 field helpers and reads to the Node SDK.
`blob()` marks a field as blob v2 and lets you set the storage
thresholds. Inputs can be bytes, a URI, or a data/uri struct.
Queries return descriptors. `fetchBlobs()` reads the bytes by row ID,
and `fetchBlobFiles()` gives you lazy handles for full or range reads.
`blobColumns()` lists the blob fields, including nested ones.
Fetch uses the table’s current checkout. It preserves order, duplicates,
and nulls. Holding row IDs across compaction still requires stable row
IDs.
```javascript
const db = await connect("./data");
const video = await readFile("clip.mp4");
const table = await db.createTable(
"videos",
[{ id: 1n, video }],
{
schema: new Schema([
new Field("id", new Int64()),
blob("video"),
]),
},
);
const rows = await table.query().select(["id"]).withRowId().toArray();
const rowIds = rows.map((row) => row._rowid as bigint);
const bytes = await table.fetchBlobs("video", rowIds);
const [handle] = await table.fetchBlobFiles("video", rowIds);
const header = await handle!.readRange(0n, 65536n);
```
### Testing
- cover input validation, thresholds, nested fields, fetch ordering,
nulls, and range reads.
Adds [typos](https://github.com/crate-ci/typos) as a CI check and
pre-commit hook, the same way Lance does it, so misspellings like the
ones fixed in #4146 get caught automatically going forward.
This also fixes the misspellings `typos` found across the repo (Rust,
Python, TypeScript source, comments, and generated docs), and adds a
small `.typos.toml` with `extend-words` entries for terms that are
correct but look like typos: `AKS` (Azure Kubernetes Service), `RabitQ`
(a real quantization algorithm name), `mmaped` (the actual name of a
`candle-core` API we call), and `Writeable` (from Python's
`_typeshed.WriteableBuffer`). Third-party license files are excluded.
Fixes#4147
Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
A 1M-row column refresh over 200 fragments produced no visible result,
and the client could only ever say `"running"`. Everything needed to
diagnose it already existed server-side — the job registry records a
`claim`/`claim_complete` pair per fragment carrying `rows_processed` —
but none of it was reachable.
## Before
Four ways to ask about a job, none of which told you much.
```python
job = table.refresh_column_async("embedding")
job.status() # "running". That was the entire debug surface.
db.get_job(job_id) # state, and a spec. No result, no progress.
db.job_history(job_id) # raw record batches, no limit, no filter
db.job(job_id) # a handle that knew nothing
```
## After
Open a job the way you open a table; the handle answers everything.
```python
job = db.open_job(job_id) # raises JobNotFoundError if there is no such job
```
```python
>>> print(job)
Job(
id='job-1',
state='failed',
job_type='refresh_column',
creation_ms=1757000000000,
spec={
"column": "embedding",
"num_workers": 4
},
failure=JobFailureInfo(phase='execute', message='worker died', retryable=True),
)
```
Individual fields are there too — `job.state`, `job.job_type`,
`job.creation_ms`, `job.spec`, `job.result`, `job.failure` — and
`job.result` carries `rows_assigned` / `rows_failed` as soon as the job
succeeds, with no `wait()` required.
Per-fragment progress *while it is still running*:
```python
done = job.events(filter="state = 'claim_complete'", limit=10_000)
done.column("rows_processed").to_pylist() # [5000, 5000, ...]
```
The handle an async action returns is the same object, one `refresh()`
away:
```python
job = table.refresh_column_async("embedding")
job.refresh()
job.state, job.result
```
TypeScript is the same experience, down to `console.log`:
```ts
const job = await db.openJob(jobId); // rejects if there is no such job
console.log(job); // same multi-line layout
job.state; job.jobType; job.spec; job.result; job.failure;
const done = await job.events({ filter: "state = 'claim_complete'", limit: 10_000 });
```
## Why each piece matters
- **A result without waiting.** `rows_assigned` / `rows_failed` used to
live only on the terminal result, so a job that never terminated
reported nothing at all.
- **`limit`.** The server caps event rows at 1000 and truncates without
saying so, which silently hid most of a 200-fragment job's history.
- **`filter`.** `claim_complete` rows carry per-claim `rows_processed` —
the only progress signal that exists mid-flight.
- **Events outlive the worker.** They live in the job registry, not in
pod logs that vanish with the pod.
- **One place to ask.** `open_job` replaces `describe_job`,
`query_job_events` and `job`, so a question about a job has one answer
instead of one per calling location.
- **A missing job is an error, not a `None`.** The common case is a job
id copied out of a log, where absence is the surprise worth raising —
and it matches `open_table`.
- **Printing is the debug surface.** Every field on its own line, JSON
payloads keeping their structure. An unrefreshed handle stays on one
line, because there is nothing to lay out.
- **In-process jobs say so.** A local refresh reports `state` and leaves
the rest null rather than inventing fields it has no record for.
`list_jobs` and `cancel_job` stay as they were: one lists, the other is
a one-shot action that should not need a describe first.
## Breaking
All shipped in 0.38.0. No deprecated aliases.
| Was | Now |
| --- | --- |
| `Connection.get_job` → `describe_job` | `Connection.open_job` returns
a populated `Job`, or raises |
| `Connection.job_history` → `query_job_events` | `job.events(...)` |
| `Connection.job` | `Connection.open_job` |
| Python events → `List[pa.RecordBatch]` | `pa.Table` |
| `JobDescription.spec_json` / `.result_json` | internal; use `job.spec`
/ `job.result` |
Node's `Job` is now a TypeScript class wrapping the native handle, so it
returns an Arrow table and parsed values like Python does. New
`Error::JobNotFound` / `JobNotFoundError`; the three job exceptions are
now in the Python API reference.
Supports fully nullable named Function outputs while preserving the
distinction between a valid all-null struct and a null/unassigned
result.
## Concrete example
This UDF contract is now valid:
```python
@udf(
input_schema=pa.schema([
pa.field("text", pa.string(), nullable=False),
]),
output_schema=pa.schema([
pa.field(
"embedding",
pa.list_(pa.float32(), list_size=1024),
nullable=True,
),
pa.field("embedding_failure_reason", pa.string(), nullable=True),
pa.field("embedding_failure_code", pa.int32(), nullable=True),
]),
)
def embed(text):
...
```
A successful row can return:
```text
embedding = [0.12, ...]
embedding_failure_reason = NULL
embedding_failure_code = NULL
```
If remote inference still fails after retries, it can return:
```text
embedding = NULL
embedding_failure_reason = "HTTP 429: rate limited"
embedding_failure_code = 429
```
An all-null but valid result struct is also assigned; it is not mistaken
for unfinished work.
## Binding shapes
- Mapping the result to one output column stores the `StructArray`
directly, including its parent validity bitmap.
- Flattening the result into top-level columns stores the parent
validity in a reserved internal nullable Boolean assignment column that
is not part of the UDF result mapping.
- An outer null struct remains unassigned/skipped. A valid struct
remains assigned regardless of which child fields are null.
- Scalar Function outputs remain non-nullable.
The contract is preserved through Python registration, Rust application
planning, persisted `FunctionBinding` metadata, schema revalidation, and
Enterprise execution.
## Summary
Add SQL execution to remote LanceDB connections. On the standard
synchronous connection, `execute_query` waits for the initial result
stream and returns its Arrow reader. `execute_query_async` is called
without Python `await` and immediately returns a query handle for status
inspection, streaming, or cancellation. Local databases report that SQL
is not supported.
The transport and query lifecycle live in Rust. Python exposes
native-backed synchronous and asynchronous connection methods and query
wrappers; it does not use PyArrow's Flight client.
## User experience
The standard synchronous connection supports both direct reads and
background query execution:
```python
db = lancedb.connect(
"db://analytics",
api_key="ldb_...",
sql_host_override="grpc+tls://sql.example.com:10026",
)
# Direct execution waits only until the initial result stream is available.
# Later batches continue streaming as the query progresses.
reader = db.execute_query(
"SELECT * FROM events",
default_namespace_path=["production"],
)
for batch in reader:
print(batch.num_rows)
# Background execution returns a query handle immediately. Despite the
# `_async` suffix, no Python `await` is needed on a synchronous connection.
query = db.execute_query_async("SELECT * FROM events")
print(query.id)
description = db.describe_query(query.id)
print(description.status)
print(description.progress)
print(description.expires_at)
# Start reading as soon as the service advertises partial results. The reader
# continues polling and yields newly available record batches until the query
# and all result endpoints are complete.
reader = query.reader()
for batch in reader:
print(batch.num_rows)
# Or cancel a different still-running query. Its status becomes "cancelling"
# while the server is still working, then "cancelled" once confirmed.
cancelled_query = db.execute_query_async("SELECT * FROM large_events")
cancelled_query.cancel()
```
The less commonly used asynchronous connection exposes the same
operations as coroutines:
```python
async_db = await lancedb.connect_async(
"db://analytics",
api_key="ldb_...",
sql_host_override="grpc+tls://sql.example.com:10026",
)
query = await async_db.execute_query_async("SELECT * FROM events")
async for batch in await query.reader():
print(batch.num_rows)
```
The UUIDv7 query id is scoped to the connection that submitted it. The
connection retains lightweight shared query state used by
`query.describe()` and `db.describe_query(query.id)`; the id does not
encode SQL or a Flight continuation token and is not a cross-connection
resume token. Abandoned state has bounded retention, and terminal state
remains available briefly.
Unqualified table names use the connected database and the `public`
namespace by default. `default_namespace_path` accepts a list such as
`["production", "events"]`. SQL can still use qualified names to
reference other databases and namespaces available to the deployment.
## Design
- Uses Arrow Flight `PollFlightInfo` for submission and long polling,
`DoGet` for results, and `CancelFlightInfo` for cancellation. Each
`PollInfo.info` is treated as the cumulative set of currently available
endpoints, so advertised tickets are consumed once and batches can be
delivered before execution is complete.
- Serializes result completion and cancellation into one lifecycle. A
server-accepted request reports `cancelling` and wakes blocked
status/result work; a later retry can confirm `cancelled`. Result
retrieval is rejected after cancellation is accepted, while cancellation
after a result was already delivered is a no-op.
- Assigns a time-ordered UUIDv7 connection-scoped query id and retains
only shared evolving lifecycle state, keeping SQL, Flight continuation
tokens, and Arrow result data out of public ids and the registry.
- Leaves admission control to the server while honoring server
expiration and a local fallback retention window for abandoned entries.
- Retains terminal ids for five minutes so they remain available for
connection-level description.
- Keeps one lazily initialized SQL client on each remote database
connection and attaches fresh authentication, routing, namespace, and
request metadata to every operation.
- Applies the configured overall timeout to each execution, description,
reader, and cancellation operation. A result reader carries one absolute
deadline from `reader()` through the end of streaming; connect and read
timeouts continue to bound their individual phases.
- Returns a bounded, backpressured, single-consumer Arrow stream rather
than collecting the full result in memory. Dropping the reader stops
downloading but does not implicitly cancel the server query.
- Preserves typed schemas for empty result sets through the stream
schema.
- Accepts Flight result messages up to 1 GiB so a valid row containing a
large blob, string, or vector is not rejected by tonic's 4 MiB default
receive limit.
- Supports the Python client first while keeping the authoritative
implementation in the Rust core.
Gatefixer
ningsh7
Wyatt Alt
Taylor
Jack Ye
Jonathan HsiehandClaude Opus 5
mikemikimike
Colin Patrick McCabe
Drew
Will JonesandClaude Sonnet 5