Jack Ye
9af7757053
Remote materialized-view creation currently expects a REST response containing a registry job ID, while refresh already submits SQL. Route both through the SQL query backend and preserve Python's synchronous and asynchronous return types. ### Query to Job mapping `SqlClient::submit_as_job()` submits an `ExecuteQueryRequest` through the same backend as `execute_query_async()`. Once submission succeeds, it retains the returned `Query` and starts one client-side task that consumes its result reader to completion. `Job::from_query_task()` wraps that task, its cached outcome, a single ID and a cancellation callback. Python exposes this as `Job[T]` or `AsyncJob[T]`. The existing `job_type` property maps SQL-backed handles to the new `"query"` kind. The shared `id` contains that query's UUID string, so Python callers can inspect it with `db.describe_query(job.id)` on the submitting connection. No separate `query_id`, backend enum or `type()` API is added. | Handle | `job_type` | `id` | Available lookup | | --- | --- | --- | --- | | SQL-backed | `"query"`, known at submission | Connection-scoped query UUID string | `describe_query(job.id)` | | Registry-backed | Existing server-reported kind, after `status()` or `refresh()` | Registry job ID string | Registry job APIs, descriptions and events | | Local | `None` | `None` | The current in-process handle | | Job concept | SQL-backed behavior | | --- | --- | | Submission | Await initial SQL submission before returning the handle. Submission errors propagate immediately. | | `status()` | Tracks the adapter task: running during result consumption/finalization, finished after both succeed, failed if either fails, or cancelled after cancellation. | | `wait()` | Returns the operation's typed terminal result. One task consumes the query reader once; repeated waits reuse its cached outcome without resubmitting SQL or reopening the reader. | | `cancel()` | Delegates to `Query.cancel()`. Rejected or unsupported cancellation leaves the task running; an accepted request stops the task. Cancelling a finished operation is a no-op. | | Registry details | Query-backed handles expose no registry description, event history, pause/resume or reattachment after a client restart. `refresh()` updates cached lifecycle state. | The Job tracks command completion rather than exposing SQL batches. A wait timeout does not cancel the query. Query IDs remain scoped to the submitting connection and cannot be used with registry APIs or as durable resume tokens. Python `describe_query()` accepts both UUID objects and the string `id` exposed by query-backed jobs. Rust, Python and TypeScript expose the same classification through their existing job-type accessors. ### Materialized-view operations - **CREATE:** Render `CREATE MATERIALIZED VIEW` with the view namespace and optional auto-refresh settings. After command completion, resolve the job to `None`. Synchronous creation waits on the job, then opens and returns the materialized view. - **REFRESH:** Submit `REFRESH MATERIALIZED VIEW` through the same adapter. After command completion, read the refreshed table's version and row count to construct the existing typed refresh result. Synchronous refresh waits on the same path. Remote creation requires the SQL service. Execution placement remains a server decision. REST endpoints are unchanged. The job guide documents the ID/job-type contract and query-backed limitations. Regression coverage exercises SQL submission, namespaces, refresh options, job-type/ID preservation through typed result mapping, repeated waits, failures and cancellation rejection. No local builds or tests were run.
LanceDB Documentation
LanceDB docs are available at docs.lancedb.com.
The SDK docs are built and deployed automatically by Github Actions
whenever a commit is pushed to the main branch. So it is possible for the docs to show
unreleased features.
Building the docs
Setup
- Install LanceDB Python. See setup in Python contributing guide.
Run
make developto install the Python package. - Install documentation dependencies. From LanceDB repo root:
pip install -r docs/requirements.txt
Preview the docs
Run these commands from the LanceDB repository root. The subshell changes into
docs to load mkdocs.yml, while leaving your shell in the repository root.
(cd docs && PYTHONPATH=. mkdocs serve)
If you want to just generate the HTML files:
(cd docs && PYTHONPATH=. mkdocs build)
If successful, you should see a docs/site directory in the repository root that
you can verify locally.
Adding examples
To make sure examples are correct, we put examples in test files so they can be run as part of our test suites.
You can see the tests are at:
- Python:
python/python/tests/docs - Typescript:
nodejs/examples/
Checking python examples
cd python
pytest -vv python/tests/docs
Checking typescript examples
The examples depend on @lancedb/lancedb at file:../dist, so the package must be
built before running the tests. This uses pnpm; see the
Typescript contributing guide for the toolchain setup.
pushd nodejs
pnpm install
pnpm build
popd
Then you can run the examples by going to the nodejs/examples directory, which is a
separate pnpm package with its own lockfile:
pushd nodejs/examples
pnpm install
pnpm test
popd
API documentation
Python
The Python API documentation is organized based on the file docs/src/python/python.md.
We manually add entries there so we can control the organization of the reference page.
However, this means any new types must be manually added to the file. No additional
steps are needed to generate the API documentation.
Typescript
The typescript API documentation is generated from the typescript source code using typedoc.
When new APIs are added, you must manually re-run the typedoc command to update the API documentation. The new files should be checked into the repository.
pushd nodejs
# `pnpm docs` would invoke pnpm's built-in `docs` command, not the script.
pnpm run docs
popd