test: update create-index default contract coverage

feat: default create_index to create-only
2026-09-12 16:22:24 +00:00 · 2026-09-03 15:52:46 -07:00 · 2026-09-03 14:24:27 -07:00
124 changed files with 1309 additions and 9693 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.39.0-beta.6"
+current_version = "0.39.0-beta.1"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -232,10 +232,7 @@ jobs:
          ALL_FEATURES=`cargo metadata --format-version=1 --no-deps \
            | jq -r '.packages[] | .features | keys | .[]' \
            | grep -v s3-test | sort | uniq | paste -s -d "," -`
-          # Run doctests before test binaries fill the runner disk. Examples are
+          cargo test --profile ci --features $ALL_FEATURES --locked
          # already built by the Linux job, so avoid retaining them here.
          cargo test --profile ci --features $ALL_FEATURES --locked --doc
          cargo test --profile ci --features $ALL_FEATURES --locked --lib --tests
  windows:
    strategy:
@@ -1,20 +0,0 @@
 name: Typo checker
 on:
  push:
    branches:
      - main
  pull_request:
 permissions:
  contents: read
 jobs:
  run:
    name: Spell Check with Typos
    runs-on: ubuntu-latest
    steps:
      - name: Check out code
        uses: actions/checkout@v6
      - name: Check spelling of the entire repository
        uses: crate-ci/typos@6802cc60d4e7f78b9d5454f6cf3935c042d5e1e3 # v1.26.0
@@ -10,10 +10,6 @@ repos:
    rev: v0.9.9
    hooks:
      - id: ruff
  - repo: https://github.com/crate-ci/typos
    rev: v1.26.0
    hooks:
      - id: typos
  # - repo: https://github.com/RobertCraigie/pyright-python
  #   rev: v1.1.395
  #   hooks:
@@ -1,19 +0,0 @@
 [default]
 extend-ignore-re = ["(?Rm)^.*(#|//)\\s*spellchecker:disable-line$"]
 [default.extend-words]
 # Azure Kubernetes Service, mentioned in rust/lancedb/src/remote/oauth.rs.
 AKS = "AKS"
 # RabitQ is the name of a vector quantization algorithm, not a typo of "Rabbit".
 Rabit = "Rabit"
 # `VarBuilder::from_mmaped_safetensors` is the real (if oddly-spelled) name of
 # the candle-core API we call in rust/lancedb/src/embeddings/sentence_transformers.rs.
 mmaped = "mmaped"
 # `WriteableBuffer` is the real name of a type from Python's `_typeshed` stubs,
 # used in python/python/lancedb/_blob.py.
 Writeable = "Writeable"
 [files]
 extend-exclude = [
    "*_THIRD_PARTY_LICENSES.*",
 ]
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 [workspace.dependencies]
-lance = { "version" = "=12.0.0-beta.17", default-features = false, "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=12.0.0-beta.11", default-features = false, "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=12.0.0-beta.17", default-features = false, "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=12.0.0-beta.11", default-features = false, "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=12.0.0-beta.17", default-features = false, "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=12.0.0-beta.11", default-features = false, "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=12.0.0-beta.17", "tag" = "v12.0.0-beta.17", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=12.0.0-beta.11", "tag" = "v12.0.0-beta.11", "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
@@ -39,7 +39,6 @@ arrow-ord = "58.0.0"
 arrow-schema = "58.0.0"
 arrow-select = "58.0.0"
 arrow-cast = "58.0.0"
 arrow-flight = { version = "58.0.0", features = ["flight-sql-experimental"] }
 async-trait = "0"
 bytes = "1"
 datafusion = { version = "54.0.0", default-features = false }
@@ -60,7 +59,7 @@ log = "0.4"
 metrics = "0.24"
 metrics-util = "0.19"
 moka = { version = "0.12", features = ["future"] }
-object_store = "0.14.1"
+object_store = "0.13.2"
 pin-project = "1.0.7"
 rand = "0.9"
 snafu = "0.8"
@@ -72,8 +71,7 @@ serde = "1"
 serde_json = "1"
 tempfile = "3.5.0"
 tokio = { version = "1.23", features = ["rt-multi-thread", "sync"] }
-tonic = { version = "0.14", features = ["tls-native-roots", "tls-ring"] }
+uuid = { version = "1.7.0", features = ["v4"] }
 uuid = { version = "1.7.0", features = ["v4", "v7"] }
 chrono = { version = "0.4", default-features = false, features = ["clock"] }
 [profile.ci]
@@ -155,7 +155,7 @@ paths:
                vector:
                  type: FixedSizeList
                  description: |
-                    The targeted vector to search for. Required.
+                    The targetted vector to search for. Required.
                vector_column:
                  type: string
                  description: |
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.39.0-beta.6</version>
+    <version>0.39.0-beta.1</version>
 </dependency>
 ```
@@ -1,62 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / BlobFile
 # Class: BlobFile
 A lazy handle to blob bytes. Create one with [Table.fetchBlobFiles](Table.md#fetchblobfiles).
 ## Methods
 ### read()
 ```ts
 read(): Promise<Buffer>
 ```
 Reads from the cursor to the end and advances the cursor.
 A second call returns an empty buffer. [BlobFile.readRange](BlobFile.md#readrange) does
 not move the cursor.
 #### Returns
 `Promise`&lt;`Buffer`&gt;
 ***
 ### readRange()
 ```ts
 readRange(start, end): Promise<Buffer>
 ```
 Reads the half-open byte range `[start, end)`.
 Fails when `end` is past the blob size. Does not move the cursor.
 #### Parameters
 * **start**: `bigint`
 * **end**: `bigint`
 #### Returns
 `Promise`&lt;`Buffer`&gt;
 ***
 ### size()
 ```ts
 size(): bigint
 ```
 Returns the blob size in bytes.
 #### Returns
 `bigint`
@@ -448,6 +448,26 @@ on the returned job to know when cleanup has finished.
 ***
 ### getJob()
 ```ts
 abstract getJob(jobId): Promise<null | JobDescription>
 ```
 Describe a single server-side job by id.
 Resolves to `null` when the server has no such job.
 #### Parameters
 * **jobId**: `string`
 #### Returns
 `Promise`&lt;`null` \| [`JobDescription`](../interfaces/JobDescription.md)&gt;
 ***
 ### isOpen()
 ```ts
@@ -462,6 +482,48 @@ Return true if the connection has not been closed
 ***
 ### job()
 ```ts
 abstract job(jobId): Job
 ```
 A [Job](Job.md) handle for a server-side job by id.
 The handle is constructed without a server round trip; an unknown id
 surfaces when the handle is used. Dropping the handle has no effect on
 the job itself.
 #### Parameters
 * **jobId**: `string`
 #### Returns
 [`Job`](Job.md)
 ***
 ### jobHistory()
 ```ts
 abstract jobHistory(jobId?): Promise<Table<any>>
 ```
 The lifecycle event history of a server-side job, as an Arrow table.
 Lists history across all jobs when `jobId` is omitted.
 #### Parameters
 * **jobId?**: `string`
 #### Returns
 `Promise`&lt;`Table`&lt;`any`&gt;&gt;
 ***
 ### listJobs()
 ```ts
@@ -586,30 +648,6 @@ A page of table names and an
 ***
 ### openJob()
 ```ts
 abstract openJob(jobId): Promise<Job>
 ```
 Open a server-side job by id, returning a handle with its record already
 populated. Rejects when the server has no such job, the way
 [Connection.openTable](Connection.md#opentable) does for a missing table.
 The returned [Job](Job.md) answers for its own state, specification,
 result, failure and event history, so there is no separate
 connection-level call for any of them.
 #### Parameters
 * **jobId**: `string`
 #### Returns
 `Promise`&lt;[`Job`](Job.md)&gt;
 ***
 ### openMaterializedView()
 ```ts
@@ -8,116 +8,28 @@
 A handle to an operation that may still be running.
-The operation may already be complete when the handle is created.
+## Constructors
-The detail getters read what the handle last observed. Submitting an
+### new Job()
 operation returns only a job id, so populating them eagerly would cost an
 extra round trip on every call:
- [Job.refresh](Job.md#refresh) and [Job.status](Job.md#status) fetch the whole record.
+```ts
- [Job.wait](Job.md#wait) records the terminal state it establishes, but not the
+new Job(): Job
-  rest of the record.
+```
- Everything is null until one of those runs.
+
 #### Returns
 [`Job`](Job.md)
 ## Accessors
 ### creationMs
 ```ts
 get creationMs(): null | number
 ```
 When the job was created, in milliseconds since the epoch.
 #### Returns
 `null` \| `number`
 ***
 ### failure
 ```ts
 get failure(): null | JobFailureInfo
 ```
 Why the job failed, when it failed and the server reports a reason.
 #### Returns
 `null` \| [`JobFailureInfo`](../interfaces/JobFailureInfo.md)
 ***
 ### id
 ```ts
 get id(): null | string
 ```
-Identifies the operation on the server that is running it.
+Identifies the operation on the server that is running it. Operations
-
+that run in this process have no server id. The value is opaque.
 Operations that run in this process have no server id. The value is
 opaque: parsing it or storing it to resume the job later is not supported.
 #### Returns
 `null` \| `string`
 ***
 ### jobType
 ```ts
 get jobType(): null | string
 ```
 The job's type, as the server names it. Null for an in-process job, which
 has no server-side record.
 #### Returns
 `null` \| `string`
 ***
 ### result
 ```ts
 get result(): any
 ```
 The job-type-specific terminal result. Null until the job succeeds, so a
 job that never terminates reports its progress through [Job.events](Job.md#events)
 instead.
 #### Returns
 `any`
 ***
 ### spec
 ```ts
 get spec(): any
 ```
 The job-type-specific specification it was submitted with.
 #### Returns
 `any`
 ***
 ### state
 ```ts
 get state(): null | string
 ```
 The last observed lifecycle state, without contacting the backend.
 #### Returns
@@ -139,61 +51,18 @@ Request cancellation. Cancelling a finished operation is a no-op.
 ***
 ### events()
 ```ts
 events(options?): Promise<Table<any>>
 ```
 This job's recorded lifecycle events.
 Where the getters above report a terminal result only once the job reaches
 one, events are written as the job runs and outlive the workers that
 produced them. A distributed job records a `claim`/`claim_complete` pair
 per unit of work, each carrying `rows_processed`, so a job that never
 finishes still accounts for what it did.
 The server caps results at 1000 rows by default and 10,000 at most, and
 truncates without saying so, so pass `limit` for a job that emits an event
 per fragment. `filter` is a SQL-like expression over the `state`,
 `updated_by`, `emitted_from`, `emitted_by`, and `claim_entity` columns.
 #### Parameters
 * **options?**: [`JobEventsOptions`](../interfaces/JobEventsOptions.md)
 #### Returns
 `Promise`&lt;`Table`&lt;`any`&gt;&gt;
 ***
 ### refresh()
 ```ts
 refresh(): Promise<void>
 ```
 Ask the backend for this job's current state, and for a server-side job
 its full record, then cache it for the getters above.
 #### Returns
 `Promise`&lt;`void`&gt;
 ***
 ### status()
 ```ts
 status(): Promise<string>
 ```
-The operation's current lifecycle state: "running", "finished", "failed",
+The operation's current lifecycle state: "running", "finished",
-or "cancelled".
+"failed", or "cancelled".
-A point snapshot; unlike [Job.wait](Job.md#wait) it does not block or reject on a
+A point snapshot; unlike [Job.wait](Job.md#wait) it does not block or reject
-terminal failure state. Also refreshes the getters above.
+on a terminal failure state. States a newer server reports that this
 client version does not know pass through as-is.
 #### Returns
@@ -201,22 +70,6 @@ terminal failure state. Also refreshes the getters above.
 ***
 ### toString()
 ```ts
 toString(): string
 ```
 Every field the handle currently knows, one per line, with the JSON
 payloads indented -- a refresh job's spec and result are the point of
 printing it.
 #### Returns
 `string`
 ***
 ### wait()
 ```ts
@@ -141,7 +141,7 @@ Currently this causes multiple copies of the row to be created
 but that behavior is subject to change.
 An optional condition may be specified.  If it is, then only
-matched rows that satisfy the condition will be updated.  Any
+matched rows that satisfy the condtion will be updated.  Any
 rows that do not satisfy the condition will be left as they
 are.  Failing to satisfy the condition does not cause a
 "matched row" to become a "not matched" row.
@@ -137,20 +137,6 @@ containing the new version number of the table after altering the columns.
 ***
 ### blobColumns()
 ```ts
 abstract blobColumns(): Promise<string[]>
 ```
 Blob v2 columns, including nested dotted paths.
 #### Returns
 `Promise`&lt;`string`[]&gt;
 ***
 ### branches()
 ```ts
@@ -513,54 +499,6 @@ Drop an index from the table.
 ***
 ### fetchBlobFiles()
 ```ts
 abstract fetchBlobFiles(column, rowIds): Promise<(null | BlobFile)[]>
 ```
 Opens lazy blob handles for `column` at the given row IDs using the
 table's current checkout.
 Preserves input order, duplicates, and nulls. Use this for large payloads.
 See [Table.fetchBlobs](Table.md#fetchblobs) for row-ID validity across versions.
 #### Parameters
 * **column**: `string`
 * **rowIds**: readonly (`number` \| `bigint`)[]
 #### Returns
 `Promise`&lt;(`null` \| [`BlobFile`](BlobFile.md))[]&gt;
 ***
 ### fetchBlobs()
 ```ts
 abstract fetchBlobs(column, rowIds): Promise<(null | Buffer)[]>
 ```
 Bytes for `column` at row IDs from [Query.withRowId](Query.md#withrowid).
 Reads the table's current checkout. IDs from another version can fail after
 compaction unless stable row ids are enabled. Results keep input order and
 duplicates. Null blobs are `null`. Empty blobs are empty buffers.
 #### Parameters
 * **column**: `string`
 * **rowIds**: readonly (`number` \| `bigint`)[]
 #### Returns
 `Promise`&lt;(`null` \| `Buffer`)[]&gt;
 ***
 ### flushLsm()
 ```ts
@@ -1328,7 +1266,7 @@ value is 0")
 Note: if your condition is something like "some_id_column == 7" and
 you are updating many rows (with different ids) then you will get
 better performance with a single [`merge_insert`] call instead of
-repeatedly calling this method.
+repeatedly calilng this method.
 ##### Parameters
@@ -1,55 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / blob
 # Function: blob()
 ```ts
 function blob(name, options): Field
 ```
 Declares a `lance.blob.v2` column.
 Query results are descriptors, not payload bytes. Use [Table.fetchBlobs](../classes/Table.md#fetchblobs)
 or [Table.fetchBlobFiles](../classes/Table.md#fetchblobfiles) to read bytes.
 ## Parameters
 * **name**: `string`
 * **options**: [`BlobOptions`](../type-aliases/BlobOptions.md) = `{}`
 ## Returns
 `Field`
 ## Example
 ```ts
 import { readFile } from "node:fs/promises";
 import { Field, Int64, Schema } from "apache-arrow";
 import { blob, connect } from "@lancedb/lancedb";
 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 size = handle!.size();
 const header = await handle!.readRange(0n, size < 65536n ? size : 65536n);
 ```
@@ -1,22 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / isBlobField
 # Function: isBlobField()
 ```ts
 function isBlobField(field): boolean
 ```
 Checks for the `lance.blob.v2` extension marker. Does not validate the
 field's storage type.
 ## Parameters
 * **field**: `Field`&lt;`any`&gt;
 ## Returns
 `boolean`
@@ -19,7 +19,6 @@
 ## Classes
 - [AutoQuery](classes/AutoQuery.md)
 - [BlobFile](classes/BlobFile.md)
 - [BooleanQuery](classes/BooleanQuery.md)
 - [BoostQuery](classes/BoostQuery.md)
 - [BranchContents](classes/BranchContents.md)
@@ -97,7 +96,7 @@
 - [IvfFlatOptions](interfaces/IvfFlatOptions.md)
 - [IvfPqOptions](interfaces/IvfPqOptions.md)
 - [IvfRqOptions](interfaces/IvfRqOptions.md)
- [JobEventsOptions](interfaces/JobEventsOptions.md)
+- [JobDescription](interfaces/JobDescription.md)
 - [JobFailureInfo](interfaces/JobFailureInfo.md)
 - [JobInfo](interfaces/JobInfo.md)
 - [ListNamespacesOptions](interfaces/ListNamespacesOptions.md)
@@ -144,7 +143,6 @@
 - [AnalyzePlanDistributedMetrics](type-aliases/AnalyzePlanDistributedMetrics.md)
 - [BaseTokenizer](type-aliases/BaseTokenizer.md)
 - [BlobOptions](type-aliases/BlobOptions.md)
 - [Data](type-aliases/Data.md)
 - [DataLike](type-aliases/DataLike.md)
 - [FieldLike](type-aliases/FieldLike.md)
@@ -160,11 +158,9 @@
 ## Functions
 - [RecordBatchIterator](functions/RecordBatchIterator.md)
 - [blob](functions/blob.md)
 - [connect](functions/connect.md)
 - [connectNamespace](functions/connectNamespace.md)
 - [instrumentLanceDbMetrics](functions/instrumentLanceDbMetrics.md)
 - [isBlobField](functions/isBlobField.md)
 - [makeArrowTable](functions/makeArrowTable.md)
 - [packBits](functions/packBits.md)
 - [permutationBuilder](functions/permutationBuilder.md)
@@ -118,7 +118,7 @@ Number of sub-vectors of PQ.
 This value controls how much the vector is compressed during the quantization step.
 The more sub vectors there are the less the vector is compressed.  The default is
 the dimension of the vector divided by 16.  If the dimension is not evenly divisible
-by 16 we use the dimension divided by 8.
+by 16 we use the dimension divded by 8.
 The above two cases are highly preferred.  Having 8 or 16 values per subvector allows
 us to use efficient SIMD instructions.
@@ -16,7 +16,7 @@ optional config: Index;
 Advanced index configuration
-This option allows you to specify a specific index to create and also
+This option allows you to specify a specfic index to create and also
 allows you to pass in configuration for training the index.
 See the static methods on Index for details on the various index types.
@@ -50,7 +50,7 @@ If this is false, and another index already exists on the same columns
 and the same name, then an error will be returned.  This is true even if
 that index is out of date.
-The default is true
+The default is false
 ***
@@ -112,7 +112,7 @@ Number of sub-vectors of PQ.
 This value controls how much the vector is compressed during the quantization step.
 The more sub vectors there are the less the vector is compressed.  The default is
 the dimension of the vector divided by 16.  If the dimension is not evenly divisible
-by 16 we use the dimension divided by 8.
+by 16 we use the dimension divded by 8.
 The above two cases are highly preferred.  Having 8 or 16 values per subvector allows
 us to use efficient SIMD instructions.
@@ -0,0 +1,66 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / JobDescription
 # Interface: JobDescription
 A described job from `Connection.getJob`.
 ## Properties
 ### creationMs
 ```ts
 creationMs: number;
 ```
 When the job was created, in milliseconds since the epoch.
 ***
 ### failure?
 ```ts
 optional failure: JobFailureInfo;
 ```
 Why the job failed, when the job is failed and the server reports a
 reason.
 ***
 ### jobId
 ```ts
 jobId: string;
 ```
 ***
 ### jobType
 ```ts
 jobType: string;
 ```
 ***
 ### specJson?
 ```ts
 optional specJson: string;
 ```
 The job-type-specific specification as a JSON string, when present.
 ***
 ### state
 ```ts
 state: string;
 ```
 Lifecycle state: "running", "finished", "failed", or "cancelled".
@@ -1,29 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / JobEventsOptions
 # Interface: JobEventsOptions
 Which of a job's events [Job.events](../classes/Job.md#events) returns.
 ## Properties
 ### filter?
 ```ts
 optional filter: string;
 ```
 SQL-like filter over the event columns.
 ***
 ### limit?
 ```ts
 optional limit: number;
 ```
 Maximum event rows to return, up to the server maximum of 10,000.
@@ -26,7 +26,7 @@ When the job was created, in milliseconds since the epoch.
 jobId: string;
 ```
-The job id -- what `Connection.openJob` and `Connection.cancelJob`
+The job id -- what `Connection.getJob` and `Connection.cancelJob`
 accept.
 ***
@@ -1,48 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / BlobOptions
 # Type Alias: BlobOptions
 ```ts
 type BlobOptions: object;
 ```
 ## Type declaration
 ### dedicatedSizeThreshold?
 ```ts
 optional dedicatedSizeThreshold: number;
 ```
 Max payload bytes stored in a packed sidecar before a dedicated file. Must
 be a positive safe integer.
 ### inlineSizeThreshold?
 ```ts
 optional inlineSizeThreshold: number;
 ```
 Max payload bytes kept inline in the data file. Zero is allowed. Must be a
 safe integer.
 ### nullable?
 ```ts
 optional nullable: boolean;
 ```
 Defaults to true.
 ### packFileSizeThreshold?
 ```ts
 optional packFileSizeThreshold: number;
 ```
 Max bytes in one packed sidecar before starting another. Must be a positive
 safe integer.
@@ -28,59 +28,6 @@ is also an [asynchronous API client](#connections-asynchronous).
 ::: lancedb.Session
 ## Remote SQL
 Submit SQL against a remote LanceDB database through the connection.
 The connected database and `default_namespace_path=["public"]` are used for
 unqualified tables. Fully qualified references can still query other databases
 and namespaces available to the same deployment. `execute_query` returns a
 reader as soon as its initial result stream is available. `execute_query_async`
 returns a query handle immediately; use it to inspect progress, open a reader,
 or cancel the query. The SQL client is initialized by the first query and
 retained for the lifetime of the remote connection. Query ids are random,
 connection-scoped references rather than encoded SQL or durable resume tokens:
 ```python
 import lancedb
 db = lancedb.connect(
    "db://analytics",
    api_key="ldb_...",
    host_override="https://api.example.com",
    sql_host_override="grpc+tls://sql.example.com:10026",
 )
 reader = db.execute_query(
    """
    SELECT events.id, accounts.name
    FROM analytics.public.events AS events
    JOIN users.public.accounts AS accounts ON events.user_id = accounts.id
    """,
    default_namespace_path=["public"],
 )
 for batch in reader:
    print(batch.num_rows)
 query = db.execute_query_async("SELECT * FROM events")
 print(query.id)
 print(query.describe().status)
 for batch in query.reader():
    print(batch.num_rows)
 # The async connection exposes the same lifecycle without blocking:
 # async_db = await lancedb.connect_async(
 #     "db://analytics",
 #     api_key="ldb_...",
 #     host_override="https://api.example.com",
 #     sql_host_override="grpc+tls://sql.example.com:10026",
 # )
 # reader = await async_db.execute_query("SELECT * FROM events")
 # query = await async_db.execute_query_async("SELECT * FROM events")
 # description = await async_db.describe_query(query.id)
 # async for batch in await query.reader():
 #     print(batch.num_rows)
 # await query.cancel()
 ```
 ## Namespaces (Synchronous)
 A namespace-backed connection resolves tables through a
@@ -147,8 +94,6 @@ listing a storage directory.
 ::: lancedb.functions.OutputMapping
 ::: lancedb.functions.AssignmentMapping
 ::: lancedb.functions.FunctionBinding
 ::: lancedb.functions.RefreshColumnResult
@@ -157,18 +102,6 @@ listing a storage directory.
 ::: lancedb.job.AsyncJob
 ::: lancedb.job.JobInfo
 ::: lancedb.job.JobDescription
 ::: lancedb.job.JobFailureInfo
 ::: lancedb.sql.Query
 ::: lancedb.sql.AsyncQuery
 ::: lancedb.sql.QueryDescription
 ## Materialized Views (Synchronous)
 ::: lancedb.materialized_view.MaterializedView
@@ -316,12 +249,6 @@ still work. Queries return descriptors. Call
 ::: lancedb.exceptions.MissingColumnError
 ::: lancedb.exceptions.JobNotFoundError
 ::: lancedb.exceptions.JobFailedError
 ::: lancedb.exceptions.JobCancelledError
 ## Integrations
 ## Pydantic
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.39.0-beta.6</version>
+      <version>0.39.0-beta.1</version>
      <relativePath>../pom.xml</relativePath>
    </parent>
@@ -6,7 +6,7 @@
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.39.0-beta.6</version>
+    <version>0.39.0-beta.1</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>12.0.0-beta.17</lance-core.version>
+        <lance-core.version>12.0.0-beta.11</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>
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.39.0-beta.6"
+version = "0.39.0-beta.1"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -1,185 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import { Field, Int64, List, Schema, Struct, Utf8 } from "apache-arrow";
 import { makeArrowTable } from "../lancedb/arrow";
 import { BlobFile, blob, coerceBlobValue, isBlobField } from "../lancedb/blob";
 describe("blob()", () => {
  it("marks the field as lance.blob.v2", () => {
    const field = blob("image", { nullable: false });
    expect(field.nullable).toBe(false);
    expect(isBlobField(field)).toBe(true);
    expect(field.metadata.get("ARROW:extension:name")).toBe("lance.blob.v2");
  });
  it("writes encoding thresholds as field metadata", () => {
    const field = blob("video", {
      inlineSizeThreshold: 1024,
      dedicatedSizeThreshold: 2 * 1024 * 1024,
      packFileSizeThreshold: 64 * 1024 * 1024,
    });
    expect(
      field.metadata.get("lance-encoding:blob-inline-size-threshold"),
    ).toBe("1024");
    expect(
      field.metadata.get("lance-encoding:blob-dedicated-size-threshold"),
    ).toBe(String(2 * 1024 * 1024));
    expect(
      field.metadata.get("lance-encoding:blob-pack-file-size-threshold"),
    ).toBe(String(64 * 1024 * 1024));
  });
  it("rejects invalid thresholds", () => {
    expect(() => blob("image", { inlineSizeThreshold: -1 })).toThrow(
      /inlineSizeThreshold must be non-negative/,
    );
    expect(() => blob("image", { dedicatedSizeThreshold: 0 })).toThrow(
      /dedicatedSizeThreshold must be positive/,
    );
    expect(() => blob("image", { packFileSizeThreshold: 1.5 })).toThrow(
      /packFileSizeThreshold must be a safe integer/,
    );
    expect(() =>
      blob("image", { dedicatedSizeThreshold: Number.MAX_SAFE_INTEGER + 1 }),
    ).toThrow(/dedicatedSizeThreshold must be a safe integer/);
  });
 });
 describe("coerceBlobValue", () => {
  it.each([
    ["Buffer", Buffer.from("x"), { data: Buffer.from("x"), uri: null }],
    [
      "Uint8Array",
      new Uint8Array([120]),
      { data: new Uint8Array([120]), uri: null },
    ],
    ["URI string", "s3://bucket/key", { data: null, uri: "s3://bucket/key" }],
    [
      "data struct",
      { data: Buffer.from("y") },
      { data: Buffer.from("y"), uri: null },
    ],
    [
      "uri struct",
      { uri: "s3://bucket/key" },
      { data: null, uri: "s3://bucket/key" },
    ],
    ["null", null, null],
  ])("accepts %s", (_name, input, expected) => {
    expect(coerceBlobValue(input)).toEqual(expected);
  });
  it.each([
    ["empty URI", "", /uri cannot be empty/],
    ["object without data or uri", { position: 0 }, /data' or 'uri/],
    [
      "Int16Array",
      new Int16Array([1]),
      /Blob data must be Buffer or Uint8Array/,
    ],
    [
      "both data and uri",
      { data: Buffer.from("y"), uri: "s3://bucket/key" },
      /exactly one of 'data' or 'uri'/,
    ],
    [
      "neither data nor uri",
      { data: null, uri: null },
      /exactly one of 'data' or 'uri'/,
    ],
  ])("rejects %s", (_name, input, message) => {
    expect(() => coerceBlobValue(input)).toThrow(message);
  });
 });
 describe("BlobFile", () => {
  it("rejects constructing BlobFile without a native handle", () => {
    expect(() => new (BlobFile as unknown as { new (): BlobFile })()).toThrow(
      /fetchBlobFiles/,
    );
  });
 });
 describe("makeArrowTable blob columns", () => {
  it("coerces Buffer input onto a blob field", () => {
    const schema = new Schema([
      new Field("id", new Int64(), true),
      blob("image"),
    ]);
    const table = makeArrowTable([{ id: 1n, image: Buffer.from("hello") }], {
      schema,
    });
    expect(isBlobField(table.schema.fields[1])).toBe(true);
    const image = table.getChild("image")!;
    expect(image.nullCount).toBe(0);
    expect(image.getChild("uri")!.get(0)).toBeNull();
    expect(image.getChild("data")!.nullCount).toBe(0);
    expect(Buffer.from(image.getChild("data")!.get(0)!).toString()).toBe(
      "hello",
    );
  });
  it("coerces Buffer elements inside a list and keeps null slots", () => {
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field("images", new List(blob("image")), true),
    ]);
    const table = makeArrowTable(
      [
        { id: 1n, images: [Buffer.from("a"), Buffer.from("bb")] },
        { id: 2n, images: null },
        { id: 3n, images: [Buffer.from("c"), null] },
        { id: 4n, images: [] },
      ],
      { schema },
    );
    const images = table.getChild("images")!;
    expect(images.nullCount).toBe(1);
    const rows = images.toArray();
    expect(rows[1]).toBeNull();
    expect(Array.from(rows[3] as Iterable<unknown>)).toHaveLength(0);
    const first = Array.from(rows[0] as Iterable<{ data: Uint8Array | null }>);
    expect(Buffer.from(first[0].data!).toString()).toBe("a");
    expect(Buffer.from(first[1].data!).toString()).toBe("bb");
    const third = Array.from(
      rows[2] as Iterable<{ data: Uint8Array | null } | null>,
    );
    expect(Buffer.from(third[0]!.data!).toString()).toBe("c");
    expect(third[1]).toBeNull();
  });
  it("coerces Buffer fields inside list structs", () => {
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field(
        "items",
        new List(
          new Field(
            "item",
            new Struct([new Field("name", new Utf8(), true), blob("image")]),
            true,
          ),
        ),
        true,
      ),
    ]);
    const table = makeArrowTable(
      [
        {
          id: 1n,
          items: [{ name: "one", image: Buffer.from("alpha") }],
        },
      ],
      { schema },
    );
    const items = Array.from(
      table.getChild("items")!.toArray()[0] as Iterable<{
        name: string;
        image: { data: Uint8Array | null };
      }>,
    );
    expect(items[0].name).toBe("one");
    expect(Buffer.from(items[0].image.data!).toString()).toBe("alpha");
  });
 });
@@ -939,7 +939,6 @@ describe("remote connection jobs surface", () => {
    const { tableFromArrays, tableToIPC } = await import("apache-arrow");
    const eventsTable = tableFromArrays({ state: ["created", "succeeded"] });
    const eventsBody = Buffer.from(tableToIPC(eventsTable, "stream"));
    const queryEventsPayloads: Record<string, unknown>[] = [];
    await withMockDatabase(
      (req, res) => {
@@ -968,16 +967,6 @@ describe("remote connection jobs surface", () => {
                );
            }
          } else if (req.url === "/v1/jobs/describe") {
            if (payload["job_id"] === "job-2") {
              res
                .writeHead(200, { "Content-Type": "application/json" })
                .end(
                  '{"job_id": "job-2", "job_type": "refresh_column", ' +
                    '"job_state": "DONE", "creation_ms": 2000, ' +
                    '"result": {"rows_assigned": 1000000}}',
                );
              return;
            }
            if (payload["job_id"] !== "job-1") {
              res.writeHead(404).end("no such job");
              return;
@@ -999,7 +988,6 @@ describe("remote connection jobs surface", () => {
              .writeHead(200, { "Content-Type": "application/json" })
              .end('{"job_id": "job-1"}');
          } else if (req.url === "/v1/jobs/query_events") {
            queryEventsPayloads.push(payload);
            res
              .writeHead(200, {
                "Content-Type": "application/vnd.apache.arrow.stream",
@@ -1016,65 +1004,22 @@ describe("remote connection jobs surface", () => {
        expect(jobs[0].state).toEqual("running");
        expect(jobs[1].state).toEqual("finished");
        const description = await db.getJob("job-1");
        expect(description?.state).toEqual("failed");
        expect(JSON.parse(description?.specJson ?? "")).toEqual({
          column: "vec",
        });
        expect(description?.failure?.message).toEqual("worker died");
        expect(await db.getJob("missing")).toBeNull();
        expect(await db.cancelJob("job-1")).toBe(true);
        expect(await db.cancelJob("missing")).toBe(false);
-        // Opening a job hands back a populated handle; a missing one rejects.
+        const history = await db.jobHistory("job-1");
-        await expect(db.openJob("missing")).rejects.toThrow("not found");
+        expect(history.numRows).toEqual(2);
        const finished = await db.openJob("job-2");
        expect(finished.state).toEqual("finished");
        expect(finished.result).toEqual({
          // biome-ignore lint/style/useNamingConvention: snake_case mandated by the server wire format
          rows_assigned: 1000000,
        });
-        const job = await db.openJob("job-1");
+        const job = db.job("job-1");
        expect(job.id).toEqual("job-1");
        // openJob already populated the handle; refresh() re-reads it.
        expect(job.state).toEqual("failed");
        await job.refresh();
        expect(job.state).toEqual("failed");
        expect(job.jobType).toEqual("create_index");
        expect(job.creationMs).toEqual(1000);
        expect(job.spec).toEqual({ column: "vec" });
        expect(job.result).toBeNull();
        expect(job.failure?.message).toEqual("worker died");
        // The handle reaches its own events, supplying its job id.
        const jobEvents = await job.events({
          limit: 500,
          filter: "state = 'claim_complete'",
        });
        expect(jobEvents.numRows).toEqual(2);
        expect(queryEventsPayloads.pop()).toEqual({
          // biome-ignore lint/style/useNamingConvention: snake_case mandated by the server wire format
          job_id: "job-1",
          limit: 500,
          filter: "state = 'claim_complete'",
        });
        // Printing lays every known field out on its own line, with the JSON
        // payloads indented rather than crammed onto one line.
        expect(`${job}`).toEqual(
          [
            "Job(",
            '    id="job-1",',
            '    state="failed",',
            '    jobType="create_index",',
            "    creationMs=1000,",
            "    spec={",
            '        "column": "vec"',
            "    },",
            "    failure={",
            '        "phase": "execute",',
            '        "message": "worker died",',
            '        "retryable": true',
            "    },",
            ")",
          ].join("\n"),
        );
        expect(await job.status()).toEqual("failed");
        await expect(job.wait()).rejects.toThrow("worker died");
      },
@@ -18,7 +18,6 @@ import {
  Query,
  Table,
  VectorQuery,
  blob,
  connect,
  tokenize,
 } from "../lancedb";
@@ -282,7 +281,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
        numIndices: 0,
        numRows: 3,
        // Full on-disk size of the two data files, footers and metadata included.
-        totalBytes: 550,
+        totalBytes: 684,
      });
      // Index files count toward totalBytes too (only deletion files and
@@ -290,7 +289,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      await table.createIndex("id", { config: Index.btree() });
      const statsWithIndex = await table.stats();
      expect(statsWithIndex.numIndices).toBe(1);
-      expect(statsWithIndex.totalBytes).toBeGreaterThan(550);
+      expect(statsWithIndex.totalBytes).toBeGreaterThan(684);
    });
    it("should overwrite data if asked", async () => {
@@ -1527,11 +1526,7 @@ describe("When creating an index", () => {
  it("should allow me to replace (or not) an existing index", async () => {
    await tbl.createIndex("id");
-    // Default is replace=true
+    await expect(tbl.createIndex("id")).rejects.toThrow("already exists");
    await tbl.createIndex("id");
    await expect(tbl.createIndex("id", { replace: false })).rejects.toThrow(
      "already exists",
    );
    await tbl.createIndex("id", { replace: true });
  });
@@ -2402,276 +2397,6 @@ describe("when dealing with versioning", () => {
  });
 });
 describe("when dealing with blob columns", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => {
    tmpDir.removeCallback();
  });
  it("discovers blob columns", async () => {
    const { table } = await openBlobTable();
    expect(await table.blobColumns()).toEqual(["image"]);
  });
  it("preserves order, duplicates, and nulls", async () => {
    const { table, rowIds } = await openBlobTable();
    const [alphaId, betaId, nullId] = rowIds;
    const bytes = await table.fetchBlobs("image", [
      betaId,
      alphaId,
      betaId,
      nullId,
    ]);
    expect(bytes.map((b) => (b == null ? null : b.toString()))).toEqual([
      "beta",
      "alpha",
      "beta",
      null,
    ]);
    const files = await table.fetchBlobFiles("image", [
      betaId,
      nullId,
      alphaId,
    ]);
    expect(files.map((f) => f == null)).toEqual([false, true, false]);
  });
  it("reads full blob contents", async () => {
    const { table, rowIds, alpha, beta } = await openBlobTable();
    const bytes = await table.fetchBlobs("image", rowIds);
    expect(bytes[0]!.equals(alpha)).toBe(true);
    expect(bytes[1]!.equals(beta)).toBe(true);
    const files = await table.fetchBlobFiles("image", rowIds);
    expect(files[0]!.size()).toBe(BigInt(alpha.length));
    expect(Buffer.from(await files[0]!.read()).toString()).toBe("alpha");
    expect(Buffer.from(await files[1]!.read()).toString()).toBe("beta");
  });
  it("reads a half-open range", async () => {
    const { table, rowIds } = await openBlobTable();
    const files = await table.fetchBlobFiles("image", rowIds);
    expect(Buffer.from(await files[0]!.readRange(0n, 2n)).toString()).toBe(
      "al",
    );
  });
  it("readRange does not move the cursor", async () => {
    const { table, rowIds, alpha } = await openBlobTable();
    const [handle] = await table.fetchBlobFiles("image", rowIds);
    expect((await handle!.readRange(1n, 3n)).toString()).toBe("lp");
    expect(await handle!.read()).toEqual(alpha);
    expect(await handle!.read()).toEqual(Buffer.alloc(0));
  });
  it("fails when readRange end is past the blob size", async () => {
    const { table, rowIds, alpha } = await openBlobTable();
    const files = await table.fetchBlobFiles("image", rowIds);
    await expect(
      files[0]!.readRange(0n, BigInt(alpha.length + 1)),
    ).rejects.toThrow(/exceeds blob size/);
  });
  it("rejects fetchBlobs on a non-blob column", async () => {
    const { table, rowIds } = await openBlobTable();
    await expect(table.fetchBlobs("id", rowIds)).rejects.toThrow(/blob/i);
  });
  it("discovers and fetches nested blob columns", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field("info", new Struct([blob("image")]), true),
    ]);
    const payload = Buffer.from("nested");
    const table = await db.createTable(
      "nested_blobs",
      [{ id: 1n, info: { image: payload } }],
      { schema },
    );
    expect(await table.blobColumns()).toEqual(["info.image"]);
    const rows = await table.query().withRowId().toArray();
    const bytes = await table.fetchBlobs("info.image", [
      rows[0]._rowid as bigint,
    ]);
    expect(bytes[0]!.equals(payload)).toBe(true);
  });
  it("creates and adds list blob columns", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field("images", new List(blob("image")), true),
    ]);
    const alpha = Buffer.from("alpha");
    const beta = Buffer.from("beta");
    const gamma = Buffer.from("gamma");
    const table = await db.createTable(
      "list_blobs",
      [{ id: 1n, images: [alpha, beta] }],
      { schema },
    );
    await table.add([
      { id: 2n, images: null },
      { id: 3n, images: [gamma, null] },
      { id: 4n, images: [] },
    ]);
    expect(await table.blobColumns()).toEqual(["images.image"]);
    const rows = await table.query().toArray();
    const byId = new Map(rows.map((row) => [Number(row.id), row]));
    expect(descriptorSizes(byId.get(1)!.images)).toEqual([
      alpha.length,
      beta.length,
    ]);
    expect(byId.get(2)!.images).toBeNull();
    expect(descriptorSizes(byId.get(3)!.images)).toEqual([gamma.length, null]);
    expect(Array.from(byId.get(4)!.images as Iterable<unknown>)).toHaveLength(
      0,
    );
  });
  it("creates and adds list struct blob columns", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field(
        "items",
        new List(
          new Field(
            "item",
            new Struct([new Field("name", new Utf8(), true), blob("image")]),
            true,
          ),
        ),
        true,
      ),
    ]);
    const alpha = Buffer.from("nested-alpha");
    const beta = Buffer.from("nested-beta");
    const table = await db.createTable(
      "list_struct_blobs",
      [{ id: 1n, items: [{ name: "one", image: alpha }] }],
      { schema },
    );
    await table.add([
      {
        id: 2n,
        items: [
          { name: "two", image: beta },
          { name: "three", image: null },
        ],
      },
    ]);
    const rows = await table.query().toArray();
    const byId = new Map(rows.map((row) => [Number(row.id), row]));
    expect(
      descriptorSizes(
        Array.from(byId.get(1)!.items as Iterable<{ image: unknown }>).map(
          (item) => item.image,
        ),
      ),
    ).toEqual([alpha.length]);
    expect(
      descriptorSizes(
        Array.from(byId.get(2)!.items as Iterable<{ image: unknown }>).map(
          (item) => item.image,
        ),
      ),
    ).toEqual([beta.length, null]);
  });
  it("rejects blob fields inside a fixed-size list", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field("frames", new FixedSizeList(2, blob("frame")), true),
    ]);
    await expect(
      db.createTable(
        "fsl_blobs",
        [{ id: 1n, frames: [Buffer.from("a"), Buffer.from("b")] }],
        { schema },
      ),
    ).rejects.toThrow(
      "Blob fields inside FixedSizeList are not supported. Use List instead.",
    );
  });
  it("rejects blob fields inside a nested fixed-size list", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field(
        "clip",
        new Struct([
          new Field("frames", new FixedSizeList(2, blob("frame")), true),
        ]),
        true,
      ),
    ]);
    await expect(
      db.createTable(
        "nested_fsl_blobs",
        [
          {
            id: 1n,
            clip: { frames: [Buffer.from("a"), Buffer.from("b")] },
          },
        ],
        { schema },
      ),
    ).rejects.toThrow(
      "Blob fields inside FixedSizeList are not supported. Use List instead.",
    );
  });
  it("rejects an Arrow table with blob fields inside a fixed-size list", async () => {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      new Field("frames", new FixedSizeList(2, blob("frame")), true),
    ]);
    await expect(
      db.createTable("fsl_blobs_ipc", new ArrowTable(schema)),
    ).rejects.toThrow(
      "Blob fields inside FixedSizeList are not supported. Use List instead.",
    );
  });
  function descriptorSizes(values: unknown): (number | null)[] {
    return Array.from(
      values as Iterable<{ size?: bigint | number } | null>,
    ).map((value) => (value == null ? null : Number(value.size)));
  }
  async function openBlobTable() {
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), true),
      blob("image"),
    ]);
    const alpha = Buffer.from("alpha");
    const beta = Buffer.from("beta");
    const table = await db.createTable(
      "blobs",
      [
        { id: 1n, image: alpha },
        { id: 2n, image: beta },
        { id: 3n, image: null },
      ],
      { schema },
    );
    const rows = await table.query().withRowId().toArray();
    const rowIdById = new Map(
      rows.map((r) => [Number(r.id), r._rowid as bigint]),
    );
    const rowIds = [1, 2, 3].map((id) => rowIdById.get(id)!);
    return { table, rowIds, alpha, beta };
  }
 });
 describe("when dealing with tags", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
@@ -3523,7 +3248,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      const db = await connect(tmpDir.name);
      const data = [
        { text: "fa", vector: [0.1, 0.2, 0.3] },
-        { text: "fo", vector: [0.4, 0.5, 0.6] }, // spellchecker:disable-line
+        { text: "fo", vector: [0.4, 0.5, 0.6] },
        { text: "fob", vector: [0.4, 0.5, 0.6] },
        { text: "focus", vector: [0.4, 0.5, 0.6] },
        { text: "foo", vector: [0.4, 0.5, 0.6] },
@@ -3548,7 +3273,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      const resultSet = new Set(fuzzyResults.map((r) => r.text));
      expect(resultSet.has("foo")).toBe(true);
      expect(resultSet.has("fob")).toBe(true);
-      expect(resultSet.has("fo")).toBe(true); // spellchecker:disable-line
+      expect(resultSet.has("fo")).toBe(true);
      expect(resultSet.has("food")).toBe(true);
      const prefixResults = await table
@@ -40,7 +40,6 @@ import {
 } from "apache-arrow";
 import { Buffers } from "apache-arrow/data";
 import { typedArrayToArrowType } from "./arrow_type";
 import { coerceBlobValue, isBlobField } from "./blob";
 import { type EmbeddingFunction } from "./embedding/embedding_function";
 import {
  EmbeddingFunctionConfig,
@@ -431,14 +430,12 @@ export function makeArrowTable(
      throw new Error("A schema must be provided if data is empty");
    } else {
      schema = new Schema(schema.fields, schemaMetadata);
      validateBlobSchema(schema);
      return new ArrowTable(schema);
    }
  }
  let inferredSchema = inferSchema(data, schema, opt);
  inferredSchema = new Schema(inferredSchema.fields, schemaMetadata);
  validateBlobSchema(inferredSchema);
  const finalColumns: Record<string, Vector> = {};
  for (const field of inferredSchema.fields) {
@@ -448,35 +445,6 @@ export function makeArrowTable(
  return new ArrowTable(inferredSchema, finalColumns);
 }
 function validateBlobSchema(schema: Schema): void {
  for (const field of schema.fields) {
    validateBlobField(field);
  }
 }
 function validateBlobField(field: Field): void {
  if (
    isFixedSizeList(field.type) &&
    containsBlobField(field.type.children[0])
  ) {
    throw new Error(
      "Blob fields inside FixedSizeList are not supported. Use List instead.",
    );
  }
  for (const child of field.type.children ?? []) {
    validateBlobField(child);
  }
 }
 function containsBlobField(field: Field): boolean {
  if (isBlobField(field)) {
    return true;
  }
  return (field.type.children ?? []).some((child: Field) =>
    containsBlobField(child),
  );
 }
 function isObject(value: unknown): value is Record<string, unknown> {
  return (
    typeof value === "object" &&
@@ -512,32 +480,6 @@ function transposeData(
  path: string[] = [],
 ): Vector {
  const valuesPath = [...path, field.name];
  if (isBlobField(field) && field.type instanceof Struct) {
    const blobRows = data.map((datum) =>
      coerceBlobValue(valueAtPath(datum, valuesPath)),
    );
    const childVectors = field.type.children.map((child) => {
      const values = blobRows.map((row) =>
        row == null ? null : (row[child.name as "data" | "uri"] ?? null),
      );
      return makeVector(values, child.type, undefined, child.nullable);
    });
    const nullCount = blobRows.filter((row) => row === null).length;
    const structData = makeData({
      type: field.type,
      length: blobRows.length,
      nullCount,
      nullBitmap:
        nullCount > 0
          ? arrowUtil.packBools(blobRows.map((row) => row !== null))
          : undefined,
      children: childVectors.map((v) => v.data[0]),
    });
    return arrowMakeVector(structData);
  }
  if (isList(field.type) && containsBlobField(field.type.children[0])) {
    return transposeListData(data, field, valuesPath);
  }
  const values = data.map((datum) => valueAtPath(datum, valuesPath));
  if (field.type instanceof Struct) {
    const childFields = field.type.children;
@@ -553,7 +495,7 @@ function transposeData(
        nullCount > 0
          ? arrowUtil.packBools(values.map((value) => value !== null))
          : undefined,
-      children: childVectors.map((v) => v.data[0]),
+      children: childVectors as unknown as ArrowData<DataType>[],
    });
    return arrowMakeVector(structData);
  } else {
@@ -561,48 +503,6 @@ function transposeData(
  }
 }
 function transposeListData(
  data: Record<string, unknown>[],
  field: Field,
  valuesPath: string[],
 ): Vector {
  const listType = field.type as List;
  const childField = listType.children[0];
  const lists = data.map((datum) => valueAtPath(datum, valuesPath));
  const flattened: Record<string, unknown>[] = [];
  const validity: boolean[] = [];
  const offsets: number[] = [0];
  for (const list of lists) {
    if (list == null) {
      validity.push(false);
      offsets.push(flattened.length);
      continue;
    }
    if (!Array.isArray(list)) {
      throw new Error(`expected an array for list field '${field.name}'`);
    }
    validity.push(true);
    for (const element of list) {
      flattened.push({ [childField.name]: element });
    }
    offsets.push(flattened.length);
  }
  const childVector = transposeData(flattened, childField, []);
  const nullCount = validity.filter((valid) => !valid).length;
  return arrowMakeVector(
    makeData({
      type: listType,
      length: lists.length,
      nullCount,
      nullBitmap: nullCount > 0 ? arrowUtil.packBools(validity) : undefined,
      valueOffsets: Int32Array.from(offsets),
      child: childVector.data[0],
    }),
  );
 }
 /**
 * Create an empty Arrow table with the provided schema
 */
@@ -700,7 +600,7 @@ function makeVector(
  }
  if (values.length === 0) {
    throw Error(
-      "makeVector requires at least one value or the type must be specified",
+      "makeVector requires at least one value or the type must be specfied",
    );
  }
  const sampleValue = values.find((val) => val !== null && val !== undefined);
@@ -958,7 +858,7 @@ async function applyEmbeddings<T>(
 * customized by the `embeddingDataType` property of the embedding function.
 *
 * If a schema is provided in `makeTableOptions` then it should include the
- * embedding columns.  If no schema is provided then embedding columns will
+ * embedding columns.  If no schema is provded then embedding columns will
 * be placed at the end of the table, after all of the input columns.
 */
 export async function convertToTable(
@@ -1052,7 +952,6 @@ export async function fromTableToBuffer(
    schema = sanitizeSchema(schema);
  }
  const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
  validateBlobSchema(tableWithEmbeddings.schema);
  const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings);
  return Buffer.from(await writer.toUint8Array());
 }
@@ -1,236 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import { Field, LargeBinary, Struct, Utf8 } from "apache-arrow";
 import { BlobFile as NativeBlobFile } from "./native";
 const BLOB_V2_EXTENSION_NAME = "lance.blob.v2";
 const INLINE_SIZE_THRESHOLD_KEY = "lance-encoding:blob-inline-size-threshold";
 const DEDICATED_SIZE_THRESHOLD_KEY =
  "lance-encoding:blob-dedicated-size-threshold";
 const PACK_FILE_SIZE_THRESHOLD_KEY =
  "lance-encoding:blob-pack-file-size-threshold";
 export type BlobInput = {
  data: Buffer | Uint8Array | null;
  uri: string | null;
 };
 export type BlobOptions = {
  /** Defaults to true. */
  nullable?: boolean;
  /**
   * Max payload bytes kept inline in the data file. Zero is allowed. Must be a
   * safe integer.
   */
  inlineSizeThreshold?: number;
  /**
   * Max payload bytes stored in a packed sidecar before a dedicated file. Must
   * be a positive safe integer.
   */
  dedicatedSizeThreshold?: number;
  /**
   * Max bytes in one packed sidecar before starting another. Must be a positive
   * safe integer.
   */
  packFileSizeThreshold?: number;
 };
 /**
 * Declares a `lance.blob.v2` column.
 *
 * Query results are descriptors, not payload bytes. Use {@link Table.fetchBlobs}
 * or {@link Table.fetchBlobFiles} to read bytes.
 *
 * @example
 * ```ts
 * import { readFile } from "node:fs/promises";
 * import { Field, Int64, Schema } from "apache-arrow";
 * import { blob, connect } from "@lancedb/lancedb";
 *
 * 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 size = handle!.size();
 * const header = await handle!.readRange(0n, size < 65536n ? size : 65536n);
 * ```
 */
 export function blob(name: string, options: BlobOptions = {}): Field {
  const metadata = new Map<string, string>([
    ["ARROW:extension:name", BLOB_V2_EXTENSION_NAME],
  ]);
  setThreshold(
    metadata,
    INLINE_SIZE_THRESHOLD_KEY,
    "inlineSizeThreshold",
    options.inlineSizeThreshold,
    0,
  );
  setThreshold(
    metadata,
    DEDICATED_SIZE_THRESHOLD_KEY,
    "dedicatedSizeThreshold",
    options.dedicatedSizeThreshold,
    1,
  );
  setThreshold(
    metadata,
    PACK_FILE_SIZE_THRESHOLD_KEY,
    "packFileSizeThreshold",
    options.packFileSizeThreshold,
    1,
  );
  return new Field(
    name,
    new Struct([
      new Field("data", new LargeBinary(), true),
      new Field("uri", new Utf8(), true),
    ]),
    options.nullable ?? true,
    metadata,
  );
 }
 /**
 * Checks for the `lance.blob.v2` extension marker. Does not validate the
 * field's storage type.
 */
 export function isBlobField(field: Field): boolean {
  return field.metadata?.get("ARROW:extension:name") === BLOB_V2_EXTENSION_NAME;
 }
 /**
 * A lazy handle to blob bytes. Create one with {@link Table.fetchBlobFiles}.
 *
 * @hideconstructor
 */
 export class BlobFile {
  private readonly inner: NativeBlobFile;
  private constructor(inner: NativeBlobFile) {
    if (!(inner instanceof NativeBlobFile)) {
      throw new Error("BlobFile handles come from Table.fetchBlobFiles");
    }
    this.inner = inner;
  }
  /** @ignore */
  static fromNative(inner: NativeBlobFile): BlobFile {
    return new BlobFile(inner);
  }
  /** Returns the blob size in bytes. */
  size(): bigint {
    return this.inner.size();
  }
  /**
   * Reads from the cursor to the end and advances the cursor.
   *
   * A second call returns an empty buffer. {@link BlobFile.readRange} does
   * not move the cursor.
   */
  read(): Promise<Buffer> {
    return this.inner.read();
  }
  /**
   * Reads the half-open byte range `[start, end)`.
   *
   * Fails when `end` is past the blob size. Does not move the cursor.
   */
  readRange(start: bigint, end: bigint): Promise<Buffer> {
    return this.inner.readRange(start, end);
  }
 }
 export function coerceBlobValue(value: unknown): BlobInput | null {
  if (value == null) {
    return null;
  }
  if (isBlobBytes(value)) {
    return { data: value, uri: null };
  }
  if (ArrayBuffer.isView(value)) {
    throw new Error("Blob data must be Buffer or Uint8Array");
  }
  if (typeof value === "string") {
    if (value === "") {
      throw new Error("Blob uri cannot be empty");
    }
    return { data: null, uri: value };
  }
  if (typeof value === "object") {
    const record = value as Record<string, unknown>;
    if (!("data" in record) && !("uri" in record)) {
      throw new Error(
        "Blob struct values must include a 'data' or 'uri' field",
      );
    }
    const uri = record.uri;
    if (uri === "") {
      throw new Error("Blob uri cannot be empty");
    }
    if (uri != null && typeof uri !== "string") {
      throw new Error(`Blob uri must be a string or null, got ${typeof uri}`);
    }
    const data = record.data;
    if (data != null && !isBlobBytes(data)) {
      throw new Error("Blob data must be Buffer, Uint8Array, or null");
    }
    const bytes = (data as Buffer | Uint8Array | null | undefined) ?? null;
    const uriValue = uri ?? null;
    if ((bytes == null) === (uriValue == null)) {
      throw new Error(
        "Blob struct values must set exactly one of 'data' or 'uri'",
      );
    }
    return { data: bytes, uri: uriValue };
  }
  throw new Error(
    "Blob column values must be Buffer, Uint8Array, a URI string, null, or { data?, uri? }",
  );
 }
 function isBlobBytes(value: unknown): value is Buffer | Uint8Array {
  return Buffer.isBuffer(value) || value instanceof Uint8Array;
 }
 function setThreshold(
  metadata: Map<string, string>,
  key: string,
  optionName: string,
  value: number | undefined,
  minimum: number,
 ): void {
  if (value === undefined) {
    return;
  }
  if (!Number.isSafeInteger(value)) {
    throw new Error(`${optionName} must be a safe integer`);
  }
  if (value < minimum) {
    throw new Error(
      minimum <= 0
        ? `${optionName} must be non-negative`
        : `${optionName} must be positive`,
    );
  }
  metadata.set(key, String(value));
 }
@@ -1,6 +1,7 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import { tableFromIPC } from "apache-arrow";
 import {
  Data,
  SchemaLike,
@@ -15,7 +16,6 @@ import {
  makeEmptyTable,
 } from "./arrow";
 import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
 import { Job } from "./job";
 import {
  MaterializedView,
  MaterializedViewSelect,
@@ -27,6 +27,8 @@ import type {
  CreateNamespaceResponse,
  DescribeNamespaceResponse,
  DropNamespaceResponse,
  Job,
  JobDescription,
  JobInfo,
  ListNamespacesResponse,
  ListTablesResponse,
@@ -555,19 +557,24 @@ export abstract class Connection {
  ): Promise<void>;
  /**
-   * Open a server-side job by id, returning a handle with its record already
+   * A {@link Job} handle for a server-side job by id.
   * populated. Rejects when the server has no such job, the way
   * {@link Connection.openTable} does for a missing table.
   *
-   * The returned {@link Job} answers for its own state, specification,
+   * The handle is constructed without a server round trip; an unknown id
-   * result, failure and event history, so there is no separate
+   * surfaces when the handle is used. Dropping the handle has no effect on
-   * connection-level call for any of them.
+   * the job itself.
   */
-  abstract openJob(jobId: string): Promise<Job>;
+  abstract job(jobId: string): Job;
  /** List server-side jobs across the database's tables. */
  abstract listJobs(): Promise<JobInfo[]>;
  /**
   * Describe a single server-side job by id.
   *
   * Resolves to `null` when the server has no such job.
   */
  abstract getJob(jobId: string): Promise<JobDescription | null>;
  /**
   * Request cancellation of a server-side job by id.
   *
@@ -575,6 +582,13 @@ export abstract class Connection {
   * such job exists. Cancelling an already-terminal job is a no-op success.
   */
  abstract cancelJob(jobId: string): Promise<boolean>;
  /**
   * The lifecycle event history of a server-side job, as an Arrow table.
   *
   * Lists history across all jobs when `jobId` is omitted.
   */
  abstract jobHistory(jobId?: string): Promise<ArrowTable>;
 }
 /** @hideconstructor */
@@ -855,7 +869,7 @@ export class LocalConnection extends Connection {
  }
  async dropTableAsync(name: string, namespacePath?: string[]): Promise<Job> {
-    return new Job(await this.inner.dropTableAsync(name, namespacePath ?? []));
+    return this.inner.dropTableAsync(name, namespacePath ?? []);
  }
  async dropAllTables(namespacePath?: string[]): Promise<void> {
@@ -914,17 +928,29 @@ export class LocalConnection extends Connection {
    );
  }
-  async openJob(jobId: string): Promise<Job> {
+  job(jobId: string): Job {
-    return new Job(await this.inner.openJob(jobId));
+    return this.inner.job(jobId);
  }
  async listJobs(): Promise<JobInfo[]> {
    return this.inner.listJobs();
  }
  async getJob(jobId: string): Promise<JobDescription | null> {
    return this.inner.getJob(jobId);
  }
  async cancelJob(jobId: string): Promise<boolean> {
    return this.inner.cancelJob(jobId);
  }
  async jobHistory(jobId?: string): Promise<ArrowTable> {
    const buf = await this.inner.jobHistory(jobId);
    if (buf.length === 0) {
      return new ArrowTable();
    }
    return tableFromIPC(buf);
  }
 }
 /**
@@ -77,9 +77,6 @@ export {
  VectorColumnOptions,
 } from "./arrow";
 export { blob, isBlobField, BlobFile } from "./blob";
 export type { BlobOptions } from "./blob";
 export {
  Connection,
  CreateTableOptions,
@@ -97,9 +94,13 @@ export {
  RenameTableOptions,
 } from "./connection";
-export { JobFailureInfo, JobInfo, Session } from "./native.js";
+export {
-
+  Job,
-export { Job, JobEventsOptions } from "./job";
+  JobDescription,
  JobFailureInfo,
  JobInfo,
  Session,
 } from "./native.js";
 export {
  AutoQuery,
@@ -26,7 +26,7 @@ export interface IvfPqOptions {
   * This value controls how much the vector is compressed during the quantization step.
   * The more sub vectors there are the less the vector is compressed.  The default is
   * the dimension of the vector divided by 16.  If the dimension is not evenly divisible
-   * by 16 we use the dimension divided by 8.
+   * by 16 we use the dimension divded by 8.
   *
   * The above two cases are highly preferred.  Having 8 or 16 values per subvector allows
   * us to use efficient SIMD instructions.
@@ -228,7 +228,7 @@ export interface HnswPqOptions {
   * This value controls how much the vector is compressed during the quantization step.
   * The more sub vectors there are the less the vector is compressed.  The default is
   * the dimension of the vector divided by 16.  If the dimension is not evenly divisible
-   * by 16 we use the dimension divided by 8.
+   * by 16 we use the dimension divded by 8.
   *
   * The above two cases are highly preferred.  Having 8 or 16 values per subvector allows
   * us to use efficient SIMD instructions.
@@ -825,7 +825,7 @@ export interface IndexOptions {
  /**
   * Advanced index configuration
   *
-   * This option allows you to specify a specific index to create and also
+   * This option allows you to specify a specfic index to create and also
   * allows you to pass in configuration for training the index.
   *
   * See the static methods on Index for details on the various index types.
@@ -841,7 +841,7 @@ export interface IndexOptions {
   * and the same name, then an error will be returned.  This is true even if
   * that index is out of date.
   *
-   * The default is true
+   * The default is false
   */
  replace?: boolean;
@@ -1,188 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import { Table as ArrowTable, tableFromIPC } from "apache-arrow";
 import { JobFailureInfo, Job as NativeJob } from "./native";
 /** Which of a job's events {@link Job.events} returns. */
 export interface JobEventsOptions {
  /** Maximum event rows to return, up to the server maximum of 10,000. */
  limit?: number;
  /** SQL-like filter over the event columns. */
  filter?: string;
 }
 /**
 * A handle to an operation that may still be running.
 *
 * The operation may already be complete when the handle is created.
 *
 * The detail getters read what the handle last observed. Submitting an
 * operation returns only a job id, so populating them eagerly would cost an
 * extra round trip on every call:
 *
 * - {@link Job.refresh} and {@link Job.status} fetch the whole record.
 * - {@link Job.wait} records the terminal state it establishes, but not the
 *   rest of the record.
 * - Everything is null until one of those runs.
 *
 * @hideconstructor
 */
 export class Job {
  private readonly inner: NativeJob;
  constructor(inner: NativeJob) {
    this.inner = inner;
  }
  /**
   * Identifies the operation on the server that is running it.
   *
   * Operations that run in this process have no server id. The value is
   * opaque: parsing it or storing it to resume the job later is not supported.
   */
  get id(): string | null {
    return this.inner.id ?? null;
  }
  /** The last observed lifecycle state, without contacting the backend. */
  get state(): string | null {
    return this.inner.state ?? null;
  }
  /**
   * The job's type, as the server names it. Null for an in-process job, which
   * has no server-side record.
   */
  get jobType(): string | null {
    return this.inner.jobType ?? null;
  }
  /** When the job was created, in milliseconds since the epoch. */
  get creationMs(): number | null {
    return this.inner.creationMs ?? null;
  }
  /** The job-type-specific specification it was submitted with. */
  // biome-ignore lint/suspicious/noExplicitAny: shape varies by job type
  get spec(): any | null {
    return parseJson(this.inner.specJson);
  }
  /**
   * The job-type-specific terminal result. Null until the job succeeds, so a
   * job that never terminates reports its progress through {@link Job.events}
   * instead.
   */
  // biome-ignore lint/suspicious/noExplicitAny: shape varies by job type
  get result(): any | null {
    return parseJson(this.inner.resultJson);
  }
  /** Why the job failed, when it failed and the server reports a reason. */
  get failure(): JobFailureInfo | null {
    return this.inner.failure ?? null;
  }
  /**
   * The operation's current lifecycle state: "running", "finished", "failed",
   * or "cancelled".
   *
   * A point snapshot; unlike {@link Job.wait} it does not block or reject on a
   * terminal failure state. Also refreshes the getters above.
   */
  async status(): Promise<string> {
    return this.inner.status();
  }
  /** Wait until the operation reaches a terminal state. */
  async wait(): Promise<void> {
    return this.inner.wait();
  }
  /** Request cancellation. Cancelling a finished operation is a no-op. */
  async cancel(): Promise<void> {
    return this.inner.cancel();
  }
  /**
   * Ask the backend for this job's current state, and for a server-side job
   * its full record, then cache it for the getters above.
   */
  async refresh(): Promise<void> {
    return this.inner.refresh();
  }
  /**
   * This job's recorded lifecycle events.
   *
   * Where the getters above report a terminal result only once the job reaches
   * one, events are written as the job runs and outlive the workers that
   * produced them. A distributed job records a `claim`/`claim_complete` pair
   * per unit of work, each carrying `rows_processed`, so a job that never
   * finishes still accounts for what it did.
   *
   * The server caps results at 1000 rows by default and 10,000 at most, and
   * truncates without saying so, so pass `limit` for a job that emits an event
   * per fragment. `filter` is a SQL-like expression over the `state`,
   * `updated_by`, `emitted_from`, `emitted_by`, and `claim_entity` columns.
   */
  async events(options?: JobEventsOptions): Promise<ArrowTable> {
    const buf = await this.inner.events(options?.limit, options?.filter);
    if (buf.length === 0) {
      return new ArrowTable();
    }
    return tableFromIPC(buf);
  }
  /**
   * Every field the handle currently knows, one per line, with the JSON
   * payloads indented -- a refresh job's spec and result are the point of
   * printing it.
   */
  toString(): string {
    if (this.state === null) {
      const known = this.id === null ? "" : `id=${JSON.stringify(this.id)}, `;
      return `Job(${known}not refreshed)`;
    }
    const fields: string[] = [];
    if (this.id !== null) {
      fields.push(`id=${JSON.stringify(this.id)}`);
    }
    fields.push(`state=${JSON.stringify(this.state)}`);
    if (this.jobType !== null) {
      fields.push(`jobType=${JSON.stringify(this.jobType)}`);
    }
    if (this.creationMs !== null) {
      fields.push(`creationMs=${this.creationMs}`);
    }
    for (const [name, value] of [
      ["spec", this.spec],
      ["result", this.result],
    ] as const) {
      if (value !== null) {
        fields.push(`${name}=${indentJson(value)}`);
      }
    }
    if (this.failure !== null) {
      fields.push(`failure=${indentJson(this.failure)}`);
    }
    return `Job(${fields.map((field) => `\n${REPR_INDENT}${field},`).join("")}\n)`;
  }
  [Symbol.for("nodejs.util.inspect.custom")](): string {
    return this.toString();
  }
 }
 const REPR_INDENT = "    ";
 // biome-ignore lint/suspicious/noExplicitAny: shape varies by job type
 function indentJson(value: any): string {
  return JSON.stringify(value, null, 4).replace(/\n/g, `\n${REPR_INDENT}`);
 }
 // biome-ignore lint/suspicious/noExplicitAny: shape varies by job type
 function parseJson(raw: string | null | undefined): any | null {
  return raw === null || raw === undefined ? null : JSON.parse(raw);
 }
@@ -27,7 +27,7 @@ export class MergeInsertBuilder {
   * but that behavior is subject to change.
   *
   * An optional condition may be specified.  If it is, then only
-   * matched rows that satisfy the condition will be updated.  Any
+   * matched rows that satisfy the condtion will be updated.  Any
   * rows that do not satisfy the condition will be left as they
   * are.  Failing to satisfy the condition does not cause a
   * "matched row" to become a "not matched" row.
@@ -3,7 +3,7 @@
 // The utilities in this file help sanitize data from the user's arrow
 // library into the types expected by vectordb's arrow library.  Node
-// generally allows for multiple versions of the same library (and sometimes
+// generally allows for mulitple versions of the same library (and sometimes
 // even multiple copies of the same version) to be installed at the same
 // time.  However, arrow-js uses instanceof which expected that the input
 // comes from the exact same library instance.  This is not always the case
@@ -17,10 +17,8 @@ import {
  tableFromIPC,
 } from "./arrow";
 import { BlobFile } from "./blob";
 import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
 import { IndexOptions } from "./indices";
 import { Job } from "./job";
 import { MergeInsertBuilder } from "./merge";
 import {
  AddColumnsResult,
@@ -32,6 +30,7 @@ import {
  DropColumnsResult,
  IndexConfig,
  IndexStatistics,
  Job,
  LsmStats,
  Branches as NativeBranches,
  OptimizeStats,
@@ -314,7 +313,7 @@ export abstract class Table {
   * Note: if your condition is something like "some_id_column == 7" and
   * you are updating many rows (with different ids) then you will get
   * better performance with a single [`merge_insert`] call instead of
-   * repeatedly calling this method.
+   * repeatedly calilng this method.
   * @param {Map<string, string> | Record<string, string>} updates - the
   * columns to update
   * @returns {Promise<UpdateResult>} A promise that resolves to an object
@@ -511,35 +510,6 @@ export abstract class Table {
   */
  abstract takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery;
  /**
   * Blob v2 columns, including nested dotted paths.
   */
  abstract blobColumns(): Promise<string[]>;
  /**
   * Bytes for `column` at row IDs from {@link Query.withRowId}.
   *
   * Reads the table's current checkout. IDs from another version can fail after
   * compaction unless stable row ids are enabled. Results keep input order and
   * duplicates. Null blobs are `null`. Empty blobs are empty buffers.
   */
  abstract fetchBlobs(
    column: string,
    rowIds: readonly (bigint | number)[],
  ): Promise<(Buffer | null)[]>;
  /**
   * Opens lazy blob handles for `column` at the given row IDs using the
   * table's current checkout.
   *
   * Preserves input order, duplicates, and nulls. Use this for large payloads.
   * See {@link Table.fetchBlobs} for row-ID validity across versions.
   */
  abstract fetchBlobFiles(
    column: string,
    rowIds: readonly (bigint | number)[],
  ): Promise<(BlobFile | null)[]>;
  /**
   * Create a search query to find the nearest neighbors
   * of the given query
@@ -1154,15 +1124,13 @@ export class LocalTable extends Table {
  ): Promise<Job> {
    // biome-ignore lint/suspicious/noExplicitAny: skip
    const nativeIndex = (options?.config as any)?.inner;
-    return new Job(
+    return await this.inner.createIndexAsync(
-      await this.inner.createIndexAsync(
+      nativeIndex,
-        nativeIndex,
+      column,
-        column,
+      options?.replace,
-        options?.replace,
+      options?.waitTimeoutSeconds,
-        options?.waitTimeoutSeconds,
+      options?.name,
-        options?.name,
+      options?.train,
        options?.train,
      ),
    );
  }
@@ -1190,34 +1158,23 @@ export class LocalTable extends Table {
  }
  takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery {
-    return new TakeQuery(this.inner.takeRowIds(rowIdsToBigInts(rowIds)));
+    const ids = rowIds.map((id) => {
-  }
+      if (typeof id === "bigint") {
        return id;
      }
      if (!Number.isInteger(id)) {
        throw new Error("Row id must be an integer (or bigint)");
      }
      if (id < 0) {
        throw new Error("Row id cannot be negative");
      }
      if (!Number.isSafeInteger(id)) {
        throw new Error("Row id is too large for number; use bigint instead");
      }
      return BigInt(id);
    });
-  blobColumns(): Promise<string[]> {
+    return new TakeQuery(this.inner.takeRowIds(ids));
    return this.inner.blobColumns();
  }
  async fetchBlobs(
    column: string,
    rowIds: readonly (bigint | number)[],
  ): Promise<(Buffer | null)[]> {
    const values = await this.inner.fetchBlobs(column, rowIdsToBigInts(rowIds));
    // N-API Option maps missing values to undefined. Collapse those to null.
    return values.map((value) => value ?? null);
  }
  async fetchBlobFiles(
    column: string,
    rowIds: readonly (bigint | number)[],
  ): Promise<(BlobFile | null)[]> {
    const files = await this.inner.fetchBlobFiles(
      column,
      rowIdsToBigInts(rowIds),
    );
    // N-API Option maps missing values to undefined. Collapse those to null.
    return files.map((file) =>
      file == null ? null : BlobFile.fromNative(file),
    );
  }
  query(): Query {
@@ -1356,7 +1313,7 @@ export class LocalTable extends Table {
  }
  async refreshColumnAsync(column: string): Promise<Job> {
-    return new Job(await this.inner.refreshColumnAsync(column));
+    return await this.inner.refreshColumnAsync(column);
  }
  async refreshMaterializedView(
@@ -1774,21 +1731,3 @@ export class Branches {
    )) as unknown as CherryPickResult;
  }
 }
 function rowIdsToBigInts(rowIds: readonly (bigint | number)[]): bigint[] {
  return rowIds.map((id) => {
    if (typeof id === "bigint") {
      return id;
    }
    if (!Number.isInteger(id)) {
      throw new Error("Row id must be an integer (or bigint)");
    }
    if (id < 0) {
      throw new Error("Row id cannot be negative");
    }
    if (!Number.isSafeInteger(id)) {
      throw new Error("Row id is too large for number; use bigint instead");
    }
    return BigInt(id);
  });
 }
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.39.0-beta.6",
+  "version": "0.39.0-beta.1",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.39.0-beta.6",
+	"version": "0.39.0-beta.1",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.39.0-beta.6",
+  "version": "0.39.0-beta.1",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -41,7 +41,7 @@ importers:
        version: 3.7.0(@emnapi/core@1.10.0)(@emnapi/runtime@1.11.3)(@types/node@22.7.4)
      '@opentelemetry/sdk-metrics':
        specifier: ^2.10.0
-        version: 2.11.0(@opentelemetry/api@1.9.1)
+        version: 2.10.0(@opentelemetry/api@1.9.1)
      '@types/axios':
        specifier: ^0.14.0
        version: 0.14.4
@@ -80,7 +80,7 @@ importers:
        version: 0.2.7
      ts-jest:
        specifier: ^29.1.2
-        version: 29.4.12(@babel/core@7.29.7)(@jest/transform@29.7.0)(@jest/types@29.6.3)(babel-jest@29.7.0(@babel/core@7.29.7))(jest-util@29.7.0)(jest@29.7.0(@types/node@22.7.4))(typescript@5.5.4)
+        version: 29.4.9(@babel/core@7.29.7)(@jest/transform@29.7.0)(@jest/types@29.6.3)(babel-jest@29.7.0(@babel/core@7.29.7))(jest-util@29.7.0)(jest@29.7.0(@types/node@22.7.4))(typescript@5.5.4)
      typedoc:
        specifier: 0.26.4
        version: 0.26.4(typescript@5.5.4)
@@ -1394,20 +1394,20 @@ packages:
    resolution: {integrity: sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q==}
    engines: {node: '>=8.0.0'}
-  '@opentelemetry/core@2.11.0':
+  '@opentelemetry/core@2.10.0':
-    resolution: {integrity: sha512-7YP44XH0tV6+Mb54x2YGf84i7yi+31MBZlE8JwvozkxyTvXbSp10X7cI7YE49ChJ3shMJoBmCJF3+1QFBJctGA==}
+    resolution: {integrity: sha512-/wNZ8twnEQQA4HoHu22+vcsdru6pWPWxW+7w+FlxT6Id7PE/WIbZmVKkte+PF72e0F2dnImFeHD2syyE1Mw6MQ==}
    engines: {node: ^18.19.0 || >=20.6.0}
    peerDependencies:
      '@opentelemetry/api': '>=1.0.0 <1.10.0'
-  '@opentelemetry/resources@2.11.0':
+  '@opentelemetry/resources@2.10.0':
-    resolution: {integrity: sha512-Ie7+8q8MDF4FAEQCKVMTx3ReUvxiIAgIiiW3c9JdmP8+HMcDy20puT+AHjexnExgnbvBxjQ9fjkFDWrikJ2jQA==}
+    resolution: {integrity: sha512-q6MMm2zhggzsHVNbabYwut+a6nbuQQe3URUoxaojM/8K1IBfwwPzvxIjNi2/lI1TFe+fMHMW9MWhrtDLEXEnkA==}
    engines: {node: ^18.19.0 || >=20.6.0}
    peerDependencies:
      '@opentelemetry/api': '>=1.3.0 <1.10.0'
-  '@opentelemetry/sdk-metrics@2.11.0':
+  '@opentelemetry/sdk-metrics@2.10.0':
-    resolution: {integrity: sha512-7GXXcObyHyDUUSG+L+kJoquty01bzm7ivE7+SSgXXJcHuPzGviptxwARmI2c+bnnxjexGQbJnyNlN8HxBP/Y7A==}
+    resolution: {integrity: sha512-t6r1VSvXNtSDnPXU1FbZeetJb7yyovHmgu0wRSoftxtE0g2rSNhQZQUy69sRUCL+iioJpX8SN/S6wq6ZtvLySQ==}
    engines: {node: ^18.19.0 || >=20.6.0}
    peerDependencies:
      '@opentelemetry/api': '>=1.9.0 <1.10.0'
@@ -1480,7 +1480,6 @@ packages:
  '@smithy/core@3.24.1':
    resolution: {integrity: sha512-3mT7o4qQyUWttYnVK3A0Z/u3Xha3E81tXn32Tz6vjZiUXhBrkEivpw1hBYfh84iFF9CSzkBU9Y1DJ3Q6RQ231g==}
    engines: {node: '>=18.0.0'}
    deprecated: Deprecated due to bug in browser bundling instructions https://github.com/smithy-lang/smithy-typescript/issues/2025
  '@smithy/credential-provider-imds@4.3.1':
    resolution: {integrity: sha512-0S/acwHnqX4WrjXzhdiDRxsG2s9SC0cpPIK9nZ1R6UOHd+j7uL28+4bHu22urbLk2TVw3fkp6na/+fkUt/pLNQ==}
@@ -3239,8 +3238,8 @@ packages:
    peerDependencies:
      typescript: '>=4.2.0'
-  ts-jest@29.4.12:
+  ts-jest@29.4.9:
-    resolution: {integrity: sha512-Ov6ClY53Fflh6BGAnY2DlTq1hYDrTycz2PVTXBWFW2CU+9zrEqAp9fWdGXl42EXO5RLSFAcAZ2JFKbP+zBTFfw==}
+    resolution: {integrity: sha512-LTb9496gYPMCqjeDLdPrKuXtncudeV1yRZnF4Wo5l3SFi0RYEnYRNgMrFIdg+FHvfzjCyQk1cLncWVqiSX+EvQ==}
    engines: {node: ^14.15.0 || ^16.10.0 || ^18.0.0 || >=20.0.0}
    hasBin: true
    peerDependencies:
@@ -5111,22 +5110,22 @@ snapshots:
  '@opentelemetry/api@1.9.1': {}
-  '@opentelemetry/core@2.11.0(@opentelemetry/api@1.9.1)':
+  '@opentelemetry/core@2.10.0(@opentelemetry/api@1.9.1)':
    dependencies:
      '@opentelemetry/api': 1.9.1
      '@opentelemetry/semantic-conventions': 1.43.0
-  '@opentelemetry/resources@2.11.0(@opentelemetry/api@1.9.1)':
+  '@opentelemetry/resources@2.10.0(@opentelemetry/api@1.9.1)':
    dependencies:
      '@opentelemetry/api': 1.9.1
-      '@opentelemetry/core': 2.11.0(@opentelemetry/api@1.9.1)
+      '@opentelemetry/core': 2.10.0(@opentelemetry/api@1.9.1)
      '@opentelemetry/semantic-conventions': 1.43.0
-  '@opentelemetry/sdk-metrics@2.11.0(@opentelemetry/api@1.9.1)':
+  '@opentelemetry/sdk-metrics@2.10.0(@opentelemetry/api@1.9.1)':
    dependencies:
      '@opentelemetry/api': 1.9.1
-      '@opentelemetry/core': 2.11.0(@opentelemetry/api@1.9.1)
+      '@opentelemetry/core': 2.10.0(@opentelemetry/api@1.9.1)
-      '@opentelemetry/resources': 2.11.0(@opentelemetry/api@1.9.1)
+      '@opentelemetry/resources': 2.10.0(@opentelemetry/api@1.9.1)
  '@opentelemetry/semantic-conventions@1.43.0': {}
@@ -5575,7 +5574,7 @@ snapshots:
      globby: 11.1.0
      is-glob: 4.0.3
      minimatch: 9.0.9
-      semver: 7.8.5
+      semver: 7.8.0
      ts-api-utils: 1.4.3(typescript@5.5.4)
    optionalDependencies:
      typescript: 5.5.4
@@ -6427,7 +6426,7 @@ snapshots:
      '@babel/parser': 7.29.3
      '@istanbuljs/schema': 0.1.6
      istanbul-lib-coverage: 3.2.2
-      semver: 7.8.5
+      semver: 7.8.0
    transitivePeerDependencies:
      - supports-color
@@ -6706,7 +6705,7 @@ snapshots:
      jest-util: 29.7.0
      natural-compare: 1.4.0
      pretty-format: 29.7.0
-      semver: 7.8.5
+      semver: 7.8.0
    transitivePeerDependencies:
      - supports-color
@@ -6829,7 +6828,7 @@ snapshots:
  make-dir@4.0.0:
    dependencies:
-      semver: 7.8.5
+      semver: 7.8.0
  make-error@1.3.6: {}
@@ -7163,7 +7162,8 @@ snapshots:
  semver@7.8.0: {}
-  semver@7.8.5: {}
+  semver@7.8.5:
    optional: true
  sharp@0.35.4(@types/node@22.7.4):
    dependencies:
@@ -7327,7 +7327,7 @@ snapshots:
    dependencies:
      typescript: 5.5.4
-  ts-jest@29.4.12(@babel/core@7.29.7)(@jest/transform@29.7.0)(@jest/types@29.6.3)(babel-jest@29.7.0(@babel/core@7.29.7))(jest-util@29.7.0)(jest@29.7.0(@types/node@22.7.4))(typescript@5.5.4):
+  ts-jest@29.4.9(@babel/core@7.29.7)(@jest/transform@29.7.0)(@jest/types@29.6.3)(babel-jest@29.7.0(@babel/core@7.29.7))(jest-util@29.7.0)(jest@29.7.0(@types/node@22.7.4))(typescript@5.5.4):
    dependencies:
      bs-logger: 0.2.6
      fast-json-stable-stringify: 2.1.0
@@ -7336,7 +7336,7 @@ snapshots:
      json5: 2.2.3
      lodash.memoize: 4.1.2
      make-error: 1.3.6
-      semver: 7.8.5
+      semver: 7.8.0
      type-fest: 4.41.0
      typescript: 5.5.4
      yargs-parser: 21.1.1
@@ -1,95 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 use std::ops::Range;
 use std::sync::Arc;
 use arrow_array::{Array, LargeBinaryArray};
 use lancedb::blob::BlobFile as LanceBlobFile;
 use napi::bindgen_prelude::*;
 use napi_derive::napi;
 use crate::error::convert_error;
 #[napi]
 pub struct BlobFile {
    inner: Arc<LanceBlobFile>,
 }
 impl BlobFile {
    pub(crate) fn new(inner: LanceBlobFile) -> Self {
        Self {
            inner: Arc::new(inner),
        }
    }
 }
 #[napi]
 impl BlobFile {
    #[napi]
    pub fn size(&self) -> BigInt {
        BigInt::from(self.inner.size())
    }
    #[napi]
    pub async fn read(&self) -> napi::Result<Buffer> {
        let bytes = self.inner.read().await.map_err(|err| convert_error(&err))?;
        Ok(Buffer::from(bytes.as_ref()))
    }
    #[napi]
    pub async fn read_range(&self, start: BigInt, end: BigInt) -> napi::Result<Buffer> {
        let range = bigint_range(start, end)?;
        let bytes = self
            .inner
            .read_range(range)
            .await
            .map_err(|err| convert_error(&err))?;
        Ok(Buffer::from(bytes.as_ref()))
    }
 }
 fn bigint_range(start: BigInt, end: BigInt) -> napi::Result<Range<u64>> {
    let start = parse_u64(start, "start")?;
    let end = parse_u64(end, "end")?;
    if start > end {
        return Err(napi::Error::from_reason(format!(
            "invalid blob range: start ({start}) > end ({end})"
        )));
    }
    Ok(start..end)
 }
 pub(crate) fn parse_u64(value: BigInt, name: &str) -> napi::Result<u64> {
    let (negative, value, lossless) = value.get_u64();
    if negative {
        return Err(napi::Error::from_reason(format!(
            "{name} cannot be negative"
        )));
    }
    if !lossless {
        return Err(napi::Error::from_reason(format!(
            "{name} is too large to fit in u64"
        )));
    }
    Ok(value)
 }
 pub(crate) fn parse_row_ids(row_ids: Vec<BigInt>) -> napi::Result<Vec<u64>> {
    row_ids
        .into_iter()
        .map(|id| parse_u64(id, "row id"))
        .collect()
 }
 pub(crate) fn copy_blob_buffers(array: LargeBinaryArray) -> Vec<Option<Buffer>> {
    (0..array.len())
        .map(|i| {
            if array.is_null(i) {
                None
            } else {
                Some(Buffer::from(array.value(i).to_vec()))
            }
        })
        .collect()
 }
@@ -442,15 +442,13 @@ impl Connection {
        self.get_inner()?.drop_all_tables(&ns).await.default_error()
    }
-    /// Open a server-side job by id, returning a handle with its record
+    /// A `Job` handle for a server-side job by id.
    /// already populated. Rejects when the server has no such job.
    ///
-    /// The returned handle answers for its own state, specification, result,
+    /// The handle is constructed without a server round trip; an unknown id
-    /// failure and event history, so there is no separate connection-level
+    /// surfaces when the handle is used.
-    /// call for any of them.
+    #[napi]
-    #[napi(catch_unwind)]
+    pub fn job(&self, job_id: String) -> napi::Result<crate::job::Job> {
-    pub async fn open_job(&self, job_id: String) -> napi::Result<crate::job::Job> {
+        let job = self.get_inner()?.job(job_id).default_error()?;
        let job = self.get_inner()?.open_job(&job_id).await.default_error()?;
        Ok(crate::job::Job::new(job))
    }
@@ -461,6 +459,17 @@ impl Connection {
        Ok(jobs.into_iter().map(Into::into).collect())
    }
    /// Describe a single server-side job by id. `null` when the server has
    /// no such job.
    #[napi(catch_unwind)]
    pub async fn get_job(
        &self,
        job_id: String,
    ) -> napi::Result<Option<crate::job::JobDescription>> {
        let description = self.get_inner()?.get_job(&job_id).await.default_error()?;
        Ok(description.map(Into::into))
    }
    /// Request cancellation of a server-side job by id. Returns true if the
    /// server accepted the cancellation, false if no such job exists.
    #[napi(catch_unwind)]
@@ -468,6 +477,34 @@ impl Connection {
        self.get_inner()?.cancel_job(&job_id).await.default_error()
    }
    /// The lifecycle event history of a server-side job (all jobs when
    /// `job_id` is null), as an Arrow IPC stream buffer. Empty when there is
    /// no history.
    #[napi(catch_unwind)]
    pub async fn job_history(&self, job_id: Option<String>) -> napi::Result<Buffer> {
        let batches = self
            .get_inner()?
            .job_history(job_id.as_deref())
            .await
            .default_error()?;
        let Some(first) = batches.first() else {
            return Ok(Buffer::from(Vec::<u8>::new()));
        };
        let mut out = Vec::new();
        let mut writer = arrow_ipc::writer::StreamWriter::try_new(&mut out, &first.schema())
            .map_err(|e| napi::Error::from_reason(e.to_string()))?;
        for batch in &batches {
            writer
                .write(batch)
                .map_err(|e| napi::Error::from_reason(e.to_string()))?;
        }
        writer
            .finish()
            .map_err(|e| napi::Error::from_reason(e.to_string()))?;
        drop(writer);
        Ok(Buffer::from(out))
    }
    #[napi(catch_unwind)]
    /// Describe a namespace and return its properties.
    pub async fn describe_namespace(
@@ -3,9 +3,6 @@
 use std::sync::Arc;
 use arrow_array::RecordBatch;
 use lancedb::job::JobEventsRequest;
 use napi::bindgen_prelude::Buffer;
 use napi_derive::napi;
 use crate::error::NapiErrorExt;
@@ -58,98 +55,12 @@ impl Job {
    pub async fn cancel(&self) -> napi::Result<()> {
        self.inner.cancel().await.default_error()
    }
    /// Ask the backend for this job's current state, and for a server-side job
    /// its full record, then cache it for the getters below.
    ///
    /// They are all null until this runs, because submitting an operation
    /// returns only a job id. {@link Job.status} fetches the whole record too;
    /// {@link Job.wait} records only the terminal state it establishes.
    #[napi(catch_unwind)]
    pub async fn refresh(&self) -> napi::Result<()> {
        self.inner.refresh().await.default_error()
    }
    /// The last observed lifecycle state, without contacting the backend.
    #[napi(getter)]
    pub fn state(&self) -> Option<String> {
        self.inner.state()
    }
    /// The job's type, as the server names it. Null for an in-process job,
    /// which has no server-side record.
    #[napi(getter)]
    pub fn job_type(&self) -> Option<String> {
        self.inner.job_type()
    }
    /// When the job was created, in milliseconds since the epoch.
    #[napi(getter)]
    pub fn creation_ms(&self) -> Option<i64> {
        self.inner.creation_ms()
    }
    /// The job-type-specific specification as a JSON string, when present.
    #[napi(getter)]
    pub fn spec_json(&self) -> Option<String> {
        self.inner.spec().map(|spec| spec.to_string())
    }
    /// The job-type-specific terminal result as a JSON string. Null until the
    /// job succeeds, so a job that never terminates reports its progress
    /// through {@link Job.events} instead.
    #[napi(getter)]
    pub fn result_json(&self) -> Option<String> {
        self.inner.result().map(|result| result.to_string())
    }
    /// Why the job failed, when it failed and the server reports a reason.
    #[napi(getter)]
    pub fn failure(&self) -> Option<JobFailureInfo> {
        self.inner.failure().map(|failure| JobFailureInfo {
            phase: failure.phase,
            message: failure.message,
            retryable: failure.retryable,
        })
    }
    /// This job's recorded lifecycle events, as an Arrow IPC stream buffer.
    /// The TypeScript wrapper turns it into an Arrow table.
    #[napi(catch_unwind)]
    pub async fn events(&self, limit: Option<u32>, filter: Option<String>) -> napi::Result<Buffer> {
        let batches = self
            .inner
            .events(JobEventsRequest { limit, filter })
            .await
            .default_error()?;
        batches_to_ipc_buffer(&batches)
    }
 }
 /// Serialise Arrow batches as a single IPC stream for the TypeScript layer.
 fn batches_to_ipc_buffer(batches: &[RecordBatch]) -> napi::Result<Buffer> {
    let Some(first) = batches.first() else {
        return Ok(Buffer::from(Vec::<u8>::new()));
    };
    let mut out = Vec::new();
    let mut writer = arrow_ipc::writer::StreamWriter::try_new(&mut out, &first.schema())
        .map_err(|e| napi::Error::from_reason(e.to_string()))?;
    for batch in batches {
        writer
            .write(batch)
            .map_err(|e| napi::Error::from_reason(e.to_string()))?;
    }
    writer
        .finish()
        .map_err(|e| napi::Error::from_reason(e.to_string()))?;
    drop(writer);
    Ok(Buffer::from(out))
 }
 /// A row from `Connection.listJobs`: one server-side job.
 #[napi(object)]
 pub struct JobInfo {
-    /// The job id -- what `Connection.openJob` and `Connection.cancelJob`
+    /// The job id -- what `Connection.getJob` and `Connection.cancelJob`
    /// accept.
    pub job_id: String,
    /// The table the job runs against, without URI or namespace.
@@ -180,3 +91,36 @@ pub struct JobFailureInfo {
    pub message: Option<String>,
    pub retryable: Option<bool>,
 }
 /// A described job from `Connection.getJob`.
 #[napi(object)]
 pub struct JobDescription {
    pub job_id: String,
    pub job_type: String,
    /// Lifecycle state: "running", "finished", "failed", or "cancelled".
    pub state: String,
    /// When the job was created, in milliseconds since the epoch.
    pub creation_ms: i64,
    /// The job-type-specific specification as a JSON string, when present.
    pub spec_json: Option<String>,
    /// Why the job failed, when the job is failed and the server reports a
    /// reason.
    pub failure: Option<JobFailureInfo>,
 }
 impl From<lancedb::database::JobDescription> for JobDescription {
    fn from(description: lancedb::database::JobDescription) -> Self {
        Self {
            job_id: description.job_id,
            job_type: description.job_type,
            state: description.state,
            creation_ms: description.creation_ms,
            spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
            failure: description.failure.map(|failure| JobFailureInfo {
                phase: failure.phase,
                message: failure.message,
                retryable: failure.retryable,
            }),
        }
    }
 }
@@ -10,7 +10,6 @@ use std::collections::HashMap;
 use env_logger::Env;
 use napi_derive::*;
 mod blob;
 mod connection;
 mod error;
 mod header;
@@ -15,7 +15,6 @@ use napi::bindgen_prelude::*;
 use napi::threadsafe_function::{ThreadsafeFunction, ThreadsafeFunctionCallMode};
 use napi_derive::napi;
 use crate::blob::{BlobFile, copy_blob_buffers, parse_row_ids};
 use crate::error::NapiErrorExt;
 use crate::index::Index;
 use crate::merge::NativeMergeInsertBuilder;
@@ -330,44 +329,6 @@ impl Table {
        ))
    }
    #[napi(catch_unwind)]
    pub async fn blob_columns(&self) -> napi::Result<Vec<String>> {
        self.inner_ref()?.blob_columns().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn fetch_blobs(
        &self,
        column: String,
        row_ids: Vec<BigInt>,
    ) -> napi::Result<Vec<Option<Buffer>>> {
        let row_ids = parse_row_ids(row_ids)?;
        let array = self
            .inner_ref()?
            .fetch_blobs(column.as_str(), &row_ids)
            .await
            .default_error()?;
        Ok(copy_blob_buffers(array))
    }
    #[napi(catch_unwind)]
    pub async fn fetch_blob_files(
        &self,
        column: String,
        row_ids: Vec<BigInt>,
    ) -> napi::Result<Vec<Option<BlobFile>>> {
        let row_ids = parse_row_ids(row_ids)?;
        let files = self
            .inner_ref()?
            .fetch_blob_files(column.as_str(), &row_ids)
            .await
            .default_error()?;
        Ok(files
            .into_iter()
            .map(|file| file.map(BlobFile::new))
            .collect())
    }
    #[napi(catch_unwind)]
    pub fn vector_search(&self, vector: Float32Array) -> napi::Result<VectorQuery> {
        self.query()?.nearest_to(vector)
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.39.0-beta.6"
+version = "0.39.0-beta.1"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
@@ -28,7 +28,7 @@ env_logger.workspace = true
 log.workspace = true
 # Maturin enables extension-module mode for Python builds. Keeping it out of
 # Cargo features lets Rust unit tests link against libpython.
-pyo3 = { version = "0.28", features = ["abi3-py310", "chrono", "uuid"] }
+pyo3 = { version = "0.28", features = ["abi3-py310", "chrono"] }
 chrono.workspace = true
 pyo3-async-runtimes = { version = "0.28", features = [
    "attributes",
@@ -40,7 +40,6 @@ serde.workspace = true
 serde_json.workspace = true
 snafu.workspace = true
 tokio.workspace = true
 uuid.workspace = true
 libc = "0.2"
 [build-dependencies]
@@ -139,7 +139,6 @@ include = [
    "python/lancedb/exceptions.py",
    "python/lancedb/background_loop.py",
    "python/lancedb/schema.py",
    "python/lancedb/sql.py",
    "python/lancedb/remote/__init__.py",
    "python/lancedb/remote/errors.py",
    "python/lancedb/embeddings/__init__.py",
@@ -22,11 +22,7 @@ from .remote.db import RemoteDBConnection
 from .expr import Expr, col, lit, func
 from .schema import blob, vector
 from .job import AsyncJob, Job
 from .sql import AsyncQuery as AsyncSqlQuery
 from .sql import Query as SqlQuery
 from .sql import QueryDescription
 from .functions import (
    AssignmentMapping as AssignmentMapping,
    FunctionArtifactRequest as FunctionArtifactRequest,
    FunctionApplication as FunctionApplication,
    FunctionBinding as FunctionBinding,
@@ -105,7 +101,6 @@ def connect(
    api_key: Optional[str] = None,
    region: str = "us-east-1",
    host_override: Optional[str] = None,
    sql_host_override: Optional[str] = None,
    read_consistency_interval: Optional[timedelta] = None,
    request_thread_pool: Optional[Union[int, ThreadPoolExecutor]] = None,
    client_config: Union[ClientConfig, Dict[str, Any], None] = None,
@@ -134,9 +129,6 @@ def connect(
        The region to use for LanceDB Cloud.
    host_override: str, optional
        The override url for LanceDB Cloud.
    sql_host_override: str, optional
        The remote SQL service endpoint override. The client connects lazily when SQL
        is first executed and retains that connection.
    read_consistency_interval: timedelta, default None
        The interval at which to check for updates to the table from other
        processes. If None, then consistency is not checked. For performance
@@ -278,7 +270,6 @@ def connect(
            api_key,
            region,
            host_override,
            sql_host_override=sql_host_override,
            # TODO: remove this (deprecation warning downstream)
            request_thread_pool=request_thread_pool,
            client_config=client_config,
@@ -421,7 +412,6 @@ def deserialize_conn(
            parsed["api_key"],
            parsed.get("region", "us-east-1"),
            host_override=parsed.get("host_override"),
            sql_host_override=parsed.get("sql_host_override"),
            client_config=parsed.get("client_config"),
            storage_options=storage_options,
        )
@@ -435,7 +425,6 @@ async def connect_async(
    api_key: Optional[str] = None,
    region: str = "us-east-1",
    host_override: Optional[str] = None,
    sql_host_override: Optional[str] = None,
    read_consistency_interval: Optional[timedelta] = None,
    client_config: Optional[Union[ClientConfig, Dict[str, Any]]] = None,
    storage_options: Optional[Dict[str, str]] = None,
@@ -458,9 +447,6 @@ async def connect_async(
        The region to use for LanceDB Cloud.
    host_override: str, optional
        The override url for LanceDB Cloud.
    sql_host_override: str, optional
        The remote SQL service endpoint override. The client connects lazily when SQL
        is first executed and retains that connection.
    read_consistency_interval: timedelta, default None
        The interval at which to check for updates to the table from other
        processes. If None, then consistency is not checked. For performance
@@ -548,7 +534,6 @@ async def connect_async(
            api_key,
            region,
            host_override,
            sql_host_override,
            read_consistency_interval_secs,
            client_config,
            storage_options,
@@ -571,7 +556,6 @@ __all__ = [
    "connect_namespace_async",
    "AsyncConnection",
    "AsyncJob",
    "AsyncSqlQuery",
    "AsyncLanceNamespaceDBConnection",
    "AsyncTable",
    "FtsToken",
@@ -586,8 +570,6 @@ __all__ = [
    "vector",
    "DBConnection",
    "Job",
    "QueryDescription",
    "SqlQuery",
    "LanceDBConnection",
    "LanceNamespaceDBConnection",
    "LsmWriteSpec",
@@ -1,7 +1,6 @@
 from datetime import date, datetime, timedelta
 from decimal import Decimal
 from typing import Dict, List, Optional, Tuple, Any, TypedDict, Union, Literal
 from uuid import UUID
 import pyarrow as pa
@@ -148,20 +147,17 @@ class Connection(object):
        start_after: Optional[str],
        limit: Optional[int],
    ) -> list[str]: ...  # Deprecated: Use list_tables instead
-    async def open_job(self, job_id: str) -> Job: ...
+    def job(self, job_id: str) -> Job: ...
    async def create_function_async(self, request_json: str) -> Job: ...
    async def get_function(self, name: str, version: str) -> str: ...
    async def list_functions(self) -> List[str]: ...
    async def drop_function(self, name: str, version: str) -> bool: ...
    async def list_jobs(self) -> List[JobInfo]: ...
    async def get_job(self, job_id: str) -> Optional[JobDescription]: ...
    async def cancel_job(self, job_id: str) -> bool: ...
-    async def execute_query_async(
+    async def job_history(
-        self,
+        self, job_id: Optional[str] = None
-        query: str,
+    ) -> List[pa.RecordBatch]: ...
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> SqlQuery: ...
    async def describe_query(self, query_id: UUID) -> QueryDescription: ...
    async def create_table(
        self,
        name: str,
@@ -240,20 +236,9 @@ class BlobFile:
 class Job:
    @property
    def id(self) -> Optional[str]: ...
    @property
    def _state(self) -> Optional[str]: ...
    @property
    def _description(self) -> Optional[JobDescription]: ...
    async def status(self) -> str: ...
    async def wait(self) -> Optional[str]: ...
    async def cancel(self) -> None: ...
    async def refresh(self) -> None: ...
    async def events(
        self,
        *,
        limit: Optional[int] = None,
        filter: Optional[str] = None,
    ) -> pa.Table: ...
 class JobInfo:
    @property
@@ -285,33 +270,10 @@ class JobDescription:
    @property
    def creation_ms(self) -> int: ...
    @property
-    def _spec_json(self) -> Optional[str]: ...
+    def spec_json(self) -> Optional[str]: ...
    @property
    def _result_json(self) -> Optional[str]: ...
    @property
    def spec(self) -> Optional[Any]: ...
    @property
    def result(self) -> Optional[Any]: ...
    @property
    def failure(self) -> Optional[JobFailureInfo]: ...
 class SqlQuery:
    @property
    def id(self) -> UUID: ...
    async def describe(self) -> QueryDescription: ...
    async def reader(self) -> RecordBatchStream: ...
    async def cancel(self) -> None: ...
 class QueryDescription:
    @property
    def id(self) -> UUID: ...
    @property
    def status(self) -> str: ...
    @property
    def progress(self) -> Optional[float]: ...
    @property
    def expires_at(self) -> Optional[datetime]: ...
 class Table:
    def name(self) -> str: ...
    def __repr__(self) -> str: ...
@@ -490,7 +452,6 @@ async def connect(
    api_key: Optional[str],
    region: Optional[str],
    host_override: Optional[str],
    sql_host_override: Optional[str],
    read_consistency_interval: Optional[float],
    client_config: Optional[Union[ClientConfig, Dict[str, Any]]],
    storage_options: Optional[Dict[str, str]],
@@ -19,7 +19,6 @@ from typing import (
    Optional,
    Union,
 )
 from uuid import UUID
 if sys.version_info >= (3, 12):
    from typing import override
@@ -48,9 +47,6 @@ from . import __version__
 from ._lancedb import connect as lancedb_connect  # type: ignore
 from .functions import FunctionVersion, UdfDefinition
 from .job import AsyncJob, Job, _typed_job
 from .sql import AsyncQuery as AsyncSqlQuery
 from .sql import Query as SqlQuery
 from .sql import QueryDescription
 from .materialized_view import (
    AsyncMaterializedView,
    MaterializedView,
@@ -72,11 +68,10 @@ import deprecation
 if TYPE_CHECKING:
    import pyarrow as pa
    from .arrow import AsyncRecordBatchReader
    from .pydantic import LanceModel
    from ._lancedb import Connection as LanceDbConnection
-    from ._lancedb import JobInfo
+    from ._lancedb import JobDescription, JobInfo
    from .common import DATA, URI
    from .embeddings import EmbeddingFunctionConfig
    from ._lancedb import Session
@@ -745,23 +740,26 @@ class DBConnection(EnforceOverrides):
            "Function catalog operations are not supported for this connection type"
        )
-    def open_job(self, job_id: str) -> Job:
+    def job(self, job_id: str) -> Job:
-        """Open a server-side job by id, returning a handle with its record
+        """A [Job][lancedb.job.Job] handle for a server-side job by id.
        already populated.
-        The returned [Job][lancedb.job.Job] answers for its own state,
+        The handle is constructed without a server round trip; an unknown id
-        specification, result, failure and event history, so there is no
+        surfaces when the handle is used. Dropping the handle has no effect
-        separate connection-level call for any of them.
+        on the job itself.
        Raises `JobNotFoundError` when the server has no such job, the way
        `open_table` does for a missing table.
        """
-        raise NotImplementedError("open_job is not supported for this connection type")
+        raise NotImplementedError("job is not supported for this connection type")
    def list_jobs(self) -> List[JobInfo]:
        """List server-side jobs across the database's tables."""
        raise NotImplementedError("list_jobs is not supported for this connection type")
    def get_job(self, job_id: str) -> Optional[JobDescription]:
        """Describe a single server-side job by id.
        Returns None when the server has no such job.
        """
        raise NotImplementedError("get_job is not supported for this connection type")
    def cancel_job(self, job_id: str) -> bool:
        """Request cancellation of a server-side job by id.
@@ -773,38 +771,14 @@ class DBConnection(EnforceOverrides):
            "cancel_job is not supported for this connection type"
        )
-    def execute_query(
+    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        self,
+        """The lifecycle event history of a server-side job, as Arrow batches.
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> pa.RecordBatchReader:
        """Execute SQL and return a blocking Arrow reader.
-        This submits through :meth:`execute_query_async` and waits until the
+        Lists history across all jobs when `job_id` is None.
        initial result stream is readable. It does not wait for the full query
        to finish.
        """
-        return self.execute_query_async(
+        raise NotImplementedError(
-            query,
+            "job_history is not supported for this connection type"
-            default_namespace_path=default_namespace_path,
+        )
        ).reader()
    def execute_query_async(
        self,
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> SqlQuery:
        """Start executing SQL and return its query handle.
        Local connections do not support SQL.
        """
        raise NotImplementedError("SQL is not supported for this connection type")
    def describe_query(self, query_id: UUID) -> QueryDescription:
        """Describe a submitted SQL query by its connection-scoped id."""
        raise NotImplementedError("SQL is not supported for this connection type")
 class LanceDBConnection(DBConnection):
@@ -901,7 +875,6 @@ class LanceDBConnection(DBConnection):
                None,
                None,
                None,
                None,
                read_consistency_interval_secs,
                None,
                storage_options,
@@ -1450,11 +1423,14 @@ class LanceDBConnection(DBConnection):
        )
    @override
-    def open_job(self, job_id: str) -> Job:
+    def job(self, job_id: str) -> Job:
-        """Open a server-side job by id. See
+        """A [Job][lancedb.job.Job] handle for a server-side job by id.
-        [DBConnection.open_job][lancedb.db.DBConnection.open_job].
+
        The handle is constructed without a server round trip; an unknown id
        surfaces when the handle is used. Dropping the handle has no effect
        on the job itself.
        """
-        return Job(LOOP.run(self._conn.open_job(job_id)))
+        return Job(self._conn.job(job_id))
    @override
    def create_function_async(self, definition: UdfDefinition) -> Job[FunctionVersion]:
@@ -1478,6 +1454,14 @@ class LanceDBConnection(DBConnection):
        """List server-side jobs across the database's tables."""
        return LOOP.run(self._conn.list_jobs())
    @override
    def get_job(self, job_id: str) -> Optional[JobDescription]:
        """Describe a single server-side job by id.
        Returns None when the server has no such job.
        """
        return LOOP.run(self._conn.get_job(job_id))
    @override
    def cancel_job(self, job_id: str) -> bool:
        """Request cancellation of a server-side job by id.
@@ -1488,6 +1472,14 @@ class LanceDBConnection(DBConnection):
        """
        return LOOP.run(self._conn.cancel_job(job_id))
    @override
    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
        """The lifecycle event history of a server-side job, as Arrow batches.
        Lists history across all jobs when `job_id` is None.
        """
        return LOOP.run(self._conn.job_history(job_id))
    @override
    def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.
@@ -2258,11 +2250,15 @@ class AsyncConnection(object):
            namespace_path = []
        await self._inner.drop_all_tables(namespace_path=namespace_path)
-    async def open_job(self, job_id: str) -> AsyncJob:
+    def job(self, job_id: str) -> AsyncJob:
-        """Open a server-side job by id. See
+        """An [AsyncJob][lancedb.job.AsyncJob] handle for a server-side job
-        [DBConnection.open_job][lancedb.db.DBConnection.open_job].
+        by id.
        The handle is constructed without a server round trip; an unknown id
        surfaces when the handle is used. Dropping the handle has no effect
        on the job itself.
        """
-        return AsyncJob(await self._inner.open_job(job_id))
+        return AsyncJob(self._inner.job(job_id))
    async def create_function_async(
        self, definition: UdfDefinition
@@ -2302,6 +2298,13 @@ class AsyncConnection(object):
        """List server-side jobs across the database's tables."""
        return await self._inner.list_jobs()
    async def get_job(self, job_id: str) -> Optional[JobDescription]:
        """Describe a single server-side job by id.
        Returns None when the server has no such job.
        """
        return await self._inner.get_job(job_id)
    async def cancel_job(self, job_id: str) -> bool:
        """Request cancellation of a server-side job by id.
@@ -2311,46 +2314,12 @@ class AsyncConnection(object):
        """
        return await self._inner.cancel_job(job_id)
-    async def execute_query(
+    async def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        self,
+        """The lifecycle event history of a server-side job, as Arrow batches.
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> AsyncRecordBatchReader:
        """Execute SQL and return an asynchronous Arrow reader.
-        This submits through :meth:`execute_query_async` and waits until the
+        Lists history across all jobs when `job_id` is None.
        initial result stream is readable. It does not wait for the full query
        to finish.
        """
-        submitted = await self.execute_query_async(
+        return await self._inner.job_history(job_id)
            query,
            default_namespace_path=default_namespace_path,
        )
        return await submitted.reader()
    async def execute_query_async(
        self,
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> AsyncSqlQuery:
        """Start executing SQL and return its query handle.
        The database from ``connect_async`` is used for unqualified database
        references. The namespace defaults to ``["public"]``. Local
        connections raise ``NotImplementedError``.
        """
        return AsyncSqlQuery(
            await self._inner.execute_query_async(
                query,
                default_namespace_path=default_namespace_path,
            )
        )
    async def describe_query(self, query_id: UUID) -> QueryDescription:
        """Describe a submitted SQL query by its connection-scoped id."""
        return await self._inner.describe_query(query_id)
    async def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.
@@ -21,7 +21,7 @@ class GteEmbeddings(TextEmbeddingFunction):
    An embedding function that uses GTE-LARGE MLX format(for Apple silicon devices only)
    as well as the standard cpu/gpu version from: https://huggingface.co/thenlper/gte-large.
-    For Apple users, you will need the mlx package installed, which can be done with:
+    For Apple users, you will need the mlx package insalled, which can be done with:
        pip install mlx
    Parameters
@@ -60,7 +60,7 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):
    import lancedb
    from lancedb.pydantic import LanceModel, Vector
-    from lancedb.embeddings import get_registry, InstructorEmbeddingFunction
+    from lancedb.embeddings import get_registry, InstuctorEmbeddingFunction
    instructor = get_registry().get("instructor").create(
        source_instruction="represent the document for retrieval",
@@ -35,9 +35,3 @@ class JobCancelledError(RuntimeError):
    """Exception raised when an asynchronous job was cancelled."""
    pass
 class JobNotFoundError(ValueError):
    """Exception raised when opening a job the server does not have."""
    pass
@@ -470,7 +470,11 @@ class InputBinding(_RemoteValue):
 class OutputMapping(_RemoteValue):
-    """One stable result-field mapping."""
+    """One stable result-field mapping.
    Assignment state is outside the Slice 1 client contract. During the NULL
    transition Lance exposes no public cell-flag identifier to persist here.
    """
    result_field: str
    output_name: str
@@ -480,13 +484,6 @@ class OutputMapping(_RemoteValue):
    nullable: bool
 class AssignmentMapping(_RemoteValue):
    """Internal physical column preserving flattened struct validity."""
    output_name: str
    output_field_id: _Int32
 class FunctionBinding(_RemoteValue):
    """Immutable Function binding persisted by the Enterprise table service."""
@@ -494,7 +491,6 @@ class FunctionBinding(_RemoteValue):
    function: FunctionVersionRef
    inputs: tuple[InputBinding, ...]
    outputs: tuple[OutputMapping, ...]
    assignment: Optional[AssignmentMapping] = None
    input_schema: Optional[Mapping[str, Any]] = None
    output_schema: Optional[Mapping[str, Any]] = None
@@ -915,6 +911,8 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
    if not fields:
        raise ValueError("named-struct Function output must contain at least one field")
    if any(field.nullable for field in fields):
        raise ValueError("Function output fields must be non-nullable")
    for field in fields:
        _validate_exact_arrow_field(field)
    names = [field.name for field in fields]
@@ -926,7 +924,7 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
            FunctionResultField(
                name=field.name,
                arrow_type=_canonical_arrow_field(field),
-                nullable=field.nullable,
+                nullable=False,
            )
            for field in fields
        ),
@@ -1309,9 +1307,8 @@ def udf(
    Input and output signatures are inferred from supported annotations. For
    Arrow types annotations cannot express precisely, pass ``input_schema``
-    and ``output_schema`` together. Scalar outputs must be non-nullable. Every
+    and ``output_schema`` together. Nullable outputs are rejected because V1
-    named-struct field may be nullable; Enterprise preserves the struct's
+    uses physical NULL to represent unassigned computed-column rows.
    validity when the result is expanded into sibling columns.
    Parameters
    ----------
@@ -1323,8 +1320,8 @@ def udf(
        Explicit input fields in the exact order of the callable parameters.
        Must be provided together with ``output_schema``.
    output_schema : pyarrow.DataType, pyarrow.Field, or pyarrow.Schema, optional
-        Explicit scalar or named-struct output. Scalar outputs must be
+        Explicit scalar or named-struct output. Must be non-nullable and be
-        non-nullable. Must be provided together with ``input_schema``.
+        provided together with ``input_schema``.
    pip : sequence of str, optional
        Pip requirements for the remote environment.
    conda : sequence of str, optional
@@ -1390,7 +1387,6 @@ def udf(
 __all__ = [
    "AssignmentMapping",
    "ApplicationInput",
    "FunctionApplication",
    "FunctionArtifact",
@@ -751,7 +751,7 @@ class IvfPq:
        This value controls how much the vector is compressed during the
        quantization step.  The more sub vectors there are the less the vector is
        compressed.  The default is the dimension of the vector divided by 16.  If
-        the dimension is not evenly divisible by 16 we use the dimension divided by
+        the dimension is not evenly divisible by 16 we use the dimension divded by
        8.
        The above two cases are highly preferred.  Having 8 or 16 values per
@@ -4,27 +4,15 @@
 """Handles to operations a server may run asynchronously."""
 import asyncio
 import json
 from datetime import timedelta
 from typing import Any, Callable, Generic, Optional, TypeVar, cast
 import pyarrow as pa
 from lancedb.background_loop import LOOP
 from . import _lancedb
 from ._lancedb import JobDescription, JobFailureInfo, JobInfo
 T = TypeVar("T")
 __all__ = [
    "AsyncJob",
    "Job",
    "JobDescription",
    "JobFailureInfo",
    "JobInfo",
 ]
 class AsyncJob(Generic[T]):
    """A handle to an operation that may still be running.
@@ -90,149 +78,6 @@ class AsyncJob(Generic[T]):
            return
        await self._inner.cancel()
    async def refresh(self) -> None:
        """Ask the backend for this job's current state, and for a server-side
        job its full record, then cache it for the properties below.
        The properties are all `None` until this runs, because submitting an
        operation returns only a job id. `status` fetches the whole record too;
        `wait` records only the terminal state it establishes.
        """
        if self._inner is None:
            return
        await self._inner.refresh()
    @property
    def state(self) -> Optional[str]:
        """The last observed lifecycle state, without contacting the backend.
        `None` until the handle has talked to it. See :meth:`AsyncJob.refresh`.
        """
        if self._inner is None:
            return "finished"
        return self._inner._state
    @property
    def job_type(self) -> Optional[str]:
        """The job's type, as the server names it.
        `None` for an in-process job, which has no server-side record.
        """
        return self._field("job_type")
    @property
    def creation_ms(self) -> Optional[int]:
        """When the job was created, in milliseconds since the epoch."""
        return self._field("creation_ms")
    @property
    def spec(self) -> Optional[Any]:
        """The job-type-specific specification it was submitted with."""
        return self._field("spec")
    @property
    def result(self) -> Optional[Any]:
        """The job-type-specific terminal result, as reported data rather than
        the typed model :meth:`AsyncJob.wait` returns.
        `None` until the job succeeds, so a job that never terminates reports
        its progress through :meth:`AsyncJob.events` instead.
        """
        return self._field("result")
    @property
    def failure(self) -> Optional[JobFailureInfo]:
        """Why the job failed, when it failed and the server reports a reason."""
        return self._field("failure")
    @property
    def _spec_json(self) -> Optional[str]:
        return self._field("_spec_json")
    @property
    def _result_json(self) -> Optional[str]:
        return self._field("_result_json")
    def _field(self, name: str) -> Optional[Any]:
        description = self._inner._description if self._inner is not None else None
        return getattr(description, name) if description is not None else None
    async def events(
        self,
        *,
        limit: Optional[int] = None,
        filter: Optional[str] = None,
    ) -> "pa.Table":
        """This job's recorded lifecycle events.
        Where the properties above report a terminal result only once the job
        reaches one, events are written as the job runs and outlive the workers
        that produced them. A distributed job records a `claim`/`claim_complete`
        pair per unit of work, each carrying `rows_processed`, so a job that
        never finishes still accounts for what it did.
        Parameters
        ----------
        limit: int, optional
            Maximum event rows to return. The server caps results at 1000 by
            default and 10,000 at most, and truncates without saying so, so
            pass this for a job that emits an event per fragment.
        filter: str, optional
            SQL-like expression over the `state`, `updated_by`, `emitted_from`,
            `emitted_by`, and `claim_entity` columns, such as
            ``state = 'claim_complete'``.
        """
        if self._inner is None:
            raise NotImplementedError(
                "job event history is only available for server-side jobs"
            )
        return await self._inner.events(limit=limit, filter=filter)
    def __repr__(self) -> str:
        return _job_repr("AsyncJob", self)
 _REPR_INDENT = " " * 4
 def _repr_payload(value: Any) -> str:
    """Render a job payload as indented JSON, aligned under its field."""
    try:
        rendered = json.dumps(value, indent=4)
    except TypeError:
        return repr(value)
    return rendered.replace("\n", "\n" + _REPR_INDENT)
 def _job_repr(kind: str, job: Any) -> str:
    """Render every field the handle currently knows, omitting the rest.
    One field per line, with the JSON payloads indented, because a refresh
    job's spec and result are the point of printing it.
    """
    state = job.state
    if state is None:
        # Nothing has been fetched yet, so there is nothing to lay out.
        known = f"id={job.id!r}, " if job.id is not None else ""
        return f"{kind}({known}not refreshed)"
    fields = []
    if job.id is not None:
        fields.append(f"id={job.id!r}")
    fields.append(f"state={state!r}")
    for name in ("job_type", "creation_ms"):
        value = getattr(job, name)
        if value is not None:
            fields.append(f"{name}={value!r}")
    for name in ("spec", "result"):
        value = getattr(job, name)
        if value is not None:
            fields.append(f"{name}={_repr_payload(value)}")
    if job.failure is not None:
        fields.append(f"failure={job.failure!r}")
    body = "".join(f"\n{_REPR_INDENT}{field}," for field in fields)
    return f"{kind}({body}\n)"
 class Job(Generic[T]):
    """Synchronous counterpart of `AsyncJob` with the same result type."""
@@ -277,75 +122,6 @@ class Job(Generic[T]):
            return
        LOOP.run(self._inner.cancel())
    def refresh(self) -> None:
        """Ask the backend for this job's current state and record.
        See :meth:`AsyncJob.refresh`.
        """
        if self._inner is None:
            return
        LOOP.run(self._inner.refresh())
    @property
    def state(self) -> Optional[str]:
        """The last observed lifecycle state. See :attr:`AsyncJob.state`."""
        return self._inner.state if self._inner is not None else "finished"
    @property
    def job_type(self) -> Optional[str]:
        """The job's type. See :attr:`AsyncJob.job_type`."""
        return self._field("job_type")
    @property
    def creation_ms(self) -> Optional[int]:
        """When the job was created. See :attr:`AsyncJob.creation_ms`."""
        return self._field("creation_ms")
    @property
    def spec(self) -> Optional[Any]:
        """The job's specification. See :attr:`AsyncJob.spec`."""
        return self._field("spec")
    @property
    def result(self) -> Optional[Any]:
        """The job's terminal result. See :attr:`AsyncJob.result`."""
        return self._field("result")
    @property
    def failure(self) -> Optional[JobFailureInfo]:
        """Why the job failed. See :attr:`AsyncJob.failure`."""
        return self._field("failure")
    @property
    def _spec_json(self) -> Optional[str]:
        return self._field("_spec_json")
    @property
    def _result_json(self) -> Optional[str]:
        return self._field("_result_json")
    def _field(self, name: str) -> Optional[Any]:
        return getattr(self._inner, name) if self._inner is not None else None
    def events(
        self,
        *,
        limit: Optional[int] = None,
        filter: Optional[str] = None,
    ) -> "pa.Table":
        """This job's recorded lifecycle events.
        See :meth:`AsyncJob.events`.
        """
        if self._inner is None:
            raise NotImplementedError(
                "job event history is only available for server-side jobs"
            )
        return LOOP.run(self._inner.events(limit=limit, filter=filter))
    def __repr__(self) -> str:
        return _job_repr("Job", self)
 def _typed_job(
    inner: "_lancedb.Job", result_decoder: Callable[[str], T]
@@ -12,7 +12,6 @@ from __future__ import annotations
 import sys
 from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
 from uuid import UUID
 if sys.version_info >= (3, 12):
    from typing import override
@@ -49,11 +48,8 @@ from lancedb._lancedb import (
    connect_namespace_client as _connect_namespace_client,
 )
 from lancedb.background_loop import LOOP
 from lancedb.arrow import AsyncRecordBatchReader
 from lancedb.db import AsyncConnection, DBConnection
 from lancedb.job import AsyncJob, Job
 from lancedb.sql import AsyncQuery as AsyncSqlQuery
 from lancedb.sql import QueryDescription
 from lance_namespace import (
    LanceNamespace,
    connect as namespace_connect,
@@ -1451,37 +1447,6 @@ class AsyncLanceNamespaceDBConnection:
            namespace_path=namespace_path, page_token=page_token, limit=limit
        )
    async def execute_query(
        self,
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> AsyncRecordBatchReader:
        """Execute SQL when supported by the underlying connection."""
        return await self._inner.execute_query(
            query,
            default_namespace_path=default_namespace_path,
        )
    async def execute_query_async(
        self,
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> AsyncSqlQuery:
        """Start executing SQL when supported by the underlying connection.
        Namespace-backed local connections do not support SQL.
        """
        return await self._inner.execute_query_async(
            query,
            default_namespace_path=default_namespace_path,
        )
    async def describe_query(self, query_id: UUID) -> QueryDescription:
        """Describe a submitted SQL query when supported."""
        return await self._inner.describe_query(query_id)
    async def namespace_client(self) -> LanceNamespace:
        """Get the namespace client for this connection.
@@ -78,10 +78,6 @@ if TYPE_CHECKING:
 T = TypeVar("T", bound="LanceModel")
 AnalyzePlanDistributedMetrics = Literal["aggregate", "per_worker", "full"]
 # Number of rows a hybrid query returns when no limit was set on it. This
 # mirrors the default the Rust query builder applies to its sub-queries.
 DEFAULT_HYBRID_LIMIT = 10
@runtime_checkable
 class _LanceScanner(Protocol):
@@ -863,7 +859,7 @@ class Query(pydantic.BaseModel):
        return query
    # This tells pydantic to allow custom types (needed for the `vector` query since
-    # pa.Array wouldn't be allowed otherwise)
+    # pa.Array wouln't be allowed otherwise)
    model_config = pydantic.ConfigDict(arbitrary_types_allowed=True)
@@ -3897,54 +3893,14 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        return self
    def _create_child_queries(
        self,
    ) -> Tuple["AsyncFTSQuery", "AsyncVectorQuery", int, int]:
        """Build the sub-queries that make up this hybrid query.
        Execution, `explain_plan` and `analyze_plan` all go through here so that
        the plans that are reported are the plans that actually run.
        Returns the two sub-queries along with the effective limit and offset of
        the hybrid query itself.
        """
        fts_query = AsyncFTSQuery(self._inner.to_fts_query(), self._table)
        vec_query = AsyncVectorQuery(self._inner.to_vector_query(), self._table)
        fts_req = fts_query._inner.to_query_request()
        vec_req = vec_query._inner.to_query_request()
        # Only one of the two sub-queries carries the limit when it was never
        # set explicitly: nearest_to()/nearest_to_text() build the sibling query
        # from scratch, and that is where the default gets filled in. Which one
        # that is depends on the order the hybrid query was built in, so look at
        # both rather than at a single side.
        limit = fts_req.limit if fts_req.limit is not None else vec_req.limit
        if limit is None:
            limit = DEFAULT_HYBRID_LIMIT
        offset = fts_req.offset or vec_req.offset or 0
        fts_query.with_row_id()
        vec_query.with_row_id()
        # offset() pushes the offset down into both sub-queries, which would make
        # each of them skip its own first `offset` rows. The window has to be
        # taken out of the combined, reranked results instead, so fetch the
        # skipped prefix here too and slice it off afterwards.
        fts_query.limit(limit + offset)
        vec_query.limit(limit + offset)
        fts_query.offset(0)
        vec_query.offset(0)
        return fts_query, vec_query, limit, offset
    async def to_batches(
        self,
        *,
        max_batch_length: Optional[int] = None,
        timeout: Optional[timedelta] = None,
    ) -> AsyncRecordBatchReader:
-        fts_query, vec_query, limit, offset = self._create_child_queries()
+        fts_query = AsyncFTSQuery(self._inner.to_fts_query(), self._table)
        vec_query = AsyncVectorQuery(self._inner.to_vector_query(), self._table)
        req = fts_query._inner.to_query_request()
        blob_auto_row_id = False
@@ -3964,6 +3920,9 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        self._blob_auto_row_id = blob_auto_row_id
        self._blob_paths = blob_paths
        fts_query.with_row_id()
        vec_query.with_row_id()
        fts_results, vector_results = await asyncio.gather(
            fts_query.to_arrow(timeout=timeout),
            vec_query.to_arrow(timeout=timeout),
@@ -3975,9 +3934,8 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
            norm=self._norm,
            fts_query=fts_query.get_query(),
            reranker=self._reranker,
-            limit=limit,
+            limit=self._inner.get_limit(),
            with_row_ids=True,
            offset=offset,
        )
        if (
            not self._user_requested_row_id()
@@ -4006,14 +3964,14 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        ...     print(plan)
        >>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
        RRFReranker(K=60)
-            ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance, _rowid@1 as _rowid]
+            ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
              LanceRead: uri=..., projection=[text], source=stream(_rowid)
                GlobalLimitExec: skip=0, fetch=10
                  FilterExec: _distance@2 IS NOT NULL
                    SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
                      KNNVectorDistance: metric=l2
                        LanceRead: uri=..., projection=[vector], ...
-            ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score, _rowid@0 as _rowid]
+            ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
              LanceRead: uri=..., projection=[vector, text], source=stream(_rowid)
                GlobalLimitExec: skip=0, fetch=10
                  MatchQuery: column=text, query=[hello]
@@ -4028,9 +3986,8 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        plan : str
        """  # noqa: E501
-        fts_query, vec_query, _, _ = self._create_child_queries()
+        vector_plan = await self._inner.to_vector_query().explain_plan(verbose)
-        vector_plan = await vec_query.explain_plan(verbose)
+        fts_plan = await self._inner.to_fts_query().explain_plan(verbose)
        fts_plan = await fts_query.explain_plan(verbose)
        # Indent sub-plans under the reranker
        indented_vector = "\n".join("  " + line for line in vector_plan.splitlines())
        indented_fts = "\n".join("  " + line for line in fts_plan.splitlines())
@@ -4057,12 +4014,14 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        -------
        plan : str
        """
        fts_query, vec_query, _, _ = self._create_child_queries()
        results = ["Vector Search Query:"]
-        results.append(await vec_query.analyze_plan(distributed_metrics))
+        results.append(
            await self._inner.to_vector_query().analyze_plan(distributed_metrics)
        )
        results.append("FTS Search Query:")
-        results.append(await fts_query.analyze_plan(distributed_metrics))
+        results.append(
            await self._inner.to_fts_query().analyze_plan(distributed_metrics)
        )
        return "\n".join(results)
@@ -9,7 +9,6 @@ from concurrent.futures import ThreadPoolExecutor
 import sys
 from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
 from urllib.parse import urlparse
 from uuid import UUID
 import warnings
 if sys.version_info >= (3, 12):
@@ -26,12 +25,10 @@ from ..common import DATA
 from ..db import DBConnection, LOOP
 from ..functions import FunctionVersion, UdfDefinition
 from ..job import AsyncJob, Job
 from ..sql import Query as SqlQuery
 from ..sql import QueryDescription
 from ..materialized_view import MaterializedView, SelectArg
 if TYPE_CHECKING:
-    from .._lancedb import JobInfo
+    from .._lancedb import JobDescription, JobInfo
 from ..embeddings import EmbeddingFunctionConfig
 from lance_namespace import (
    LanceNamespace,
@@ -119,7 +116,6 @@ class RemoteDBConnection(DBConnection):
        read_timeout: Optional[float] = None,
        storage_options: Optional[Dict[str, str]] = None,
        read_consistency_interval: Optional[timedelta] = None,
        sql_host_override: Optional[str] = None,
    ):
        """Connect to a remote LanceDB database."""
        if isinstance(client_config, dict):
@@ -165,7 +161,6 @@ class RemoteDBConnection(DBConnection):
        self.api_key = api_key
        self.region = region
        self.host_override = host_override
        self.sql_host_override = sql_host_override
        self.storage_options = storage_options
        self.db_name = parsed.netloc
@@ -180,7 +175,6 @@ class RemoteDBConnection(DBConnection):
                api_key=api_key,
                region=region,
                host_override=host_override,
                sql_host_override=sql_host_override,
                client_config=client_config,
                storage_options=storage_options,
                read_consistency_interval=read_consistency_interval,
@@ -199,7 +193,6 @@ class RemoteDBConnection(DBConnection):
                "api_key": self.api_key,
                "region": self.region,
                "host_override": self.host_override,
                "sql_host_override": self.sql_host_override,
                "client_config": _client_config_to_dict(self.client_config),
                "storage_options": self.storage_options,
            }
@@ -739,11 +732,14 @@ class RemoteDBConnection(DBConnection):
        )
    @override
-    def open_job(self, job_id: str) -> Job:
+    def job(self, job_id: str) -> Job:
-        """Open a server-side job by id. See
+        """A [Job][lancedb.job.Job] handle for a server-side job by id.
-        [DBConnection.open_job][lancedb.db.DBConnection.open_job].
+
        The handle is constructed without a server round trip; an unknown id
        surfaces when the handle is used. Dropping the handle has no effect
        on the job itself.
        """
-        return Job(LOOP.run(self._conn.open_job(job_id)))
+        return Job(self._conn.job(job_id))
    @override
    def create_function_async(self, definition: UdfDefinition) -> Job[FunctionVersion]:
@@ -766,6 +762,14 @@ class RemoteDBConnection(DBConnection):
        """List server-side jobs across the database's tables."""
        return LOOP.run(self._conn.list_jobs())
    @override
    def get_job(self, job_id: str) -> Optional["JobDescription"]:
        """Describe a single server-side job by id.
        Returns None when the server has no such job.
        """
        return LOOP.run(self._conn.get_job(job_id))
    @override
    def cancel_job(self, job_id: str) -> bool:
        """Request cancellation of a server-side job by id.
@@ -777,35 +781,12 @@ class RemoteDBConnection(DBConnection):
        return LOOP.run(self._conn.cancel_job(job_id))
    @override
-    def execute_query_async(
+    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        self,
+        """The lifecycle event history of a server-side job, as Arrow batches.
        query: str,
        *,
        default_namespace_path: Optional[List[str]] = None,
    ) -> SqlQuery:
        """Start executing SQL through this remote connection.
-        Unqualified tables use this connection's database and the
+        Lists history across all jobs when `job_id` is None.
        ``["public"]`` namespace by default. Fully qualified table names may
        reference other databases available to the same deployment.
        """
-        return SqlQuery(
+        return LOOP.run(self._conn.job_history(job_id))
            LOOP.run(
                self._conn.execute_query_async(
                    query,
                    default_namespace_path=default_namespace_path,
                )
            )
        )
    @override
    def describe_query(self, query_id: UUID) -> QueryDescription:
        """Describe a submitted SQL query by its connection-scoped id."""
        return LOOP.run(
            self._conn.describe_query(
                query_id,
            )
        )
    @override
    def namespace_client(self) -> LanceNamespace:
@@ -177,7 +177,4 @@ class OAuthProvider(HeaderProvider):
        if not self._current_token:
            raise RuntimeError("Failed to obtain OAuth token")
-        return {
+        return {"Authorization": f"Bearer {self._current_token}"}
            "Authorization": f"Bearer {self._current_token}",
            "x-lancedb-credential-type": "oidc",
        }
@@ -402,6 +402,7 @@ class RemoteTable(Table):
        /,
        *,
        config: IndexConfigType,
        replace: bool = ...,
        wait_timeout: Optional[timedelta] = ...,
        name: Optional[str] = ...,
        train: bool = ...,
@@ -416,7 +417,7 @@ class RemoteTable(Table):
        index_cache_size: Optional[int] = ...,
        num_partitions: Optional[int] = ...,
        num_sub_vectors: Optional[int] = ...,
-        replace: Optional[bool] = ...,
+        replace: bool = ...,
        accelerator: Optional[str] = ...,
        index_type: Literal[
            "VECTOR", "IVF_FLAT", "IVF_SQ", "IVF_PQ", "IVF_HNSW_SQ", "IVF_HNSW_PQ"
@@ -435,7 +436,7 @@ class RemoteTable(Table):
        index_cache_size: Optional[int] = None,
        num_partitions: Optional[int] = None,
        num_sub_vectors: Optional[int] = None,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        accelerator: Optional[str] = None,
        index_type="vector",
        wait_timeout: Optional[timedelta] = None,
@@ -479,7 +480,6 @@ class RemoteTable(Table):
            vector_column_name,
            accelerator,
            index_cache_size,
            replace,
        )
        if is_legacy:
@@ -503,12 +503,6 @@ class RemoteTable(Table):
                    "If you have 100M+ vectors to index,"
                    "please contact us at contact@lancedb.com"
                )
            if replace is not None:
                logging.warning(
                    "replace is not supported on LanceDB cloud."
                    "Existing indexes will always be replaced."
                )
            idx_type = index_type.upper()
            if idx_type == "VECTOR" or idx_type == "IVF_PQ":
                config = IvfPq(
@@ -561,7 +555,7 @@ class RemoteTable(Table):
        column: str,
        *,
        config: IndexConfigType,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
@@ -593,7 +587,6 @@ class RemoteTable(Table):
        vector_column_name: str,
        accelerator: Optional[str],
        index_cache_size: Optional[int],
        replace: Optional[bool],
    ) -> bool:
        """Detect if this is a legacy create_index call."""
        if config is not None:
@@ -605,7 +598,6 @@ class RemoteTable(Table):
                num_sub_vectors,
                accelerator,
                index_cache_size,
                replace,
            )
        ):
            return True
@@ -720,7 +712,7 @@ class RemoteTable(Table):
        Parameters
        ----------
        query: list/np.ndarray/str/PIL.Image.Image, default None
-            The targeted vector to search for.
+            The targetted vector to search for.
            - *default None*.
            Acceptable types are: list, np.ndarray, PIL.Image.Image
@@ -175,7 +175,7 @@ class Reranker(ABC):
            if the results haven't been executed yet or the results in arrow format.
        query : str or None,
            The input query. Some rerankers might not need the query to rerank.
-            In that case, it can be set to None explicitly. This is intended to
+            In that case, it can be set to None explicitly. This is inteded to
            be handled by the reranker implementations.
        deduplicate : bool, optional
            Whether to deduplicate the results based on the `_rowid` column,
@@ -1,88 +0,0 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 """Handles to SQL queries running on a remote database."""
 from uuid import UUID
 import pyarrow as pa
 from lancedb.background_loop import LOOP
 from . import _lancedb
 from .arrow import AsyncRecordBatchReader
 QueryDescription = _lancedb.QueryDescription
 class AsyncQuery:
    """A handle to a submitted SQL query on an asynchronous connection."""
    def __init__(self, inner: "_lancedb.SqlQuery"):
        self._inner = inner
    @property
    def id(self) -> UUID:
        """The stable identifier scoped to the connection that submitted it."""
        return self._inner.id
    async def describe(self) -> QueryDescription:
        """Get a point-in-time description of the query."""
        return await self._inner.describe()
    async def reader(self) -> AsyncRecordBatchReader:
        """Wait for the initial result stream and return its Arrow reader.
        Results are single-consumer. Calling this method more than once on the
        same query raises an error. Later batches are streamed as they become
        available without waiting for the full query to finish.
        """
        return AsyncRecordBatchReader(await self._inner.reader())
    async def cancel(self) -> None:
        """Request cancellation of the query."""
        await self._inner.cancel()
 class Query:
    """Synchronous counterpart of :class:`AsyncQuery`."""
    def __init__(self, inner: AsyncQuery):
        self._inner = inner
    @property
    def id(self) -> UUID:
        """The stable identifier scoped to the connection that submitted it."""
        return self._inner.id
    def describe(self) -> QueryDescription:
        """Get a point-in-time description of the query."""
        return LOOP.run(self._inner.describe())
    def reader(self) -> pa.RecordBatchReader:
        """Wait for the initial result stream and return a blocking reader.
        Results are single-consumer. Calling this method more than once on the
        same query raises an error. Later batches block only until they become
        available, without waiting for the full query to finish.
        """
        reader = LOOP.run(self._inner.reader())
        def next_batch():
            try:
                return LOOP.run(reader.__anext__())
            except StopAsyncIteration:
                return None
        def batches():
            while (batch := next_batch()) is not None:
                yield batch
        return pa.RecordBatchReader.from_batches(reader.schema, batches())
    def cancel(self) -> None:
        """Request cancellation of the query."""
        LOOP.run(self._inner.cancel())
 __all__ = ["AsyncQuery", "Query", "QueryDescription"]
@@ -1132,7 +1132,7 @@ class Table(ABC):
        num_partitions: Optional[int] = None,
        num_sub_vectors: Optional[int] = None,
        vector_column_name: str = VECTOR_COLUMN_NAME,
-        replace: bool = True,
+        replace: bool = False,
        accelerator: Optional[str] = None,
        index_cache_size: Optional[int] = None,
        *,
@@ -1166,7 +1166,7 @@ class Table(ABC):
            The index configuration object. If provided, uses the new unified API.
            Can be one of: IvfFlat, IvfPq, IvfSq, IvfRq, HnswPq, HnswSq,
            BTree, Bitmap, LabelList, Fm, FTS.
-        replace : bool, default True
+        replace : bool, default False
            Whether to replace an existing index on this column.
        wait_timeout : timedelta, optional
            Timeout to wait for async indexing to complete.
@@ -1198,7 +1198,7 @@ class Table(ABC):
        column: str,
        *,
        config: IndexConfigType,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
@@ -1260,7 +1260,7 @@ class Table(ABC):
        self,
        column: str,
        *,
-        replace: bool = True,
+        replace: bool = False,
        index_type: ScalarIndexType = "BTREE",
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
@@ -1272,7 +1272,7 @@ class Table(ABC):
        column : str
            The column to be indexed.  Must be a boolean, integer, float,
            or string column.
-        replace : bool, default True
+        replace : bool, default False
            Replace the existing index if it exists.
        index_type: Literal["BTREE", "BITMAP", "LABEL_LIST"], default "BTREE"
            The type of index to create.
@@ -1619,7 +1619,7 @@ class Table(ABC):
        Parameters
        ----------
        query: list/np.ndarray/str/PIL.Image.Image, default None
-            The targeted vector to search for.
+            The targetted vector to search for.
            - *default None*.
            Acceptable types are: list, np.ndarray, PIL.Image.Image
@@ -1793,9 +1793,6 @@ class Table(ABC):
        The result has the same length and order as ``row_ids``. Null blobs
        produce null slots; valid empty blobs produce ``b""``.
        ``_rowid`` values stay valid after compaction when the table has stable
        row ids.
        Convenience for small payloads. For large values use
        :meth:`fetch_blob_files`.
        """
@@ -1813,9 +1810,6 @@ class Table(ABC):
        The result has the same length and order as ``requests``; null blobs
        produce null slots and empty ranges on non-null blobs produce ``b""``.
        ``_rowid`` values stay valid after compaction when the table has stable
        row ids.
        Row IDs can be obtained from a query with ``with_row_id(True)``. This
        API is currently supported only by local tables.
        """
@@ -1831,9 +1825,6 @@ class Table(ABC):
        ``_rowid`` or a ``_lance_row_id`` field on the blob descriptor. Null
        rows are ``None``. Remote tables require LanceDB Cloud server 0.5.0 or
        newer.
        ``_rowid`` values stay valid after compaction when the table has stable
        row ids.
        """
    @abstractmethod
@@ -2997,7 +2988,7 @@ class LanceTable(Table):
        num_partitions: Optional[int] = None,
        num_sub_vectors: Optional[int] = None,
        vector_column_name: str = VECTOR_COLUMN_NAME,
-        replace: bool = True,
+        replace: bool = False,
        accelerator: Optional[str] = None,
        index_cache_size: Optional[int] = None,
        num_bits: int = 8,
@@ -3039,7 +3030,7 @@ class LanceTable(Table):
            The index configuration object. If provided, uses the new unified API.
            Can be one of: IvfFlat, IvfPq, IvfSq, IvfRq, HnswPq, HnswSq,
            BTree, Bitmap, LabelList, Fm, FTS.
-        replace : bool, default True
+        replace : bool, default False
            Whether to replace an existing index on this column.
        wait_timeout : timedelta, optional
            Timeout to wait for async indexing to complete.
@@ -3178,7 +3169,7 @@ class LanceTable(Table):
        column: str,
        *,
        config: IndexConfigType,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
@@ -3433,7 +3424,7 @@ class LanceTable(Table):
        self,
        column: str,
        *,
-        replace: bool = True,
+        replace: bool = False,
        index_type: ScalarIndexType = "BTREE",
        name: Optional[str] = None,
    ):
@@ -3841,7 +3832,7 @@ class LanceTable(Table):
        Parameters
        ----------
        query: list/np.ndarray/str/PIL.Image.Image, default None
-            The targeted vector to search for.
+            The targetted vector to search for.
            - *default None*.
            Acceptable types are: list, np.ndarray, PIL.Image.Image
@@ -5322,7 +5313,7 @@ class AsyncTable:
        self,
        column: str,
        *,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        config: Optional[
            Union[
                IvfFlat,
@@ -5353,14 +5344,14 @@ class AsyncTable:
        ----------
        column: str
            The column to index.
-        replace: bool, default True
+        replace: bool, default False
            Whether to replace the existing index
            If this is false, and another index already exists on the same columns
            and the same name, then an error will be returned.  This is true even if
            that index is out of date.
-            The default is True
+            The default is False
        config: default None
            For advanced configuration you can specify the type of index you would
            like to create.   You can also specify index-specific parameters when
@@ -5418,7 +5409,7 @@ class AsyncTable:
        self,
        column: str,
        *,
-        replace: Optional[bool] = None,
+        replace: bool = False,
        config: Optional[
            Union[
                IvfFlat,
@@ -5638,7 +5629,7 @@ class AsyncTable:
        if fill_value is None:
            fill_value = 0.0
-        # _sanitize_data is an old code path, but we will use it until the
+        # _santitize_data is an old code path, but we will use it until the
        # new code path is ready.
        if mode == "overwrite":
            # For overwrite, apply the same preprocessing as create_table
@@ -5814,7 +5805,7 @@ class AsyncTable:
        Parameters
        ----------
        query: list/np.ndarray/str/PIL.Image.Image, default None
-            The targeted vector to search for.
+            The targetted vector to search for.
            - *default None*.
            Acceptable types are: list, np.ndarray, PIL.Image.Image
@@ -66,25 +66,6 @@ def _row_ids_by_id(table):
    return dict(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
 def _assert_missing_blob_row_ids(exc_info):
    message = str(exc_info.value)
    assert "row ids" in message
    assert "rowaddr" not in message
    assert "fragment" not in message
 def _assert_fetch_apis_reject_missing_row_ids(table, row_ids):
    with pytest.raises(ValueError) as exc_info:
        table.fetch_blobs("image", row_ids)
    _assert_missing_blob_row_ids(exc_info)
    with pytest.raises(ValueError) as exc_info:
        table.fetch_blob_files("image", row_ids)
    _assert_missing_blob_row_ids(exc_info)
    with pytest.raises(ValueError) as exc_info:
        table.fetch_blob_ranges("image", [(row_id, 0, 1) for row_id in row_ids])
    _assert_missing_blob_row_ids(exc_info)
 def test_blob_factory_declares_v2_field():
    field = lancedb.blob("image")
    assert isinstance(field.type, pa.ExtensionType)
@@ -297,10 +278,7 @@ def test_blob_v2_projection_sources_use_typed_column_name():
 def _legacy_v1_table(name):
-    # Legacy v1 blob columns are only writable at file version <= 2.1.
+    db = lancedb.connect("memory:///")
    db = lancedb.connect(
        "memory:///", storage_options={"new_table_data_storage_version": "2.1"}
    )
    schema = pa.schema(
        [
            pa.field("id", pa.int64()),
@@ -713,25 +691,6 @@ def test_fetch_blobs_accepts_query_result():
    assert {blobs[i].as_py() for i in range(len(blobs))} == {b"gamma"}
 def test_fetch_blobs_after_compact_with_stable_row_ids(tmp_path):
    db = lancedb.connect(
        tmp_path, storage_options={"new_table_enable_stable_row_ids": "true"}
    )
    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
    table = db.create_table("t", schema=schema)
    table.add([{"id": 1, "image": b"frag-one"}])
    table.add([{"id": 2, "image": b"frag-two"}])
    by_id = _row_ids_by_id(table)
    ids = [by_id[1], by_id[2]]
    table.optimize()
    blobs = table.fetch_blobs("image", ids)
    assert blobs.to_pylist() == [b"frag-one", b"frag-two"]
    ranges = table.fetch_blob_ranges("image", [(ids[0], 5, 3), (ids[1], 5, 3)])
    assert ranges.to_pylist() == [b"one", b"two"]
 def test_fetch_blobs_preserves_null_and_empty_values():
    table = _blob_table(
        "nulls",
@@ -780,25 +739,8 @@ def test_fetch_blob_ranges_validates_requests():
    with pytest.raises(ValueError, match="offset \\+ length overflowed"):
        table.fetch_blob_ranges("image", [(row_id, 2**64 - 1, 1)])
-    with pytest.raises(ValueError) as exc_info:
+    with pytest.raises(ValueError, match="row IDs"):
        table.fetch_blob_ranges("image", [(2**64 - 1, 0, 1)])
    _assert_missing_blob_row_ids(exc_info)
 def test_fetch_blob_apis_reject_missing_fragment_row_addr():
    table = _blob_table("missing_frag", [{"id": 1, "image": b"x"}])
    live = _row_ids_by_id(table)[1]
    _assert_fetch_apis_reject_missing_row_ids(table, [1 << 32, live])
 def test_fetch_blob_apis_reject_deleted_row_ids():
    table = _blob_table(
        "deleted_rows",
        [{"id": 1, "image": b"one"}, {"id": 2, "image": b"two"}],
    )
    by_id = _row_ids_by_id(table)
    table.delete("id = 2")
    _assert_fetch_apis_reject_missing_row_ids(table, [by_id[2], by_id[1]])
 def test_fetch_blob_ranges_empty_requests_returns_empty_array():
@@ -327,8 +327,8 @@ def test_embedding_function_with_pandas(tmp_path):
        ) -> List[np.array]:
            return [np.random.randn(self.ndims()).tolist() for _ in range(len(texts))]
-    registry = get_registry()
+    registery = get_registry()
-    func = registry.get("mock-embedding").create()
+    func = registery.get("mock-embedding").create()
    class TestSchema(LanceModel):
        text: str = func.SourceField()
@@ -394,9 +394,9 @@ def test_multiple_embeddings_for_pandas(tmp_path):
        ) -> List[np.array]:
            return [np.random.randn(self.ndims()).tolist() for _ in range(len(texts))]
-    registry = get_registry()
+    registery = get_registry()
-    func1 = registry.get("mock-embedding").create()
+    func1 = registery.get("mock-embedding").create()
-    func2 = registry.get("mock-embedding2").create()
+    func2 = registery.get("mock-embedding2").create()
    class TestSchema(LanceModel):
        text: str = func1.SourceField()
@@ -850,43 +850,6 @@ def test_named_struct_function_can_include_a_blob_result_field():
    ]
 def test_named_struct_function_preserves_nullable_result_fields():
    @udf(
        input_schema=pa.schema([pa.field("value", pa.int64(), nullable=False)]),
        output_schema=pa.schema(
            [
                pa.field("result", pa.int64(), nullable=True),
                pa.field("failure_code", pa.int32(), nullable=False),
            ]
        ),
    )
    def nullable_result(value):
        return {"result": value, "failure_code": 0}
    output = nullable_result.registration_request.signature.output
    assert [(field.name, field.nullable) for field in output.fields] == [
        ("result", True),
        ("failure_code", False),
    ]
    @udf(
        input_schema=pa.schema([pa.field("value", pa.int64(), nullable=False)]),
        output_schema=pa.schema(
            [
                pa.field("result", pa.int64(), nullable=True),
                pa.field("failure_code", pa.int32(), nullable=True),
            ]
        ),
    )
    def all_nullable(value):
        return {"result": value, "failure_code": None}
    assert all(
        field.nullable
        for field in all_nullable.registration_request.signature.output.fields
    )
 def test_metadata_marked_blob_field_uses_the_semantic_type():
    extension = lancedb.blob("image", nullable=False).type
    storage = (
@@ -1011,13 +1011,8 @@ def test_fts_ngram(mem_db: DBConnection):
    assert set(r["text"] for r in results) == {"lance database", "lance is cool"}
    results = (
-        table.search(
+        table.search("nce", query_type="fts").limit(10).to_list()
-            "nce",  # spellchecker:disable-line
+    )  # spellchecker:disable-line
            query_type="fts",
        )
        .limit(10)
        .to_list()
    )
    assert len(results) == 2
    assert set(r["text"] for r in results) == {"lance database", "lance is cool"}
@@ -1039,13 +1034,8 @@ def test_fts_ngram(mem_db: DBConnection):
    assert set(r["text"] for r in results) == {"lance database", "lance is cool"}
    results = (
-        table.search(
+        table.search("nce", query_type="fts").limit(10).to_list()
-            "nce",  # spellchecker:disable-line
+    )  # spellchecker:disable-line
            query_type="fts",
        )
        .limit(10)
        .to_list()
    )
    assert len(results) == 0
    results = table.search("la", query_type="fts").limit(10).to_list()
@@ -54,10 +54,7 @@ class TestOAuthProvider:
        provider = OAuthProvider(fetcher)
        headers = provider.get_headers()
-        assert headers == {
+        assert headers == {"Authorization": "Bearer token123"}
            "Authorization": "Bearer token123",
            "x-lancedb-credential-type": "oidc",
        }
        assert provider._current_token == "token123"
        assert provider._token_expires_at is not None
@@ -76,20 +73,14 @@ class TestOAuthProvider:
        # First call
        headers1 = provider.get_headers()
-        assert headers1 == {
+        assert headers1 == {"Authorization": "Bearer token1"}
            "Authorization": "Bearer token1",
            "x-lancedb-credential-type": "oidc",
        }
        # Wait for token to expire
        time.sleep(1.1)
        # Second call should refresh
        headers2 = provider.get_headers()
-        assert headers2 == {
+        assert headers2 == {"Authorization": "Bearer token2"}
            "Authorization": "Bearer token2",
            "x-lancedb-credential-type": "oidc",
        }
        assert call_count == 2
    def test_no_expiry_info(self):
@@ -101,18 +92,12 @@ class TestOAuthProvider:
        provider = OAuthProvider(fetcher)
        headers = provider.get_headers()
-        assert headers == {
+        assert headers == {"Authorization": "Bearer permanent_token"}
            "Authorization": "Bearer permanent_token",
            "x-lancedb-credential-type": "oidc",
        }
        assert provider._token_expires_at is None
        # Should not refresh on second call
        headers2 = provider.get_headers()
-        assert headers2 == {
+        assert headers2 == {"Authorization": "Bearer permanent_token"}
            "Authorization": "Bearer permanent_token",
            "x-lancedb-credential-type": "oidc",
        }
    def test_missing_access_token(self):
        """Test error handling when access_token is missing."""
@@ -136,10 +121,7 @@ class TestOAuthProvider:
        provider = OAuthProvider(fetcher)
        headers = provider.get_headers()
-        assert headers == {
+        assert headers == {"Authorization": "Bearer sync_token"}
            "Authorization": "Bearer sync_token",
            "x-lancedb-credential-type": "oidc",
        }
 class TestClientConfigIntegration:
@@ -203,93 +203,6 @@ async def test_async_hybrid_query_default_limit(table: AsyncTable):
    assert texts.count("a") == 1
@pytest.mark.asyncio
 async def test_async_hybrid_query_offset(table: AsyncTable):
    # The offset window of a hybrid query must be a suffix of the same query
    # run without an offset. Skipping the first rows of each sub-query instead
    # of the first rows of the fused result silently changes which rows land in
    # the window.
    full = await (
        table.query()
        .nearest_to([0.0, 0.4])
        .nearest_to_text("dog")
        .limit(4)
        .with_row_id()
        .to_arrow()
    )
    assert len(full) == 4
    second_page = await (
        table.query()
        .nearest_to([0.0, 0.4])
        .nearest_to_text("dog")
        .offset(2)
        .limit(2)
        .with_row_id()
        .to_arrow()
    )
    assert second_page["_rowid"].to_pylist() == full["_rowid"].to_pylist()[2:]
    first_page = await (
        table.query()
        .nearest_to([0.0, 0.4])
        .nearest_to_text("dog")
        .limit(2)
        .with_row_id()
        .to_arrow()
    )
    # Paging through the result must visit every row exactly once: no row
    # repeated from the previous page and none dropped between the two.
    paged = first_page["_rowid"].to_pylist() + second_page["_rowid"].to_pylist()
    assert sorted(paged) == sorted(full["_rowid"].to_pylist())
@pytest.mark.asyncio
 async def test_async_hybrid_query_fts_first_default_limit(table: AsyncTable):
    # nearest_to() and nearest_to_text() build their new sibling sub-query from
    # scratch, and that is the sub-query the default limit ends up on. So the
    # side that carries the limit depends on the order the hybrid query was
    # built in, and looking at only one side loses the limit for half the ways
    # a hybrid query can be written. Without a limit the combined results are
    # not truncated at all and the whole union of both candidate lists is
    # returned.
    await table.add([{"text": "dog", "vector": [50.0 + i, 50.0]} for i in range(10)])
    result = await (
        table.query().nearest_to_text("dog").nearest_to([0.1, 0.1]).to_arrow()
    )
    assert len(result) == 10
    offset_result = await (
        table.query().nearest_to_text("dog").nearest_to([0.1, 0.1]).offset(2).to_arrow()
    )
    assert len(offset_result) == 10
@pytest.mark.asyncio
 async def test_async_hybrid_query_explain_plan_matches_execution(table: AsyncTable):
    # Paging rewrites the sub-queries: each one fetches limit + offset rows with
    # no offset of its own, and the window is sliced out after fusion. The plans
    # have to be built from those rewritten sub-queries, otherwise explain_plan
    # and analyze_plan describe a query that is never run.
    query = (
        table.query().nearest_to([0.0, 0.4]).nearest_to_text("dog").offset(2).limit(2)
    )
    await query.to_arrow()
    plan = await query.explain_plan()
    assert [
        line.strip() for line in plan.splitlines() if "GlobalLimitExec" in line
    ] == [
        "GlobalLimitExec: skip=0, fetch=4",
        "GlobalLimitExec: skip=0, fetch=4",
    ]
    analyzed = await query.analyze_plan()
    assert analyzed.count("skip=0, fetch=4") == 2
    assert "skip=2" not in analyzed
 def test_hybrid_query_offset(sync_table: Table):
    # The offset window of a hybrid query must be a suffix of the same query
    # run without an offset -- it must not be silently ignored.
@@ -97,6 +97,9 @@ async def test_create_index_async_returns_done_job(some_table: AsyncTable):
 async def test_create_scalar_index(some_table: AsyncTable):
    # Can create
    await some_table.create_index("id")
    # Can't recreate by default
    with pytest.raises(RuntimeError, match="already exists"):
        await some_table.create_index("id")
    # Can recreate if replace=True
    await some_table.create_index("id", replace=True)
    indices = await some_table.list_indices()
@@ -110,7 +113,7 @@ async def test_create_scalar_index(some_table: AsyncTable):
    with pytest.raises(RuntimeError, match="already exists"):
        await some_table.create_index("id", replace=False)
    # can also specify index type
-    await some_table.create_index("id", config=BTree())
+    await some_table.create_index("id", config=BTree(), replace=True)
    await some_table.drop_index("id_idx")
    indices = await some_table.list_indices()
@@ -351,13 +354,18 @@ async def test_full_text_search_index(some_table: AsyncTable):
 async def test_create_vector_index(some_table: AsyncTable):
    # Can create
    await some_table.create_index("vector")
    # Can't recreate by default
    with pytest.raises(RuntimeError, match="already exists"):
        await some_table.create_index("vector")
    # Can recreate if replace=True
    await some_table.create_index("vector", replace=True)
    # Can't recreate if replace=False
    with pytest.raises(RuntimeError, match="already exists"):
        await some_table.create_index("vector", replace=False)
    # Can also specify index type
-    await some_table.create_index("vector", config=IvfPq(num_partitions=100))
+    await some_table.create_index(
        "vector", config=IvfPq(num_partitions=100), replace=True
    )
    indices = await some_table.list_indices()
    assert len(indices) == 1
    assert indices[0].index_type == "IvfPq"
@@ -193,13 +193,7 @@ class TestNamespaceConnection:
            ),
        )
-        # Legacy v1 blob columns are only writable at file version <= 2.1.
+        table = db.create_table("blob_table", data, namespace_path=["test_ns"])
        table = db.create_table(
            "blob_table",
            data,
            namespace_path=["test_ns"],
            storage_options={"new_table_data_storage_version": "2.1"},
        )
        df = table.to_pandas(blob_mode="lazy").sort_values("id")
        blob = df["blob"].iloc[0]
@@ -40,10 +40,6 @@ from utils import exception_output
 from importlib.util import find_spec
 # Legacy v1 blob columns are only writable at file version <= 2.1.
 LEGACY_BLOB_STORAGE_OPTIONS = {"new_table_data_storage_version": "2.1"}
 def _blob_query_data():
    return pa.table(
        {
@@ -123,17 +119,13 @@ def _assert_blob_bytes_projection(df):
 def _blob_query_table(db, name, blob_schema):
    if blob_schema == "v1":
-        return db.create_table(
+        return db.create_table(name, _blob_query_data())
            name, _blob_query_data(), storage_options=LEGACY_BLOB_STORAGE_OPTIONS
        )
    return _create_blob_v2_query_table(db, name)
 async def _blob_query_table_async(db, name, blob_schema):
    if blob_schema == "v1":
-        return await db.create_table(
+        return await db.create_table(name, _blob_query_data())
            name, _blob_query_data(), storage_options=LEGACY_BLOB_STORAGE_OPTIONS
        )
    return await _create_blob_v2_query_table_async(db, name)
@@ -283,9 +275,7 @@ async def test_query_to_pandas_kwargs(table, table_async):
 def test_plain_scan_query_to_pandas_blob_modes(tmp_db, blob_mode):
    pytest.importorskip("lance")
    table = tmp_db.create_table(
-        f"test_query_to_pandas_blob_{blob_mode}",
+        f"test_query_to_pandas_blob_{blob_mode}", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    df = (
@@ -332,9 +322,7 @@ def test_plain_scan_query_to_pandas_blob_mode_does_not_collect_arrow(
 ):
    pytest.importorskip("lance")
    table = tmp_db.create_table(
-        "test_query_to_pandas_blob_no_arrow_collect",
+        "test_query_to_pandas_blob_no_arrow_collect", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    query = table.search().where("id = 1").select(["id", "blob"])
@@ -359,9 +347,7 @@ def test_plain_scan_query_to_pandas_blob_descriptions_flatten_uses_scanner(
 ):
    pytest.importorskip("lance")
    table = tmp_db.create_table(
-        "test_query_to_pandas_blob_desc_flatten",
+        "test_query_to_pandas_blob_desc_flatten", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    query = table.search().where("id = 1").select(["id", "blob"])
@@ -379,11 +365,7 @@ def test_plain_scan_query_to_pandas_blob_descriptions_flatten_uses_scanner(
 def test_plain_scan_query_to_pandas_scanner_state(tmp_db):
    pytest.importorskip("lance")
    data = _blob_query_data()
-    table = tmp_db.create_table(
+    table = tmp_db.create_table("test_query_to_pandas_scanner_state", data.slice(0, 2))
        "test_query_to_pandas_scanner_state",
        data.slice(0, 2),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    table.add(data.slice(2, 2))
    fragments = table.to_lance().get_fragments()
@@ -418,9 +400,7 @@ def test_plain_scan_query_to_pandas_scanner_state(tmp_db):
 async def test_async_plain_scan_query_to_pandas_blob_projection(tmp_db_async):
    pytest.importorskip("lance")
    table = await tmp_db_async.create_table(
-        "test_async_query_to_pandas_blob_projection",
+        "test_async_query_to_pandas_blob_projection", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    lazy_df = await (
@@ -472,9 +452,7 @@ async def test_async_plain_scan_query_to_pandas_blob_mode_does_not_collect_arrow
 ):
    pytest.importorskip("lance")
    table = await tmp_db_async.create_table(
-        "test_async_query_to_pandas_blob_no_arrow_collect",
+        "test_async_query_to_pandas_blob_no_arrow_collect", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    query = table.query().where("id = 1").select(["id", "blob"])
@@ -496,11 +474,7 @@ async def test_async_plain_scan_query_to_pandas_blob_mode_does_not_collect_arrow
 def test_vector_query_to_pandas_blob_mode_requires_native_path(tmp_db):
    pytest.importorskip("lance")
-    table = tmp_db.create_table(
+    table = tmp_db.create_table("test_vector_query_blob_mode", _blob_query_data())
        "test_vector_query_blob_mode",
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    with pytest.raises(RuntimeError, match="Lance native pandas conversion"):
        table.search([1.0, 0.0]).select(["blob", "vector"]).limit(1).to_pandas(
@@ -511,9 +485,7 @@ def test_vector_query_to_pandas_blob_mode_requires_native_path(tmp_db):
 def test_vector_query_to_pandas_blob_descriptions_requires_plain_scan(tmp_db):
    pytest.importorskip("lance")
    table = tmp_db.create_table(
-        "test_vector_query_blob_descriptions",
+        "test_vector_query_blob_descriptions", _blob_query_data()
        _blob_query_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    with pytest.raises(RuntimeError, match="plain scan query"):
@@ -834,7 +834,7 @@ def test_table_create_indices():
        vector_req = received_requests[2]
        assert "name" in vector_req
        assert vector_req["name"] == "custom_vector_idx"
-        assert "replace" not in vector_req
+        assert vector_req["replace"] is False
        table.wait_for_index(["custom_scalar_idx"], timedelta(seconds=2))
        table.wait_for_index(
@@ -2467,7 +2467,7 @@ def test_remote_blob_byte_apis_not_supported_on_old_server():
 def test_remote_connection_jobs_surface():
-    from lancedb.exceptions import JobFailedError, JobNotFoundError
+    from lancedb.exceptions import JobFailedError
    schema = pa.schema([("state", pa.string())])
    batch = pa.record_batch([pa.array(["created", "done"])], schema=schema)
@@ -2475,7 +2475,6 @@ def test_remote_connection_jobs_surface():
    with pa.ipc.new_stream(sink, schema) as writer:
        writer.write_batch(batch)
    events_body = sink.getvalue().to_pybytes()
    query_events_payloads = []
    def handler(request):
        content_len = int(request.headers.get("Content-Length", 0))
@@ -2513,22 +2512,6 @@ def test_remote_connection_jobs_surface():
            request.end_headers()
            request.wfile.write(json.dumps(rsp).encode())
        elif request.path == "/v1/jobs/describe":
            if payload["job_id"] == "job-2":
                request.send_response(200)
                request.send_header("Content-Type", "application/json")
                request.end_headers()
                request.wfile.write(
                    json.dumps(
                        dict(
                            job_id="job-2",
                            job_type="refresh_column",
                            job_state="DONE",
                            creation_ms=2000,
                            result=dict(rows_assigned=1000000, rows_failed=0),
                        )
                    ).encode()
                )
                return
            if payload["job_id"] != "job-1":
                request.send_response(404)
                request.end_headers()
@@ -2560,7 +2543,7 @@ def test_remote_connection_jobs_surface():
            request.end_headers()
            request.wfile.write(b'{"job_id": "job-1"}')
        elif request.path == "/v1/jobs/query_events":
-            query_events_payloads.append(payload)
+            assert payload["job_id"] == "job-1"
            request.send_response(200)
            request.send_header("Content-Type", "application/vnd.apache.arrow.stream")
            request.end_headers()
@@ -2576,109 +2559,24 @@ def test_remote_connection_jobs_surface():
        assert jobs[0].table == "t1"
        assert jobs[1].state == "finished"
        description = db.get_job("job-1")
        assert description.job_type == "create_index"
        assert description.state == "failed"
        assert json.loads(description.spec_json) == {"column": "vec"}
        assert description.failure.message == "worker died"
        assert description.failure.retryable is True
        assert db.get_job("missing") is None
        assert db.cancel_job("job-1") is True
        assert db.cancel_job("missing") is False
-        # Opening a job hands back a populated handle; a missing one fails.
+        batches = db.job_history("job-1")
-        with pytest.raises(JobNotFoundError, match="missing"):
+        assert len(batches) == 1
-            db.open_job("missing")
+        assert batches[0].num_rows == 2
-        finished = db.open_job("job-2")
+        assert batches[0].column("state").to_pylist() == ["created", "done"]
        assert finished.state == "finished"
        assert finished.result == {"rows_assigned": 1000000, "rows_failed": 0}
-        job = db.open_job("job-1")
+        job = db.job("job-1")
        assert job.id == "job-1"
        # Opening already populated the handle.
        assert job.state == "failed"
        assert job.spec == {"column": "vec"}
        assert job.failure.message == "worker died"
        assert job.status() == "failed"
        with pytest.raises(JobFailedError, match="worker died"):
            job.wait(timeout=timedelta(seconds=5))
 def test_remote_job_handle_reports_its_own_detail():
    schema = pa.schema([("state", pa.string())])
    batch = pa.record_batch([pa.array(["claim_complete"])], schema=schema)
    sink = pa.BufferOutputStream()
    with pa.ipc.new_stream(sink, schema) as writer:
        writer.write_batch(batch)
    events_body = sink.getvalue().to_pybytes()
    event_payloads = []
    def handler(request):
        content_len = int(request.headers.get("Content-Length", 0))
        body = request.rfile.read(content_len) if content_len > 0 else b""
        payload = json.loads(body) if body else {}
        if request.path == "/v1/jobs/describe":
            request.send_response(200)
            request.send_header("Content-Type", "application/json")
            request.end_headers()
            request.wfile.write(
                json.dumps(
                    dict(
                        job_id="job-1",
                        job_type="refresh_column",
                        job_state="DONE",
                        creation_ms=2000,
                        spec=dict(column="vec"),
                        result=dict(rows_assigned=1000000),
                    )
                ).encode()
            )
        elif request.path == "/v1/jobs/query_events":
            event_payloads.append(payload)
            request.send_response(200)
            request.send_header("Content-Type", "application/vnd.apache.arrow.stream")
            request.end_headers()
            request.wfile.write(events_body)
        else:
            request.send_response(404)
            request.end_headers()
    with mock_lancedb_connection(handler) as db:
        job = db.open_job("job-1")
        # Opening populates the handle in the same round trip.
        assert job.state == "finished"
        job.refresh()
        assert job.job_type == "refresh_column"
        assert job.creation_ms == 2000
        assert job.spec == {"column": "vec"}
        assert job.result == {"rows_assigned": 1000000}
        assert job.failure is None
        # The JSON payloads stay reachable, but as internal APIs.
        assert json.loads(job._spec_json) == {"column": "vec"}
        assert json.loads(job._result_json) == {"rows_assigned": 1000000}
        # print() shows everything the handle knows and nothing it does not.
        # print() lays every known field out on its own line, with the JSON
        # payloads indented rather than crammed onto one line.
        assert repr(job) == "\n".join(
            [
                "Job(",
                "    id='job-1',",
                "    state='finished',",
                "    job_type='refresh_column',",
                "    creation_ms=2000,",
                "    spec={",
                '        "column": "vec"',
                "    },",
                "    result={",
                '        "rows_assigned": 1000000',
                "    },",
                ")",
            ]
        )
        # Nothing it does not know shows up.
        assert "failure" not in repr(job)
        events = job.events(filter="state = 'claim_complete'", limit=500)
        assert isinstance(events, pa.Table)
        assert events.column("state").to_pylist() == ["claim_complete"]
        # The handle supplies job_id; the caller only narrows the query.
        assert event_payloads[-1] == {
            "job_id": "job-1",
            "limit": 500,
            "filter": "state = 'claim_complete'",
        }
@@ -81,7 +81,7 @@ def get_test_table(tmp_path):
        "but his son was mortal",
        "there hasn't been a good battlefield game since 2142",
        "I wish they would make another one",
-        "campaigns are not as good as they used to be",
+        "campains are not as good as they used to be",
        "Multiplayer and open world games have destroyed the single player experience",
        "Maybe the future is console games",
        "I don't know",
@@ -1,162 +0,0 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 from uuid import UUID
 import pytest
 import pyarrow as pa
 import lancedb
 from lancedb import _lancedb
 from lancedb.arrow import AsyncRecordBatchReader
 from lancedb.db import AsyncConnection
 from lancedb.remote.db import RemoteDBConnection
 from lancedb.sql import AsyncQuery, Query
 NIL_QUERY_ID = UUID(int=0)
 class FakeNativeQuery:
    id = UUID("0198f1b2-c3d4-7e5f-8123-456789abcdef")
    async def reader(self):
        return pa.table({"value": [1, 2]})
 class FakeNativeConnection:
    async def execute_query_async(self, query, *, default_namespace_path=None):
        return FakeNativeQuery()
 class FakeAsyncConnection:
    async def execute_query_async(self, query, *, default_namespace_path=None):
        return AsyncQuery(FakeNativeQuery())
 def remote_connection(sql_host_override=None):
    return lancedb.connect(
        "db://analytics",
        api_key="test-key",
        host_override="http://localhost:10024",
        sql_host_override=sql_host_override,
    )
 def test_sql_is_connection_scoped():
    assert hasattr(lancedb, "sql")
    assert not callable(lancedb.sql)
    assert not hasattr(_lancedb, "sql")
    assert not hasattr(remote_connection(), "sql")
    assert hasattr(remote_connection(), "execute_query")
    assert hasattr(remote_connection(), "execute_query_async")
    assert hasattr(remote_connection(), "describe_query")
 def test_query_id_is_uuid():
    query = AsyncQuery(FakeNativeQuery())
    assert isinstance(query.id, UUID)
    assert Query(query).id == query.id
 def test_connection_serializes_sql_host_override():
    endpoint = "grpc+tls://sql.example.com:10026"
    restored = lancedb.deserialize_conn(
        remote_connection(sql_host_override=endpoint).serialize()
    )
    assert restored.sql_host_override == endpoint
@pytest.mark.asyncio
 async def test_async_sql_reader_is_record_batch_stream():
    reader = await AsyncQuery(FakeNativeQuery()).reader()
    assert isinstance(reader, AsyncRecordBatchReader)
    assert (await reader.read_all())[0].column(0).to_pylist() == [1, 2]
 def test_sync_sql_reader_is_record_batch_reader():
    reader = Query(AsyncQuery(FakeNativeQuery())).reader()
    assert isinstance(reader, pa.RecordBatchReader)
    assert reader.read_all().column(0).to_pylist() == [1, 2]
 def test_execute_query_returns_blocking_reader():
    connection = RemoteDBConnection.__new__(RemoteDBConnection)
    connection._conn = FakeAsyncConnection()
    reader = connection.execute_query("SELECT 1")
    assert isinstance(reader, pa.RecordBatchReader)
    assert reader.read_all().column(0).to_pylist() == [1, 2]
@pytest.mark.asyncio
 async def test_async_execute_query_returns_async_reader():
    connection = AsyncConnection(FakeNativeConnection())
    reader = await connection.execute_query("SELECT 1")
    assert isinstance(reader, AsyncRecordBatchReader)
    assert (await reader.read_all())[0].column(0).to_pylist() == [1, 2]
 def test_local_connection_rejects_sql(tmp_path):
    connection = lancedb.connect(tmp_path)
    with pytest.raises(NotImplementedError, match="SQL"):
        connection.execute_query("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        connection.execute_query_async("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        connection.describe_query(NIL_QUERY_ID)
@pytest.mark.asyncio
 async def test_local_async_connection_rejects_sql(tmp_path):
    connection = await lancedb.connect_async(tmp_path)
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.execute_query("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.execute_query_async("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.describe_query(NIL_QUERY_ID)
@pytest.mark.asyncio
 async def test_async_namespace_connection_rejects_sql(tmp_path):
    connection = lancedb.connect_namespace_async("dir", {"root": str(tmp_path)})
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.execute_query("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.execute_query_async("SELECT 1")
    with pytest.raises(NotImplementedError, match="SQL"):
        await connection.describe_query(NIL_QUERY_ID)
 def test_describe_query_requires_uuid():
    with pytest.raises(TypeError, match="UUID"):
        remote_connection().describe_query(str(NIL_QUERY_ID))
@pytest.mark.parametrize(
    "default_namespace_path",
    ["public", ("public",), [1]],
 )
 def test_execute_query_async_requires_namespace_path_list(default_namespace_path):
    with pytest.raises(ValueError, match="default_namespace_path"):
        remote_connection().execute_query_async(
            "SELECT 1", default_namespace_path=default_namespace_path
        )
 def test_execute_query_async_rejects_invalid_endpoint():
    connection = remote_connection(sql_host_override="invalid://localhost")
    with pytest.raises(ValueError, match="sql_host_override"):
        connection.execute_query_async("SELECT 1")
@pytest.mark.parametrize(
    "default_namespace_path",
    [[""], ["café"], ["pub\tlic"], ["events$raw"]],
 )
 def test_execute_query_async_rejects_invalid_namespace_components(
    default_namespace_path,
 ):
    with pytest.raises(ValueError, match="default_namespace_path"):
        remote_connection().execute_query_async(
            "SELECT 1", default_namespace_path=default_namespace_path
        )
@@ -64,23 +64,15 @@ async def _blob_v2_table_async(db: AsyncConnection, name: str):
    return table
 # Legacy v1 blob columns are only writable at file version <= 2.1.
 LEGACY_BLOB_STORAGE_OPTIONS = {"new_table_data_storage_version": "2.1"}
 def _blob_table(db: DBConnection, name: str, blob_schema: str):
    if blob_schema == "v1":
-        return db.create_table(
+        return db.create_table(name, data=_blob_test_data())
            name, data=_blob_test_data(), storage_options=LEGACY_BLOB_STORAGE_OPTIONS
        )
    return _blob_v2_table(db, name)
 async def _blob_table_async(db: AsyncConnection, name: str, blob_schema: str):
    if blob_schema == "v1":
-        return await db.create_table(
+        return await db.create_table(name, data=_blob_test_data())
            name, data=_blob_test_data(), storage_options=LEGACY_BLOB_STORAGE_OPTIONS
        )
    return await _blob_v2_table_async(db, name)
@@ -155,11 +147,7 @@ def test_table_to_pandas_invalid_blob_mode_non_blob_table(tmp_db: DBConnection):
@pytest.mark.parametrize("blob_mode", ["lazy", "bytes", "descriptions"])
 def test_table_to_pandas_blob_modes(tmp_db: DBConnection, blob_mode):
    pytest.importorskip("lance")
-    table = tmp_db.create_table(
+    table = tmp_db.create_table(f"test_to_pandas_blob_{blob_mode}", _blob_test_data())
        f"test_to_pandas_blob_{blob_mode}",
        _blob_test_data(),
        storage_options=LEGACY_BLOB_STORAGE_OPTIONS,
    )
    df = table.to_pandas(blob_mode=blob_mode)
@@ -1612,7 +1600,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
    )
    mock_create_index.assert_called_with(
        "my_vector",
-        replace=True,
+        replace=False,
        config=expected_config,
        wait_timeout=None,
        name=None,
@@ -1632,7 +1620,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
    )
    mock_create_index.assert_called_with(
        "my_vector",
-        replace=True,
+        replace=False,
        config=expected_config,
        wait_timeout=None,
        name=None,
@@ -1658,7 +1646,7 @@ def test_create_index_name_and_train_parameters(
    expected_config = IvfPq()  # Default config
    mock_create_index.assert_called_with(
        "vector",
-        replace=True,
+        replace=False,
        config=expected_config,
        wait_timeout=None,
        name="my_custom_index",
@@ -1669,7 +1657,7 @@ def test_create_index_name_and_train_parameters(
    table.create_index(vector_column_name="vector", train=False)
    mock_create_index.assert_called_with(
        "vector",
-        replace=True,
+        replace=False,
        config=expected_config,
        wait_timeout=None,
        name=None,
@@ -1680,7 +1668,7 @@ def test_create_index_name_and_train_parameters(
    table.create_index(vector_column_name="vector", name="my_index_name", train=True)
    mock_create_index.assert_called_with(
        "vector",
-        replace=True,
+        replace=False,
        config=expected_config,
        wait_timeout=None,
        name="my_index_name",
@@ -1717,7 +1705,7 @@ def test_create_index_new_api(mock_create_index, mem_db: DBConnection):
        table.create_index("vector", config=IvfPq(distance_type="l2"))
    mock_create_index.assert_called_with(
        "vector",
-        replace=True,
+        replace=False,
        config=IvfPq(distance_type="l2"),
        wait_timeout=None,
        name=None,
@@ -1728,7 +1716,7 @@ def test_create_index_new_api(mock_create_index, mem_db: DBConnection):
    table.create_index("category", config=BTree())
    mock_create_index.assert_called_with(
        "category",
-        replace=True,
+        replace=False,
        config=BTree(),
        wait_timeout=None,
        name=None,
@@ -1739,7 +1727,7 @@ def test_create_index_new_api(mock_create_index, mem_db: DBConnection):
    table.create_index("text", config=FTS(with_position=True))
    mock_create_index.assert_called_with(
        "text",
-        replace=True,
+        replace=False,
        config=FTS(with_position=True),
        wait_timeout=None,
        name=None,
@@ -3354,7 +3342,7 @@ def test_empty_query(mem_db: DBConnection):
    # None is the same as default
    df = table.search().select(["id"]).limit(None).to_arrow()
    assert df.num_rows == 100
-    # invalid limist is the same as None, which is the same as default
+    # invalid limist is the same as None, wihch is the same as default
    df = table.search().select(["id"]).limit(-1).to_arrow()
    assert df.num_rows == 100
    # valid limit should work
@@ -3971,7 +3959,7 @@ def test_stats(mem_db: DBConnection):
    print(f"{stats=}")
    assert stats == {
        # Full on-disk size of the data file, footer and metadata included.
-        "total_bytes": 637,
+        "total_bytes": 633,
        "num_rows": 2,
        "num_indices": 0,
        "fragment_stats": {
@@ -13,7 +13,11 @@ use crate::{
    runtime::future_into_py,
    table::Table,
 };
-use arrow::{datatypes::Schema, ffi_stream::ArrowArrayStreamReader, pyarrow::FromPyArrow};
+use arrow::{
    datatypes::Schema,
    ffi_stream::ArrowArrayStreamReader,
    pyarrow::{FromPyArrow, ToPyArrow},
 };
 use lancedb::{
    connection::Connection as LanceConnection,
    connection::NamespaceClientPushdownOperation,
@@ -24,7 +28,7 @@ use pyo3::{
    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
    exceptions::{PyRuntimeError, PyValueError},
    pyclass, pyfunction, pymethods,
-    types::{PyAnyMethods, PyDict, PyDictMethods, PyList},
+    types::{PyDict, PyDictMethods, PyList, PyListMethods},
 };
 #[pyclass]
@@ -82,24 +86,6 @@ impl Connection {
    }
 }
 fn parse_default_namespace_path(path: Option<Bound<'_, PyAny>>) -> PyResult<Vec<String>> {
    match path {
        Some(path) => {
            if !path.is_instance_of::<PyList>() {
                return Err(PyValueError::new_err(
                    "Connection.execute_query_async default_namespace_path must be a list",
                ));
            }
            path.extract::<Vec<String>>().map_err(|_| {
                PyValueError::new_err(
                    "Connection.execute_query_async default_namespace_path components must be strings",
                )
            })
        }
        None => Ok(vec!["public".to_string()]),
    }
 }
 #[pymethods]
 impl Connection {
    fn __repr__(&self) -> String {
@@ -122,40 +108,6 @@ impl Connection {
        self.get_inner().map(|inner| inner.uri().to_string())
    }
    #[pyo3(signature = (query, *, default_namespace_path=None))]
    pub fn execute_query_async<'a>(
        self_: PyRef<'a, Self>,
        query: String,
        default_namespace_path: Option<Bound<'_, PyAny>>,
    ) -> PyResult<Bound<'a, PyAny>> {
        let inner = self_.get_inner()?.clone();
        let default_namespace_path = parse_default_namespace_path(default_namespace_path)?;
        future_into_py(self_.py(), async move {
            let operation = inner
                .execute_query_async(query)
                .default_namespace_path(default_namespace_path);
            operation
                .execute()
                .await
                .map(crate::sql::Query::new)
                .infer_error()
        })
    }
    pub fn describe_query<'a>(
        self_: PyRef<'a, Self>,
        query_id: uuid::Uuid,
    ) -> PyResult<Bound<'a, PyAny>> {
        let inner = self_.get_inner()?.clone();
        future_into_py(self_.py(), async move {
            inner
                .describe_query(query_id)
                .await
                .map(crate::sql::QueryDescription::from)
                .infer_error()
        })
    }
    #[pyo3(signature = ())]
    pub fn get_read_consistency_interval(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.get_inner()?.clone();
@@ -640,12 +592,9 @@ impl Connection {
        })
    }
-    pub fn open_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
+    pub fn job(&self, job_id: String) -> PyResult<crate::job::Job> {
-        let inner = self_.get_inner()?.clone();
+        let inner = self.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
+        Ok(crate::job::Job::new(inner.job(job_id).infer_error()?))
            let job = inner.open_job(&job_id).await.infer_error()?;
            Ok(crate::job::Job::new(job))
        })
    }
    pub fn create_function_async(
@@ -715,16 +664,42 @@ impl Connection {
        })
    }
    pub fn get_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.get_inner()?.clone();
        future_into_py(self_.py(), async move {
            let description = inner.get_job(&job_id).await.infer_error()?;
            Ok(description.map(crate::job::JobDescription::from))
        })
    }
    pub fn cancel_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.get_inner()?.clone();
        future_into_py(self_.py(), async move {
            inner.cancel_job(&job_id).await.infer_error()
        })
    }
    #[pyo3(signature = (job_id=None))]
    pub fn job_history(
        self_: PyRef<'_, Self>,
        job_id: Option<String>,
    ) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.get_inner()?.clone();
        future_into_py(self_.py(), async move {
            let batches = inner.job_history(job_id.as_deref()).await.infer_error()?;
            Python::attach(|py| {
                let list = PyList::empty(py);
                for batch in batches {
                    list.append(batch.to_pyarrow(py)?)?;
                }
                Ok(list.unbind())
            })
        })
    }
 }
 #[pyfunction]
-#[pyo3(signature = (uri, api_key=None, region=None, host_override=None, sql_host_override=None, read_consistency_interval=None, client_config=None, storage_options=None, session=None, manifest_enabled=false, namespace_client_properties=None, oauth_config=None))]
+#[pyo3(signature = (uri, api_key=None, region=None, host_override=None, read_consistency_interval=None, client_config=None, storage_options=None, session=None, manifest_enabled=false, namespace_client_properties=None, oauth_config=None))]
 #[allow(clippy::too_many_arguments)]
 pub fn connect(
    py: Python<'_>,
@@ -732,7 +707,6 @@ pub fn connect(
    api_key: Option<String>,
    region: Option<String>,
    host_override: Option<String>,
    sql_host_override: Option<String>,
    read_consistency_interval: Option<f64>,
    client_config: Option<PyClientConfig>,
    storage_options: Option<HashMap<String, String>>,
@@ -752,12 +726,6 @@ pub fn connect(
        if let Some(host_override) = host_override {
            builder = builder.host_override(&host_override);
        }
        #[cfg(feature = "remote")]
        if let Some(sql_host_override) = sql_host_override {
            builder = builder.sql_host_override(&sql_host_override);
        }
        #[cfg(not(feature = "remote"))]
        let _ = sql_host_override;
        if let Some(read_consistency_interval) = read_consistency_interval {
            let read_consistency_interval = Duration::from_secs_f64(read_consistency_interval);
            builder = builder.read_consistency_interval(read_consistency_interval);
@@ -114,12 +114,6 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
                        .getattr(intern!(py, "JobCancelledError"))?;
                    Err(PyErr::from_value(cls.call1((err.to_string(),))?))
                }),
                LanceError::JobNotFound { .. } => Python::attach(|py| {
                    let cls = py
                        .import(intern!(py, "lancedb.exceptions"))?
                        .getattr(intern!(py, "JobNotFoundError"))?;
                    Err(PyErr::from_value(cls.call1((err.to_string(),))?))
                }),
                _ => self.runtime_error(),
            },
        }
@@ -4,50 +4,11 @@
 use std::sync::Arc;
 use crate::runtime::future_into_py;
-use arrow::{
+use pyo3::{Bound, PyAny, PyRef, PyResult, pyclass, pymethods};
    datatypes::Schema,
    pyarrow::{IntoPyArrow, Table as PyArrowTable},
 };
 use lancedb::job::JobEventsRequest;
 use pyo3::{
    Bound, PyAny, PyRef, PyResult, Python,
    exceptions::PyValueError,
    pyclass, pymethods,
    types::{PyAnyMethods, PyDict, PyDictMethods},
 };
 use serde::Serialize;
 use crate::error::PythonErrorExt;
 const REPR_INDENT: &str = "    ";
 /// Parse a stored JSON payload into Python data. The bindings carry these as
 /// strings because that is what crosses the boundary cheaply; the public
 /// Python surface is the parsed form.
 fn parse_json_payload<'py>(
    py: Python<'py>,
    raw: Option<&str>,
 ) -> PyResult<Option<Bound<'py, PyAny>>> {
    match raw {
        None => Ok(None),
        Some(raw) => Ok(Some(py.import("json")?.call_method1("loads", (raw,))?)),
    }
 }
 /// A payload rendered as indented JSON, aligned under the field that holds it.
 fn pretty_json_payload(py: Python<'_>, raw: Option<&str>) -> PyResult<Option<String>> {
    let Some(parsed) = parse_json_payload(py, raw)? else {
        return Ok(None);
    };
    let kwargs = PyDict::new(py);
    kwargs.set_item("indent", 4)?;
    let rendered: String = py
        .import("json")?
        .call_method("dumps", (parsed,), Some(&kwargs))?
        .extract()?;
    Ok(Some(rendered.replace('\n', &format!("\n{REPR_INDENT}"))))
 }
 #[pyclass]
 pub struct Job {
    inner: Arc<lancedb::Job<std::result::Result<Option<String>, String>>>,
@@ -106,48 +67,6 @@ impl Job {
            Ok(())
        })
    }
    pub fn refresh(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            inner.refresh().await.infer_error()?;
            Ok(())
        })
    }
    /// The last observed lifecycle state, without contacting the backend.
    #[getter]
    pub fn _state(&self) -> Option<String> {
        self.inner.state()
    }
    /// The last observed server-side record. `None` for an in-process job.
    #[getter]
    pub fn _description(&self) -> Option<JobDescription> {
        self.inner.description().map(JobDescription::from)
    }
    #[pyo3(signature = (*, limit=None, filter=None))]
    pub fn events(
        self_: PyRef<'_, Self>,
        limit: Option<u32>,
        filter: Option<String>,
    ) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner.clone();
        let request = JobEventsRequest { limit, filter };
        future_into_py(self_.py(), async move {
            let batches = inner.events(request).await.infer_error()?;
            Python::attach(|py| {
                let schema = batches
                    .first()
                    .map(|batch| batch.schema())
                    .unwrap_or_else(|| Arc::new(Schema::empty()));
                let table = PyArrowTable::try_new(batches, schema)
                    .map_err(|err| PyValueError::new_err(err.to_string()))?;
                table.into_pyarrow(py).map(|table| table.unbind())
            })
        })
    }
 }
 /// A row from `Connection.list_jobs`: one server-side job.
@@ -202,7 +121,7 @@ impl JobFailureInfo {
    }
 }
-/// The server-side record behind a `Job` handle.
+/// A described job from `Connection.get_job`.
 #[pyclass(get_all, skip_from_py_object)]
 #[derive(Clone)]
 pub struct JobDescription {
@@ -210,49 +129,17 @@ pub struct JobDescription {
    job_type: String,
    state: String,
    creation_ms: i64,
-    /// Internal: the wire form behind the `spec` property.
+    spec_json: Option<String>,
    _spec_json: Option<String>,
    /// Internal: the wire form behind the `result` property.
    _result_json: Option<String>,
    failure: Option<JobFailureInfo>,
 }
 #[pymethods]
 impl JobDescription {
-    /// The job-type-specific specification it was submitted with.
+    fn __repr__(&self) -> String {
-    #[getter]
+        format!(
-    fn spec<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
+            "JobDescription(job_id={:?}, job_type={:?}, state={:?}, creation_ms={})",
-        parse_json_payload(py, self._spec_json.as_deref())
+            self.job_id, self.job_type, self.state, self.creation_ms
-    }
+        )
    /// The job-type-specific terminal result. `None` until the job succeeds.
    #[getter]
    fn result<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
        parse_json_payload(py, self._result_json.as_deref())
    }
    fn __repr__(&self, py: Python<'_>) -> PyResult<String> {
        let mut fields = vec![
            format!("job_id={:?}", self.job_id),
            format!("job_type={:?}", self.job_type),
            format!("state={:?}", self.state),
            format!("creation_ms={}", self.creation_ms),
        ];
        // Lay the payloads out as indented JSON, the same way the `Job` repr
        // does, so the two agree on how the same data looks.
        for (name, payload) in [("spec", &self._spec_json), ("result", &self._result_json)] {
            if let Some(rendered) = pretty_json_payload(py, payload.as_deref())? {
                fields.push(format!("{name}={rendered}"));
            }
        }
        if let Some(failure) = &self.failure {
            fields.push(format!("failure={}", failure.__repr__()));
        }
        let body = fields
            .iter()
            .map(|field| format!("\n{REPR_INDENT}{field},"))
            .collect::<String>();
        Ok(format!("JobDescription({body}\n)"))
    }
 }
@@ -263,11 +150,7 @@ impl From<lancedb::database::JobDescription> for JobDescription {
            job_type: description.job_type,
            state: description.state,
            creation_ms: description.creation_ms,
-            _spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
+            spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
            _result_json: description
                .result
                .filter(|result| !result.is_null())
                .map(|result| result.to_string()),
            failure: description.failure.map(|failure| JobFailureInfo {
                phase: failure.phase,
                message: failure.message,
@@ -34,7 +34,6 @@ pub mod permutation;
 pub mod query;
 pub mod runtime;
 pub mod session;
 pub mod sql;
 pub mod table;
 pub mod util;
@@ -51,8 +50,6 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<crate::job::JobInfo>()?;
    m.add_class::<crate::job::JobDescription>()?;
    m.add_class::<crate::job::JobFailureInfo>()?;
    m.add_class::<crate::sql::Query>()?;
    m.add_class::<crate::sql::QueryDescription>()?;
    m.add_class::<PyBlobFile>()?;
    m.add_class::<IndexConfig>()?;
    m.add_class::<Query>()?;
@@ -334,7 +334,7 @@ pub struct PyQueryRequest {
    pub column: Option<String>,
    pub query_vector: Option<PyQueryVectors>,
    pub minimum_nprobes: Option<usize>,
-    // None means user did not set it and default should be used (currently 20)
+    // None means user did not set it and default shoud be used (currenty 20)
    // Some(0) means user set it to None and there is no limit
    pub maximum_nprobes: Option<usize>,
    pub lower_bound: Option<f32>,
@@ -1,90 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 use std::sync::Arc;
 use chrono::{DateTime, Utc};
 use pyo3::{Bound, PyAny, PyRef, PyResult, pyclass, pymethods};
 use uuid::Uuid;
 use crate::arrow::RecordBatchStream;
 use crate::error::PythonErrorExt;
 use crate::runtime::future_into_py;
 #[pyclass(name = "SqlQuery")]
 pub struct Query {
    inner: Arc<lancedb::sql::Query>,
 }
 impl Query {
    pub(crate) fn new(inner: lancedb::sql::Query) -> Self {
        Self {
            inner: Arc::new(inner),
        }
    }
 }
 #[pymethods]
 impl Query {
    #[getter]
    pub fn id(&self) -> Uuid {
        self.inner.id()
    }
    pub fn describe(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            inner
                .describe()
                .await
                .map(QueryDescription::from)
                .infer_error()
        })
    }
    pub fn reader(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            let stream = inner.reader().await.infer_error()?;
            Ok(RecordBatchStream::new(stream))
        })
    }
    pub fn cancel(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            inner.cancel().await.infer_error()?;
            Ok(())
        })
    }
 }
 #[pyclass(get_all, skip_from_py_object)]
 #[derive(Clone)]
 pub struct QueryDescription {
    id: Uuid,
    status: String,
    progress: Option<f64>,
    expires_at: Option<DateTime<Utc>>,
 }
 #[pymethods]
 impl QueryDescription {
    fn __repr__(&self) -> String {
        format!(
            "QueryDescription(id={:?}, status={:?}, progress={:?}, expires_at={:?})",
            self.id, self.status, self.progress, self.expires_at
        )
    }
 }
 impl From<lancedb::sql::QueryDescription> for QueryDescription {
    fn from(description: lancedb::sql::QueryDescription) -> Self {
        Self {
            id: description.id,
            status: description.status.to_string(),
            progress: description.progress,
            expires_at: description.expires_at,
        }
    }
 }
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.39.0-beta.6"
+version = "0.39.0-beta.1"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -21,8 +21,6 @@ arrow-select = { workspace = true }
 arrow-ord = { workspace = true }
 arrow-cast = { workspace = true }
 arrow-ipc.workspace = true
 arrow-flight = { workspace = true, optional = true }
 prost = { version = "0.14", optional = true }
 chrono = { workspace = true }
 datafusion-catalog.workspace = true
 datafusion-common.workspace = true
@@ -79,7 +77,6 @@ reqwest = { version = "0.12.0", default-features = false, features = [
    "rustls-tls-native-roots",
    "stream",
 ], optional = true }
 tonic = { workspace = true, optional = true }
 http = { version = "1", optional = true } # Matching what is in reqwest
 urlencoding = { version = "2", optional = true }
 uuid = { workspace = true, features = ["v5"] }
@@ -148,11 +145,8 @@ huggingface = [
 ]
 dynamodb = ["lance/dynamodb", "aws"]
 remote = [
    "dep:arrow-flight",
    "dep:prost",
    "dep:reqwest",
    "dep:http",
    "dep:tonic",
    "dep:urlencoding",
    "lance-namespace-impls/rest",
    "lance-namespace-impls/rest-adapter",
@@ -163,7 +163,7 @@ pub struct PolarsDataFrameRecordBatchReader {
 impl PolarsDataFrameRecordBatchReader {
    /// Creates a new `PolarsDataFrameRecordBatchReader` from a given Polars DataFrame.
    /// If the input dataframe does not have aligned chunks, this function undergoes
-    /// the costly operation of reallocating each series as a single contiguous chunk.
+    /// the costly operation of reallocating each series as a single contigous chunk.
    pub fn new(mut df: DataFrame) -> Result<Self> {
        df.align_chunks();
        let arrow_schema =
@@ -7,9 +7,7 @@
 //! raw `Binary` / `LargeBinary` into the blob struct layout. Queries return
 //! small descriptors, not bytes.
 //!
-//! Blob tables require Lance file format >= 2.2. `_rowid` values stay valid
+//! Blob tables require Lance file format >= 2.2 and stable row ids at create.
 //! after compaction when the table has stable row ids. Overwrite is a new
 //! create and does not keep the previous table's stable row id setting.
 use std::ops::Range;
 use std::sync::Arc;
@@ -326,7 +324,6 @@ pub(crate) fn blob_column_names(schema: &Schema) -> Vec<String> {
 }
 /// Bumps storage format to at least [`LanceFileVersion::V2_2`] for blob schemas.
 /// Leaves `enable_stable_row_ids` unchanged.
 pub(crate) fn ensure_blob_storage_version(schema: &Schema, params: &mut WriteParams) {
    if !has_blob_columns(schema) {
        return;
@@ -388,30 +385,6 @@ fn ensure_all_row_ids_resolved(column: &str, requested: usize, resolved: usize)
    }
 }
 /// Lance take reports a missing physical row address as NotSupported or InvalidInput.
 fn map_blob_take_error(column: &str, requested: usize, err: lance::Error) -> Error {
    let missing_row_addr = match &err {
        lance::Error::NotSupported { source, .. } => {
            source.to_string().contains("must not target deleted rows")
        }
        lance::Error::InvalidInput { source, .. } => source
            .to_string()
            .contains("belongs to non-existent fragment"),
        _ => false,
    };
    if missing_row_addr {
        Error::InvalidInput {
            message: format!(
                "blob read for column '{column}' requested {requested} row ids but some \
                 do not exist in the table; pass row ids collected from this table"
            ),
        }
    } else {
        err.into()
    }
 }
 /// Materialize blob-local ranges (same length and order as `requests`, nulls preserved).
 pub(crate) async fn take_blob_ranges_aligned(
    dataset: &Arc<Dataset>,
@@ -432,8 +405,7 @@ pub(crate) async fn take_blob_ranges_aligned(
        .with_row_ids(lance_requests)
        .preserve_order(true)
        .execute()
-        .await
+        .await?;
        .map_err(|err| map_blob_take_error(column, requests.len(), err))?;
    ensure_all_row_ids_resolved(column, requests.len(), payloads.len())?;
    let mut builder = LargeBinaryBuilder::new();
@@ -462,8 +434,7 @@ pub(crate) async fn take_blobs_aligned(
        .with_row_ids(row_ids.to_vec())
        .preserve_order(true)
        .execute()
-        .await
+        .await?;
        .map_err(|err| map_blob_take_error(column, row_ids.len(), err))?;
    ensure_all_row_ids_resolved(column, row_ids.len(), payloads.len())?;
    let mut builder = LargeBinaryBuilder::new();
@@ -487,10 +458,7 @@ pub(crate) async fn take_blob_files_aligned(
        return Ok(Vec::new());
    }
-    let handles = dataset
+    let handles = dataset.take_blobs(row_ids, column).await?;
        .take_blobs(row_ids, column)
        .await
        .map_err(|err| map_blob_take_error(column, row_ids.len(), err))?;
    ensure_all_row_ids_resolved(column, row_ids.len(), handles.len())?;
    Ok(handles
        .into_iter()
@@ -532,27 +500,10 @@ mod tests {
    fn storage_version_bumps_to_v2_2() {
        let mut params = WriteParams::default();
        ensure_blob_storage_version(&blob_schema(), &mut params);
-        let resolved = params
+        assert_eq!(
-            .data_storage_version
+            params.data_storage_version.unwrap().resolve(),
-            .unwrap_or(LanceFileVersion::Stable)
+            ConcreteFileVersion::V2_2
-            .resolve();
+        );
        assert_eq!(resolved, ConcreteFileVersion::V2_2);
        assert!(!params.enable_stable_row_ids);
    }
    #[test]
    fn storage_version_leaves_stable_row_ids_enabled() {
        let mut params = WriteParams {
            enable_stable_row_ids: true,
            ..Default::default()
        };
        ensure_blob_storage_version(&blob_schema(), &mut params);
        assert!(params.enable_stable_row_ids);
        let resolved = params
            .data_storage_version
            .unwrap_or(LanceFileVersion::Stable)
            .resolve();
        assert_eq!(resolved, ConcreteFileVersion::V2_2);
    }
    #[test]
@@ -625,6 +576,5 @@ mod tests {
        let mut params = WriteParams::default();
        ensure_blob_storage_version(&schema, &mut params);
        assert!(params.data_storage_version.is_none());
        assert!(!params.enable_stable_row_ids);
    }
 }
@@ -23,18 +23,15 @@ use crate::connection::create_table::CreateTableBuilder;
 use crate::data::scannable::Scannable;
 use crate::database::listing::ListingDatabase;
 use crate::database::{
-    CloneTableRequest, Database, DatabaseOptions, JobInfo, OpenTableRequest, ReadConsistency,
+    CloneTableRequest, Database, DatabaseOptions, JobDescription, JobInfo, OpenTableRequest,
-    TableNamesRequest,
+    ReadConsistency, TableNamesRequest,
 };
 use crate::embeddings::{EmbeddingRegistry, MemoryRegistry};
 use crate::error::{Error, Result};
 #[cfg(feature = "remote")]
 use crate::remote::{
    client::ClientConfig,
-    db::{
+    db::{OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION},
        OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION,
        OPT_REMOTE_SQL_HOST_OVERRIDE,
    },
 };
 use lance::io::ObjectStoreParams;
 pub use lance_file::version::LanceFileVersion;
@@ -325,43 +322,6 @@ pub struct CloneTableBuilder {
    request: CloneTableRequest,
 }
 /// Builder for asynchronously executing a SQL statement on a remote database.
 pub struct ExecuteQueryAsyncBuilder {
    parent: Arc<dyn Database>,
    query: String,
    default_namespace_path: Vec<String>,
 }
 impl ExecuteQueryAsyncBuilder {
    fn new(parent: Arc<dyn Database>, query: String) -> Self {
        Self {
            parent,
            query,
            default_namespace_path: vec!["public".to_string()],
        }
    }
    /// Set the namespace used for unqualified table names.
    ///
    /// An empty path is treated as `public`, which is the SQL name for the
    /// root Lance namespace.
    pub fn default_namespace_path<I, S>(mut self, path: I) -> Self
    where
        I: IntoIterator<Item = S>,
        S: Into<String>,
    {
        self.default_namespace_path = path.into_iter().map(Into::into).collect();
        self
    }
    /// Start the statement and return its asynchronous query handle.
    pub async fn execute(self) -> Result<crate::sql::Query> {
        self.parent
            .execute_query_async(&self.query, &self.default_namespace_path)
            .await
    }
 }
 impl CloneTableBuilder {
    fn new(parent: Arc<dyn Database>, target_table_name: String, source_uri: String) -> Self {
        Self {
@@ -445,51 +405,6 @@ impl Connection {
        &self.internal
    }
    /// Start executing SQL on a remote LanceDB database.
    ///
    /// The query can reference tables in other databases with SQL dot notation.
    /// Use [`ExecuteQueryAsyncBuilder::default_namespace_path`] to avoid qualifying
    /// tables in the default namespace. Local connections return
    /// [`Error::NotSupported`].
    ///
    /// # Example
    ///
    /// ```no_run
    /// # async fn query(db: &lancedb::Connection) -> lancedb::Result<()> {
    /// use futures::TryStreamExt;
    ///
    /// let query = db
    ///     .execute_query_async("SELECT * FROM events LIMIT 10")
    ///     .default_namespace_path(["public"])
    ///     .execute()
    ///     .await?;
    /// println!("query id: {}", query.id());
    /// let mut batches = query.reader().await?;
    /// while let Some(batch) = batches.try_next().await? {
    ///     println!("received {} rows", batch.num_rows());
    /// }
    /// # Ok(())
    /// # }
    /// ```
    pub fn execute_query_async(&self, query: impl Into<String>) -> ExecuteQueryAsyncBuilder {
        ExecuteQueryAsyncBuilder::new(self.internal.clone(), query.into())
    }
    /// Describe a submitted SQL query by its connection-scoped id.
    ///
    /// This performs one bounded status poll using state retained by this
    /// connection. Running state with a live query handle is not evicted;
    /// abandoned state has bounded retention, and server expiration is
    /// honored. Terminal state is retained briefly.
    /// Query ids are not portable to another connection. Local connections
    /// return [`Error::NotSupported`].
    pub async fn describe_query(
        &self,
        query_id: uuid::Uuid,
    ) -> Result<crate::sql::QueryDescription> {
        self.internal.describe_query(query_id).await
    }
    /// Get the names of all tables in the database
    ///
    /// The names will be returned in lexicographical order (ascending)
@@ -670,34 +585,14 @@ impl Connection {
        self.internal.read_consistency().await
    }
-    /// Open a server-side job by id, returning a handle with its record
+    /// A [`crate::job::Job`] handle for a server-side job by id, suitable for
-    /// already populated. Fails with [`crate::Error::JobNotFound`] when the
+    /// waiting on or cancelling the job.
    /// server has no such job, the way [`Connection::open_table`] does for a
    /// missing table.
    ///
-    /// This is the one way in: the returned [`crate::job::Job`] answers for
+    /// The handle is constructed without a server round trip; an unknown id
-    /// its own state, specification, result, failure and event history, so
+    /// surfaces when the handle is used. Only server-backed databases support
-    /// there is no separate connection-level call for any of them.
+    /// job handles by id.
-    ///
+    pub fn job(&self, job_id: impl AsRef<str>) -> Result<crate::job::Job> {
-    /// # Example
+        self.internal.job(job_id.as_ref())
    ///
    /// ```no_run
    /// # use lancedb::job::JobEventsRequest;
    /// # async fn open_job(
    /// #     connection: &lancedb::Connection,
    /// #     job_id: &str,
    /// # ) -> Result<(), Box<dyn std::error::Error>> {
    /// let job = connection.open_job(job_id).await?;
    /// println!("{:?} {:?}", job.state(), job.result());
    /// let done = job
    ///     .events(JobEventsRequest::default().filter("state = 'claim_complete'"))
    ///     .await?;
    /// println!("{} completions", done.iter().map(|b| b.num_rows()).sum::<usize>());
    /// # Ok(())
    /// # }
    /// ```
    pub async fn open_job(&self, job_id: impl AsRef<str>) -> Result<crate::job::Job> {
        self.internal.open_job(job_id.as_ref()).await
    }
    /// List server-side jobs across the database's tables.
@@ -705,12 +600,24 @@ impl Connection {
        self.internal.list_jobs().await
    }
    /// Describe a single server-side job by id. `None` when the server has no
    /// such job.
    pub async fn get_job(&self, job_id: impl AsRef<str>) -> Result<Option<JobDescription>> {
        self.internal.get_job(job_id.as_ref()).await
    }
    /// Request cancellation of a server-side job by id. Returns true if the
    /// server accepted the cancellation, false if no such job exists.
    pub async fn cancel_job(&self, job_id: impl AsRef<str>) -> Result<bool> {
        self.internal.cancel_job(job_id.as_ref()).await
    }
    /// The lifecycle event history of a server-side job (all jobs when
    /// `job_id` is `None`), as recorded Arrow batches.
    pub async fn job_history(&self, job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
        self.internal.job_history(job_id).await
    }
    /// Drop a table in the database.
    ///
    /// # Arguments
@@ -827,7 +734,7 @@ impl Connection {
 pub struct ConnectRequest {
    /// Database URI
    ///
-    /// ### Accepted URI formats
+    /// ### Accpeted URI formats
    ///
    /// - `/path/to/database` - local database on file system.
    /// - `s3://bucket/path/to/database` or `gs://bucket/path/to/database` - database on cloud object store
@@ -957,19 +864,6 @@ impl ConnectBuilder {
        self
    }
    /// Set the SQL service host override for a remote connection.
    ///
    /// The SQL client is initialized lazily when the connection first executes
    /// SQL and is retained for the connection's lifetime.
    #[cfg(feature = "remote")]
    pub fn sql_host_override(mut self, sql_host_override: &str) -> Self {
        self.request.options.insert(
            OPT_REMOTE_SQL_HOST_OVERRIDE.to_string(),
            sql_host_override.to_string(),
        );
        self
    }
    /// Set the database specific options
    ///
    /// See [crate::database::listing::ListingDatabaseOptions] for the options available for
@@ -1159,7 +1053,6 @@ impl ConnectBuilder {
        let mut merged_options = self.request.options.clone();
        Self::apply_env_defaults(&ENV_VARS_TO_STORAGE_OPTS, &mut merged_options);
        let sql_host_override = merged_options.get(OPT_REMOTE_SQL_HOST_OVERRIDE).cloned();
        let options = RemoteDatabaseOptions::parse_from_map(&merged_options)?;
        let region = options.region.ok_or_else(|| Error::InvalidInput {
@@ -1201,15 +1094,11 @@ impl ConnectBuilder {
        }
        let storage_options = StorageOptions(options.storage_options.clone());
        let host_overrides = crate::remote::db::RemoteHostOverrides {
            rest: options.host_override,
            sql: sql_host_override,
        };
        let internal = Arc::new(crate::remote::db::RemoteDatabase::try_new(
            &self.request.uri,
            &api_key,
            &region,
-            host_overrides,
+            options.host_override,
            client_config,
            storage_options.into(),
            self.request.read_consistency_interval,
@@ -1503,23 +1392,6 @@ mod tests {
        assert_eq!(tc.connection.uri(), tc.uri);
    }
    #[tokio::test]
    async fn test_local_connection_rejects_sql_queries() {
        let directory = tempdir().unwrap();
        let connection = connect(directory.path().to_str().unwrap())
            .execute()
            .await
            .unwrap();
        assert!(matches!(
            connection.execute_query_async("SELECT 1").execute().await,
            Err(Error::NotSupported { .. })
        ));
        assert!(matches!(
            connection.describe_query(uuid::Uuid::nil()).await,
            Err(Error::NotSupported { .. })
        ));
    }
    #[cfg(feature = "remote")]
    #[test]
    fn test_apply_env_defaults() {
@@ -18,6 +18,8 @@ use std::collections::HashMap;
 use std::sync::Arc;
 use std::time::Duration;
 use arrow_array::RecordBatch;
 use lance::dataset::ReadParams;
 use lance_namespace::LanceNamespace;
 use lance_namespace::models::{
@@ -204,8 +206,8 @@ pub enum ReadConsistency {
 /// compaction, column refresh, ...).
 #[derive(Debug, Clone)]
 pub struct JobInfo {
-    /// The job id -- what [`Database::open_job`] and
+    /// The job id -- what [`Database::get_job`] and [`Database::cancel_job`]
-    /// [`Database::cancel_job`] accept.
+    /// accept.
    pub job_id: String,
    /// The table the job runs against, without URI or namespace.
    pub table: String,
@@ -216,8 +218,8 @@ pub struct JobInfo {
    pub created_at_millis: i64,
 }
-/// The server-side record behind a [`crate::job::Job`] handle: lifecycle
+/// A described job from [`Database::get_job`]: lifecycle state plus the
-/// state plus the job-type-specific specification and result.
+/// job-type-specific specification.
 #[derive(Debug, Clone)]
 pub struct JobDescription {
    pub job_id: String,
@@ -228,10 +230,6 @@ pub struct JobDescription {
    pub creation_ms: i64,
    /// The job-type-specific specification. Null when the server omits it.
    pub spec: serde_json::Value,
    /// The job-type-specific terminal result, for job types that define one.
    /// `None` until the job succeeds, so a job that never terminates reports
    /// its progress through [`crate::job::Job::events`] instead.
    pub result: Option<serde_json::Value>,
    /// Why the job failed, when the job is failed and the server reports a
    /// reason.
    pub failure: Option<crate::error::JobFailure>,
@@ -317,37 +315,30 @@ pub trait Database:
    async fn drop_function(&self, _name: &str, _version: &str) -> Result<bool> {
        function_catalog_not_supported()
    }
-    /// Open a job by id, returning a handle with its record already
+    /// A [`crate::job::Job`] handle for a server-side job by id, suitable for
-    /// populated. Fails with [`crate::Error::JobNotFound`] when the server has
+    /// waiting on or cancelling the job. The handle is constructed without a
-    /// no such job.
+    /// server round trip; an unknown id surfaces when the handle is used.
-    async fn open_job(&self, _job_id: &str) -> Result<crate::job::Job> {
+    fn job(&self, _job_id: &str) -> Result<crate::job::Job> {
-        job_op_not_supported("open_job")
+        job_op_not_supported("job")
    }
    /// List server-side jobs across the database's tables.
    async fn list_jobs(&self) -> Result<Vec<JobInfo>> {
        job_op_not_supported("list_jobs")
    }
    /// Describe a single job by id. `None` when the server has no such job.
    async fn get_job(&self, _job_id: &str) -> Result<Option<JobDescription>> {
        job_op_not_supported("get_job")
    }
    /// Request cancellation of a job by id. Returns true if the server
    /// accepted the cancellation, false if no such job exists. Cancelling an
    /// already-terminal job is a no-op success.
    async fn cancel_job(&self, _job_id: &str) -> Result<bool> {
        job_op_not_supported("cancel_job")
    }
-    /// Start executing a SQL statement on a remote database.
+    /// The lifecycle event history of a job (all jobs when `job_id` is
-    async fn execute_query_async(
+    /// `None`), as recorded Arrow batches.
-        &self,
+    async fn job_history(&self, _job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
-        _query: &str,
+        job_op_not_supported("job_history")
        _default_namespace_path: &[String],
    ) -> Result<crate::sql::Query> {
        Err(crate::error::Error::NotSupported {
            message: "SQL is not supported by this database".to_string(),
        })
    }
    /// Describe a submitted SQL query by its connection-scoped id.
    async fn describe_query(&self, _query_id: uuid::Uuid) -> Result<crate::sql::QueryDescription> {
        Err(crate::error::Error::NotSupported {
            message: "SQL is not supported by this database".to_string(),
        })
    }
    /// Open a table in the database
    async fn open_table(&self, request: OpenTableRequest) -> Result<Arc<dyn BaseTable>>;
@@ -18,7 +18,7 @@ use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
 use snafu::ResultExt;
-use crate::blob::ensure_blob_storage_version;
+use crate::blob::{ensure_blob_storage_version, has_blob_columns};
 use crate::connection::ConnectRequest;
 use crate::database::ReadConsistency;
 use crate::database::namespace::LanceNamespaceDatabase;
@@ -512,7 +512,7 @@ impl ListingDatabase {
                // iter thru the query params and extract the commit store param
                let mut engine = None;
                let mut mirrored_store = None;
-                let mut filtered_queries = vec![];
+                let mut filtered_querys = vec![];
                // WARNING: specifying engine is NOT a publicly supported feature in lancedb yet
                // THE API WILL CHANGE
@@ -528,13 +528,13 @@ impl ListingDatabase {
                        mirrored_store = Some(value.to_string());
                    } else {
                        // to owned so we can modify the url
-                        filtered_queries.push((key.to_string(), value.to_string()));
+                        filtered_querys.push((key.to_string(), value.to_string()));
                    }
                }
                // Filter out the commit store query param -- it's a lancedb param
                url.query_pairs_mut().clear();
-                url.query_pairs_mut().extend_pairs(filtered_queries);
+                url.query_pairs_mut().extend_pairs(filtered_querys);
                // Take a copy of the query string so we can propagate it to lance.
                // `query_pairs_mut()` leaves the URL with `Some("")` even when no
                // pairs survive (or none existed in the first place), so an empty
@@ -827,6 +827,7 @@ impl ListingDatabase {
        if let Some(enable_stable_row_ids) = overrides
            .enable_stable_row_ids
            .or(self.new_table_config.enable_stable_row_ids)
            .or(has_blob_columns(&data_schema).then_some(true))
        {
            write_params.enable_stable_row_ids = enable_stable_row_ids;
        }
@@ -896,11 +897,11 @@ impl Database for ListingDatabase {
    }
    async fn read_consistency(&self) -> Result<ReadConsistency> {
-        if let Some(interval) = self.read_consistency_interval {
+        if let Some(read_consistency_inverval) = self.read_consistency_interval {
-            if interval.is_zero() {
+            if read_consistency_inverval.is_zero() {
                Ok(ReadConsistency::Strong)
            } else {
-                Ok(ReadConsistency::Eventual(interval))
+                Ok(ReadConsistency::Eventual(read_consistency_inverval))
            }
        } else {
            Ok(ReadConsistency::Manual)
@@ -3043,15 +3044,15 @@ mod tests {
    /// across platforms — see the `file://` test below).
    fn capture_query_like_connect(input_uri: &str) -> Option<String> {
        let mut url = url::Url::parse(input_uri).unwrap();
-        let mut filtered_queries = Vec::new();
+        let mut filtered_querys = Vec::new();
        for (key, value) in url.query_pairs() {
            if key == ENGINE || key == MIRRORED_STORE {
                continue;
            }
-            filtered_queries.push((key.to_string(), value.to_string()));
+            filtered_querys.push((key.to_string(), value.to_string()));
        }
        url.query_pairs_mut().clear();
-        url.query_pairs_mut().extend_pairs(filtered_queries);
+        url.query_pairs_mut().extend_pairs(filtered_querys);
        url.query().filter(|q| !q.is_empty()).map(|s| s.to_string())
    }
@@ -3,7 +3,6 @@
 //! Namespace-based database implementation that delegates table management to lance-namespace
 use lance_datafusion::utils::StreamingWriteSource;
 use std::collections::{HashMap, HashSet};
 use std::sync::{Arc, Mutex};
@@ -24,7 +23,7 @@ use lance_namespace_impls::ConnectBuilder;
 use lance_table::io::commit::CommitHandler;
 use lance_table::io::commit::external_manifest::ExternalManifestCommitHandler;
-use crate::blob::ensure_blob_storage_version;
+use crate::blob::{ensure_blob_storage_version, has_blob_columns};
 use crate::connection::NamespaceClientPushdownOperation;
 use crate::database::ReadConsistency;
 use crate::database::listing::{NewTableConfig, take_request_creation_overrides};
@@ -218,6 +217,7 @@ impl LanceNamespaceDatabase {
        if let Some(enable_stable_row_ids) = overrides
            .enable_stable_row_ids
            .or(self.new_table_config.enable_stable_row_ids)
            .or(has_blob_columns(data_schema.as_ref()).then_some(true))
        {
            params.enable_stable_row_ids = enable_stable_row_ids;
        }
@@ -251,11 +251,11 @@ impl Database for LanceNamespaceDatabase {
    }
    async fn read_consistency(&self) -> Result<ReadConsistency> {
-        if let Some(interval) = self.read_consistency_interval {
+        if let Some(read_consistency_inverval) = self.read_consistency_interval {
-            if interval.is_zero() {
+            if read_consistency_inverval.is_zero() {
                Ok(ReadConsistency::Strong)
            } else {
-                Ok(ReadConsistency::Eventual(interval))
+                Ok(ReadConsistency::Eventual(read_consistency_inverval))
            }
        } else {
            Ok(ReadConsistency::Manual)
@@ -305,10 +305,6 @@ impl Database for LanceNamespaceDatabase {
    }
    async fn create_table(&self, request: DbCreateTableRequest) -> Result<Arc<dyn BaseTable>> {
        // Refuse a bad declaration before the namespace records a table.
        crate::table::computed_columns::ensure_declarations_are_planned(
            &request.data.arrow_schema(),
        )?;
        let mut table_id = request.namespace_path.clone();
        table_id.push(request.name.clone());
        let mut existing_table = None;
@@ -102,8 +102,6 @@ pub enum Error {
    },
    #[snafu(display("Job{} was cancelled", job_id.as_ref().map(|id| format!(" {id}")).unwrap_or_default()))]
    JobCancelled { job_id: Option<String> },
    #[snafu(display("Job '{job_id}' was not found"))]
    JobNotFound { job_id: String },
    // 3rd party / external errors
    #[snafu(display("object_store error: {source}"))]
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
ChilePiquin	477a49cecb	test: update create-index default contract coverage	2026-09-03 15:52:46 -07:00
ChilePiquin	bd86cc5aa6	feat: default create_index to create-only	2026-09-03 14:24:27 -07:00