docs(python): fix cross-references that resolved to the wrong page

`mkdocs build --strict` only catches references it cannot resolve. A bare anchor such as `[limit][]` or `[vector search][search]` is matched by autorefs against any heading on the site, so six of them silently linked into the JavaScript reference instead. The relative links in `permutation.py` and `remote/errors.py` pointed at in-page anchors and paths that do not exist. Targets that still exist here or in an imported inventory now use mkdocstrings references; the guide pages deleted in #2770 use their lancedb.com URLs. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
docs: clear the mkdocs warning backlog so --strict passes
2026-08-27 16:38:31 +00:00 · 2026-07-30 16:19:38 -07:00 · 2026-07-29 14:15:20 -07:00 · 2026-07-29 13:59:23 -07:00 · 2026-07-29 13:46:45 -07:00
158 changed files with 2407 additions and 21933 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.38.0-beta.2"
+current_version = "0.37.1-beta.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -4,14 +4,14 @@ on:
  workflow_call:
    inputs:
      tag:
-        description: "Tag name from Lance (e.g. `v7.2.0-beta.1`). If omitted, the newest release is resolved automatically — stable releases are preferred over pre-releases — and the run is skipped if it is not newer than the version currently pinned in Cargo.toml."
+        description: "Tag name from Lance. If omitted, the skill will use the latest Lance release that needs an update."
        required: false
        default: ""
        type: string
  workflow_dispatch:
    inputs:
      tag:
-        description: "Tag name from Lance (e.g. `v7.2.0-beta.1`). Leave empty to resolve the newest release automatically — stable releases are preferred over pre-releases — and skip the run if it is not newer than the version currently pinned in Cargo.toml."
+        description: "Tag name from Lance. Leave empty to use the latest Lance release that needs an update."
        required: false
        default: ""
        type: string
@@ -1,243 +0,0 @@
 name: Check doc links
 # Checking external links is inherently noisy: third-party sites rate-limit
 # automated clients, reject non-browser user agents, and go down temporarily.
 # Blocking pull requests on that trades a lot of false failures for very little
 # signal, so this runs on a schedule and reports findings in a single tracking
 # issue instead of failing anyone's build.
 on:
  schedule:
    - cron: "0 7 * * *"
  workflow_dispatch:
 # The report lives in one repository-global issue, so runs must not overlap: a
 # lookup racing a create produces duplicate issues, and a healthy run closing
 # the issue while a failing run only rewrites its body would leave a broken
 # report closed. The group is deliberately ref-independent so that a manual
 # dispatch serializes against the scheduled run.
 concurrency:
  group: docs-link-check
  cancel-in-progress: false
 permissions: {}
 env:
  REPORT_TITLE: "Docs link checker report"
 jobs:
  scan:
    name: Scan links
    runs-on: ubuntu-24.04
    # lychee-action is pinned by SHA, but its wrapper downloads the lychee
    # release tarball at run time without verifying a digest, and hands the
    # resulting binary a GitHub token. Release assets remain replaceable, so
    # that binary is confined to a job whose token can only read public
    # content; everything that writes runs in the report job below.
    permissions:
      contents: read
    outputs:
      checker_outcome: ${{ steps.lychee.outcome }}
      exit_code: ${{ steps.lychee.outputs.exit_code }}
      status: ${{ steps.validate.outputs.status }}
    steps:
      - name: Checkout
        uses: actions/checkout@v6
        with:
          # workflow_dispatch can run from any ref, but the report is
          # repository-global. Always measure the default branch so a manual
          # run from a topic branch cannot close a report that main warrants,
          # or overwrite it with branch-only findings.
          ref: ${{ github.event.repository.default_branch }}
          persist-credentials: false
      - name: Check links
        id: lychee
        continue-on-error: true
        uses: lycheeverse/lychee-action@e7477775783ea5526144ba13e8db5eec57747ce8 # v2.9.0
        with:
          # Restricted to http(s) on purpose. Much of docs/src is generated
          # API reference (the js/ tree comes from `npm run docs` in nodejs)
          # and the hand-written pages use mkdocstrings cross-references and
          # nav-relative paths that only resolve in the site mkdocs builds,
          # not in this checkout, so relative links would be reported as
          # broken on every run.
          args: >-
            --scheme https
            --scheme http
            --no-progress
            --max-retries 3
            --timeout 20
            'docs/src/**/*.md'
          format: json
          output: ./lychee/out.json
          jobSummary: false
          # The report issue, not a red workflow run, is the signal for link
          # findings and checker failures alike.
          fail: false
      - name: Validate report
        id: validate
        # lychee does not reserve exit code 2 for broken links: its CLI
        # parser also exits 2 on an invalid option, before any link was
        # checked or any report written. Only a parseable report whose
        # counts agree with a completed exit code (0 or 2) counts as a link
        # verdict. Everything else becomes a checker-error report instead of
        # failing the workflow. Exit 2 covers timeouts as well as errors, and a
        # timed-out host is exactly the transient unavailability this report
        # exists to surface, so both count as findings. Requiring total > 0
        # also catches a glob that silently stopped matching any file.
        if: always()
        env:
          CHECKER_OUTCOME: ${{ steps.lychee.outcome }}
          EXIT_CODE: ${{ steps.lychee.outputs.exit_code }}
        run: |
          status=checker-error
          if [[ "$CHECKER_OUTCOME" == success ]] &&
             [[ "$EXIT_CODE" == 0 || "$EXIT_CODE" == 2 ]] &&
             jq -e --argjson code "$EXIT_CODE" '
               (.total > 0) and
               (if $code == 0
                then .errors == 0 and .timeouts == 0
                  and (.error_map | length == 0) and (.timeout_map | length == 0)
                else (.errors + .timeouts) > 0
                  and ((.error_map | length) + (.timeout_map | length)) > 0
                end)
             ' ./lychee/out.json
          then
            if [[ "$EXIT_CODE" == 0 ]]; then
              status=healthy
            else
              status=findings
            fi
          fi
          echo "status=$status" >> "$GITHUB_OUTPUT"
          echo "Validated link check as $status"
      - name: Upload report
        if: steps.validate.outputs.status == 'findings'
        uses: actions/upload-artifact@v7
        with:
          name: link-report
          path: ./lychee/out.json
          retention-days: 7
  report:
    name: Update report issue
    needs: scan
    runs-on: ubuntu-24.04
    # Deliberately no checkout: this job needs the report artifact and the
    # issues API, not the repository contents.
    permissions:
      issues: write
    env:
      CHECKER_OUTCOME: ${{ needs.scan.outputs.checker_outcome }}
      EXIT_CODE: ${{ needs.scan.outputs.exit_code }}
      STATUS: ${{ needs.scan.outputs.status }}
      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
    steps:
      - name: Find existing report issue
        id: report
        # Matched on title alone, and through search rather than a listing:
        # the issue action applies labels in a separate call after creating the
        # issue, so a label filter misses a half-created report, and this
        # repository has far more open issues than one listing page holds.
        # Closed issues are included because a healthy run closes the report:
        # an open-only lookup would forget that identity and the next failing
        # run would open a duplicate. The oldest match stays the canonical
        # report and is reopened below when a problem recurs.
        run: |
          match=$(gh issue list --repo "$GITHUB_REPOSITORY" --state all \
            --search "in:title \"$REPORT_TITLE\" author:app/github-actions" \
            --limit 50 --json number,title,state \
            --jq "[.[] | select(.title == \"$REPORT_TITLE\")] | sort_by(.number) | first // empty")
          echo "number=$(jq -r '.number // empty' <<<"$match")" >> "$GITHUB_OUTPUT"
          echo "state=$(jq -r '.state // empty' <<<"$match")" >> "$GITHUB_OUTPUT"
      - name: Download report
        if: env.STATUS == 'findings'
        uses: actions/download-artifact@v8
        with:
          name: link-report
          path: ./lychee
      - name: Compose report
        if: env.STATUS == 'findings'
        run: |
          run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
          {
            echo "Broken documentation links found by [\`$GITHUB_WORKFLOW\`]($run_url)."
            echo
            echo "This issue is rewritten by every scheduled run and closed automatically once all links resolve."
            echo
            echo "Entries can be false positives: some sites rate-limit or block automated clients while working fine in a browser. Confirm before editing the docs, and add persistent offenders to \`--exclude\` in \`.github/workflows/docs-link-check.yml\`."
            echo
            # Timeouts are reported alongside errors: entries land in
            # timeout_map with a status text instead of an HTTP code.
            jq -r '
              "\(.errors) of \(.total) links failed, \(.timeouts) timed out.",
              "",
              ([(.error_map | to_entries[]), (.timeout_map | to_entries[])]
               | group_by(.key)[] |
                "### Errors in \(.[0].key)",
                "",
                (map(.value[])[] | "* [\(.status.code // .status.text // "ERR")] <\(.url)> — \(.status.details // .status.text // "unknown error")"),
                "")
            ' ./lychee/out.json
          } > ./lychee/issue.md
      - name: Compose checker error report
        if: env.STATUS == 'checker-error'
        run: |
          mkdir -p ./lychee
          run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
          {
            echo "The documentation link check did not complete in [the latest run]($run_url)."
            echo
            echo "This issue is rewritten by every scheduled run and closed automatically once a trustworthy run finds that all links resolve."
            echo
            echo "The checker did not produce a trustworthy link verdict. Treat the previous result, if any, as stale until a later run completes."
            echo
            echo "* Action outcome: \`$CHECKER_OUTCOME\`"
            echo "* Exit code: \`${EXIT_CODE:-not reported}\`"
            echo "* Verdict validation: \`failed\`"
          } > ./lychee/issue.md
      - name: Reopen report issue
        # A healthy run closes the report, and the issue action below only
        # rewrites the body of whatever number it is given. Without an
        # explicit reopen, a later finding or checker error would rewrite a
        # closed issue. A CLOSED state implies the lookup found a canonical
        # issue, so no separate emptiness check.
        if: >-
          env.STATUS != 'healthy' &&
          steps.report.outputs.state == 'CLOSED'
        env:
          ISSUE_NUMBER: ${{ steps.report.outputs.number }}
        run: |
          run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
          gh issue reopen "$ISSUE_NUMBER" --repo "$GITHUB_REPOSITORY" \
            --comment "The documentation link checker reported a problem again in [the latest run]($run_url)."
      - name: Report link-check problem
        if: env.STATUS != 'healthy'
        uses: peter-evans/create-issue-from-file@fca9117c27cdc29c6c4db3b86c48e4115a786710 # v6.0.0
        with:
          # Empty on the first failing run, which creates the issue; afterwards
          # the same issue is updated in place.
          issue-number: ${{ steps.report.outputs.number }}
          title: ${{ env.REPORT_TITLE }}
          content-filepath: ./lychee/issue.md
          labels: documentation
      - name: Close report issue once links are healthy
        # An OPEN state implies the lookup found a canonical issue; a report
        # that is already closed needs nothing.
        if: >-
          env.STATUS == 'healthy' &&
          steps.report.outputs.state == 'OPEN'
        env:
          ISSUE_NUMBER: ${{ steps.report.outputs.number }}
        run: |
          run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
          gh issue close "$ISSUE_NUMBER" --repo "$GITHUB_REPOSITORY" \
            --comment "All documentation links resolved in [the latest run]($run_url)."
@@ -69,16 +69,6 @@ jobs:
        uses: actions/setup-python@v6
        with:
          python-version: "3.10"
      - name: Add swap for Arm fat LTO
        if: matrix.config.platform == 'aarch64'
        shell: bash
        run: |
          swap_file="$RUNNER_TEMP/lancedb-swap"
          sudo fallocate --length 16G "$swap_file"
          sudo chmod 600 "$swap_file"
          sudo mkswap "$swap_file"
          sudo swapon "$swap_file"
          free -h
      - uses: ./.github/workflows/build_linux_wheel
        with:
          python-minor-version: 10
@@ -296,18 +296,16 @@ jobs:
          cargo update -p aws-types --precise 1.3.9
          cargo update -p aws-sigv4 --precise 1.3.5
          cargo update -p aws-credential-types --precise 1.2.8
-          # aws-smithy-checksums must stay at or above 0.63.13: OpenDAL's S3
+          cargo update -p aws-smithy-checksums --precise 0.63.9
          # service needs crc-fast ~1.9, and older releases pin it to ~1.3.
          cargo update -p aws-smithy-checksums --precise 0.63.13
          cargo update -p aws-smithy-runtime --precise 1.9.3
-          cargo update -p aws-smithy-http --precise 0.62.6
+          cargo update -p aws-smithy-http --precise 0.62.4
-          cargo update -p aws-smithy-eventstream --precise 0.60.14
+          cargo update -p aws-smithy-eventstream --precise 0.60.12
          cargo update -p aws-smithy-http-client --precise 1.1.3
          cargo update -p aws-smithy-observability --precise 0.1.4
          cargo update -p aws-smithy-query --precise 0.60.8
-          cargo update -p aws-smithy-runtime-api --precise 1.9.3
+          cargo update -p aws-smithy-runtime-api --precise 1.9.1
-          cargo update -p aws-smithy-async --precise 1.2.7
+          cargo update -p aws-smithy-async --precise 1.2.6
-          cargo update -p aws-smithy-types --precise 1.3.6
+          cargo update -p aws-smithy-types --precise 1.3.5
          cargo update -p aws-smithy-xml --precise 0.60.11
          cargo update -p home --precise 0.5.9
      - name: cargo +${{ matrix.msrv }} check
@@ -13,23 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 [workspace.dependencies]
-# TEMPORARY: `ObjectStore::read_dir_page` is not in a lance release yet, so these point at
+lance = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-# lance-format/lance#8606 cherry-picked onto the v11.0.0-beta.15 tag. Put the tag back once that
+lance-core = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-# PR has merged and shipped in a release.
+lance-datagen = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance = { "version" = "=11.0.0-beta.15", default-features = false, "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=11.0.0-beta.15", default-features = false, "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=11.0.0-beta.15", default-features = false, "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
 lance-datafusion = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
 lance-encoding = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
 lance-arrow = { "version" = "=11.0.0-beta.15", "rev" = "d7b1d570461c6d2adde8f3a84ae88db4823c726f", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "58.0.0", optional = false }
@@ -55,7 +52,7 @@ env_logger = "0.11"
 half = { "version" = "2.7.1", default-features = false, features = [
    "num-traits",
 ] }
-futures = "0.3"
+futures = "0"
 log = "0.4"
 metrics = "0.24"
 metrics-util = "0.19"
@@ -101,19 +101,6 @@ ignore = [
    # https://rustsec.org/advisories/RUSTSEC-2026-0195
    { id = "RUSTSEC-2026-0194", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
    { id = "RUSTSEC-2026-0195", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
    # smartstring: unmaintained — the repository was archived by its author on
    # 2026-05-03. Not a vulnerability. Reached only transitively through polars
    # (polars-core/-io/-ops/-time/-utils); nothing in LanceDB depends on it directly.
    # The advisory states no safe upgrade is available: upstream recommends
    # compact_str/smol_str, so clearing this requires polars to migrate.
    # https://rustsec.org/advisories/RUSTSEC-2026-0249
    { id = "RUSTSEC-2026-0249", reason = "smartstring unmaintained via polars; no fixed upstream release" },
    # h2 0.3: empty DATA frames can be queued without limit. The patched
    # h2 0.4 line is locked to 0.4.16, but no patched 0.3 release exists.
    # The old copy is pulled in by aws-smithy's legacy hyper 0.14 client.
    # https://rustsec.org/advisories/RUSTSEC-2026-0258
    { id = "RUSTSEC-2026-0258", reason = "h2 0.3 via legacy aws-smithy/hyper 0.14; no patched 0.3 release" },
 ]
 # ---------------------------------------------------------------------------
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.38.0-beta.2</version>
+    <version>0.37.1-beta.0</version>
 </dependency>
 ```
@@ -55,38 +55,6 @@ LanceNamespace namespaceClient = LanceDbNamespaceClientBuilder.newBuilder()
 | `region(String)` | AWS region (default: "us-east-1") | No |
 | `config(String, String)` | Additional configuration parameters | No |
 ### Opening a Table with Vended Credentials
 When the catalog vends temporary object store credentials, open the table through the
 namespace client. The Lance dataset builder fetches the table location and storage options
 from the catalog and refreshes the credentials when they expire.
 ```java
 import com.lancedb.LanceDbNamespaceClientBuilder;
 import org.lance.Dataset;
 import org.lance.namespace.LanceNamespace;
 import java.util.Arrays;
 LanceNamespace namespaceClient = LanceDbNamespaceClientBuilder.newBuilder()
    .apiKey(System.getenv("LANCEDB_API_KEY"))
    .database(System.getenv("LANCEDB_DATABASE"))
    // Set the endpoint for a LanceDB Enterprise deployment.
    // .endpoint("https://your-enterprise-endpoint")
    .build();
 try (Dataset dataset = Dataset.open()
        .namespaceClient(namespaceClient)
        .tableId(Arrays.asList("my_namespace", "my_table"))
        .build()) {
    System.out.println("Rows: " + dataset.countRows());
 }
 ```
 Do not call `describeTable()` and then open the returned location with `Dataset.open(uri)`.
 Opening through `namespaceClient()` is what applies the vended storage options and enables
 automatic credential refresh. No object store credentials need to be passed by the application.
 ## Metadata Operations
 ### Creating a Namespace Path
@@ -25,27 +25,6 @@ the underlying connection has been closed.
 ## Methods
 ### cancelJob()
 ```ts
 abstract cancelJob(jobId): Promise<boolean>
 ```
 Request cancellation of a server-side job by id.
 Resolves to true if the server accepted the cancellation, false if no
 such job exists. Cancelling an already-terminal job is a no-op success.
 #### Parameters
 * **jobId**: `string`
 #### Returns
 `Promise`&lt;`boolean`&gt;
 ***
 ### cloneTable()
 ```ts
@@ -386,49 +365,6 @@ Drop an existing table.
 ***
 ### dropTableAsync()
 ```ts
 abstract dropTableAsync(name, namespacePath?): Promise<Job>
 ```
 Start dropping a table and return its cleanup job.
 The table may become unavailable before its data files are removed. Wait
 on the returned job to know when cleanup has finished.
 #### Parameters
 * **name**: `string`
 * **namespacePath?**: `string`[]
 #### Returns
 `Promise`&lt;[`Job`](Job.md)&gt;
 ***
 ### 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
@@ -443,62 +379,6 @@ 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
 abstract listJobs(): Promise<JobInfo[]>
 ```
 List server-side jobs across the database's tables.
 #### Returns
 `Promise`&lt;[`JobInfo`](../interfaces/JobInfo.md)[]&gt;
 ***
 ### listNamespaces()
 ```ts
@@ -529,71 +409,6 @@ Child namespace names and
 ***
 ### listTables()
 #### listTables(options)
 ```ts
 abstract listTables(options?): Promise<ListTablesResponse>
 ```
 List a page of tables in this database.
 Results may be paginated. To retrieve subsequent pages, pass the
 `pageToken` returned by a previous call. A page may be shorter than
 `limit` without being the last one, so walk until the response carries no
 page token:
 ```ts
 const names = [];
 let pageToken = undefined;
 do {
  const page = await conn.listTables({ pageToken, limit: 100 });
  names.push(...page.tables);
  pageToken = page.pageToken;
 } while (pageToken);
 ```
 ##### Parameters
 * **options?**: `Partial`&lt;[`ListTablesOptions`](../interfaces/ListTablesOptions.md)&gt;
    Pagination options
    (`pageToken`, `limit`).
 ##### Returns
 `Promise`&lt;[`ListTablesResponse`](../interfaces/ListTablesResponse.md)&gt;
 Table names and an optional token
  for fetching the next page.
 #### listTables(namespacePath, options)
 ```ts
 abstract listTables(namespacePath?, options?): Promise<ListTablesResponse>
 ```
 List a page of tables in this database.
 ##### Parameters
 * **namespacePath?**: `string`[]
    The namespace path to list tables from
    (defaults to root namespace)
 * **options?**: `Partial`&lt;[`ListTablesOptions`](../interfaces/ListTablesOptions.md)&gt;
    Pagination options
    (`pageToken`, `limit`).
 ##### Returns
 `Promise`&lt;[`ListTablesResponse`](../interfaces/ListTablesResponse.md)&gt;
 Table names and an optional token
  for fetching the next page.
 ***
 ### openTable()
 ```ts
@@ -655,7 +470,7 @@ a "not supported" error.
 ***
-### ~~tableNames()~~
+### tableNames()
 #### tableNames(options)
@@ -677,10 +492,6 @@ Tables will be returned in lexicographical order.
 `Promise`&lt;`string`[]&gt;
 ##### Deprecated
 Use [Connection.listTables](Connection.md#listtables) instead.
 #### tableNames(namespacePath, options)
 ```ts
@@ -703,7 +514,3 @@ Tables will be returned in lexicographical order.
 ##### Returns
 `Promise`&lt;`string`[]&gt;
 ##### Deprecated
 Use [Connection.listTables](Connection.md#listtables) instead.
@@ -1,83 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / Job
 # Class: Job
 A handle to an operation that may still be running.
 ## Constructors
 ### new Job()
 ```ts
 new Job(): Job
 ```
 #### Returns
 [`Job`](Job.md)
 ## Accessors
 ### id
 ```ts
 get id(): null | string
 ```
 Identifies the operation on the server that is running it. Operations
 that run in this process have no server id. The value is opaque.
 #### Returns
 `null` \| `string`
 ## Methods
 ### cancel()
 ```ts
 cancel(): Promise<void>
 ```
 Request cancellation. Cancelling a finished operation is a no-op.
 #### Returns
 `Promise`&lt;`void`&gt;
 ***
 ### status()
 ```ts
 status(): Promise<string>
 ```
 The operation's current lifecycle state: "running", "finished",
 "failed", or "cancelled".
 A point snapshot; unlike [Job.wait](Job.md#wait) it does not block or reject
 on a terminal failure state. States a newer server reports that this
 client version does not know pass through as-is.
 #### Returns
 `Promise`&lt;`string`&gt;
 ***
 ### wait()
 ```ts
 wait(): Promise<void>
 ```
 Wait until the operation reaches a terminal state.
 #### Returns
 `Promise`&lt;`void`&gt;
@@ -69,34 +69,14 @@ abstract addColumns(newColumnTransforms): Promise<AddColumnsResult>
 Add new columns with defined values.
 The `{ computed }` form stores the expression rather than evaluating it
 now: the column is committed with no values, and rows get them from
 [Table#refreshColumn](Table.md#refreshcolumn). Declaring one therefore costs the same on a
 large table as on an empty one.
 A refresh does not revisit rows it has already filled, so mutating an
 input leaves the value computed at fill time; recomputing means dropping
 the column and declaring it again. While a declaration reads a column,
 that column cannot be renamed, retyped or dropped.
 On LanceDB Cloud and Enterprise the expression is planned by the
 server, and the refresh runs as a server job -- see
 [Table#refreshColumnAsync](Table.md#refreshcolumnasync).
 #### Parameters
-* **newColumnTransforms**:
+* **newColumnTransforms**: `Field`&lt;`any`&gt; \| `Field`&lt;`any`&gt;[] \| `Schema`&lt;`any`&gt; \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
    \| `Field`&lt;`any`&gt;
    \| `Field`&lt;`any`&gt;[]
    \| `Schema`&lt;`any`&gt;
    \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
    \| `object`
    Either:
    - An array of objects with column names and SQL expressions to calculate values
    - A single Arrow Field defining one column with its data type (column will be initialized with null values)
    - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
    - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
    - `{ computed }`, declaring columns defined by a SQL expression whose type and inputs are derived from it
 #### Returns
@@ -105,13 +85,6 @@ server, and the refresh runs as a server job -- see
 A promise that resolves to an object
 containing the new version number of the table after adding the columns.
 #### Example
 ```ts
 await table.addColumns({ computed: [{ name: "doubled", valueSql: "x * 2" }] });
 const { rowsFilled } = await table.refreshColumn("doubled");
 ```
 ***
 ### alterColumns()
@@ -213,39 +186,6 @@ version of the table.
 ***
 ### checkpointLsm()
 ```ts
 abstract checkpointLsm(): Promise<void>
 ```
 Converge this table's LSM write path into its base table.
 Seals once, then triggers compaction and polls until the L0 that existed
 at the start is gone. The target set is fixed at the start, so
 generations created *during* the checkpoint are ignored — that is what
 lets it terminate under write load, and what makes it best-effort: it
 converges the fresh tier as of some instant. Idempotent, abandonable at
 any point, and safe to run on a cadence.
 There is no liveness bound — the compactor pool is shared across tables,
 so a checkpoint queued behind unrelated work looks exactly like one that
 is merging. The caller owns the deadline.
 #### Returns
 `Promise`&lt;`void`&gt;
 #### Example
 ```ts
 const before = await table.getLsmStats();
 await table.checkpointLsm();
 const after = await table.getLsmStats();
 ```
 ***
 ### close()
 ```ts
@@ -283,24 +223,6 @@ It is a no-op when no writers are cached.
 ***
 ### compactLsm()
 ```ts
 abstract compactLsm(): Promise<void>
 ```
 Trigger a background L0 → base compaction pass per bucket.
 Returns once the passes are *dispatched*, not once they finish — watch
 [Table#getLsmStats](Table.md#getlsmstats) for progress, or use
 [Table#checkpointLsm](Table.md#checkpointlsm) to wait for convergence.
 #### Returns
 `Promise`&lt;`void`&gt;
 ***
 ### countRows()
 ```ts
@@ -373,29 +295,6 @@ await table.createIndex("my_float_col");
 ***
 ### createIndexAsync()
 ```ts
 abstract createIndexAsync(column, options?): Promise<Job>
 ```
 Create an index, returning a handle to the indexing job.
 The job may already be complete when returned; callers must not assume
 the index exists until [Job.wait](Job.md#wait) resolves.
 #### Parameters
 * **column**: `string`
 * **options?**: `Partial`&lt;[`IndexOptions`](../interfaces/IndexOptions.md)&gt;
 #### Returns
 `Promise`&lt;[`Job`](Job.md)&gt;
 ***
 ### currentBranch()
 ```ts
@@ -499,48 +398,6 @@ Drop an index from the table.
 ***
 ### flushLsm()
 ```ts
 abstract flushLsm(): Promise<void>
 ```
 Seal every bucket's active memtable into a new L0 generation.
 Returns once the seal is committed. Sealing an empty memtable is a no-op,
 so this is safe to call repeatedly.
 #### Returns
 `Promise`&lt;`void`&gt;
 ***
 ### getLsmStats()
 ```ts
 abstract getLsmStats(includeGenerationRows?): Promise<undefined | LsmStats>
 ```
 Read live per-bucket LSM state.
 Answers "how far behind is my fresh tier", "which bucket is hot", and
 "why is my fresh-tier vector search brute-force". Mutates no table state.
 Resolves to `undefined` only when the LSM write path is not enabled.
 #### Parameters
 * **includeGenerationRows?**: `boolean`
    Also count rows per L0 generation.
    Off by default because each count opens an uncached Lance dataset.
 #### Returns
 `Promise`&lt;`undefined` \| [`LsmStats`](../interfaces/LsmStats.md)&gt;
 ***
 ### getLsmWriteSpec()
 ```ts
@@ -551,10 +408,9 @@ Read the [LsmWriteSpec](../interfaces/LsmWriteSpec.md) currently installed on th
 Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
 spec has been set, or it was removed with [Table#unsetLsmWriteSpec](Table.md#unsetlsmwritespec)).
-The returned spec mirrors what was passed to
+The returned spec — including its `maintainedIndexes` and
-[Table#setLsmWriteSpec](Table.md#setlsmwritespec), except that `maintainedIndexes` always
+`writerConfigDefaults` — mirrors what was passed to
-reports the concrete list resolved when the spec was set — `undefined`
+[Table#setLsmWriteSpec](Table.md#setlsmwritespec).
 never round-trips.
 #### Returns
@@ -838,67 +694,6 @@ for await (const batch of table.query()) {
 ***
 ### refreshColumn()
 ```ts
 abstract refreshColumn(column): Promise<RefreshColumnResult>
 ```
 Fill the rows of a computed column that hold no value yet.
 Rows appended since the last refresh are filled by the next one; rows
 already filled are left as they are, so the call is idempotent and does
 not observe a mutated input. Local tables only: a remote refresh runs
 as a server job, through [Table#refreshColumnAsync](Table.md#refreshcolumnasync).
 #### Parameters
 * **column**: `string`
    The name of the computed column to fill.
 #### Returns
 `Promise`&lt;[`RefreshColumnResult`](../interfaces/RefreshColumnResult.md)&gt;
 A promise that resolves to the
 number of rows filled and the new version number of the table.
 ***
 ### refreshColumnAsync()
 ```ts
 abstract refreshColumnAsync(column): Promise<Job>
 ```
 Like [Table#refreshColumn](Table.md#refreshcolumn), but returns a handle to the refresh
 job instead of blocking until it completes.
 The job may already be complete when returned; callers must not assume
 the column is filled until [Job.wait](Job.md#wait) resolves. Invalid input --
 an unknown column, or one that is not computed -- rejects here rather
 than failing the job. On local tables the job runs in-process; on
 LanceDB Cloud and Enterprise it is the server's backfill job.
 #### Parameters
 * **column**: `string`
    The name of the computed column to fill.
 #### Returns
 `Promise`&lt;[`Job`](Job.md)&gt;
 #### Example
 ```ts
 const job = await table.refreshColumnAsync("doubled");
 await job.wait();
 console.log(await job.status()); // "finished"
 ```
 ***
 ### restore()
 ```ts
@@ -988,11 +783,6 @@ All variants require the table to have an unenforced primary key
 ([Table#setUnenforcedPrimaryKey](Table.md#setunenforcedprimarykey)); bucket sharding additionally
 requires it to be the single column being bucketed.
 Omitting `maintainedIndexes` maintains every index on the table, resolved
 here, failing if one cannot be maintained — name them to install anyway.
 Naming them pins an exact set, and a still-building index is rejected
 rather than quietly omitted.
 #### Parameters
 * **spec**: [`LsmWriteSpec`](../interfaces/LsmWriteSpec.md)
@@ -25,7 +25,6 @@
 - [Connection](classes/Connection.md)
 - [HeaderProvider](classes/HeaderProvider.md)
 - [Index](classes/Index.md)
 - [Job](classes/Job.md)
 - [MakeArrowTableOptions](classes/MakeArrowTableOptions.md)
 - [MatchQuery](classes/MatchQuery.md)
 - [MergeInsertBuilder](classes/MergeInsertBuilder.md)
@@ -58,7 +57,6 @@
 - [BranchDiff](interfaces/BranchDiff.md)
 - [BranchIndexSummary](interfaces/BranchIndexSummary.md)
 - [BranchRowCountSummary](interfaces/BranchRowCountSummary.md)
 - [BucketStats](interfaces/BucketStats.md)
 - [ClientConfig](interfaces/ClientConfig.md)
 - [ColumnAlteration](interfaces/ColumnAlteration.md)
 - [ColumnOrdering](interfaces/ColumnOrdering.md)
@@ -82,7 +80,6 @@
 - [FtsToken](interfaces/FtsToken.md)
 - [FullTextQuery](interfaces/FullTextQuery.md)
 - [FullTextSearchOptions](interfaces/FullTextSearchOptions.md)
 - [GenerationStats](interfaces/GenerationStats.md)
 - [HnswPqOptions](interfaces/HnswPqOptions.md)
 - [HnswSqOptions](interfaces/HnswSqOptions.md)
 - [IndexConfig](interfaces/IndexConfig.md)
@@ -91,16 +88,9 @@
 - [IvfFlatOptions](interfaces/IvfFlatOptions.md)
 - [IvfPqOptions](interfaces/IvfPqOptions.md)
 - [IvfRqOptions](interfaces/IvfRqOptions.md)
 - [JobDescription](interfaces/JobDescription.md)
 - [JobFailureInfo](interfaces/JobFailureInfo.md)
 - [JobInfo](interfaces/JobInfo.md)
 - [ListNamespacesOptions](interfaces/ListNamespacesOptions.md)
 - [ListNamespacesResponse](interfaces/ListNamespacesResponse.md)
 - [ListTablesOptions](interfaces/ListTablesOptions.md)
 - [ListTablesResponse](interfaces/ListTablesResponse.md)
 - [LsmStats](interfaces/LsmStats.md)
 - [LsmWriteSpec](interfaces/LsmWriteSpec.md)
 - [MemtableStats](interfaces/MemtableStats.md)
 - [MergeBlocker](interfaces/MergeBlocker.md)
 - [MergeBranchResult](interfaces/MergeBranchResult.md)
 - [MergePreview](interfaces/MergePreview.md)
@@ -111,7 +101,6 @@
 - [OptimizeOptions](interfaces/OptimizeOptions.md)
 - [OptimizeStats](interfaces/OptimizeStats.md)
 - [QueryExecutionOptions](interfaces/QueryExecutionOptions.md)
 - [RefreshColumnResult](interfaces/RefreshColumnResult.md)
 - [RemovalStats](interfaces/RemovalStats.md)
 - [RenameTableOptions](interfaces/RenameTableOptions.md)
 - [RestNamespaceConfig](interfaces/RestNamespaceConfig.md)
@@ -1,116 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / BucketStats
 # Interface: BucketStats
 Live state of one bucket. A table is N buckets on one node; flattening to a
 single number hides the one hot bucket that is usually why someone opened
 this endpoint.
 ## Properties
 ### compacting
 ```ts
 compacting: boolean;
 ```
 Whether a pass owns this bucket's compaction latch right now. Says *a*
 driver is running, not *whose*, and the latch is held from dispatch —
 including while the pass queues for a pod-wide compactor permit. Read it
 as "do not pile on", never as "mine is progressing".
 ***
 ### currentGeneration
 ```ts
 currentGeneration: number;
 ```
 The generation the active memtable will become.
 ***
 ### generations
 ```ts
 generations: GenerationStats[];
 ```
 Flushed L0 generations not yet merged into the base table.
 ***
 ### manifestVersion
 ```ts
 manifestVersion: number;
 ```
 Version of the shard manifest these numbers were read from.
 ***
 ### memtables?
 ```ts
 optional memtables: MemtableStats[];
 ```
 Oldest first, active last. Absent for a `"Sealed"` bucket, whose
 in-memory state is torn down.
 ***
 ### replayAfterWalEntryPosition
 ```ts
 replayAfterWalEntryPosition: number;
 ```
 WAL position replay resumes from.
 ***
 ### shardId
 ```ts
 shardId: string;
 ```
 The shard this bucket writes.
 ***
 ### status
 ```ts
 status: string;
 ```
 `"Active"` or `"Sealed"` (drop-table 2PC in flight).
 ***
 ### walEntryPositionLastSeen
 ```ts
 walEntryPositionLastSeen: number;
 ```
 Highest WAL position the writer has seen. The difference against
 `replayAfterWalEntryPosition` is the WAL lag.
 ***
 ### writerEpoch
 ```ts
 writerEpoch: number;
 ```
 Epoch of the writer that currently owns the shard.
@@ -1,40 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / GenerationStats
 # Interface: GenerationStats
 One flushed L0 generation.
 ## Properties
 ### bytes
 ```ts
 bytes: number;
 ```
 On-disk size of the generation.
 ***
 ### generation
 ```ts
 generation: number;
 ```
 The generation number. Increases as memtables are sealed into L0.
 ***
 ### rows?
 ```ts
 optional rows: number;
 ```
 Present only when `includeGenerationRows` was requested. Off by default
 because each count opens an uncached Lance dataset.
@@ -1,66 +0,0 @@
 [**@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".
@@ -1,33 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / JobFailureInfo
 # Interface: JobFailureInfo
 The server's account of why a job failed.
 ## Properties
 ### message?
 ```ts
 optional message: string;
 ```
 ***
 ### phase?
 ```ts
 optional phase: string;
 ```
 ***
 ### retryable?
 ```ts
 optional retryable: boolean;
 ```
@@ -1,58 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / JobInfo
 # Interface: JobInfo
 A row from `Connection.listJobs`: one server-side job.
 ## Properties
 ### createdAtMillis
 ```ts
 createdAtMillis: number;
 ```
 When the job was created, in milliseconds since the epoch.
 ***
 ### jobId
 ```ts
 jobId: string;
 ```
 The job id -- what `Connection.getJob` and `Connection.cancelJob`
 accept.
 ***
 ### jobType
 ```ts
 jobType: string;
 ```
 ***
 ### state
 ```ts
 state: string;
 ```
 Lifecycle state: "running", "finished", "failed", or "cancelled".
 ***
 ### table
 ```ts
 table: string;
 ```
 The table the job runs against, without URI or namespace.
@@ -1,33 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / ListTablesOptions
 # Interface: ListTablesOptions
 ## Properties
 ### limit?
 ```ts
 optional limit: number;
 ```
 An upper bound on how many tables to return.
 A page may hold fewer than this and still not be the last one, so continue
 while the response carries a page token rather than while pages are full.
 ***
 ### pageToken?
 ```ts
 optional pageToken: string;
 ```
 Token from a previous response for pagination.
 The token is opaque: it carries whatever the database needs to resume, and
 callers should not construct or interpret one.
@@ -1,23 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / ListTablesResponse
 # Interface: ListTablesResponse
 ## Properties
 ### pageToken?
 ```ts
 optional pageToken: string;
 ```
 ***
 ### tables
 ```ts
 tables: string[];
 ```
@@ -1,22 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / LsmStats
 # Interface: LsmStats
 Live per-bucket LSM state, as returned by `Table#getLsmStats`.
 Nothing here is derived: sums and differences (total L0 bytes, WAL lag) are
 the caller's to compute.
 ## Properties
 ### buckets
 ```ts
 buckets: BucketStats[];
 ```
 One entry per bucket backing this table.
@@ -34,9 +34,7 @@ Bucket and identity variants: the sharding column.
 optional maintainedIndexes: string[];
 ```
-Indexes the MemWAL keeps up to date. Omit to maintain every supported
+Names of indexes the MemWAL should keep up to date during writes.
 index, resolved on install — a snapshot, so indexes created later are not
 maintained. Pass `[]` for none.
 ***
@@ -1,60 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / MemtableStats
 # Interface: MemtableStats
 One in-memory memtable.
 ## Properties
 ### batches
 ```ts
 batches: number;
 ```
 Record batches currently buffered.
 ***
 ### bytes
 ```ts
 bytes: number;
 ```
 Estimated in-memory size.
 ***
 ### generation
 ```ts
 generation: number;
 ```
 The generation this memtable will become once sealed.
 ***
 ### indexes
 ```ts
 indexes: string[];
 ```
 Names of the indexes this memtable carries. An absent name is the whole
 answer to "why is my fresh-tier search on that column brute-force".
 ***
 ### rows
 ```ts
 rows: number;
 ```
 Rows currently buffered.
@@ -1,23 +0,0 @@
 [**@lancedb/lancedb**](../README.md) • **Docs**
 ***
 [@lancedb/lancedb](../globals.md) / RefreshColumnResult
 # Interface: RefreshColumnResult
 ## Properties
 ### rowsFilled
 ```ts
 rowsFilled: number;
 ```
 ***
 ### version
 ```ts
 version: number;
 ```
@@ -4,16 +4,11 @@
 [@lancedb/lancedb](../globals.md) / TableNamesOptions
-# Interface: ~~TableNamesOptions~~
+# Interface: TableNamesOptions
 ## Deprecated
 Use [ListTablesOptions](ListTablesOptions.md) with [Connection.listTables](../classes/Connection.md#listtables)
 instead.
 ## Properties
-### ~~limit?~~
+### limit?
 ```ts
 optional limit: number;
@@ -23,7 +18,7 @@ An optional limit to the number of results to return.
 ***
-### ~~startAfter?~~
+### startAfter?
 ```ts
 optional startAfter: string;
@@ -44,7 +44,4 @@ The number of rows in the table
 totalBytes: number;
 ```
-The total size, in bytes, of the table's data files, index files, and
+The total number of bytes in the table
 overlay files
 Read from the manifest, so this excludes deletion files and manifests.
@@ -31,7 +31,7 @@ is also an [asynchronous API client](#connections-asynchronous).
 ## Namespaces (Synchronous)
 A namespace-backed connection resolves tables through a
-[Lance namespace](https://lance-format.github.io/lance-namespace/) service instead of
+[Lance namespace](https://lancedb.github.io/lance-namespace/) service instead of
 listing a storage directory.
 ::: lancedb.connect_namespace
@@ -52,8 +52,6 @@ listing a storage directory.
 ::: lancedb.table.Branches
 ::: lancedb.LsmWriteSpec
 ## Expressions
 Type-safe expression builder for filters and projections. Use these instead
@@ -29,48 +29,6 @@ LanceNamespace namespaceClient = LanceDbNamespaceClientBuilder.newBuilder()
    .build();
 ```
 ## MemWAL LSM write path
 Most table operations reach LanceDB through the `LanceNamespace` above, which is
 generated from the Lance Namespace specification. The MemWAL LSM routes are not part
 of that specification, so they are issued through a separate client:
 ```java
 import com.lancedb.LanceDbRestClient;
 import com.lancedb.LanceDbTableLsm;
 import com.lancedb.LsmWriteSpec;
 LanceDbRestClient client = LanceDbNamespaceClientBuilder.newBuilder()
    .apiKey("your_lancedb_cloud_api_key")
    .database("your_database_name")
    .buildRestClient();
 LanceDbTableLsm lsm = new LanceDbTableLsm(client, "my_table");
 // Route future merge_insert upserts through the MemWAL, hash-bucketed by `id`.
 lsm.setLsmWriteSpec(LsmWriteSpec.bucket("id", 16));
 // ... merge_insert traffic ...
 // Converge the fresh tier into the base table.
 lsm.checkpointLsm();
 // Inspect live per-bucket state.
 lsm.getLsmStats().ifPresent(stats -> stats.buckets().forEach(bucket ->
    System.out.println(bucket.shardId() + ": " + bucket.generations().size() + " L0 generations")));
 client.close();
 ```
 `maintainedIndexes` is tri-state, and the null default is the opposite of what a Java
 reader usually expects:
 | Value | Meaning |
 | --- | --- |
 | unset (null) | Maintain **every** index the MemWAL can, resolved on install |
 | `Collections.emptyList()` | Maintain **none** |
 | `Arrays.asList("id_idx")` | Maintain exactly those |
 ## Development
 Build:
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.38.0-beta.2</version>
+      <version>0.37.1-beta.0</version>
      <relativePath>../pom.xml</relativePath>
    </parent>
@@ -33,20 +33,6 @@
            <artifactId>arrow-memory-netty</artifactId>
        </dependency>
        <!-- Transport for the LanceDB routes outside the Lance Namespace spec.
             Versions match what lance-namespace-apache-client resolves to. -->
        <dependency>
            <groupId>org.apache.httpcomponents.client5</groupId>
            <artifactId>httpclient5</artifactId>
            <version>5.2.1</version>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.17.1</version>
        </dependency>
        <dependency>
            <groupId>org.junit.jupiter</groupId>
            <artifactId>junit-jupiter</artifactId>
@@ -1,194 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
 import java.util.Optional;
 import java.util.OptionalLong;
 /**
 * Live state of one bucket. A table is N buckets on one node; flattening to a single number hides
 * the one hot bucket that is usually why someone opened this endpoint.
 */
 public class BucketStats {
  private static final String CONTEXT = "bucket stats";
  private final String shardId;
  private final String status;
  private final long writerEpoch;
  private final long manifestVersion;
  private final long currentGeneration;
  private final long replayAfterWalEntryPosition;
  private final long walEntryPositionLastSeen;
  private final List<GenerationStats> generations;
  private final boolean compacting;
  private final List<MemtableStats> memtables;
  BucketStats(
      String shardId,
      String status,
      long writerEpoch,
      long manifestVersion,
      long currentGeneration,
      long replayAfterWalEntryPosition,
      long walEntryPositionLastSeen,
      List<GenerationStats> generations,
      boolean compacting,
      List<MemtableStats> memtables) {
    this.shardId = shardId;
    this.status = status;
    this.writerEpoch = writerEpoch;
    this.manifestVersion = manifestVersion;
    this.currentGeneration = currentGeneration;
    this.replayAfterWalEntryPosition = replayAfterWalEntryPosition;
    this.walEntryPositionLastSeen = walEntryPositionLastSeen;
    this.generations = Collections.unmodifiableList(generations);
    this.compacting = compacting;
    this.memtables = memtables == null ? null : Collections.unmodifiableList(memtables);
  }
  /** The shard this bucket writes. */
  public String shardId() {
    return shardId;
  }
  /** {@code "Active"} or {@code "Sealed"} (drop-table 2PC in flight). */
  public String status() {
    return status;
  }
  /** Epoch of the writer that currently owns the shard. */
  public long writerEpoch() {
    return writerEpoch;
  }
  /** Version of the shard manifest these numbers were read from. */
  public long manifestVersion() {
    return manifestVersion;
  }
  /** The generation the active memtable will become. */
  public long currentGeneration() {
    return currentGeneration;
  }
  /** WAL position replay resumes from. */
  public long replayAfterWalEntryPosition() {
    return replayAfterWalEntryPosition;
  }
  /**
   * Highest WAL position the writer has seen. The difference against {@link
   * #replayAfterWalEntryPosition()} is the WAL lag.
   */
  public long walEntryPositionLastSeen() {
    return walEntryPositionLastSeen;
  }
  /** Flushed L0 generations not yet merged into the base table. */
  public List<GenerationStats> generations() {
    return generations;
  }
  /**
   * Whether a pass owns this bucket's compaction latch right now. Says <em>a</em> driver is
   * running, not <em>whose</em>, and the latch is held from dispatch — including while the pass
   * queues for a pod-wide compactor permit. Read it as "do not pile on", never as "mine is
   * progressing".
   */
  public boolean compacting() {
    return compacting;
  }
  /** Oldest first, active last. Empty for a {@code "Sealed"} bucket, whose state is torn down. */
  public Optional<List<MemtableStats>> memtables() {
    return Optional.ofNullable(memtables);
  }
  /** The newest flushed generation, or empty when L0 is empty. */
  OptionalLong newestGeneration() {
    OptionalLong newest = OptionalLong.empty();
    for (GenerationStats generation : generations) {
      if (!newest.isPresent() || generation.generation() > newest.getAsLong()) {
        newest = OptionalLong.of(generation.generation());
      }
    }
    return newest;
  }
  /**
   * How many generations at or below {@code target} are still in L0.
   *
   * <p>A count, not a boolean: one pass drains a bounded prefix rather than the whole target set,
   * so a boolean would read as "no progress" for every pass but the last. Compaction drains
   * oldest-first, so this decreases monotonically.
   */
  long outstandingGenerations(long target) {
    long count = 0;
    for (GenerationStats generation : generations) {
      if (generation.generation() <= target) {
        count++;
      }
    }
    return count;
  }
  static BucketStats fromJson(JsonNode node) {
    JsonFields.requiredObject(node, CONTEXT);
    List<GenerationStats> generations = new ArrayList<GenerationStats>();
    for (JsonNode generation : JsonFields.requiredArray(node, "generations", CONTEXT)) {
      generations.add(GenerationStats.fromJson(generation));
    }
    JsonNode memtablesNode = JsonFields.optionalArray(node, "memtables", CONTEXT);
    List<MemtableStats> memtables = null;
    if (memtablesNode != null) {
      memtables = new ArrayList<MemtableStats>();
      for (JsonNode memtable : memtablesNode) {
        memtables.add(MemtableStats.fromJson(memtable));
      }
    }
    return new BucketStats(
        JsonFields.requiredText(node, "shard_id", CONTEXT),
        JsonFields.requiredText(node, "status", CONTEXT),
        JsonFields.requiredLong(node, "writer_epoch", CONTEXT),
        JsonFields.requiredLong(node, "manifest_version", CONTEXT),
        JsonFields.requiredLong(node, "current_generation", CONTEXT),
        JsonFields.requiredLong(node, "replay_after_wal_entry_position", CONTEXT),
        JsonFields.requiredLong(node, "wal_entry_position_last_seen", CONTEXT),
        generations,
        JsonFields.requiredBoolean(node, "compacting", CONTEXT),
        memtables);
  }
  @Override
  public String toString() {
    return "BucketStats{shardId="
        + shardId
        + ", status="
        + status
        + ", currentGeneration="
        + currentGeneration
        + ", generations="
        + generations
        + ", compacting="
        + compacting
        + "}";
  }
 }
@@ -1,64 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.OptionalLong;
 /** One flushed L0 generation. */
 public class GenerationStats {
  private static final String CONTEXT = "generation stats";
  private final long generation;
  private final long bytes;
  private final Long rows;
  GenerationStats(long generation, long bytes, Long rows) {
    this.generation = generation;
    this.bytes = bytes;
    this.rows = rows;
  }
  /** The generation number. Increases as memtables are sealed into L0. */
  public long generation() {
    return generation;
  }
  /** On-disk size of the generation. */
  public long bytes() {
    return bytes;
  }
  /**
   * Rows in this generation, present only when {@code includeGenerationRows} was requested. Off by
   * default because each count opens an uncached Lance dataset.
   */
  public OptionalLong rows() {
    return rows == null ? OptionalLong.empty() : OptionalLong.of(rows);
  }
  static GenerationStats fromJson(JsonNode node) {
    JsonFields.requiredObject(node, CONTEXT);
    return new GenerationStats(
        JsonFields.requiredLong(node, "generation", CONTEXT),
        JsonFields.requiredLong(node, "bytes", CONTEXT),
        JsonFields.optionalLong(node, "rows", CONTEXT));
  }
  @Override
  public String toString() {
    return "GenerationStats{generation=" + generation + ", bytes=" + bytes + ", rows=" + rows + "}";
  }
 }
@@ -1,109 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 /**
 * Strict readers for decoding LanceDB JSON responses.
 *
 * <p>Every reader fails closed: a missing, null, or wrong-typed field throws rather than
 * defaulting. That mirrors the serde decoding the Rust client applies to the same payloads in
 * {@code rust/lancedb/src/table/lsm_stats.rs}, where a required field has no default and a
 * malformed response is an error rather than a zero.
 *
 * <p>The alternative — Jackson's {@code path()}, which yields a missing node that reads as an empty
 * array or a zero — is unsafe here because {@link LanceDbTableLsm#checkpointLsm()} decides
 * convergence from these numbers. A defaulted {@code generations} array is indistinguishable from a
 * drained one, so a malformed response would report a checkpoint that never happened.
 */
 final class JsonFields {
  private JsonFields() {}
  /** The node itself, once confirmed to be a JSON object. */
  static JsonNode requiredObject(JsonNode node, String context) {
    if (node == null || !node.isObject()) {
      throw new IllegalStateException(context + " is not a JSON object: " + node);
    }
    return node;
  }
  static String requiredText(JsonNode owner, String field, String context) {
    JsonNode value = required(owner, field, context);
    if (!value.isTextual()) {
      throw new IllegalStateException(fieldIs(context, field, "a string", value));
    }
    return value.asText();
  }
  static long requiredLong(JsonNode owner, String field, String context) {
    JsonNode value = required(owner, field, context);
    if (!value.isIntegralNumber()) {
      throw new IllegalStateException(fieldIs(context, field, "an integer", value));
    }
    return value.asLong();
  }
  static boolean requiredBoolean(JsonNode owner, String field, String context) {
    JsonNode value = required(owner, field, context);
    if (!value.isBoolean()) {
      throw new IllegalStateException(fieldIs(context, field, "a boolean", value));
    }
    return value.asBoolean();
  }
  static JsonNode requiredArray(JsonNode owner, String field, String context) {
    JsonNode value = required(owner, field, context);
    if (!value.isArray()) {
      throw new IllegalStateException(fieldIs(context, field, "an array", value));
    }
    return value;
  }
  /** Null when the field is absent or JSON null, mirroring a serde {@code Option}. */
  static Long optionalLong(JsonNode owner, String field, String context) {
    JsonNode value = owner.get(field);
    if (value == null || value.isNull()) {
      return null;
    }
    if (!value.isIntegralNumber()) {
      throw new IllegalStateException(fieldIs(context, field, "an integer", value));
    }
    return value.asLong();
  }
  /** Null when the field is absent or JSON null, mirroring a serde {@code Option}. */
  static JsonNode optionalArray(JsonNode owner, String field, String context) {
    JsonNode value = owner.get(field);
    if (value == null || value.isNull()) {
      return null;
    }
    if (!value.isArray()) {
      throw new IllegalStateException(fieldIs(context, field, "an array", value));
    }
    return value;
  }
  private static JsonNode required(JsonNode owner, String field, String context) {
    JsonNode value = owner.get(field);
    if (value == null || value.isNull()) {
      throw new IllegalStateException(context + " is missing required field '" + field + "'");
    }
    return value;
  }
  private static String fieldIs(String context, String field, String expected, JsonNode value) {
    return context + " field '" + field + "' is not " + expected + ": " + value;
  }
 }
@@ -136,48 +136,29 @@ public class LanceDbNamespaceClientBuilder {
   * @throws IllegalStateException if required parameters are missing
   */
  public LanceNamespace build() {
-    validate();
+    // Validate required fields
    // Build configuration map
    Map<String, String> config = new HashMap<>(additionalConfig);
    config.put("header.x-lancedb-database", database);
    config.put("header.x-api-key", apiKey);
    config.put("uri", resolveUri());
    return LanceNamespace.connect("rest", config, null);
  }
  /**
   * Build a {@link LanceDbRestClient} for the same endpoint.
   *
   * <p>Needed only for LanceDB routes that the Lance Namespace specification does not cover — the
   * MemWAL LSM write path, reached through {@link LanceDbTableLsm}. Every other table operation
   * belongs on the {@link LanceNamespace} from {@link #build()}.
   *
   * <p>The returned client owns an HTTP connection pool; close it when you are done with it.
   *
   * @return A configured LanceDbRestClient
   * @throws IllegalStateException if required parameters are missing
   */
  public LanceDbRestClient buildRestClient() {
    validate();
    return new LanceDbRestClient(resolveUri(), apiKey, database);
  }
  private void validate() {
    if (apiKey == null) {
      throw new IllegalStateException("API key is required");
    }
    if (database == null) {
      throw new IllegalStateException("Database is required");
    }
  }
-  /** The custom endpoint when set, else the LanceDB Cloud URL for this database and region. */
+    // Build configuration map
-  private String resolveUri() {
+    Map<String, String> config = new HashMap<>(additionalConfig);
    config.put("header.x-lancedb-database", database);
    config.put("header.x-api-key", apiKey);
    // Determine base URL
    String uri;
    if (endpoint.isPresent()) {
-      return endpoint.get();
+      uri = endpoint.get();
    } else {
      String effectiveRegion = region.orElse(DEFAULT_REGION);
      uri = String.format(CLOUD_URL_PATTERN, database, effectiveRegion);
    }
-    return String.format(CLOUD_URL_PATTERN, database, region.orElse(DEFAULT_REGION));
+    config.put("uri", uri);
    return LanceNamespace.connect("rest", config, null);
  }
 }
@@ -1,119 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import org.apache.hc.client5.http.classic.methods.HttpPost;
 import org.apache.hc.client5.http.impl.classic.CloseableHttpClient;
 import org.apache.hc.client5.http.impl.classic.HttpClients;
 import org.apache.hc.core5.http.ContentType;
 import org.apache.hc.core5.http.io.entity.EntityUtils;
 import org.apache.hc.core5.http.io.entity.StringEntity;
 import java.io.Closeable;
 import java.io.IOException;
 import java.io.UncheckedIOException;
 /**
 * Minimal HTTP client for LanceDB Cloud and Enterprise routes that the Lance Namespace
 * specification does not cover.
 *
 * <p>Most table operations reach LanceDB through {@link org.lance.namespace.LanceNamespace}, which
 * is generated from the namespace spec. A handful of routes — the MemWAL LSM write path in
 * particular — are served by the same endpoint but are not part of that spec, so they are issued
 * directly here. See {@link LanceDbTableLsm}.
 *
 * <p>Obtain one from {@link LanceDbNamespaceClientBuilder#buildRestClient()}.
 */
 public class LanceDbRestClient implements Closeable {
  private static final ObjectMapper MAPPER = new ObjectMapper();
  private final String baseUri;
  private final String apiKey;
  private final String database;
  private final CloseableHttpClient http;
  LanceDbRestClient(String baseUri, String apiKey, String database) {
    this.baseUri = baseUri.endsWith("/") ? baseUri.substring(0, baseUri.length() - 1) : baseUri;
    this.apiKey = apiKey;
    this.database = database;
    // Automatic retries off, deliberately. The default strategy retries 429 and 503 —
    // exactly the two statuses LanceDbTableLsm.checkpointLsm() acts on — which would
    // silently double its explicit retry budget and would also retry compact_lsm in
    // place, where the loop is designed to fall through to a fresh stats poll instead.
    // The checkpoint loop owns the 421/429/503 transitions; the transport must not.
    this.http = HttpClients.custom().disableAutomaticRetries().build();
  }
  /**
   * POST {@code path}, sending {@code body} as JSON when it is non-null.
   *
   * @param path Absolute request path, beginning with {@code /}.
   * @param body Object to serialize as the request body, or null to send no body.
   * @return The parsed response body, or null when the response carried no content.
   * @throws HttpException if the server returned a non-2xx status.
   */
  public JsonNode post(String path, Object body) {
    HttpPost request = new HttpPost(baseUri + path);
    request.setHeader("x-api-key", apiKey);
    request.setHeader("x-lancedb-database", database);
    try {
      if (body != null) {
        request.setEntity(
            new StringEntity(MAPPER.writeValueAsString(body), ContentType.APPLICATION_JSON));
      }
      return http.execute(
          request,
          response -> {
            String text =
                response.getEntity() == null ? "" : EntityUtils.toString(response.getEntity());
            int status = response.getCode();
            if (status < 200 || status >= 300) {
              throw new HttpException(status, "LanceDB request to " + path + " failed: " + text);
            }
            return text.isEmpty() ? null : MAPPER.readTree(text);
          });
    } catch (IOException e) {
      throw new UncheckedIOException("LanceDB request to " + path + " failed", e);
    }
  }
  @Override
  public void close() throws IOException {
    http.close();
  }
  /**
   * A non-2xx response.
   *
   * <p>The status is exposed because callers act on it: {@link LanceDbTableLsm#checkpointLsm()}
   * treats 429 and 503 as retryable and 421 as a lost node claim.
   */
  public static class HttpException extends RuntimeException {
    private static final long serialVersionUID = 1L;
    private final int statusCode;
    public HttpException(int statusCode, String message) {
      super(message);
      this.statusCode = statusCode;
    }
    /** The HTTP status the failed response carried. */
    public int statusCode() {
      return statusCode;
    }
  }
 }
@@ -1,394 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.HashMap;
 import java.util.LinkedHashMap;
 import java.util.Map;
 import java.util.Optional;
 import java.util.OptionalLong;
 /**
 * The MemWAL LSM write path for one LanceDB Cloud or Enterprise table.
 *
 * <p>Installing an {@link LsmWriteSpec} routes {@code mergeInsert} upserts through Lance's MemWAL —
 * an LSM-style append — instead of the standard merge path. Rows land in an in-memory memtable,
 * seal into L0 generations, and are merged into the base table by compaction.
 *
 * <p>These routes are not part of the Lance Namespace specification, so they are issued directly
 * rather than through {@link org.lance.namespace.LanceNamespace}.
 *
 * <pre>{@code
 * LanceDbRestClient client = LanceDbNamespaceClientBuilder.newBuilder()
 *     .apiKey("your_lancedb_cloud_api_key")
 *     .database("your_database_name")
 *     .buildRestClient();
 *
 * LanceDbTableLsm lsm = new LanceDbTableLsm(client, "my_table");
 * lsm.setLsmWriteSpec(LsmWriteSpec.bucket("id", 16));
 * // ... merge_insert traffic ...
 * lsm.checkpointLsm();
 * }</pre>
 */
 public class LanceDbTableLsm {
  /**
   * Interval between {@code get_lsm_stats} polls during a checkpoint. One interval is roughly one
   * compaction pass, the granularity at which the answer can change.
   */
  private static final long POLL_INTERVAL_MS = 5_000L;
  /**
   * Cap on re-issues from {@code flushLsm} after a 421, so a crash-looping node cannot turn flush →
   * compact → 421 → flush into a spin.
   *
   * <p>Deliberately not shared with {@link #MAX_RETRIES}: a claim that keeps evaporating is a
   * broken node, while contention is routine and wants a real budget.
   */
  private static final int MAX_REISSUES = 3;
  /**
   * Retryable faults tolerated on a <em>single</em> request, reset on every success — scattered
   * contention across a long checkpoint must not accumulate toward a cap.
   */
  private static final int MAX_RETRIES = 8;
  private static final long RETRY_BACKOFF_BASE_MS = 100L;
  private static final long RETRY_BACKOFF_MAX_MS = 5_000L;
  private final LanceDbRestClient client;
  private final String tableIdentifier;
  /**
   * Bind the LSM routes for one table.
   *
   * @param client Transport for the LanceDB endpoint.
   * @param tableIdentifier The table's full identifier, {@code $}-delimited when it sits inside a
   *     namespace, such as {@code analytics$events}.
   */
  public LanceDbTableLsm(LanceDbRestClient client, String tableIdentifier) {
    if (client == null) {
      throw new IllegalArgumentException("Client cannot be null");
    }
    if (tableIdentifier == null || tableIdentifier.trim().isEmpty()) {
      throw new IllegalArgumentException("Table identifier cannot be null or empty");
    }
    this.client = client;
    this.tableIdentifier = tableIdentifier;
  }
  /**
   * Install an {@link LsmWriteSpec} on this table, selecting the MemWAL LSM write path for future
   * {@code mergeInsert} calls.
   *
   * <p>All variants require the table to have an unenforced primary key; bucket sharding
   * additionally requires it to be the single column being bucketed.
   */
  public void setLsmWriteSpec(LsmWriteSpec spec) {
    if (spec == null) {
      throw new IllegalArgumentException("Spec cannot be null");
    }
    client.post(route("set_lsm_write_spec"), spec.toRequestBody());
  }
  /**
   * Remove the {@link LsmWriteSpec} from this table, reverting to the standard {@code mergeInsert}
   * write path.
   *
   * <p>Errors if no spec is currently set.
   */
  public void unsetLsmWriteSpec() {
    client.post(route("unset_lsm_write_spec"), null);
  }
  /**
   * Read the {@link LsmWriteSpec} currently installed on this table.
   *
   * <p>Empty when the LSM write path is not enabled. The returned spec mirrors what was installed,
   * except that {@link LsmWriteSpec#maintainedIndexes()} always reports the concrete list resolved
   * when the spec was set — a null selection never round-trips.
   */
  public Optional<LsmWriteSpec> getLsmWriteSpec() {
    JsonNode response = client.post(route("get_lsm_write_spec"), null);
    if (response == null || !response.hasNonNull("lsm_write_spec")) {
      return Optional.empty();
    }
    return Optional.of(LsmWriteSpec.fromJson(response.get("lsm_write_spec")));
  }
  /**
   * Seal every bucket's active memtable into a new L0 generation.
   *
   * <p>Returns once the seal is committed. Sealing an empty memtable is a no-op, so this is safe to
   * call repeatedly.
   */
  public void flushLsm() {
    client.post(route("flush_lsm"), null);
  }
  /**
   * Trigger a background L0 → base compaction pass per bucket.
   *
   * <p>Returns once the passes are <em>dispatched</em>, not once they finish — watch {@link
   * #getLsmStats}, or use {@link #checkpointLsm} to wait for convergence.
   */
  public void compactLsm() {
    client.post(route("compact_lsm"), null);
  }
  /**
   * Read live per-bucket LSM state.
   *
   * <p>Answers "how far behind is my fresh tier", "which bucket is hot", and "why is my fresh-tier
   * vector search brute-force". Mutates no table state.
   *
   * <p>Empty only when the LSM write path is not enabled — that is, when the server sends an absent
   * or null {@code lsm_stats}. A stats object that is present is decoded strictly, and a malformed
   * one throws rather than decoding to something empty, because {@link #checkpointLsm} reads
   * convergence out of these numbers and cannot tell a defaulted array from a drained one.
   *
   * @param includeGenerationRows Also count rows per L0 generation. Off by default because each
   *     count opens an uncached Lance dataset.
   * @throws IllegalStateException if the response is absent or does not decode.
   */
  public Optional<LsmStats> getLsmStats(boolean includeGenerationRows) {
    Map<String, Object> body = new LinkedHashMap<String, Object>();
    body.put("include_generation_rows", includeGenerationRows);
    JsonNode response = client.post(route("get_lsm_stats"), body);
    if (response == null) {
      throw new IllegalStateException("get_lsm_stats returned an empty response body");
    }
    JsonNode stats = response.get("lsm_stats");
    if (stats == null || stats.isNull()) {
      return Optional.empty();
    }
    return Optional.of(LsmStats.fromJson(stats));
  }
  /** Equivalent to {@code getLsmStats(false)}. */
  public Optional<LsmStats> getLsmStats() {
    return getLsmStats(false);
  }
  /**
   * Converge this table's LSM write path into its base table.
   *
   * <p>Seals once, fixes a target watermark from the resulting L0, then triggers compaction and
   * polls until that L0 is gone. The target set is fixed at the start, so generations created
   * <em>during</em> the checkpoint are ignored — that is what lets it terminate under write load,
   * and what makes it best-effort: it converges the fresh tier as of some instant. Idempotent,
   * abandonable at any point, safe on a cadence.
   *
   * <p>The loop runs here, not on the server: {@link #compactLsm} dispatches a pass and returns, so
   * nothing holds a socket and a client can vanish mid-operation with nothing to reconcile.
   * Completion is read from generation numbers in the shard manifest — durable state, unlike a
   * count in a compact response, which a concurrent write invalidates.
   *
   * <p>No liveness bound — the caller owns the deadline. The compactor pool is shared across
   * tables, so a checkpoint queued behind unrelated work looks exactly like one that is merging.
   */
  public void checkpointLsm() {
    for (int reissue = 0; reissue <= MAX_REISSUES; reissue++) {
      // The seal turns everything written before this call into a generation, so the
      // watermark has to be read after it. Idempotent: sealing an empty memtable is a
      // no-op, so a re-issue does not churn empty generations.
      if (issueVoid(this::flushLsm)) {
        backoff(reissue);
        continue;
      }
      Attempt<Optional<LsmStats>> stats = issue(() -> getLsmStats(false));
      if (stats.lostClaim) {
        backoff(reissue);
        continue;
      }
      if (!stats.value.isPresent()) {
        // Not WAL-backed; flushLsm would have errored first but for a race.
        return;
      }
      Map<String, Long> targets = newestGenerations(stats.value.get());
      if (targets.isEmpty()) {
        return;
      }
      if (drainToTargets(targets)) {
        return;
      }
      backoff(reissue);
    }
    throw new IllegalStateException(
        "checkpointLsm: the owning node kept losing its claim; re-issued from flush the maximum "
            + "number of times");
  }
  /**
   * Trigger and poll until no bucket holds a generation at or below its target.
   *
   * @return true when the drain finished, false when the table needs re-claiming from flush.
   */
  private boolean drainToTargets(Map<String, Long> targets) {
    while (true) {
      Attempt<Optional<LsmStats>> stats = issue(() -> getLsmStats(false));
      if (stats.lostClaim) {
        return false;
      }
      if (!stats.value.isPresent()) {
        return true;
      }
      // `compacting` is the bucket's compaction latch, held from dispatch until the pass
      // ends — including while it waits on a pod-wide permit. So it answers one question
      // only: do not pile on. Buckets with nothing outstanding are skipped, not counted
      // as idle.
      long outstanding = 0;
      boolean allCompacting = true;
      for (BucketStats bucket : stats.value.get().buckets()) {
        Long target = targets.get(bucket.shardId());
        if (target == null) {
          continue;
        }
        long remaining = bucket.outstandingGenerations(target);
        if (remaining > 0) {
          outstanding += remaining;
          allCompacting &= bucket.compacting();
        }
      }
      if (outstanding == 0) {
        return true;
      }
      if (!allCompacting) {
        try {
          compactLsm();
        } catch (LanceDbRestClient.HttpException e) {
          if (isLostClaim(e)) {
            return false;
          }
          if (!isRetryable(e)) {
            throw e;
          }
          // A 429 here means the server could latch no bucket at all, which the poll
          // above already handles. Not retried in place: the latch it would contend for
          // is the one doing the work, so fall through and re-read — POLL_INTERVAL_MS is
          // the backoff.
        }
      }
      sleep(POLL_INTERVAL_MS);
    }
  }
  /** The newest generation held by each bucket, skipping buckets holding none. */
  private static Map<String, Long> newestGenerations(LsmStats stats) {
    Map<String, Long> targets = new HashMap<String, Long>();
    for (BucketStats bucket : stats.buckets()) {
      OptionalLong newest = bucket.newestGeneration();
      if (newest.isPresent()) {
        targets.put(bucket.shardId(), newest.getAsLong());
      }
    }
    return targets;
  }
  /**
   * 429 (latch held, pool saturated, or the pod replaying its WAL) and 503 (a draining node, or a
   * proxy between here and it).
   */
  private static boolean isRetryable(LanceDbRestClient.HttpException e) {
    return e.statusCode() == 429 || e.statusCode() == 503;
  }
  /**
   * 421: the owning node holds no claim. Only {@code flush} re-claims and replays, so this cannot
   * be retried in place — the caller has to start over.
   */
  private static boolean isLostClaim(LanceDbRestClient.HttpException e) {
    return e.statusCode() == 421;
  }
  /**
   * Issue one LSM request, retrying in place while the fault is retryable.
   *
   * <p>The two recoverable faults have separate budgets: contention clears on its own and retries
   * here against {@link #MAX_RETRIES}, while a 421 needs {@code flush} to re-claim, which only the
   * caller can drive.
   *
   * <p>An exhausted budget propagates the last error as itself rather than a synthesized one — "429
   * after nine tries" beats "checkpoint failed".
   */
  private static <T> Attempt<T> issue(Call<T> call) {
    int retries = 0;
    while (true) {
      try {
        return new Attempt<T>(call.run(), false);
      } catch (LanceDbRestClient.HttpException e) {
        if (isLostClaim(e)) {
          return new Attempt<T>(null, true);
        }
        if (!isRetryable(e) || retries >= MAX_RETRIES) {
          throw e;
        }
        backoff(retries);
        retries++;
      }
    }
  }
  /** {@link #issue} for a call with no return value. Returns true when the claim was lost. */
  private static boolean issueVoid(Runnable call) {
    return issue(
            () -> {
              call.run();
              return Boolean.TRUE;
            })
        .lostClaim;
  }
  /** Sleep before re-issuing a retryable request. Doubles up to {@link #RETRY_BACKOFF_MAX_MS}. */
  private static void backoff(int attempt) {
    long delay = RETRY_BACKOFF_BASE_MS << Math.min(attempt, 8);
    sleep(Math.min(delay, RETRY_BACKOFF_MAX_MS));
  }
  private static void sleep(long millis) {
    try {
      Thread.sleep(millis);
    } catch (InterruptedException e) {
      Thread.currentThread().interrupt();
      throw new IllegalStateException("Interrupted while waiting on the LSM checkpoint", e);
    }
  }
  private String route(String operation) {
    return "/v1/table/" + tableIdentifier + "/" + operation + "/";
  }
  /** What one LSM request produced: its value, or word that the owning node holds no claim. */
  private static final class Attempt<T> {
    private final T value;
    private final boolean lostClaim;
    private Attempt(T value, boolean lostClaim) {
      this.value = value;
      this.lostClaim = lostClaim;
    }
  }
  @FunctionalInterface
  private interface Call<T> {
    T run();
  }
 }
@@ -1,56 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
 /**
 * Live per-bucket LSM state, as returned by {@link LanceDbTableLsm#getLsmStats()}.
 *
 * <p>Nothing here is derived: sums and differences (total L0 bytes, WAL lag) are the caller's to
 * compute. There is no "LSM is off" shape — that case is an empty {@link java.util.Optional},
 * because a stats object of zeros would read as measurements.
 */
 public class LsmStats {
  private static final String CONTEXT = "lsm stats";
  private final List<BucketStats> buckets;
  LsmStats(List<BucketStats> buckets) {
    this.buckets = Collections.unmodifiableList(buckets);
  }
  /** One entry per bucket. */
  public List<BucketStats> buckets() {
    return buckets;
  }
  static LsmStats fromJson(JsonNode node) {
    JsonFields.requiredObject(node, CONTEXT);
    List<BucketStats> buckets = new ArrayList<BucketStats>();
    for (JsonNode bucket : JsonFields.requiredArray(node, "buckets", CONTEXT)) {
      buckets.add(BucketStats.fromJson(bucket));
    }
    return new LsmStats(buckets);
  }
  @Override
  public String toString() {
    return "LsmStats{buckets=" + buckets + "}";
  }
 }
@@ -1,260 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.HashMap;
 import java.util.LinkedHashMap;
 import java.util.List;
 import java.util.Map;
 /**
 * Specification selecting Lance's MemWAL LSM-style write path for {@code mergeInsert}.
 *
 * <p>Construct via {@link #bucket}, {@link #identity}, or {@link #unsharded}, then optionally chain
 * {@link #withMaintainedIndexes} and {@link #withWriterConfigDefaults}. Install it with {@link
 * LanceDbTableLsm#setLsmWriteSpec} and remove it with {@link LanceDbTableLsm#unsetLsmWriteSpec}.
 *
 * <p>This is deliberately not {@code org.lance.memwal.InitializeMemWalParams}. That type is Lance's
 * own, and its maintained-index default is the opposite of this one: it defaults to maintaining
 * <em>nothing</em>, while a fresh spec here maintains <em>every</em> index. It also cannot express
 * the null that asks the server to resolve the set.
 */
 public class LsmWriteSpec {
  /** How writes are routed to MemWAL shards. */
  public enum Sharding {
    /** Hash-bucket writes by a scalar column. */
    BUCKET("bucket"),
    /** Shard by the raw value of a scalar column. */
    IDENTITY("identity"),
    /** Route every write to a single shard. */
    UNSHARDED("unsharded");
    private final String wireName;
    Sharding(String wireName) {
      this.wireName = wireName;
    }
    String wireName() {
      return wireName;
    }
    static Sharding fromWireName(String name) {
      for (Sharding s : values()) {
        if (s.wireName.equals(name)) {
          return s;
        }
      }
      throw new IllegalArgumentException("Unknown sharding mode: " + name);
    }
  }
  private final Sharding sharding;
  private final String column;
  private final Integer numBuckets;
  private final List<String> maintainedIndexes;
  private final Map<String, String> writerConfigDefaults;
  private LsmWriteSpec(
      Sharding sharding,
      String column,
      Integer numBuckets,
      List<String> maintainedIndexes,
      Map<String, String> writerConfigDefaults) {
    this.sharding = sharding;
    this.column = column;
    this.numBuckets = numBuckets;
    this.maintainedIndexes = maintainedIndexes;
    this.writerConfigDefaults = writerConfigDefaults;
  }
  /**
   * Hash-bucket sharding by a scalar column, maintaining every index on the table.
   *
   * <p>Iceberg-compatible Murmur3-x86-32 (seed 0) is used, so each row's {@code bucket(column,
   * numBuckets)} value is stable across processes.
   *
   * @param column A non-nested column with a supported scalar type.
   * @param numBuckets The number of buckets, in {@code [1, 1024]}.
   */
  public static LsmWriteSpec bucket(String column, int numBuckets) {
    if (column == null || column.trim().isEmpty()) {
      throw new IllegalArgumentException("Column cannot be null or empty");
    }
    return new LsmWriteSpec(
        Sharding.BUCKET, column, numBuckets, null, new HashMap<String, String>());
  }
  /**
   * Identity sharding — shard by the raw value of {@code column} — maintaining every index on the
   * table.
   *
   * <p>{@code column} must be a deterministic function of the unenforced primary key: every row
   * with a given primary key must always produce the same {@code column} value, or upserts of that
   * key can land in different shards and a stale version can win.
   */
  public static LsmWriteSpec identity(String column) {
    if (column == null || column.trim().isEmpty()) {
      throw new IllegalArgumentException("Column cannot be null or empty");
    }
    return new LsmWriteSpec(Sharding.IDENTITY, column, null, null, new HashMap<String, String>());
  }
  /** No sharding — every write goes to a single MemWAL shard — maintaining every index. */
  public static LsmWriteSpec unsharded() {
    return new LsmWriteSpec(Sharding.UNSHARDED, null, null, null, new HashMap<String, String>());
  }
  /**
   * Set the indexes the MemWAL keeps up to date as rows are appended.
   *
   * <p>Pass {@code null} — the default for a fresh spec — to maintain every index the MemWAL can,
   * resolved when the spec is installed. That is a snapshot: indexes created later are not
   * maintained until the spec is unset and set again. Pass an empty list to maintain none.
   *
   * <p>Note that {@code null} and the empty list mean opposite things here.
   */
  public LsmWriteSpec withMaintainedIndexes(List<String> maintainedIndexes) {
    return new LsmWriteSpec(
        sharding,
        column,
        numBuckets,
        maintainedIndexes == null ? null : new ArrayList<String>(maintainedIndexes),
        writerConfigDefaults);
  }
  /**
   * Set default {@code ShardWriter} configuration recorded in the MemWAL index.
   *
   * <p>A sparse override map — only the keys you set are recorded. Recognized keys include {@code
   * durable_write}, {@code max_wal_buffer_size}, {@code max_memtable_size}, {@code
   * max_memtable_rows}, {@code max_memtable_batches}, {@code manifest_scan_batch_size}, {@code
   * max_unflushed_memtable_bytes}, and {@code enable_memtable}. Duration knobs carry an {@code _ms}
   * suffix, such as {@code max_wal_flush_interval_ms}.
   */
  public LsmWriteSpec withWriterConfigDefaults(Map<String, String> writerConfigDefaults) {
    if (writerConfigDefaults == null) {
      throw new IllegalArgumentException("writerConfigDefaults cannot be null");
    }
    return new LsmWriteSpec(
        sharding,
        column,
        numBuckets,
        maintainedIndexes,
        new HashMap<String, String>(writerConfigDefaults));
  }
  /** How writes are routed to shards. */
  public Sharding sharding() {
    return sharding;
  }
  /** The sharding column for {@link Sharding#BUCKET} and {@link Sharding#IDENTITY}, else null. */
  public String column() {
    return column;
  }
  /** The bucket count for {@link Sharding#BUCKET}, else null. */
  public Integer numBuckets() {
    return numBuckets;
  }
  /**
   * The indexes the MemWAL maintains, or null to have the server resolve every maintainable index
   * on install. An empty list means none.
   */
  public List<String> maintainedIndexes() {
    return maintainedIndexes == null ? null : Collections.unmodifiableList(maintainedIndexes);
  }
  /** Default {@code ShardWriter} configuration recorded in the MemWAL index. */
  public Map<String, String> writerConfigDefaults() {
    return Collections.unmodifiableMap(writerConfigDefaults);
  }
  /** Render this spec as the {@code set_lsm_write_spec} request body. */
  Map<String, Object> toRequestBody() {
    Map<String, Object> shardingBody = new LinkedHashMap<String, Object>();
    shardingBody.put("mode", sharding.wireName());
    if (column != null) {
      shardingBody.put("column", column);
    }
    if (numBuckets != null) {
      shardingBody.put("num_buckets", numBuckets);
    }
    Map<String, Object> body = new LinkedHashMap<String, Object>();
    body.put("sharding", shardingBody);
    // Null is meaningful: it asks the server to resolve every maintainable index.
    body.put("maintained_indexes", maintainedIndexes);
    body.put("writer_config_defaults", writerConfigDefaults);
    return body;
  }
  /**
   * Rebuild a spec from a {@code get_lsm_write_spec} response body.
   *
   * <p>The server always reports a concrete maintained-index list, so a null selection never
   * round-trips.
   */
  static LsmWriteSpec fromJson(JsonNode node) {
    JsonNode shardingNode = node.get("sharding");
    if (shardingNode == null || shardingNode.get("mode") == null) {
      throw new IllegalStateException("get_lsm_write_spec response has no sharding mode");
    }
    Sharding sharding = Sharding.fromWireName(shardingNode.get("mode").asText());
    String column = shardingNode.hasNonNull("column") ? shardingNode.get("column").asText() : null;
    Integer numBuckets =
        shardingNode.hasNonNull("num_buckets") ? shardingNode.get("num_buckets").asInt() : null;
    List<String> maintainedIndexes = new ArrayList<String>();
    JsonNode indexesNode = node.get("maintained_indexes");
    if (indexesNode != null && indexesNode.isArray()) {
      for (JsonNode index : indexesNode) {
        maintainedIndexes.add(index.asText());
      }
    }
    Map<String, String> defaults = new HashMap<String, String>();
    JsonNode defaultsNode = node.get("writer_config_defaults");
    if (defaultsNode != null && defaultsNode.isObject()) {
      defaultsNode
          .fieldNames()
          .forEachRemaining(name -> defaults.put(name, defaultsNode.get(name).asText()));
    }
    return new LsmWriteSpec(sharding, column, numBuckets, maintainedIndexes, defaults);
  }
  @Override
  public String toString() {
    return "LsmWriteSpec{sharding="
        + sharding
        + ", column="
        + column
        + ", numBuckets="
        + numBuckets
        + ", maintainedIndexes="
        + maintainedIndexes
        + ", writerConfigDefaults="
        + writerConfigDefaults
        + "}";
  }
 }
@@ -1,99 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
 /** One in-memory memtable. */
 public class MemtableStats {
  private static final String CONTEXT = "memtable stats";
  private final long generation;
  private final long rows;
  private final long bytes;
  private final long batches;
  private final List<String> indexes;
  MemtableStats(long generation, long rows, long bytes, long batches, List<String> indexes) {
    this.generation = generation;
    this.rows = rows;
    this.bytes = bytes;
    this.batches = batches;
    this.indexes = Collections.unmodifiableList(indexes);
  }
  /** The generation this memtable will become once sealed. */
  public long generation() {
    return generation;
  }
  /** Rows currently buffered. */
  public long rows() {
    return rows;
  }
  /** Estimated in-memory size. */
  public long bytes() {
    return bytes;
  }
  /** Record batches currently buffered. */
  public long batches() {
    return batches;
  }
  /**
   * Names of the indexes this memtable carries. An absent name is the whole answer to "why is my
   * fresh-tier search on that column brute-force".
   */
  public List<String> indexes() {
    return indexes;
  }
  static MemtableStats fromJson(JsonNode node) {
    JsonFields.requiredObject(node, CONTEXT);
    List<String> indexes = new ArrayList<String>();
    for (JsonNode index : JsonFields.requiredArray(node, "indexes", CONTEXT)) {
      if (!index.isTextual()) {
        throw new IllegalStateException(CONTEXT + " has a non-string index name: " + index);
      }
      indexes.add(index.asText());
    }
    return new MemtableStats(
        JsonFields.requiredLong(node, "generation", CONTEXT),
        JsonFields.requiredLong(node, "rows", CONTEXT),
        JsonFields.requiredLong(node, "bytes", CONTEXT),
        JsonFields.requiredLong(node, "batches", CONTEXT),
        indexes);
  }
  @Override
  public String toString() {
    return "MemtableStats{generation="
        + generation
        + ", rows="
        + rows
        + ", bytes="
        + bytes
        + ", batches="
        + batches
        + ", indexes="
        + indexes
        + "}";
  }
 }
@@ -1,570 +0,0 @@
 /*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 package com.lancedb;
 import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import com.sun.net.httpserver.HttpServer;
 import org.junit.jupiter.api.AfterEach;
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 import java.io.ByteArrayOutputStream;
 import java.io.IOException;
 import java.io.InputStream;
 import java.io.UncheckedIOException;
 import java.net.InetSocketAddress;
 import java.nio.charset.StandardCharsets;
 import java.util.ArrayDeque;
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.Collections;
 import java.util.Deque;
 import java.util.HashMap;
 import java.util.LinkedHashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 import java.util.concurrent.ConcurrentHashMap;
 import static org.junit.jupiter.api.Assertions.*;
 /**
 * Unit tests for the MemWAL LSM routes, run against a scripted local HTTP server.
 *
 * <p>The wire assertions mirror the Rust mocked-endpoint tests in {@code
 * rust/lancedb/src/remote/table.rs}, which are the contract these routes have to match.
 */
 public class LanceDbTableLsmTest {
  private static final ObjectMapper MAPPER = new ObjectMapper();
  private HttpServer server;
  private LanceDbRestClient client;
  private LanceDbTableLsm lsm;
  private final List<String> requestPaths = Collections.synchronizedList(new ArrayList<String>());
  private final List<String> requestBodies = Collections.synchronizedList(new ArrayList<String>());
  private final Map<String, Deque<Reply>> replies = new ConcurrentHashMap<String, Deque<Reply>>();
  @BeforeEach
  public void setUp() throws IOException {
    start();
  }
  /** Tear down and restart the scripted server, for a test that scripts several exchanges. */
  private void setUpFresh() {
    try {
      client.close();
      server.stop(0);
      requestPaths.clear();
      requestBodies.clear();
      replies.clear();
      start();
    } catch (IOException e) {
      throw new UncheckedIOException(e);
    }
  }
  private void start() throws IOException {
    server = HttpServer.create(new InetSocketAddress("127.0.0.1", 0), 0);
    server.createContext(
        "/",
        exchange -> {
          String path = exchange.getRequestURI().getPath();
          requestPaths.add(path);
          requestBodies.add(readAll(exchange.getRequestBody()));
          Reply reply = nextReply(path);
          byte[] out = reply.body.getBytes(StandardCharsets.UTF_8);
          exchange.sendResponseHeaders(reply.status, out.length == 0 ? -1 : out.length);
          if (out.length > 0) {
            exchange.getResponseBody().write(out);
          }
          exchange.close();
        });
    server.start();
    client =
        LanceDbNamespaceClientBuilder.newBuilder()
            .apiKey("test-key")
            .database("test-db")
            .endpoint("http://127.0.0.1:" + server.getAddress().getPort())
            .buildRestClient();
    lsm = new LanceDbTableLsm(client, "my_table");
  }
  @AfterEach
  public void tearDown() throws IOException {
    client.close();
    server.stop(0);
  }
  // ===========================================================================
  // set / unset / get spec
  // ===========================================================================
  @Test
  public void testSetLsmWriteSpecUnsharded() throws Exception {
    enqueue("set_lsm_write_spec", 200, "");
    lsm.setLsmWriteSpec(LsmWriteSpec.unsharded());
    assertEquals("/v1/table/my_table/set_lsm_write_spec/", requestPaths.get(0));
    JsonNode body = MAPPER.readTree(requestBodies.get(0));
    assertEquals("unsharded", body.get("sharding").get("mode").asText());
    assertFalse(body.get("sharding").has("column"));
    assertFalse(body.get("sharding").has("num_buckets"));
  }
  @Test
  public void testSetLsmWriteSpecBucket() throws Exception {
    enqueue("set_lsm_write_spec", 200, "");
    lsm.setLsmWriteSpec(
        LsmWriteSpec.bucket("id", 16).withMaintainedIndexes(Arrays.asList("id_idx")));
    JsonNode body = MAPPER.readTree(requestBodies.get(0));
    assertEquals("bucket", body.get("sharding").get("mode").asText());
    assertEquals("id", body.get("sharding").get("column").asText());
    assertEquals(16, body.get("sharding").get("num_buckets").asInt());
    assertEquals(1, body.get("maintained_indexes").size());
    assertEquals("id_idx", body.get("maintained_indexes").get(0).asText());
  }
  @Test
  public void testSetLsmWriteSpecIdentity() throws Exception {
    enqueue("set_lsm_write_spec", 200, "");
    lsm.setLsmWriteSpec(LsmWriteSpec.identity("tenant"));
    JsonNode body = MAPPER.readTree(requestBodies.get(0));
    assertEquals("identity", body.get("sharding").get("mode").asText());
    assertEquals("tenant", body.get("sharding").get("column").asText());
    assertFalse(body.get("sharding").has("num_buckets"));
  }
  /**
   * The tri-state that motivated a LanceDB-owned spec type: a null selection asks the server to
   * resolve every maintainable index, while an empty list asks for none. They must not collapse.
   */
  @Test
  public void testMaintainedIndexesNullAndEmptyAreDistinctOnTheWire() throws Exception {
    enqueue("set_lsm_write_spec", 200, "");
    lsm.setLsmWriteSpec(LsmWriteSpec.unsharded());
    JsonNode fresh = MAPPER.readTree(requestBodies.get(0));
    assertTrue(fresh.has("maintained_indexes"), "the key must be present");
    assertTrue(fresh.get("maintained_indexes").isNull(), "a fresh spec sends null, not []");
    lsm.setLsmWriteSpec(
        LsmWriteSpec.unsharded().withMaintainedIndexes(Collections.<String>emptyList()));
    JsonNode none = MAPPER.readTree(requestBodies.get(1));
    assertTrue(none.get("maintained_indexes").isArray());
    assertEquals(0, none.get("maintained_indexes").size());
  }
  @Test
  public void testSetLsmWriteSpecWriterConfigDefaults() throws Exception {
    enqueue("set_lsm_write_spec", 200, "");
    Map<String, String> defaults = new HashMap<String, String>();
    defaults.put("max_memtable_rows", "50000");
    lsm.setLsmWriteSpec(LsmWriteSpec.unsharded().withWriterConfigDefaults(defaults));
    JsonNode body = MAPPER.readTree(requestBodies.get(0));
    assertEquals("50000", body.get("writer_config_defaults").get("max_memtable_rows").asText());
  }
  @Test
  public void testUnsetLsmWriteSpec() {
    enqueue("unset_lsm_write_spec", 200, "");
    lsm.unsetLsmWriteSpec();
    assertEquals("/v1/table/my_table/unset_lsm_write_spec/", requestPaths.get(0));
    assertEquals("", requestBodies.get(0));
  }
  @Test
  public void testGetLsmWriteSpec() {
    enqueue(
        "get_lsm_write_spec",
        200,
        "{\"lsm_write_spec\":{\"sharding\":{\"mode\":\"bucket\",\"column\":\"id\","
            + "\"num_buckets\":16},\"maintained_indexes\":[\"id_idx\"],"
            + "\"writer_config_defaults\":{\"durable_write\":\"true\"}}}");
    Optional<LsmWriteSpec> spec = lsm.getLsmWriteSpec();
    assertTrue(spec.isPresent());
    assertEquals(LsmWriteSpec.Sharding.BUCKET, spec.get().sharding());
    assertEquals("id", spec.get().column());
    assertEquals(Integer.valueOf(16), spec.get().numBuckets());
    assertEquals(Arrays.asList("id_idx"), spec.get().maintainedIndexes());
    assertEquals("true", spec.get().writerConfigDefaults().get("durable_write"));
  }
  @Test
  public void testGetLsmWriteSpecAbsent() {
    enqueue("get_lsm_write_spec", 200, "{\"lsm_write_spec\":null}");
    assertFalse(lsm.getLsmWriteSpec().isPresent());
  }
  // ===========================================================================
  // stats
  // ===========================================================================
  @Test
  public void testGetLsmStats() throws Exception {
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false, 7L, 8L)));
    Optional<LsmStats> got = lsm.getLsmStats(true);
    assertEquals("/v1/table/my_table/get_lsm_stats/", requestPaths.get(0));
    assertTrue(MAPPER.readTree(requestBodies.get(0)).get("include_generation_rows").asBoolean());
    assertTrue(got.isPresent());
    BucketStats decoded = got.get().buckets().get(0);
    assertEquals("shard-0", decoded.shardId());
    assertEquals("Active", decoded.status());
    assertEquals(1, decoded.writerEpoch());
    assertEquals(2, decoded.manifestVersion());
    assertEquals(9, decoded.currentGeneration());
    assertFalse(decoded.compacting());
    assertEquals(Arrays.asList(7L, 8L), generationNumbers(decoded));
    assertEquals(1024, decoded.generations().get(0).bytes());
    assertFalse(decoded.generations().get(0).rows().isPresent(), "rows absent unless requested");
    assertFalse(decoded.memtables().isPresent(), "absent memtables stay absent");
  }
  /** The optional fields decode when the server does send them. */
  @Test
  public void testGetLsmStatsDecodesOptionalFields() {
    enqueue(
        "get_lsm_stats",
        200,
        "{\"lsm_stats\":{\"buckets\":[{\"shard_id\":\"shard-0\",\"status\":\"Active\","
            + "\"writer_epoch\":1,\"manifest_version\":2,\"current_generation\":9,"
            + "\"replay_after_wal_entry_position\":3,\"wal_entry_position_last_seen\":11,"
            + "\"generations\":[{\"generation\":7,\"bytes\":1024,\"rows\":42}],"
            + "\"compacting\":true,\"memtables\":[{\"generation\":8,\"rows\":5,"
            + "\"bytes\":64,\"batches\":2,\"indexes\":[\"id_idx\"]}]}]}}");
    BucketStats decoded = lsm.getLsmStats(true).get().buckets().get(0);
    assertEquals(3, decoded.replayAfterWalEntryPosition());
    assertEquals(11, decoded.walEntryPositionLastSeen());
    assertTrue(decoded.compacting());
    assertEquals(42, decoded.generations().get(0).rows().getAsLong());
    assertTrue(decoded.memtables().isPresent());
    MemtableStats memtable = decoded.memtables().get().get(0);
    assertEquals(8, memtable.generation());
    assertEquals(5, memtable.rows());
    assertEquals(64, memtable.bytes());
    assertEquals(2, memtable.batches());
    assertEquals(Arrays.asList("id_idx"), memtable.indexes());
  }
  @Test
  public void testGetLsmStatsAbsentWhenLsmDisabled() {
    enqueue("get_lsm_stats", 200, "{\"lsm_stats\":null}");
    assertFalse(lsm.getLsmStats().isPresent());
  }
  @Test
  public void testGetLsmStatsDefaultsToExcludingGenerationRows() throws Exception {
    enqueue("get_lsm_stats", 200, stats());
    lsm.getLsmStats();
    assertFalse(MAPPER.readTree(requestBodies.get(0)).get("include_generation_rows").asBoolean());
  }
  // ===========================================================================
  // flush / compact
  // ===========================================================================
  @Test
  public void testFlushAndCompactRoutes() {
    enqueue("flush_lsm", 200, "");
    enqueue("compact_lsm", 200, "");
    lsm.flushLsm();
    lsm.compactLsm();
    assertEquals("/v1/table/my_table/flush_lsm/", requestPaths.get(0));
    assertEquals("/v1/table/my_table/compact_lsm/", requestPaths.get(1));
  }
  @Test
  public void testHttpErrorCarriesStatus() {
    enqueue("flush_lsm", 404, "no such table");
    LanceDbRestClient.HttpException e =
        assertThrows(LanceDbRestClient.HttpException.class, () -> lsm.flushLsm());
    assertEquals(404, e.statusCode());
  }
  // ===========================================================================
  // checkpoint
  // ===========================================================================
  @Test
  public void testCheckpointReturnsWhenLsmDisabled() {
    enqueue("flush_lsm", 200, "");
    enqueue("get_lsm_stats", 200, "{\"lsm_stats\":null}");
    lsm.checkpointLsm();
    assertEquals(0, countCalls("compact_lsm"), "nothing to compact when the LSM path is off");
  }
  @Test
  public void testCheckpointReturnsWhenNoGenerationsOutstanding() {
    enqueue("flush_lsm", 200, "");
    // A bucket with no L0 generations yields no target, so the drain never starts.
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false)));
    lsm.checkpointLsm();
    assertEquals(0, countCalls("compact_lsm"));
  }
  @Test
  public void testCheckpointConvergesOnceTargetGenerationsAreGone() {
    enqueue("flush_lsm", 200, "");
    // Watermark read: shard-0 holds generations 7 and 8, so target = 8.
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false, 7L, 8L)));
    // First drain poll: both still outstanding, nothing compacting -> dispatch a pass.
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false, 7L, 8L)));
    // Second drain poll: drained past the target -> done.
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false, 9L)));
    enqueue("compact_lsm", 200, "");
    lsm.checkpointLsm();
    assertEquals(1, countCalls("compact_lsm"), "one pass dispatched");
    assertEquals(3, countCalls("get_lsm_stats"), "watermark read plus two drain polls");
  }
  @Test
  public void testCheckpointDoesNotPileOnWhileEveryTargetBucketIsCompacting() {
    enqueue("flush_lsm", 200, "");
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", true, 4L)));
    // Still compacting on the first poll, so no pass is dispatched; then it drains.
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", true, 4L)));
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false, 5L)));
    lsm.checkpointLsm();
    assertEquals(0, countCalls("compact_lsm"), "a latched bucket is left alone");
  }
  @Test
  public void testCheckpointRetriesFromFlushAfterLostClaim() {
    // 421 on the watermark read: the node lost its claim, so the whole thing restarts
    // from flush rather than retrying the read in place.
    enqueue("flush_lsm", 200, "");
    enqueue("get_lsm_stats", 421, "no claim");
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false)));
    lsm.checkpointLsm();
    assertEquals(2, countCalls("flush_lsm"), "re-issued from flush");
  }
  @Test
  public void testCheckpointRetriesRetryableStatusInPlace() {
    enqueue("flush_lsm", 429, "latch held");
    enqueue("flush_lsm", 200, "");
    enqueue("get_lsm_stats", 200, stats(bucket("shard-0", false)));
    lsm.checkpointLsm();
    assertEquals(2, countCalls("flush_lsm"), "429 retried in place, not re-issued");
  }
  @Test
  public void testCheckpointPropagatesTerminalStatus() {
    enqueue("flush_lsm", 400, "bad request");
    LanceDbRestClient.HttpException e =
        assertThrows(LanceDbRestClient.HttpException.class, () -> lsm.checkpointLsm());
    assertEquals(400, e.statusCode());
    assertEquals(1, countCalls("flush_lsm"), "a terminal status is not retried");
  }
  @Test
  public void testCheckpointGivesUpAfterRepeatedLostClaims() {
    enqueue("flush_lsm", 421, "no claim");
    IllegalStateException e = assertThrows(IllegalStateException.class, () -> lsm.checkpointLsm());
    assertTrue(e.getMessage().contains("kept losing its claim"), e.getMessage());
    assertEquals(4, countCalls("flush_lsm"), "the initial attempt plus MAX_REISSUES");
  }
  // ===========================================================================
  // strict decoding
  // ===========================================================================
  /**
   * A stats payload that does not decode must fail closed. Every one of these bodies used to be
   * read as "no buckets", which is indistinguishable from a drained table, so {@code checkpointLsm}
   * reported convergence for a checkpoint that never ran.
   */
  @Test
  public void testCheckpointRejectsMalformedStats() {
    Map<String, String> malformed = new LinkedHashMap<String, String>();
    malformed.put("no response body at all", "");
    malformed.put("stats object with no buckets", "{\"lsm_stats\":{}}");
    malformed.put("bucket missing its required fields", "{\"lsm_stats\":{\"buckets\":[{}]}}");
    malformed.put(
        "bucket missing generations",
        "{\"lsm_stats\":{\"buckets\":[{\"shard_id\":\"shard-0\",\"status\":\"Active\","
            + "\"writer_epoch\":1,\"manifest_version\":2,\"current_generation\":9,"
            + "\"replay_after_wal_entry_position\":0,\"wal_entry_position_last_seen\":0,"
            + "\"compacting\":false}]}}");
    malformed.put(
        "generation with a non-numeric generation number",
        "{\"lsm_stats\":{\"buckets\":[{\"shard_id\":\"shard-0\",\"status\":\"Active\","
            + "\"writer_epoch\":1,\"manifest_version\":2,\"current_generation\":9,"
            + "\"replay_after_wal_entry_position\":0,\"wal_entry_position_last_seen\":0,"
            + "\"generations\":[{\"generation\":\"7\",\"bytes\":1024}],"
            + "\"compacting\":false}]}}");
    for (Map.Entry<String, String> each : malformed.entrySet()) {
      setUpFresh();
      enqueue("flush_lsm", 200, "");
      enqueue("get_lsm_stats", 200, each.getValue());
      assertThrows(
          IllegalStateException.class,
          () -> lsm.checkpointLsm(),
          each.getKey() + " must not report convergence");
    }
  }
  /** The one shape that legitimately means "this table has no LSM write path". */
  @Test
  public void testCheckpointTreatsNullStatsAsNotWalBacked() {
    enqueue("flush_lsm", 200, "");
    enqueue("get_lsm_stats", 200, "{\"lsm_stats\":null}");
    lsm.checkpointLsm();
    assertEquals(1, countCalls("get_lsm_stats"));
  }
  // ===========================================================================
  // retry budget
  // ===========================================================================
  /**
   * The transport must not retry on the checkpoint loop's behalf. Apache HttpClient's default
   * strategy retries exactly 429 and 503 — the two statuses {@code isRetryable} owns — which
   * doubled every budget here and also retried {@code compact_lsm} in place, where the loop is
   * built to fall through to a fresh stats poll instead.
   */
  @Test
  public void testCheckpointRetryBudgetIsNotDoubledByTheTransport() {
    enqueue("flush_lsm", 429, "latch held");
    LanceDbRestClient.HttpException e =
        assertThrows(LanceDbRestClient.HttpException.class, () -> lsm.checkpointLsm());
    assertEquals(429, e.statusCode(), "the exhausted budget propagates the last error as itself");
    assertEquals(9, countCalls("flush_lsm"), "the initial request plus MAX_RETRIES, and no more");
  }
  // ===========================================================================
  // harness
  // ===========================================================================
  private static List<Long> generationNumbers(BucketStats bucket) {
    List<Long> numbers = new ArrayList<Long>();
    for (GenerationStats generation : bucket.generations()) {
      numbers.add(generation.generation());
    }
    return numbers;
  }
  /** Build an {@code lsm_stats} response body from bucket fragments. */
  private static String stats(String... buckets) {
    return "{\"lsm_stats\":{\"buckets\":[" + String.join(",", buckets) + "]}}";
  }
  private static String bucket(String shardId, boolean compacting, Long... generations) {
    StringBuilder gens = new StringBuilder();
    for (Long generation : generations) {
      if (gens.length() > 0) {
        gens.append(",");
      }
      gens.append("{\"generation\":").append(generation).append(",\"bytes\":1024}");
    }
    return "{\"shard_id\":\""
        + shardId
        + "\",\"status\":\"Active\",\"writer_epoch\":1,\"manifest_version\":2,"
        + "\"current_generation\":9,\"replay_after_wal_entry_position\":0,"
        + "\"wal_entry_position_last_seen\":0,\"generations\":["
        + gens
        + "],\"compacting\":"
        + compacting
        + "}";
  }
  /** Queue a reply for an operation. The last queued reply repeats once the queue drains. */
  private void enqueue(String operation, int status, String body) {
    replies.computeIfAbsent(operation, key -> new ArrayDeque<Reply>()).add(new Reply(status, body));
  }
  private Reply nextReply(String path) {
    String operation = operationOf(path);
    Deque<Reply> queued = replies.get(operation);
    if (queued == null || queued.isEmpty()) {
      return new Reply(200, "");
    }
    return queued.size() > 1 ? queued.poll() : queued.peek();
  }
  private long countCalls(String operation) {
    return requestPaths.stream().filter(path -> operationOf(path).equals(operation)).count();
  }
  /** {@code /v1/table/my_table/flush_lsm/} -> {@code flush_lsm}. */
  private static String operationOf(String path) {
    String[] segments = path.split("/");
    return segments.length == 0 ? "" : segments[segments.length - 1];
  }
  private static String readAll(InputStream in) throws IOException {
    ByteArrayOutputStream out = new ByteArrayOutputStream();
    byte[] buffer = new byte[4096];
    int read;
    while ((read = in.read(buffer)) != -1) {
      out.write(buffer, 0, read);
    }
    return new String(out.toByteArray(), StandardCharsets.UTF_8);
  }
  private static final class Reply {
    private final int status;
    private final String body;
    private Reply(int status, String body) {
      this.status = status;
      this.body = body;
    }
  }
 }
@@ -6,7 +6,7 @@
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.38.0-beta.2</version>
+    <version>0.37.1-beta.0</version>
    <packaging>pom</packaging>
    <name>${project.artifactId}</name>
    <description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>11.0.0-beta.15</lance-core.version>
+        <lance-core.version>10.0.0-beta.5</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 = "0.38.0-beta.2"
+version = "0.37.1-beta.0"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -6,9 +6,7 @@ import * as arrow17 from "apache-arrow-17";
 import * as arrow18 from "apache-arrow-18";
 import {
  Vector as CurrentVector,
  convertToTable,
  tableFromIPC as currentTableFromIPC,
  fromBufferToRecordBatch,
  fromDataToBuffer,
  fromRecordBatchToBuffer,
@@ -21,7 +19,6 @@ import {
  FunctionOptions,
 } from "../lancedb/embedding/embedding_function";
 import { EmbeddingFunctionConfig } from "../lancedb/embedding/registry";
 import { sanitizeTable } from "../lancedb/sanitize";
 // biome-ignore lint/suspicious/noExplicitAny: skip
 function sampleRecords(): Array<Record<string, any>> {
@@ -67,11 +64,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      tableFromIPC,
      DataType,
      Dictionary,
      RecordBatch: ArrowRecordBatch,
      Table: ArrowTable,
      Uint8: ArrowUint8,
      makeData: arrowMakeData,
      vectorFromArray,
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
    } = <any>arrow;
    type Schema = ApacheArrow["Schema"];
@@ -204,35 +197,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
        expect(table.getChild("d")?.toJSON()).toEqual([9n, 10n, null]);
      });
      it("will use a provided FixedSizeList schema with typed array values", function () {
        const schema = new Schema([
          new Field("text", new Utf8(), false),
          new Field(
            "vector",
            new FixedSizeList(3, new Field("item", new Float32(), false)),
            false,
          ),
        ]);
        const table = makeArrowTable(
          [
            {
              text: "foo",
              vector: new Float32Array([1, 2, 3]),
            },
          ],
          { schema },
        );
        expect(table.getChild("text")?.toJSON()).toEqual(["foo"]);
        expect(
          table
            .getChild("vector")
            ?.toJSON()
            .map((value) => value.toJSON()),
        ).toEqual([[1, 2, 3]]);
      });
      it("will assume the column `vector` is FixedSizeList<Float32> by default", async function () {
        const schema = new Schema([
          new Field("a", new Float(Precision.DOUBLE), true),
@@ -1061,114 +1025,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
    });
    describe("when using two versions of arrow", function () {
      it("preserves a dictionary shared by multiple fields", async function () {
        const values = ["alpha", "beta", "alpha"];
        const dictionaryVector = vectorFromArray(values);
        const batch = new ArrowRecordBatch({
          first: dictionaryVector.data[0],
          second: dictionaryVector.data[0],
        });
        const table = new ArrowTable([batch]);
        const sanitized = sanitizeTable(table);
        expect([...sanitized.getChild("first")!]).toEqual(values);
        expect([...sanitized.getChild("second")!]).toEqual(values);
        const firstType = sanitized.schema.fields[0].type as {
          dictionary: unknown;
        };
        const secondType = sanitized.schema.fields[1].type as {
          dictionary: unknown;
        };
        expect(secondType.dictionary).toBe(firstType.dictionary);
        expect(sanitized.batches[0].data.children[1].dictionary).toBe(
          sanitized.batches[0].data.children[0].dictionary,
        );
        const buf = await fromDataToBuffer(table);
        const actual = currentTableFromIPC(buf);
        expect([...actual.getChild("first")!]).toEqual(values);
        expect([...actual.getChild("second")!]).toEqual(values);
      });
      it("preserves shared dictionary data from another Arrow version", async function () {
        const values = ["alpha", "beta", "alpha"];
        const dictionaryVector = vectorFromArray(values);
        const firstBatch = new ArrowRecordBatch({
          label: dictionaryVector.slice(0, 2).data[0],
        });
        const secondBatch = new ArrowRecordBatch({
          label: dictionaryVector.slice(2).data[0],
        });
        const table = new ArrowTable([firstBatch, secondBatch]);
        const sanitized = sanitizeTable(table);
        expect([...sanitized.getChild("label")!]).toEqual(values);
        const dictionaries = sanitized.batches.map(
          (batch) => batch.data.children[0].dictionary,
        );
        expect(dictionaries[0]).toBeInstanceOf(CurrentVector);
        expect(dictionaries[1]).toBe(dictionaries[0]);
        const buf = await fromDataToBuffer(table);
        const actual = currentTableFromIPC(buf);
        expect([...actual.getChild("label")!]).toEqual(values);
      });
      it("preserves shared chunks in growing dictionaries", async function () {
        const type = new Dictionary(new Utf8(), new Int32(), 42, false);
        const firstDictionary = vectorFromArray(["alpha", "beta"], new Utf8());
        const secondDictionary = firstDictionary.concat(
          vectorFromArray(["gamma"], new Utf8()),
        );
        const firstData = arrowMakeData({
          type,
          data: Int32Array.from([0, 1]),
          dictionary: firstDictionary,
        });
        const secondData = arrowMakeData({
          type,
          data: Int32Array.from([2]),
          dictionary: secondDictionary,
        });
        const table = new ArrowTable([
          new ArrowRecordBatch({ label: firstData }),
          new ArrowRecordBatch({ label: secondData }),
        ]);
        const sanitized = sanitizeTable(table);
        const expected = ["alpha", "beta", "gamma"];
        expect([...sanitized.getChild("label")!]).toEqual(expected);
        const firstLocalDictionary =
          sanitized.batches[0].data.children[0].dictionary!;
        const secondLocalDictionary =
          sanitized.batches[1].data.children[0].dictionary!;
        expect(secondLocalDictionary.data[0]).toBe(
          firstLocalDictionary.data[0],
        );
        const buf = await fromTableToBuffer(sanitized);
        const actual = currentTableFromIPC(buf);
        expect([...actual.getChild("label")!]).toEqual(expected);
      });
      it("can serialize list data from another Arrow version", async function () {
        const values = [["anime", "action"], [], null];
        const vector = vectorFromArray(
          values,
          new List(new Field("item", new Utf8(), true)),
        );
        const table = new ArrowTable({ tags: vector });
        const buf = await fromDataToBuffer(table);
        const actual = currentTableFromIPC(buf);
        const actualTags = actual.getChild("tags");
        expect(actualTags?.get(0)?.toJSON()).toEqual(values[0]);
        expect(actualTags?.get(1)?.toJSON()).toEqual(values[1]);
        expect(actualTags?.get(2)).toBeNull();
      });
      it("can still import data", async function () {
        const schema = new arrow15.Schema([
          new arrow15.Field("id", new arrow15.Int32()),
@@ -4,13 +4,7 @@
 import { readdirSync } from "fs";
 import { Field, Float64, Schema } from "apache-arrow";
 import * as tmp from "tmp";
-import {
+import { Connection, Table, connect, connectNamespace } from "../lancedb";
  Connection,
  ListTablesResponse,
  Table,
  connect,
  connectNamespace,
 } from "../lancedb";
 import { LocalTable } from "../lancedb/table";
 describe("when connecting", () => {
@@ -95,16 +89,6 @@ describe("given a connection", () => {
    await db.createTable("test4", [{ id: 1 }, { id: 2 }]);
  });
  it("should return a completed job when dropping a local table", async () => {
    await db.createTable("async-drop", [{ id: 1 }]);
    const job = await db.dropTableAsync("async-drop");
    expect(job.id).toBeNull();
    await expect(job.status()).resolves.toBe("finished");
    await job.wait();
    await expect(db.tableNames()).resolves.toEqual([]);
  });
  it("should fail if creating table twice, unless overwrite is true", async () => {
    let tbl = await db.createTable("test", [{ id: 1 }, { id: 2 }]);
    await expect(tbl.countRows()).resolves.toBe(2);
@@ -135,56 +119,6 @@ describe("given a connection", () => {
    expect(tables).toEqual(["b", "c"]);
  });
  it("should list tables with a page token", async () => {
    const db = await connect(tmpDir.name);
    await db.createTable("b", [{ id: 1 }]);
    await db.createTable("a", [{ id: 1 }]);
    await db.createTable("c", [{ id: 1 }]);
    const all = await db.listTables();
    expect(all.tables).toEqual(["a", "b", "c"]);
    expect(all.pageToken).toBeUndefined();
    const first = await db.listTables({ limit: 1 });
    expect(first.tables).toEqual(["a"]);
    expect(first.pageToken).toBeDefined();
    const second = await db.listTables({
      limit: 1,
      pageToken: first.pageToken,
    });
    expect(second.tables).toEqual(["b"]);
  });
  it("should visit every table exactly once when paging", async () => {
    const db = await connect(tmpDir.name);
    const created = ["a", "b", "c", "d", "e"];
    for (const name of created) {
      await db.createTable(name, [{ id: 1 }]);
    }
    const seen: string[] = [];
    let pageToken: string | undefined = undefined;
    do {
      const page: ListTablesResponse = await db.listTables({
        limit: 2,
        pageToken,
      });
      seen.push(...page.tables);
      pageToken = page.pageToken;
    } while (pageToken);
    expect(seen.sort()).toEqual(created);
  });
  it("should reject listTables on a closed connection", async () => {
    const db = await connect(tmpDir.name);
    db.close();
    await expect(db.listTables()).rejects.toThrow("Connection is closed");
  });
  it("should create tables in v2 mode", async () => {
    const db = await connect(tmpDir.name);
    const data = [...Array(10000).keys()].map((i) => ({ id: i }));
@@ -11,11 +11,8 @@ import {
  Float16,
  Float32,
  Float64,
  Int32,
  Schema,
  Utf8,
  fromDataToBuffer,
  tableFromIPC,
 } from "../lancedb/arrow";
 import { EmbeddingFunction, LanceSchema } from "../lancedb/embedding";
 import { getRegistry, register } from "../lancedb/embedding/registry";
@@ -187,63 +184,6 @@ describe("embedding functions", () => {
    const vector0 = JSON.parse(JSON.stringify(arr[0].vector));
    expect(vector0).toEqual([1, 2, 3]);
  });
  it("should append generated vectors to a non-nullable schema", async () => {
    @register("non_nullable_schema_test")
    class MockEmbeddingFunction extends EmbeddingFunction<string> {
      ndims() {
        return 3;
      }
      embeddingDataType(): Float {
        return new Float64();
      }
      async computeSourceEmbeddings(data: string[]) {
        return data.map(() => [1, 2, 3]);
      }
    }
    const schema = new Schema([
      new Field("id", new Int32()),
      new Field("text", new Utf8()),
      new Field("type", new Utf8()),
      new Field(
        "vector",
        new FixedSizeList(3, new Field("item", new Float64())),
      ),
    ]);
    const func = new MockEmbeddingFunction();
    const db = await connect(tmpDir.name);
    const table = await db.createEmptyTable("test_non_nullable", schema, {
      embeddingFunction: {
        function: func,
        sourceColumn: "text",
      },
    });
    const data = [
      { id: 1, text: "Carrot", type: "vegetable" },
      { id: 2, text: "Apple", type: "fruit" },
    ];
    const buffer = await fromDataToBuffer(
      data,
      undefined,
      await table.schema(),
    );
    const generatedTable = tableFromIPC(buffer);
    const vectorField = generatedTable.schema.fields.find(
      (field) => field.name === "vector",
    );
    expect(vectorField?.nullable).toBe(false);
    await table.add(data);
    const rows = await table.query().toArray();
    expect(rows).toHaveLength(2);
    for (const row of rows) {
      expect([...row.vector]).toEqual([1, 2, 3]);
    }
  });
  it("should error when appending to a table with an unregistered embedding function", async () => {
    @register("mock")
    class MockEmbeddingFunction extends EmbeddingFunction<string> {
@@ -1,14 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import packageJson = require("../package.json");
 describe("package metadata", () => {
  it("requires Node.js type declarations compatible with the runtime", () => {
    expect(packageJson.engines.node).toBe(">= 18");
    expect(packageJson.peerDependencies["@types/node"]).toBe(">=18");
    expect(packageJson.peerDependenciesMeta["@types/node"]).toEqual({
      optional: true,
    });
  });
 });
@@ -110,81 +110,6 @@ describe("Query outputSchema", () => {
  });
 });
 describe("Search pagination", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
  beforeEach(async () => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
    const db = await connect(tmpDir.name);
    const schema = new Schema([
      new Field("id", new Int64(), false),
      new Field("text", new Utf8(), false),
      new Field(
        "vector",
        new FixedSizeList(2, new Field("item", new Float32())),
        false,
      ),
    ]);
    const data = makeArrowTable(
      [
        { id: 1n, text: "common", vector: [0, 0] },
        { id: 2n, text: "common common", vector: [1, 1] },
        { id: 3n, text: "common common common", vector: [2, 2] },
        { id: 4n, text: "common common common common", vector: [3, 3] },
      ],
      { schema },
    );
    table = await db.createTable("test", data);
  });
  afterEach(() => {
    tmpDir.removeCallback();
  });
  it("applies offset after the vector search limit", async () => {
    const allResults = await table
      .vectorSearch([0, 0])
      .select(["id"])
      .limit(4)
      .toArray();
    const secondPage = await table
      .vectorSearch([0, 0])
      .select(["id"])
      .limit(2)
      .offset(2)
      .toArray();
    expect(allResults).toHaveLength(4);
    expect(secondPage).toHaveLength(2);
    expect(secondPage.map((row) => row.id)).toEqual(
      allResults.slice(2, 4).map((row) => row.id),
    );
  });
  it("applies offset after the full-text search limit", async () => {
    await table.createIndex("text", { config: Index.fts() });
    const allResults = await table
      .search("common", "fts")
      .select(["id"])
      .limit(4)
      .toArray();
    const secondPage = await table
      .search("common", "fts")
      .select(["id"])
      .limit(2)
      .offset(2)
      .toArray();
    expect(allResults).toHaveLength(4);
    expect(secondPage).toHaveLength(2);
    expect(secondPage.map((row) => row.id)).toEqual(
      allResults.slice(2, 4).map((row) => row.id),
    );
  });
 });
 describe("Query orderBy", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
@@ -170,38 +170,6 @@ describe("remote connection", () => {
    );
  });
  it("surfaces JSON server errors from remote table operations", async () => {
    await withMockDatabase(
      (req, res) => {
        const path = req.url ?? "";
        if (path.endsWith("/describe/")) {
          res.writeHead(200, { "Content-Type": "application/json" }).end(
            JSON.stringify({
              name: "broken_table",
              version: 1,
              schema: { fields: [] },
            }),
          );
          return;
        }
        if (path.endsWith("/count_rows/")) {
          res
            .writeHead(400, { "Content-Type": "application/json" })
            .end(JSON.stringify({ error: "count rows failed" }));
          return;
        }
        res.writeHead(404).end();
      },
      async (db) => {
        const table = await db.openTable("broken_table");
        await expect(table.countRows()).rejects.toThrow("count rows failed");
      },
    );
  });
  it("should pass on requested extra headers", async () => {
    await withMockDatabase(
      (req, res) => {
@@ -909,96 +877,3 @@ describe("remote connection", () => {
    });
  });
 });
 describe("remote connection jobs surface", () => {
  it("lists, describes, cancels, and reads history", async () => {
    const { tableFromArrays, tableToIPC } = await import("apache-arrow");
    const eventsTable = tableFromArrays({ state: ["created", "succeeded"] });
    const eventsBody = Buffer.from(tableToIPC(eventsTable, "stream"));
    await withMockDatabase(
      (req, res) => {
        let body = "";
        req.on("data", (chunk) => {
          body += chunk;
        });
        req.on("end", () => {
          const payload = body.length > 0 ? JSON.parse(body) : {};
          if (req.url === "/v1/jobs/list") {
            if (payload["page_token"] === undefined) {
              res
                .writeHead(200, { "Content-Type": "application/json" })
                .end(
                  '{"jobs": [{"job_id": "job-1", "table": "t1", ' +
                    '"job_type": "create_index", "state": "in_progress", ' +
                    '"created_at_millis": 1000}], "page_token": "next"}',
                );
            } else {
              res
                .writeHead(200, { "Content-Type": "application/json" })
                .end(
                  '{"jobs": [{"job_id": "job-2", "table": "t2", ' +
                    '"job_type": "create_index", "state": "succeeded", ' +
                    '"created_at_millis": 2000}]}',
                );
            }
          } else if (req.url === "/v1/jobs/describe") {
            if (payload["job_id"] !== "job-1") {
              res.writeHead(404).end("no such job");
              return;
            }
            res
              .writeHead(200, { "Content-Type": "application/json" })
              .end(
                '{"job_id": "job-1", "job_type": "create_index", ' +
                  '"job_state": "FAILED", "creation_ms": 1000, ' +
                  '"spec": {"column": "vec"}, "failure": {"phase": "execute", ' +
                  '"message": "worker died", "retryable": true}}',
              );
          } else if (req.url === "/v1/jobs/cancel") {
            if (payload["job_id"] !== "job-1") {
              res.writeHead(404).end("no such job");
              return;
            }
            res
              .writeHead(200, { "Content-Type": "application/json" })
              .end('{"job_id": "job-1"}');
          } else if (req.url === "/v1/jobs/query_events") {
            res
              .writeHead(200, {
                "Content-Type": "application/vnd.apache.arrow.stream",
              })
              .end(eventsBody);
          } else {
            res.writeHead(404).end();
          }
        });
      },
      async (db) => {
        const jobs = await db.listJobs();
        expect(jobs.map((job) => job.jobId)).toEqual(["job-1", "job-2"]);
        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);
        const history = await db.jobHistory("job-1");
        expect(history.numRows).toEqual(2);
        const job = db.job("job-1");
        expect(job.id).toEqual("job-1");
        expect(await job.status()).toEqual("failed");
        await expect(job.wait()).rejects.toThrow("worker died");
      },
    );
  });
 });
@@ -86,44 +86,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      await expect(table.countRows()).resolves.toBe(3);
    });
    it("should support a foreign Float64 vector schema end to end", async () => {
      const conn = await connect(tmpDir.name);
      const schema = new arrow.Schema([
        new arrow.Field("resource_id", new arrow.Int32(), false),
        new arrow.Field(
          "vector",
          new arrow.FixedSizeList(
            3,
            new arrow.Field("value", new arrow.Float64(), true),
          ),
          false,
        ),
      ]);
      const data = [
        {
          // biome-ignore lint/style/useNamingConvention: matches the reported schema
          resource_id: 0,
          vector: [0.1, 0.1, 0.1],
        },
      ];
      const resources = await conn.createTable("resources", data, { schema });
      const existing = await resources
        .query()
        .where("resource_id = 0")
        .limit(1)
        .toArray();
      expect(existing).toHaveLength(1);
      const matched = await resources
        .search(Float64Array.from(data[0].vector))
        .limit(1)
        .toArray();
      expect(matched).toHaveLength(1);
      expect(matched[0]["resource_id"]).toBe(0);
    });
    it("should support branches", async () => {
      await table.add([{ id: 1 }]);
      expect(await table.countRows()).toBe(1);
@@ -277,16 +239,8 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
        },
        numIndices: 0,
        numRows: 3,
-        // Full on-disk size of the two data files, footers and metadata included.
+        totalBytes: 44,
        totalBytes: 684,
      });
      // Index files count toward totalBytes too (only deletion files and
      // manifests are excluded).
      await table.createIndex("id", { config: Index.btree() });
      const statsWithIndex = await table.stats();
      expect(statsWithIndex.numIndices).toBe(1);
      expect(statsWithIndex.totalBytes).toBeGreaterThan(684);
    });
    it("should overwrite data if asked", async () => {
@@ -897,11 +851,7 @@ describe("When creating an index", () => {
  afterEach(() => tmpDir.removeCallback());
  it("should create a vector index on vector columns", async () => {
-    const job = await tbl.createIndexAsync("vec");
+    await tbl.createIndex("vec");
    expect(job.id).toBeNull();
    await job.wait();
    // Cancelling a job that already finished succeeds and does nothing.
    await job.cancel();
    // check index directory
    const indexDir = path.join(tmpDir.name, "test.lance", "_indices");
@@ -3340,120 +3290,3 @@ describe("LSM merge insert", () => {
    await expect(table.query().useLsm(true).toArray()).rejects.toThrow();
  });
 });
 describe("LSM convergence and stats", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => tmpDir.removeCallback());
  async function lsmTable(conn: Connection): Promise<Table> {
    const table = await conn.createEmptyTable(
      "t",
      new arrow.Schema([new arrow.Field("id", new arrow.Utf8(), false)]),
    );
    await table.setUnenforcedPrimaryKey("id");
    await table.setLsmWriteSpec({ specType: "unsharded" });
    return table;
  }
  // These four route through the server that owns the MemWAL, so a local table
  // rejects them rather than answering. What is asserted here is that the
  // bindings reach the core at all; the behavior against a real endpoint is
  // covered by the mocked endpoint tests in rust/lancedb/src/remote/table.rs.
  it("rejects flushLsm on a local table", async () => {
    const conn = await connect(tmpDir.name);
    const table = await lsmTable(conn);
    await expect(table.flushLsm()).rejects.toThrow(/not supported/i);
  });
  it("rejects compactLsm on a local table", async () => {
    const conn = await connect(tmpDir.name);
    const table = await lsmTable(conn);
    await expect(table.compactLsm()).rejects.toThrow(/not supported/i);
  });
  it("rejects getLsmStats on a local table", async () => {
    const conn = await connect(tmpDir.name);
    const table = await lsmTable(conn);
    await expect(table.getLsmStats()).rejects.toThrow(/not supported/i);
    await expect(table.getLsmStats(true)).rejects.toThrow(/not supported/i);
  });
  it("rejects checkpointLsm on a local table", async () => {
    const conn = await connect(tmpDir.name);
    const table = await lsmTable(conn);
    // checkpointLsm seals first, so it surfaces flushLsm's rejection.
    await expect(table.checkpointLsm()).rejects.toThrow(/not supported/i);
  });
 });
 describe("computed columns", () => {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
    tmpDir = tmp.dirSync({ unsafeCleanup: true });
  });
  afterEach(() => tmpDir.removeCallback());
  it("declares a column and fills it on refresh", async () => {
    const db = await connect(tmpDir.name);
    const table = await db.createTable("computed", [{ x: 1 }, { x: 2 }]);
    await table.addColumns({
      computed: [{ name: "doubled", valueSql: "x * 2" }],
    });
    let rows = await table.query().toArray();
    expect(rows.map((r) => r.doubled)).toEqual([null, null]);
    const result = await table.refreshColumn("doubled");
    expect(result.rowsFilled).toBe(2);
    rows = await table.query().toArray();
    expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
  });
  it("returns a job handle from refreshColumnAsync", async () => {
    const db = await connect(tmpDir.name);
    const table = await db.createTable("computed_job", [{ x: 1 }, { x: 2 }]);
    await table.addColumns({
      computed: [{ name: "doubled", valueSql: "x * 2" }],
    });
    const job = await table.refreshColumnAsync("doubled");
    expect(job.id).toBeNull();
    await job.wait();
    expect(await job.status()).toBe("finished");
    const rows = await table.query().toArray();
    expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
    // Bad input rejects at the call, not through the job.
    await expect(table.refreshColumnAsync("x")).rejects.toThrow(
      "not a computed column",
    );
  });
  it("fills rows added since the last refresh", async () => {
    const db = await connect(tmpDir.name);
    const table = await db.createTable("computed_append", [{ x: 1 }]);
    await table.addColumns({
      computed: [{ name: "doubled", valueSql: "x * 2" }],
    });
    await table.refreshColumn("doubled");
    await table.add([{ x: 5 }]);
    const result = await table.refreshColumn("doubled");
    expect(result.rowsFilled).toBe(1);
    const rows = await table.query().toArray();
    expect(rows.map((r) => r.doubled).sort()).toEqual([10, 2]);
  });
 });
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import { tableFromIPC } from "apache-arrow";
 import {
  Data,
  SchemaLike,
@@ -21,18 +20,13 @@ import type {
  CreateNamespaceResponse,
  DescribeNamespaceResponse,
  DropNamespaceResponse,
  Job,
  JobDescription,
  JobInfo,
  ListNamespacesResponse,
  ListTablesResponse,
 } from "./native";
 export type {
  CreateNamespaceResponse,
  DescribeNamespaceResponse,
  DropNamespaceResponse,
  ListNamespacesResponse,
  ListTablesResponse,
 };
 import { sanitizeTable } from "./sanitize";
 import { LocalTable, Table } from "./table";
@@ -130,10 +124,6 @@ export interface OpenTableOptions {
  indexCacheSize?: number;
 }
 /**
 * @deprecated Use {@link ListTablesOptions} with {@link Connection.listTables}
 * instead.
 */
 export interface TableNamesOptions {
  /**
   * If present, only return names that come lexicographically after the
@@ -147,23 +137,6 @@ export interface TableNamesOptions {
  limit?: number;
 }
 export interface ListTablesOptions {
  /**
   * Token from a previous response for pagination.
   *
   * The token is opaque: it carries whatever the database needs to resume, and
   * callers should not construct or interpret one.
   */
  pageToken?: string;
  /**
   * An upper bound on how many tables to return.
   *
   * A page may hold fewer than this and still not be the last one, so continue
   * while the response carries a page token rather than while pages are full.
   */
  limit?: number;
 }
 export interface ListNamespacesOptions {
  /** Token from a previous response for pagination. */
  pageToken?: string;
@@ -248,7 +221,6 @@ export abstract class Connection {
   * @param {Partial<TableNamesOptions>} options - options to control the
   * paging / start point (backwards compatibility)
   *
   * @deprecated Use {@link Connection.listTables} instead.
   */
  abstract tableNames(options?: Partial<TableNamesOptions>): Promise<string[]>;
  /**
@@ -259,54 +231,12 @@ export abstract class Connection {
   * @param {Partial<TableNamesOptions>} options - options to control the
   * paging / start point
   *
   * @deprecated Use {@link Connection.listTables} instead.
   */
  abstract tableNames(
    namespacePath?: string[],
    options?: Partial<TableNamesOptions>,
  ): Promise<string[]>;
  /**
   * List a page of tables in this database.
   *
   * Results may be paginated. To retrieve subsequent pages, pass the
   * `pageToken` returned by a previous call. A page may be shorter than
   * `limit` without being the last one, so walk until the response carries no
   * page token:
   *
   * ```ts
   * const names = [];
   * let pageToken = undefined;
   * do {
   *   const page = await conn.listTables({ pageToken, limit: 100 });
   *   names.push(...page.tables);
   *   pageToken = page.pageToken;
   * } while (pageToken);
   * ```
   *
   * @param {Partial<ListTablesOptions>} options - Pagination options
   *   (`pageToken`, `limit`).
   * @returns {Promise<ListTablesResponse>} Table names and an optional token
   *   for fetching the next page.
   */
  abstract listTables(
    options?: Partial<ListTablesOptions>,
  ): Promise<ListTablesResponse>;
  /**
   * List a page of tables in this database.
   *
   * @param {string[]} namespacePath - The namespace path to list tables from
   *   (defaults to root namespace)
   * @param {Partial<ListTablesOptions>} options - Pagination options
   *   (`pageToken`, `limit`).
   * @returns {Promise<ListTablesResponse>} Table names and an optional token
   *   for fetching the next page.
   */
  abstract listTables(
    namespacePath?: string[],
    options?: Partial<ListTablesOptions>,
  ): Promise<ListTablesResponse>;
  /**
   * Open a table in the database.
   * @param {string} name - The name of the table
@@ -393,14 +323,6 @@ export abstract class Connection {
   */
  abstract dropTable(name: string, namespacePath?: string[]): Promise<void>;
  /**
   * Start dropping a table and return its cleanup job.
   *
   * The table may become unavailable before its data files are removed. Wait
   * on the returned job to know when cleanup has finished.
   */
  abstract dropTableAsync(name: string, namespacePath?: string[]): Promise<Job>;
  /**
   * Drop all tables in the database.
   * @param {string[]} namespacePath The namespace path to drop tables from (defaults to root namespace).
@@ -514,40 +436,6 @@ export abstract class Connection {
    newName: string,
    options?: RenameTableOptions,
  ): Promise<void>;
  /**
   * A {@link Job} 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.
   */
  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.
   *
   * Resolves to true if the server accepted the cancellation, false if no
   * 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 */
@@ -597,29 +485,6 @@ export class LocalConnection extends Connection {
    );
  }
  async listTables(
    namespacePathOrOptions?: string[] | Partial<ListTablesOptions>,
    options?: Partial<ListTablesOptions>,
  ): Promise<ListTablesResponse> {
    // Detect if first argument is namespacePath array or options object
    let namespacePath: string[] | undefined;
    let listTablesOptions: Partial<ListTablesOptions> | undefined;
    if (Array.isArray(namespacePathOrOptions)) {
      namespacePath = namespacePathOrOptions;
      listTablesOptions = options;
    } else {
      namespacePath = undefined;
      listTablesOptions = namespacePathOrOptions;
    }
    return this.inner.listTables(
      namespacePath ?? [],
      listTablesOptions?.pageToken,
      listTablesOptions?.limit,
    );
  }
  async openTable(
    name: string,
    namespacePath?: string[],
@@ -802,10 +667,6 @@ export class LocalConnection extends Connection {
    return this.inner.dropTable(name, namespacePath ?? []);
  }
  async dropTableAsync(name: string, namespacePath?: string[]): Promise<Job> {
    return this.inner.dropTableAsync(name, namespacePath ?? []);
  }
  async dropAllTables(namespacePath?: string[]): Promise<void> {
    return this.inner.dropAllTables(namespacePath ?? []);
  }
@@ -861,30 +722,6 @@ export class LocalConnection extends Connection {
      options?.newNamespacePath,
    );
  }
  job(jobId: string): Job {
    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);
  }
 }
 /**
@@ -50,7 +50,6 @@ export {
  MergeResult,
  AddResult,
  AddColumnsResult,
  RefreshColumnResult,
  AlterColumnsResult,
  UpdateFieldMetadataResult,
  DeleteResult,
@@ -75,26 +74,18 @@ export {
  Connection,
  CreateTableOptions,
  TableNamesOptions,
  ListTablesOptions,
  OpenTableOptions,
  ListNamespacesOptions,
  CreateNamespaceOptions,
  DropNamespaceOptions,
  ListNamespacesResponse,
  ListTablesResponse,
  CreateNamespaceResponse,
  DropNamespaceResponse,
  DescribeNamespaceResponse,
  RenameTableOptions,
 } from "./connection";
-export {
+export { Session } from "./native.js";
  Job,
  JobDescription,
  JobFailureInfo,
  JobInfo,
  Session,
 } from "./native.js";
 export {
  ExecutableQuery,
@@ -149,10 +140,6 @@ export {
  FtsToken,
  TokenizeTableOptions,
  LsmWriteSpec,
  LsmStats,
  BucketStats,
  GenerationStats,
  MemtableStats,
  ColumnAlteration,
  FieldMetadataUpdate,
 } from "./table";
@@ -9,7 +9,7 @@
 // comes from the exact same library instance.  This is not always the case
 // and so we must sanitize the input to ensure that it is compatible.
-import { BufferType, Data, Vector } from "apache-arrow";
+import { BufferType, Data } from "apache-arrow";
 import type { IntBitWidth, TKeys, TimeBitWidth } from "apache-arrow/type";
 import {
  Binary,
@@ -74,20 +74,6 @@ import {
  Utf8,
 } from "./arrow";
 type SanitizationContext = {
  types: WeakMap<object, DataType>;
  vectors: WeakMap<object, Vector>;
  data: WeakMap<object, Data<DataType>>;
 };
 function createSanitizationContext(): SanitizationContext {
  return {
    types: new WeakMap(),
    vectors: new WeakMap(),
    data: new WeakMap(),
  };
 }
 export function sanitizeMetadata(
  metadataLike?: unknown,
 ): Map<string, string> | undefined {
@@ -200,13 +186,6 @@ export function sanitizeInterval(typeLike: object) {
 }
 export function sanitizeList(typeLike: object) {
  return sanitizeListWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeListWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
      "Expected a List type to have an array-like `children` property",
@@ -215,35 +194,19 @@ function sanitizeListWithContext(
  if (typeLike.children.length !== 1) {
    throw Error("Expected a List type to have exactly one child");
  }
-  return new List(sanitizeFieldWithContext(typeLike.children[0], context));
+  return new List(sanitizeField(typeLike.children[0]));
 }
 export function sanitizeStruct(typeLike: object) {
  return sanitizeStructWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeStructWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
      "Expected a Struct type to have an array-like `children` property",
    );
  }
-  return new Struct(
+  return new Struct(typeLike.children.map((child) => sanitizeField(child)));
    typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
  );
 }
 export function sanitizeUnion(typeLike: object) {
  return sanitizeUnionWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeUnionWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (
    !("typeIds" in typeLike) ||
    !("mode" in typeLike) ||
@@ -263,7 +226,7 @@ function sanitizeUnionWithContext(
    typeLike.mode,
    // biome-ignore lint/suspicious/noExplicitAny: skip
    typeLike.typeIds as any,
-    typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
+    typeLike.children.map((child) => sanitizeField(child)),
  );
 }
@@ -271,19 +234,6 @@ export function sanitizeTypedUnion(
  typeLike: object,
  // eslint-disable-next-line @typescript-eslint/naming-convention
  UnionType: typeof DenseUnion | typeof SparseUnion,
 ) {
  return sanitizeTypedUnionWithContext(
    typeLike,
    UnionType,
    createSanitizationContext(),
  );
 }
 function sanitizeTypedUnionWithContext(
  typeLike: object,
  // eslint-disable-next-line @typescript-eslint/naming-convention
  UnionType: typeof DenseUnion | typeof SparseUnion,
  context: SanitizationContext,
 ) {
  if (!("typeIds" in typeLike)) {
    throw Error(
@@ -298,7 +248,7 @@ function sanitizeTypedUnionWithContext(
  return new UnionType(
    typeLike.typeIds as Int32Array | number[],
-    typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
+    typeLike.children.map((child) => sanitizeField(child)),
  );
 }
@@ -312,16 +262,6 @@ export function sanitizeFixedSizeBinary(typeLike: object) {
 }
 export function sanitizeFixedSizeList(typeLike: object) {
  return sanitizeFixedSizeListWithContext(
    typeLike,
    createSanitizationContext(),
  );
 }
 function sanitizeFixedSizeListWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (!("listSize" in typeLike) || typeof typeLike.listSize !== "number") {
    throw Error("Expected a FixedSizeList type to have a `listSize` property");
  }
@@ -335,18 +275,11 @@ function sanitizeFixedSizeListWithContext(
  }
  return new FixedSizeList(
    typeLike.listSize,
-    sanitizeFieldWithContext(typeLike.children[0], context),
+    sanitizeField(typeLike.children[0]),
  );
 }
 export function sanitizeMap(typeLike: object) {
  return sanitizeMapWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeMapWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
      "Expected a Map type to have an array-like `children` property",
@@ -359,10 +292,7 @@ function sanitizeMapWithContext(
    throw Error("Expected a Map type to have exactly one child");
  }
-  return new Map_(
+  return new Map_(sanitizeField(typeLike.children[0]), typeLike.keysSorted);
    sanitizeFieldWithContext(typeLike.children[0], context),
    typeLike.keysSorted,
  );
 }
 export function sanitizeDuration(typeLike: object) {
@@ -373,13 +303,6 @@ export function sanitizeDuration(typeLike: object) {
 }
 export function sanitizeDictionary(typeLike: object) {
  return sanitizeDictionaryWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeDictionaryWithContext(
  typeLike: object,
  context: SanitizationContext,
 ) {
  if (!("id" in typeLike) || typeof typeLike.id !== "number") {
    throw Error("Expected a Dictionary type to have an `id` property");
  }
@@ -393,8 +316,8 @@ function sanitizeDictionaryWithContext(
    throw Error("Expected a Dictionary type to have an `isOrdered` property");
  }
  return new Dictionary(
-    sanitizeTypeWithContext(typeLike.dictionary, context),
+    sanitizeType(typeLike.dictionary),
-    sanitizeTypeWithContext(typeLike.indices, context) as TKeys,
+    sanitizeType(typeLike.indices) as TKeys,
    typeLike.id,
    typeLike.isOrdered,
  );
@@ -402,23 +325,12 @@ function sanitizeDictionaryWithContext(
 // biome-ignore lint/suspicious/noExplicitAny: skip
 export function sanitizeType(typeLike: unknown): DataType<any> {
  return sanitizeTypeWithContext(typeLike, createSanitizationContext());
 }
 function sanitizeTypeWithContext(
  typeLike: unknown,
  context: SanitizationContext,
 ): DataType {
  if (typeof typeLike === "string") {
    return dataTypeFromName(typeLike);
  }
  if (typeof typeLike !== "object" || typeLike === null) {
    throw Error("Expected a Type but object was null/undefined");
  }
  const cached = context.types.get(typeLike);
  if (cached !== undefined) {
    return cached;
  }
  if (
    !("typeId" in typeLike) ||
    !(
@@ -437,16 +349,6 @@ function sanitizeTypeWithContext(
    throw Error("Type's typeId property was not a function or number");
  }
  const type = sanitizeTypeById(typeLike, typeId, context);
  context.types.set(typeLike, type);
  return type;
 }
 function sanitizeTypeById(
  typeLike: object,
  typeId: Type,
  context: SanitizationContext,
 ): DataType {
  switch (typeId) {
    case Type.NONE:
      throw Error("Received a Type with a typeId of NONE");
@@ -473,21 +375,21 @@ function sanitizeTypeById(
    case Type.Interval:
      return sanitizeInterval(typeLike);
    case Type.List:
-      return sanitizeListWithContext(typeLike, context);
+      return sanitizeList(typeLike);
    case Type.Struct:
-      return sanitizeStructWithContext(typeLike, context);
+      return sanitizeStruct(typeLike);
    case Type.Union:
-      return sanitizeUnionWithContext(typeLike, context);
+      return sanitizeUnion(typeLike);
    case Type.FixedSizeBinary:
      return sanitizeFixedSizeBinary(typeLike);
    case Type.FixedSizeList:
-      return sanitizeFixedSizeListWithContext(typeLike, context);
+      return sanitizeFixedSizeList(typeLike);
    case Type.Map:
-      return sanitizeMapWithContext(typeLike, context);
+      return sanitizeMap(typeLike);
    case Type.Duration:
      return sanitizeDuration(typeLike);
    case Type.Dictionary:
-      return sanitizeDictionaryWithContext(typeLike, context);
+      return sanitizeDictionary(typeLike);
    case Type.Int8:
      return new Int8();
    case Type.Int16:
@@ -531,9 +433,9 @@ function sanitizeTypeById(
    case Type.TimestampSecond:
      return sanitizeTypedTimestamp(typeLike, TimestampSecond);
    case Type.DenseUnion:
-      return sanitizeTypedUnionWithContext(typeLike, DenseUnion, context);
+      return sanitizeTypedUnion(typeLike, DenseUnion);
    case Type.SparseUnion:
-      return sanitizeTypedUnionWithContext(typeLike, SparseUnion, context);
+      return sanitizeTypedUnion(typeLike, SparseUnion);
    case Type.IntervalDayTime:
      return new IntervalDayTime();
    case Type.IntervalYearMonth:
@@ -552,13 +454,6 @@ function sanitizeTypeById(
 }
 export function sanitizeField(fieldLike: unknown): Field {
  return sanitizeFieldWithContext(fieldLike, createSanitizationContext());
 }
 function sanitizeFieldWithContext(
  fieldLike: unknown,
  context: SanitizationContext,
 ): Field {
  if (fieldLike instanceof Field) {
    return fieldLike;
  }
@@ -576,7 +471,7 @@ function sanitizeFieldWithContext(
  }
  let type: DataType;
  try {
-    type = sanitizeTypeWithContext(fieldLike.type, context);
+    type = sanitizeType(fieldLike.type);
  } catch (error: unknown) {
    throw Error(
      `Unable to sanitize type for field: ${fieldLike.name} due to error: ${error}`,
@@ -606,13 +501,6 @@ function sanitizeFieldWithContext(
 * than lancedb is using.
 */
 export function sanitizeSchema(schemaLike: SchemaLike): Schema {
  return sanitizeSchemaWithContext(schemaLike, createSanitizationContext());
 }
 function sanitizeSchemaWithContext(
  schemaLike: SchemaLike,
  context: SanitizationContext,
 ): Schema {
  if (schemaLike instanceof Schema) {
    return schemaLike;
  }
@@ -634,7 +522,7 @@ function sanitizeSchemaWithContext(
    );
  }
  const sanitizedFields = schemaLike.fields.map((field) =>
-    sanitizeFieldWithContext(field, context),
+    sanitizeField(field),
  );
  return new Schema(sanitizedFields, metadata);
 }
@@ -656,18 +544,13 @@ export function sanitizeTable(tableLike: TableLike): Table {
      "The table passed in does not appear to be a table (no 'columns' property)",
    );
  }
-  const context = createSanitizationContext();
+  const schema = sanitizeSchema(tableLike.schema);
-  const schema = sanitizeSchemaWithContext(tableLike.schema, context);
+
-  const batches = tableLike.batches.map((batch) =>
+  const batches = tableLike.batches.map(sanitizeRecordBatch);
    sanitizeRecordBatch(batch, context),
  );
  return new Table(schema, batches);
 }
-function sanitizeRecordBatch(
+function sanitizeRecordBatch(batchLike: RecordBatchLike): RecordBatch {
  batchLike: RecordBatchLike,
  context: SanitizationContext,
 ): RecordBatch {
  if (batchLike instanceof RecordBatch) {
    return batchLike;
  }
@@ -684,43 +567,19 @@ function sanitizeRecordBatch(
      "The record batch passed in does not appear to be a record batch (no 'data' property)",
    );
  }
-  const schema = sanitizeSchemaWithContext(batchLike.schema, context);
+  const schema = sanitizeSchema(batchLike.schema);
-  const data = sanitizeData(batchLike.data, context) as Data<Struct>;
+  const data = sanitizeData(batchLike.data);
  return new RecordBatch(schema, data);
 }
 type DictionaryVectorLike = {
  data: readonly DataLike[];
 };
 type DictionaryDataLike = DataLike & {
  dictionary?: DictionaryVectorLike;
 };
 function sanitizeData(
  dataLike: DataLike,
-  context: SanitizationContext,
+  // biome-ignore lint/suspicious/noExplicitAny: <explanation>
-): Data<DataType> {
+): import("apache-arrow").Data<Struct<any>> {
  if (dataLike instanceof Data) {
    return dataLike;
  }
-  const cachedData = context.data.get(dataLike);
+  return new Data(
-  if (cachedData !== undefined) {
+    dataLike.type,
    return cachedData;
  }
  const dictionaryLike = (dataLike as DictionaryDataLike).dictionary;
  let dictionary: Vector | undefined;
  if (dictionaryLike !== undefined) {
    dictionary = context.vectors.get(dictionaryLike);
    if (dictionary === undefined) {
      dictionary = new Vector(
        dictionaryLike.data.map((data) => sanitizeData(data, context)),
      );
      context.vectors.set(dictionaryLike, dictionary);
    }
  }
  const data = new Data(
    sanitizeTypeWithContext(dataLike.type, context),
    dataLike.offset,
    dataLike.length,
    dataLike.nullCount,
@@ -730,11 +589,7 @@ function sanitizeData(
      [BufferType.VALIDITY]: dataLike.nullBitmap,
      [BufferType.TYPE]: dataLike.typeIds,
    },
    dataLike.children.map((child) => sanitizeData(child, context)),
    dictionary,
  );
  context.data.set(dataLike, data);
  return data;
 }
 const constructorsByTypeName = {
@@ -30,11 +30,8 @@ import {
  DropColumnsResult,
  IndexConfig,
  IndexStatistics,
  Job,
  LsmStats,
  Branches as NativeBranches,
  OptimizeStats,
  RefreshColumnResult,
  TableStatistics,
  Tags,
  UpdateFieldMetadataResult,
@@ -51,12 +48,6 @@ import {
 import { sanitizeType } from "./sanitize";
 import { IntoSql, toSQL } from "./util";
 export { IndexConfig } from "./native";
 export {
  BucketStats,
  GenerationStats,
  LsmStats,
  MemtableStats,
 } from "./native";
 /**
 * Progress snapshot for a write operation, delivered to the `progress`
@@ -205,11 +196,7 @@ export interface LsmWriteSpec {
  column?: string;
  /** Bucket variant: the number of buckets, in `[1, 1024]`. */
  numBuckets?: number;
-  /**
+  /** Names of indexes the MemWAL should keep up to date during writes. */
   * Indexes the MemWAL keeps up to date. Omit to maintain every supported
   * index, resolved on install — a snapshot, so indexes created later are not
   * maintained. Pass `[]` for none.
   */
  maintainedIndexes?: string[];
  /** Default `ShardWriter` configuration recorded in the MemWAL index. */
  writerConfigDefaults?: Record<string, string>;
@@ -371,17 +358,6 @@ export abstract class Table {
    options?: Partial<IndexOptions>,
  ): Promise<void>;
  /**
   * Create an index, returning a handle to the indexing job.
   *
   * The job may already be complete when returned; callers must not assume
   * the index exists until {@link Job.wait} resolves.
   */
  abstract createIndexAsync(
    column: string,
    options?: Partial<IndexOptions>,
  ): Promise<Job>;
  /**
   * Drop an index from the table.
   *
@@ -533,75 +509,18 @@ export abstract class Table {
  abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
  /**
   * Add new columns with defined values.
   *
   * The `{ computed }` form stores the expression rather than evaluating it
   * now: the column is committed with no values, and rows get them from
   * {@link Table#refreshColumn}. Declaring one therefore costs the same on a
   * large table as on an empty one.
   *
   * A refresh does not revisit rows it has already filled, so mutating an
   * input leaves the value computed at fill time; recomputing means dropping
   * the column and declaring it again. While a declaration reads a column,
   * that column cannot be renamed, retyped or dropped.
   *
   * On LanceDB Cloud and Enterprise the expression is planned by the
   * server, and the refresh runs as a server job -- see
   * {@link Table#refreshColumnAsync}.
   * @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
   *   - An array of objects with column names and SQL expressions to calculate values
   *   - A single Arrow Field defining one column with its data type (column will be initialized with null values)
   *   - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
   *   - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
   *   - `{ computed }`, declaring columns defined by a SQL expression whose type and inputs are derived from it
   * @returns {Promise<AddColumnsResult>} A promise that resolves to an object
   * containing the new version number of the table after adding the columns.
   * @example
   * ```ts
   * await table.addColumns({ computed: [{ name: "doubled", valueSql: "x * 2" }] });
   * const { rowsFilled } = await table.refreshColumn("doubled");
   * ```
   */
  abstract addColumns(
-    newColumnTransforms:
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
      | AddColumnsSql[]
      | Field
      | Field[]
      | Schema
      | { computed: AddColumnsSql[] },
  ): Promise<AddColumnsResult>;
  /**
   * Fill the rows of a computed column that hold no value yet.
   *
   * Rows appended since the last refresh are filled by the next one; rows
   * already filled are left as they are, so the call is idempotent and does
   * not observe a mutated input. Local tables only: a remote refresh runs
   * as a server job, through {@link Table#refreshColumnAsync}.
   * @param {string} column The name of the computed column to fill.
   * @returns {Promise<RefreshColumnResult>} A promise that resolves to the
   * number of rows filled and the new version number of the table.
   */
  abstract refreshColumn(column: string): Promise<RefreshColumnResult>;
  /**
   * Like {@link Table#refreshColumn}, but returns a handle to the refresh
   * job instead of blocking until it completes.
   *
   * The job may already be complete when returned; callers must not assume
   * the column is filled until {@link Job.wait} resolves. Invalid input --
   * an unknown column, or one that is not computed -- rejects here rather
   * than failing the job. On local tables the job runs in-process; on
   * LanceDB Cloud and Enterprise it is the server's backfill job.
   * @param {string} column The name of the computed column to fill.
   * @example
   * ```ts
   * const job = await table.refreshColumnAsync("doubled");
   * await job.wait();
   * console.log(await job.status()); // "finished"
   * ```
   */
  abstract refreshColumnAsync(column: string): Promise<Job>;
  /**
   * Alter the name or nullability of columns.
   * @param {ColumnAlteration[]} columnAlterations One or more alterations to
@@ -664,11 +583,6 @@ export abstract class Table {
   * All variants require the table to have an unenforced primary key
   * ({@link Table#setUnenforcedPrimaryKey}); bucket sharding additionally
   * requires it to be the single column being bucketed.
   *
   * Omitting `maintainedIndexes` maintains every index on the table, resolved
   * here, failing if one cannot be maintained — name them to install anyway.
   * Naming them pins an exact set, and a still-building index is rejected
   * rather than quietly omitted.
   * @param {LsmWriteSpec} spec The sharding spec to install.
   * @returns {Promise<void>}
   * @example
@@ -696,10 +610,9 @@ export abstract class Table {
   *
   * Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
   * spec has been set, or it was removed with {@link Table#unsetLsmWriteSpec}).
-   * The returned spec mirrors what was passed to
+   * The returned spec — including its `maintainedIndexes` and
-   * {@link Table#setLsmWriteSpec}, except that `maintainedIndexes` always
+   * `writerConfigDefaults` — mirrors what was passed to
-   * reports the concrete list resolved when the spec was set — `undefined`
+   * {@link Table#setLsmWriteSpec}.
   * never round-trips.
   * @returns {Promise<LsmWriteSpec | undefined>}
   */
  abstract getLsmWriteSpec(): Promise<LsmWriteSpec | undefined>;
@@ -713,59 +626,6 @@ export abstract class Table {
   * @returns {Promise<void>}
   */
  abstract closeLsmWriters(): Promise<void>;
  /**
   * Seal every bucket's active memtable into a new L0 generation.
   *
   * Returns once the seal is committed. Sealing an empty memtable is a no-op,
   * so this is safe to call repeatedly.
   * @returns {Promise<void>}
   */
  abstract flushLsm(): Promise<void>;
  /**
   * Trigger a background L0 → base compaction pass per bucket.
   *
   * Returns once the passes are *dispatched*, not once they finish — watch
   * {@link Table#getLsmStats} for progress, or use
   * {@link Table#checkpointLsm} to wait for convergence.
   * @returns {Promise<void>}
   */
  abstract compactLsm(): Promise<void>;
  /**
   * Converge this table's LSM write path into its base table.
   *
   * Seals once, then triggers compaction and polls until the L0 that existed
   * at the start is gone. The target set is fixed at the start, so
   * generations created *during* the checkpoint are ignored — that is what
   * lets it terminate under write load, and what makes it best-effort: it
   * converges the fresh tier as of some instant. Idempotent, abandonable at
   * any point, and safe to run on a cadence.
   *
   * There is no liveness bound — the compactor pool is shared across tables,
   * so a checkpoint queued behind unrelated work looks exactly like one that
   * is merging. The caller owns the deadline.
   * @returns {Promise<void>}
   * @example
   * ```ts
   * const before = await table.getLsmStats();
   * await table.checkpointLsm();
   * const after = await table.getLsmStats();
   * ```
   */
  abstract checkpointLsm(): Promise<void>;
  /**
   * Read live per-bucket LSM state.
   *
   * Answers "how far behind is my fresh tier", "which bucket is hot", and
   * "why is my fresh-tier vector search brute-force". Mutates no table state.
   *
   * Resolves to `undefined` only when the LSM write path is not enabled.
   * @param {boolean} includeGenerationRows Also count rows per L0 generation.
   *   Off by default because each count opens an uncached Lance dataset.
   * @returns {Promise<LsmStats | undefined>}
   */
  abstract getLsmStats(
    includeGenerationRows?: boolean,
  ): Promise<LsmStats | undefined>;
  /** Retrieve the version of the table */
  abstract version(): Promise<number>;
@@ -1080,22 +940,6 @@ export class LocalTable extends Table {
    );
  }
  async createIndexAsync(
    column: string,
    options?: Partial<IndexOptions>,
  ): Promise<Job> {
    // biome-ignore lint/suspicious/noExplicitAny: skip
    const nativeIndex = (options?.config as any)?.inner;
    return await this.inner.createIndexAsync(
      nativeIndex,
      column,
      options?.replace,
      options?.waitTimeoutSeconds,
      options?.name,
      options?.train,
    );
  }
  async dropIndex(name: string): Promise<void> {
    await this.inner.dropIndex(name);
  }
@@ -1206,22 +1050,8 @@ export class LocalTable extends Table {
  // TODO: Support BatchUDF
  async addColumns(
-    newColumnTransforms:
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
      | AddColumnsSql[]
      | Field
      | Field[]
      | Schema
      | { computed: AddColumnsSql[] },
  ): Promise<AddColumnsResult> {
    // Columns defined by an expression are declared, not materialized here.
    if (
      typeof newColumnTransforms === "object" &&
      !Array.isArray(newColumnTransforms) &&
      "computed" in newColumnTransforms
    ) {
      return await this.inner.addComputedColumns(newColumnTransforms.computed);
    }
    // Handle single Field -> convert to array of Fields
    if (newColumnTransforms instanceof Field) {
      newColumnTransforms = [newColumnTransforms];
@@ -1256,14 +1086,6 @@ export class LocalTable extends Table {
    throw new Error("Invalid input type for addColumns");
  }
  async refreshColumn(column: string): Promise<RefreshColumnResult> {
    return await this.inner.refreshColumn(column);
  }
  async refreshColumnAsync(column: string): Promise<Job> {
    return await this.inner.refreshColumnAsync(column);
  }
  async alterColumns(
    columnAlterations: ColumnAlteration[],
  ): Promise<AlterColumnsResult> {
@@ -1326,24 +1148,6 @@ export class LocalTable extends Table {
    return await this.inner.closeLsmWriters();
  }
  async flushLsm(): Promise<void> {
    return await this.inner.flushLsm();
  }
  async compactLsm(): Promise<void> {
    return await this.inner.compactLsm();
  }
  async checkpointLsm(): Promise<void> {
    return await this.inner.checkpointLsm();
  }
  async getLsmStats(
    includeGenerationRows: boolean = false,
  ): Promise<LsmStats | undefined> {
    return (await this.inner.getLsmStats(includeGenerationRows)) ?? undefined;
  }
  async version(): Promise<number> {
    return await this.inner.version();
  }
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.38.0-beta.2",
+  "version": "0.37.1-beta.0",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.38.0-beta.2",
+	"version": "0.37.1-beta.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.38.0-beta.2",
+  "version": "0.37.1-beta.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.38.0-beta.2",
+      "version": "0.37.1-beta.0",
      "cpu": [
        "x64",
        "arm64"
@@ -55,13 +55,7 @@
        "openai": "4.29.2"
      },
      "peerDependencies": {
        "@types/node": ">=18",
        "apache-arrow": ">=15.0.0 <=18.1.0"
      },
      "peerDependenciesMeta": {
        "@types/node": {
          "optional": true
        }
      }
    },
    "node_modules/@aws-crypto/crc32": {
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.38.0-beta.2",
+  "version": "0.37.1-beta.0",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -101,12 +101,6 @@
    "openai": "4.29.2"
  },
  "peerDependencies": {
    "@types/node": ">=18",
    "apache-arrow": ">=15.0.0 <=18.1.0"
  },
  "peerDependenciesMeta": {
    "@types/node": {
      "optional": true
    }
  }
 }
@@ -36,12 +36,6 @@ pub struct ListNamespacesResponse {
    pub page_token: Option<String>,
 }
 #[napi(object)]
 pub struct ListTablesResponse {
    pub tables: Vec<String>,
    pub page_token: Option<String>,
 }
 #[napi(object)]
 pub struct CreateNamespaceResponse {
    pub properties: Option<HashMap<String, String>>,
@@ -195,8 +189,6 @@ impl Connection {
    /// List all tables in the dataset.
    #[napi(catch_unwind)]
    // Deprecated in favour of `list_tables`, but still exposed to JavaScript.
    #[allow(deprecated)]
    pub async fn table_names(
        &self,
        namespace_path: Option<Vec<String>>,
@@ -214,29 +206,6 @@ impl Connection {
        op.execute().await.default_error()
    }
    /// List a page of tables in the database.
    #[napi(catch_unwind)]
    pub async fn list_tables(
        &self,
        namespace_path: Option<Vec<String>>,
        page_token: Option<String>,
        limit: Option<u32>,
    ) -> napi::Result<ListTablesResponse> {
        let mut op = self.get_inner()?.list_tables();
        op = op.namespace(namespace_path.unwrap_or_default());
        if let Some(page_token) = page_token {
            op = op.page_token(page_token);
        }
        if let Some(limit) = limit {
            op = op.limit(limit);
        }
        let resp = op.execute().await.default_error()?;
        Ok(ListTablesResponse {
            tables: resp.tables,
            page_token: resp.page_token,
        })
    }
    /// Create table from a Apache Arrow IPC (file) buffer.
    ///
    /// Parameters:
@@ -365,91 +334,12 @@ impl Connection {
            .default_error()
    }
    /// Start dropping a table and return its cleanup job.
    #[napi(catch_unwind)]
    pub async fn drop_table_async(
        &self,
        name: String,
        namespace_path: Option<Vec<String>>,
    ) -> napi::Result<crate::job::Job> {
        let ns = namespace_path.unwrap_or_default();
        let job = self
            .get_inner()?
            .drop_table_async(&name, &ns)
            .await
            .default_error()?;
        Ok(crate::job::Job::new(job))
    }
    #[napi(catch_unwind)]
    pub async fn drop_all_tables(&self, namespace_path: Option<Vec<String>>) -> napi::Result<()> {
        let ns = namespace_path.unwrap_or_default();
        self.get_inner()?.drop_all_tables(&ns).await.default_error()
    }
    /// A `Job` 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.
    #[napi]
    pub fn job(&self, job_id: String) -> napi::Result<crate::job::Job> {
        let job = self.get_inner()?.job(job_id).default_error()?;
        Ok(crate::job::Job::new(job))
    }
    /// List server-side jobs across the database's tables.
    #[napi(catch_unwind)]
    pub async fn list_jobs(&self) -> napi::Result<Vec<crate::job::JobInfo>> {
        let jobs = self.get_inner()?.list_jobs().await.default_error()?;
        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)]
    pub async fn cancel_job(&self, job_id: String) -> napi::Result<bool> {
        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(
@@ -1,123 +0,0 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 use std::sync::Arc;
 use napi_derive::napi;
 use crate::error::NapiErrorExt;
 /// A handle to an operation that may still be running.
 #[napi]
 pub struct Job {
    inner: Arc<lancedb::Job>,
 }
 impl Job {
    pub(crate) fn new(inner: lancedb::Job) -> Self {
        Self {
            inner: Arc::new(inner),
        }
    }
 }
 #[napi]
 impl Job {
    /// Identifies the operation on the server that is running it. Operations
    /// that run in this process have no server id. The value is opaque.
    #[napi(getter)]
    pub fn id(&self) -> Option<String> {
        self.inner.id().map(str::to_string)
    }
    /// 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. States a newer server reports that this
    /// client version does not know pass through as-is.
    #[napi(catch_unwind)]
    pub async fn status(&self) -> napi::Result<String> {
        self.inner.status().await.default_error()
    }
    /// Wait until the operation reaches a terminal state.
    #[napi(catch_unwind)]
    pub async fn wait(&self) -> napi::Result<()> {
        self.inner.wait().await.default_error()
    }
    /// Request cancellation. Cancelling a finished operation is a no-op.
    #[napi(catch_unwind)]
    pub async fn cancel(&self) -> napi::Result<()> {
        self.inner.cancel().await.default_error()
    }
 }
 /// A row from `Connection.listJobs`: one server-side job.
 #[napi(object)]
 pub struct JobInfo {
    /// The job id -- what `Connection.getJob` and `Connection.cancelJob`
    /// accept.
    pub job_id: String,
    /// The table the job runs against, without URI or namespace.
    pub table: 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 created_at_millis: i64,
 }
 impl From<lancedb::database::JobInfo> for JobInfo {
    fn from(info: lancedb::database::JobInfo) -> Self {
        Self {
            job_id: info.job_id,
            table: info.table,
            job_type: info.job_type,
            state: info.state,
            created_at_millis: info.created_at_millis,
        }
    }
 }
 /// The server's account of why a job failed.
 #[napi(object)]
 pub struct JobFailureInfo {
    pub phase: Option<String>,
    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,
            }),
        }
    }
 }
@@ -11,7 +11,6 @@ mod error;
 mod header;
 mod index;
 mod iterator;
 mod job;
 pub mod merge;
 pub mod otel;
 pub mod permutation;
@@ -168,39 +168,6 @@ impl Table {
        builder.execute().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn create_index_async(
        &self,
        index: Option<&Index>,
        column: String,
        replace: Option<bool>,
        wait_timeout_s: Option<i64>,
        name: Option<String>,
        train: Option<bool>,
    ) -> napi::Result<crate::job::Job> {
        let lancedb_index = if let Some(index) = index {
            index.consume()?
        } else {
            lancedb::index::Index::Auto
        };
        let mut builder = self.inner_ref()?.create_index(&[column], lancedb_index);
        if let Some(replace) = replace {
            builder = builder.replace(replace);
        }
        if let Some(timeout) = wait_timeout_s {
            builder =
                builder.wait_timeout(std::time::Duration::from_secs(timeout.try_into().unwrap()));
        }
        if let Some(name) = name {
            builder = builder.name(name);
        }
        if let Some(train) = train {
            builder = builder.train(train);
        }
        let job = builder.execute_async().await.default_error()?;
        Ok(crate::job::Job::new(job))
    }
    #[napi(catch_unwind)]
    pub async fn drop_index(&self, index_name: String) -> napi::Result<()> {
        self.inner_ref()?
@@ -339,48 +306,12 @@ impl Table {
        let transforms = NewColumnTransform::SqlExpressions(transforms);
        let res = self
            .inner_ref()?
-            .add_columns()
+            .add_columns(transforms, None)
            .transform(transforms)
            .execute()
            .await
            .default_error()?;
        Ok(res.into())
    }
    #[napi(catch_unwind)]
    pub async fn add_computed_columns(
        &self,
        columns: Vec<AddColumnsSql>,
    ) -> napi::Result<AddColumnsResult> {
        let table = self.inner_ref()?;
        let mut builder = table.add_columns();
        for column in columns {
            builder = builder.computed(column.name, column.value_sql);
        }
        let res = builder.execute().await.default_error()?;
        Ok(res.into())
    }
    #[napi(catch_unwind)]
    pub async fn refresh_column(&self, column: String) -> napi::Result<RefreshColumnResult> {
        let res = self
            .inner_ref()?
            .refresh_column(column)
            .await
            .default_error()?;
        Ok(res.into())
    }
    #[napi(catch_unwind)]
    pub async fn refresh_column_async(&self, column: String) -> napi::Result<crate::job::Job> {
        let job = self
            .inner_ref()?
            .refresh_column_async(column)
            .await
            .default_error()?;
        Ok(crate::job::Job::new(job))
    }
    #[napi(catch_unwind)]
    pub async fn add_columns_with_schema(
        &self,
@@ -392,9 +323,7 @@ impl Table {
        let transforms = NewColumnTransform::AllNulls(schema);
        let res = self
            .inner_ref()?
-            .add_columns()
+            .add_columns(transforms, None)
            .transform(transforms)
            .execute()
            .await
            .default_error()?;
        Ok(res.into())
@@ -497,34 +426,6 @@ impl Table {
        self.inner_ref()?.close_lsm_writers().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn flush_lsm(&self) -> napi::Result<()> {
        self.inner_ref()?.flush_lsm().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn compact_lsm(&self) -> napi::Result<()> {
        self.inner_ref()?.compact_lsm().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn checkpoint_lsm(&self) -> napi::Result<()> {
        self.inner_ref()?.checkpoint_lsm().await.default_error()
    }
    #[napi(catch_unwind)]
    pub async fn get_lsm_stats(
        &self,
        include_generation_rows: bool,
    ) -> napi::Result<Option<LsmStats>> {
        let stats = self
            .inner_ref()?
            .get_lsm_stats(include_generation_rows)
            .await
            .default_error()?;
        Ok(stats.map(LsmStats::from))
    }
    #[napi(catch_unwind)]
    pub async fn version(&self) -> napi::Result<i64> {
        self.inner_ref()?
@@ -834,8 +735,7 @@ pub struct LsmWriteSpec {
    pub column: Option<String>,
    /// Bucket variant: the number of buckets, in `[1, 1024]`.
    pub num_buckets: Option<u32>,
-    /// Indexes the MemWAL keeps up to date. Omitted resolves every
+    /// Names of indexes the MemWAL should keep up to date during writes.
    /// maintainable index on install; an empty array means none.
    pub maintained_indexes: Option<Vec<String>>,
    /// Default `ShardWriter` configuration recorded in the MemWAL index.
    pub writer_config_defaults: Option<HashMap<String, String>>,
@@ -845,6 +745,7 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
    type Error = napi::Error;
    fn try_from(value: LsmWriteSpec) -> napi::Result<Self> {
        let maintained = value.maintained_indexes.unwrap_or_default();
        let writer_config_defaults = value.writer_config_defaults.unwrap_or_default();
        let spec = match value.spec_type.as_str() {
            "bucket" => {
@@ -871,7 +772,7 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
            }
        };
        Ok(spec
-            .with_maintained_indexes(value.maintained_indexes)
+            .with_maintained_indexes(maintained)
            .with_writer_config_defaults(writer_config_defaults))
    }
 }
@@ -889,7 +790,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
                spec_type: "bucket".to_string(),
                column: Some(column),
                num_buckets: Some(num_buckets),
-                maintained_indexes,
+                maintained_indexes: Some(maintained_indexes),
                writer_config_defaults: Some(writer_config_defaults),
            },
            Native::Identity {
@@ -900,7 +801,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
                spec_type: "identity".to_string(),
                column: Some(column),
                num_buckets: None,
-                maintained_indexes,
+                maintained_indexes: Some(maintained_indexes),
                writer_config_defaults: Some(writer_config_defaults),
            },
            Native::Unsharded {
@@ -910,136 +811,13 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
                spec_type: "unsharded".to_string(),
                column: None,
                num_buckets: None,
-                maintained_indexes,
+                maintained_indexes: Some(maintained_indexes),
                writer_config_defaults: Some(writer_config_defaults),
            },
        }
    }
 }
 /// One flushed L0 generation.
 #[napi(object)]
 #[derive(Clone, Debug)]
 pub struct GenerationStats {
    /// The generation number. Increases as memtables are sealed into L0.
    pub generation: i64,
    /// On-disk size of the generation.
    pub bytes: i64,
    /// Present only when `includeGenerationRows` was requested. Off by default
    /// because each count opens an uncached Lance dataset.
    pub rows: Option<i64>,
 }
 impl From<lancedb::table::GenerationStats> for GenerationStats {
    fn from(g: lancedb::table::GenerationStats) -> Self {
        Self {
            generation: g.generation as i64,
            bytes: g.bytes as i64,
            rows: g.rows.map(|r| r as i64),
        }
    }
 }
 /// One in-memory memtable.
 #[napi(object)]
 #[derive(Clone, Debug)]
 pub struct MemtableStats {
    /// The generation this memtable will become once sealed.
    pub generation: i64,
    /// Rows currently buffered.
    pub rows: i64,
    /// Estimated in-memory size.
    pub bytes: i64,
    /// Record batches currently buffered.
    pub batches: i64,
    /// Names of the indexes this memtable carries. An absent name is the whole
    /// answer to "why is my fresh-tier search on that column brute-force".
    pub indexes: Vec<String>,
 }
 impl From<lancedb::table::MemtableStats> for MemtableStats {
    fn from(m: lancedb::table::MemtableStats) -> Self {
        Self {
            generation: m.generation as i64,
            rows: m.rows as i64,
            bytes: m.bytes as i64,
            batches: m.batches as i64,
            indexes: m.indexes,
        }
    }
 }
 /// Live state of one bucket. A table is N buckets on one node; flattening to a
 /// single number hides the one hot bucket that is usually why someone opened
 /// this endpoint.
 #[napi(object)]
 #[derive(Clone, Debug)]
 pub struct BucketStats {
    /// The shard this bucket writes.
    pub shard_id: String,
    /// `"Active"` or `"Sealed"` (drop-table 2PC in flight).
    pub status: String,
    /// Epoch of the writer that currently owns the shard.
    pub writer_epoch: i64,
    /// Version of the shard manifest these numbers were read from.
    pub manifest_version: i64,
    /// The generation the active memtable will become.
    pub current_generation: i64,
    /// WAL position replay resumes from.
    pub replay_after_wal_entry_position: i64,
    /// Highest WAL position the writer has seen. The difference against
    /// `replayAfterWalEntryPosition` is the WAL lag.
    pub wal_entry_position_last_seen: i64,
    /// Flushed L0 generations not yet merged into the base table.
    pub generations: Vec<GenerationStats>,
    /// Whether a pass owns this bucket's compaction latch right now. Says *a*
    /// driver is running, not *whose*, and the latch is held from dispatch —
    /// including while the pass queues for a pod-wide compactor permit. Read it
    /// as "do not pile on", never as "mine is progressing".
    pub compacting: bool,
    /// Oldest first, active last. Absent for a `"Sealed"` bucket, whose
    /// in-memory state is torn down.
    pub memtables: Option<Vec<MemtableStats>>,
 }
 impl From<lancedb::table::BucketStats> for BucketStats {
    fn from(b: lancedb::table::BucketStats) -> Self {
        Self {
            shard_id: b.shard_id,
            status: b.status,
            writer_epoch: b.writer_epoch as i64,
            manifest_version: b.manifest_version as i64,
            current_generation: b.current_generation as i64,
            replay_after_wal_entry_position: b.replay_after_wal_entry_position as i64,
            wal_entry_position_last_seen: b.wal_entry_position_last_seen as i64,
            generations: b.generations.into_iter().map(Into::into).collect(),
            compacting: b.compacting,
            memtables: b
                .memtables
                .map(|ms| ms.into_iter().map(Into::into).collect()),
        }
    }
 }
 /// Live per-bucket LSM state, as returned by `Table#getLsmStats`.
 ///
 /// Nothing here is derived: sums and differences (total L0 bytes, WAL lag) are
 /// the caller's to compute.
 #[napi(object)]
 #[derive(Clone, Debug)]
 pub struct LsmStats {
    /// One entry per bucket backing this table.
    pub buckets: Vec<BucketStats>,
 }
 impl From<lancedb::table::LsmStats> for LsmStats {
    fn from(stats: lancedb::table::LsmStats) -> Self {
        Self {
            buckets: stats.buckets.into_iter().map(Into::into).collect(),
        }
    }
 }
 /// Statistics about a compaction operation.
 #[napi(object)]
 #[derive(Clone, Debug)]
@@ -1228,10 +1006,7 @@ impl From<lancedb::index::IndexStatistics> for IndexStatistics {
 #[napi(object)]
 pub struct TableStatistics {
-    /// The total size, in bytes, of the table's data files, index files, and
+    /// The total number of bytes in the table
    /// overlay files
    ///
    /// Read from the manifest, so this excludes deletion files and manifests.
    pub total_bytes: i64,
    /// The number of rows in the table
@@ -1381,21 +1156,6 @@ pub struct AddColumnsResult {
    pub version: i64,
 }
 #[napi(object)]
 pub struct RefreshColumnResult {
    pub rows_filled: i64,
    pub version: i64,
 }
 impl From<lancedb::table::RefreshColumnResult> for RefreshColumnResult {
    fn from(value: lancedb::table::RefreshColumnResult) -> Self {
        Self {
            rows_filled: value.rows_filled as i64,
            version: value.version as i64,
        }
    }
 }
 impl From<lancedb::table::AddColumnsResult> for AddColumnsResult {
    fn from(value: lancedb::table::AddColumnsResult) -> Self {
        Self {
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.38.0-beta.2"
+version = "0.37.1-beta.0"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
@@ -26,7 +26,7 @@ lance-namespace-impls.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
 log.workspace = true
-pyo3 = { version = "0.28", features = ["extension-module", "abi3-py310", "chrono"] }
+pyo3 = { version = "0.28", features = ["extension-module", "abi3-py39", "chrono"] }
 chrono = { version = "0.4", default-features = false, features = ["clock"] }
 pyo3-async-runtimes = { version = "0.28", features = [
    "attributes",
@@ -43,7 +43,7 @@ libc = "0.2"
 [build-dependencies]
 pyo3-build-config = { version = "0.28", features = [
    "extension-module",
-    "abi3-py310",
+    "abi3-py39",
 ] }
 [features]
@@ -60,7 +60,7 @@ tests = [
    "pytest-asyncio>=0.21",
    "duckdb>=0.9.0",
    "pytz>=2023.3",
-    "polars>=0.19, <=1.32.3",
+    "polars>=0.19, <=1.3.0",
    "pyarrow<25",
    "pyarrow-stubs>=16.0",
    "pylance==9.0.0rc1",
@@ -140,7 +140,6 @@ include = [
    "python/lancedb/remote/errors.py",
    "python/lancedb/embeddings/__init__.py",
    "python/lancedb/_lancedb.pyi",
    "python/type_tests/connect.py",
 ]
 exclude = ["python/tests/"]
 pythonVersion = "3.13"
@@ -12,7 +12,6 @@ __version__ = importlib.metadata.version("lancedb")
 from ._lancedb import connect as lancedb_connect
 from ._lancedb import FtsToken
 from ._lancedb import LsmWriteSpec
 from ._lancedb import tokenize as _tokenize
 from .common import URI, sanitize_uri
 from urllib.parse import urlparse
@@ -21,7 +20,6 @@ from .remote import ClientConfig
 from .remote.db import RemoteDBConnection
 from .expr import Expr, col, lit, func
 from .schema import blob, vector, BlobType
 from .job import AsyncJob, Job
 from .table import AsyncTable, Table
 from .types import BaseTokenizerType
 from ._lancedb import Session
@@ -502,7 +500,6 @@ __all__ = [
    "connect_namespace",
    "connect_namespace_async",
    "AsyncConnection",
    "AsyncJob",
    "AsyncLanceNamespaceDBConnection",
    "AsyncTable",
    "FtsToken",
@@ -516,10 +513,8 @@ __all__ = [
    "BlobType",
    "vector",
    "DBConnection",
    "Job",
    "LanceDBConnection",
    "LanceNamespaceDBConnection",
    "LsmWriteSpec",
    "RemoteDBConnection",
    "Session",
    "Table",
@@ -14,10 +14,14 @@ import pyarrow as pa
 from .expr import Expr
 from .schema import blob_v2_column_paths
 from .types import BlobMode, QueryProjection, QueryProjectionSpec
 from .util import get_uri_scheme
 if TYPE_CHECKING:
    from _typeshed import WriteableBuffer
    from .remote.table import RemoteTable
    from .table import AsyncTable, Table
 BLOB_MODE_TO_HANDLING = {
    "lazy": "blobs_descriptions",
    "bytes": "all_binary",
@@ -100,6 +104,22 @@ def validate_blob_mode(blob_mode: BlobMode) -> None:
        raise ValueError(f"blob_mode must be one of {modes}, got {blob_mode!r}")
 def supports_blob_auto_row_id(table: Table | AsyncTable | RemoteTable) -> bool:
    """Blob auto row-id applies to native tables, not LanceDB Cloud."""
    from .remote.table import RemoteTable
    if isinstance(table, RemoteTable):
        return False
    inner = getattr(table, "_inner", None)
    if inner is not None:
        uri = inner.database().uri
        if isinstance(uri, str) and get_uri_scheme(uri) == "db":
            return False
    return True
 def projection_includes_blob_column(
    projection: QueryProjection,
    blob_columns: Iterable[str],
@@ -144,14 +164,16 @@ def v2_projection_needs_row_id(
 def blob_auto_row_id_for_scan(
    table: Table | AsyncTable | RemoteTable,
    schema: pa.Schema,
    projection: QueryProjection,
    *,
    with_row_id: bool | None,
 ) -> bool:
    """Auto row-id only applies when the caller said nothing about row ids."""
    if with_row_id is not None:
        return False
    if not supports_blob_auto_row_id(table):
        return False
    return v2_projection_needs_row_id(schema, projection, with_row_id=False)
@@ -164,11 +186,6 @@ def finalize_blob_query_table(
 ) -> pa.Table:
    if user_requested_row_id or not blob_auto_row_id:
        return tbl
    if "_rowid" not in tbl.column_names:
        # A backend that ignores the row-id request leaves nothing to stash. Hand
        # back the projection as-is so fetch_blobs raises the error that names the
        # ways to supply row ids, rather than failing here about a hidden column.
        return tbl
    return stash_auto_row_ids(tbl, blob_paths)
@@ -146,13 +146,6 @@ class Connection(object):
        start_after: Optional[str],
        limit: Optional[int],
    ) -> list[str]: ...  # Deprecated: Use list_tables instead
    def job(self, job_id: str) -> Job: ...
    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 job_history(
        self, job_id: Optional[str] = None
    ) -> List[pa.RecordBatch]: ...
    async def create_table(
        self,
        name: str,
@@ -198,9 +191,6 @@ class Connection(object):
    async def drop_table(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> None: ...
    async def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> Job: ...
    async def drop_all_tables(
        self, namespace_path: Optional[List[str]] = None
    ) -> None: ...
@@ -219,47 +209,6 @@ class BlobFile:
    def read_range(self, offset: int, length: int) -> bytes: ...
    def read_up_to(self, length: int) -> bytes: ...
 class Job:
    @property
    def id(self) -> Optional[str]: ...
    async def status(self) -> str: ...
    async def wait(self) -> None: ...
    async def cancel(self) -> None: ...
 class JobInfo:
    @property
    def job_id(self) -> str: ...
    @property
    def table(self) -> str: ...
    @property
    def job_type(self) -> str: ...
    @property
    def state(self) -> str: ...
    @property
    def created_at_millis(self) -> int: ...
 class JobFailureInfo:
    @property
    def phase(self) -> Optional[str]: ...
    @property
    def message(self) -> Optional[str]: ...
    @property
    def retryable(self) -> Optional[bool]: ...
 class JobDescription:
    @property
    def job_id(self) -> str: ...
    @property
    def job_type(self) -> str: ...
    @property
    def state(self) -> str: ...
    @property
    def creation_ms(self) -> int: ...
    @property
    def spec_json(self) -> Optional[str]: ...
    @property
    def failure(self) -> Optional[JobFailureInfo]: ...
 class Table:
    def name(self) -> str: ...
    def __repr__(self) -> str: ...
@@ -299,28 +248,6 @@ class Table:
        name: Optional[str],
        train: Optional[bool],
    ): ...
    async def create_index_async(
        self,
        column: str,
        index: Union[
            IvfFlat,
            IvfSq,
            IvfPq,
            HnswPq,
            HnswSq,
            HnswFlat,
            BTree,
            Bitmap,
            LabelList,
            Fm,
            FTS,
        ],
        replace: Optional[bool],
        wait_timeout: Optional[object],
        *,
        name: Optional[str],
        train: Optional[bool],
    ) -> Job: ...
    async def list_versions(self) -> List[Dict[str, Any]]: ...
    async def version(self) -> int: ...
    async def checkout(self, version: Union[int, str]): ...
@@ -338,11 +265,6 @@ class Table:
    ) -> list[FtsToken]: ...
    async def delete(self, filter: Union[str, PyExpr]) -> DeleteResult: ...
    async def add_columns(self, columns: list[tuple[str, str]]) -> AddColumnsResult: ...
    async def add_computed_columns(
        self, columns: list[tuple[str, str]]
    ) -> AddColumnsResult: ...
    async def refresh_column(self, column: str) -> RefreshColumnResult: ...
    async def refresh_column_async(self, column: str) -> Job: ...
    async def add_columns_with_schema(self, schema: pa.Schema) -> AddColumnsResult: ...
    async def alter_columns(
        self, columns: list[dict[str, Any]]
@@ -363,10 +285,6 @@ class Table:
    async def set_lsm_write_spec(self, spec: LsmWriteSpec) -> None: ...
    async def unset_lsm_write_spec(self) -> None: ...
    async def get_lsm_write_spec(self) -> Optional[LsmWriteSpec]: ...
    async def checkpoint_lsm(self) -> None: ...
    async def flush_lsm(self) -> None: ...
    async def compact_lsm(self) -> None: ...
    async def get_lsm_stats(self, include_generation_rows: bool) -> Optional[dict]: ...
    async def close_lsm_writers(self) -> None: ...
    @property
    def tags(self) -> Tags: ...
@@ -661,10 +579,9 @@ class LsmWriteSpec:
    def identity(column: str) -> "LsmWriteSpec": ...
    @staticmethod
    def unsharded() -> "LsmWriteSpec": ...
-    def with_maintained_indexes(self, indexes: Optional[List[str]]) -> "LsmWriteSpec":
+    def with_maintained_indexes(self, indexes: List[str]) -> "LsmWriteSpec":
-        """Set which indexes the MemWAL keeps up to date. None resolves every
+        """Return a copy of this spec asking the MemWAL to keep the named
-        index on the table at install, failing if one cannot be maintained;
+        indexes up to date as rows are appended."""
        a list is verbatim, empty means none."""
        ...
    def with_writer_config_defaults(self, defaults: Dict[str, str]) -> "LsmWriteSpec":
        """Return a copy of this spec recording the given default
@@ -679,19 +596,13 @@ class LsmWriteSpec:
    @property
    def num_buckets(self) -> Optional[int]: ...
    @property
-    def maintained_indexes(self) -> Optional[List[str]]:
+    def maintained_indexes(self) -> List[str]: ...
        """Indexes the MemWAL keeps up to date, or None for every supported one."""
        ...
    @property
    def writer_config_defaults(self) -> Dict[str, str]: ...
 class AddColumnsResult:
    version: int
 class RefreshColumnResult:
    rows_filled: int
    version: int
 class AlterColumnsResult:
    version: int
@@ -45,7 +45,6 @@ from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError
 from . import __version__
 from ._lancedb import connect as lancedb_connect  # type: ignore
 from .job import AsyncJob, Job
 from .table import (
    AsyncTable,
    LanceTable,
@@ -64,7 +63,6 @@ if TYPE_CHECKING:
    from .pydantic import LanceModel
    from ._lancedb import Connection as LanceDbConnection
    from ._lancedb import JobDescription, JobInfo
    from .common import DATA, URI
    from .embeddings import EmbeddingFunctionConfig
    from ._lancedb import Session
@@ -180,51 +178,6 @@ class DBConnection(EnforceOverrides):
            "Namespace operations are not supported for this connection type"
        )
    def namespace_exists(self, namespace_id: List[str]) -> bool:
        """Check if a namespace exists.
        Parameters
        ----------
        namespace_id: List[str]
            The namespace identifier to check.
        Returns
        -------
        bool
            True if the namespace exists, False otherwise.
        Raises
        ------
        NotImplementedError
            If the connection type does not support namespace operations.
        """
        raise NotImplementedError(
            "Namespace operations are not supported for this connection type"
        )
    def table_exists(self, table_id: List[str]) -> bool:
        """Check if a table exists.
        Parameters
        ----------
        table_id: List[str]
            The table identifier to check (full path including namespace
            segments and table name).
        Returns
        -------
        bool
            True if the table exists, False otherwise.
        Raises
        ------
        NotImplementedError
            If the connection type does not support namespace operations.
        """
        raise NotImplementedError(
            "Namespace operations are not supported for this connection type"
        )
    def list_tables(
        self,
        namespace_path: Optional[List[str]] = None,
@@ -524,12 +477,6 @@ class DBConnection(EnforceOverrides):
            namespace_path = []
        raise NotImplementedError
    def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> Job:
        """Start dropping a table and return its cleanup job."""
        raise NotImplementedError
    def rename_table(
        self,
        cur_name: str,
@@ -616,46 +563,6 @@ class DBConnection(EnforceOverrides):
        """
        raise NotImplementedError("serialize is not supported for this connection type")
    def job(self, job_id: str) -> Job:
        """A [Job][lancedb.job.Job] 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.
        """
        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.
        Returns True if the server accepted the cancellation, False if no
        such job exists. Cancelling an already-terminal job is a no-op
        success.
        """
        raise NotImplementedError(
            "cancel_job is not supported for this connection type"
        )
    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.
        """
        raise NotImplementedError(
            "job_history is not supported for this connection type"
        )
 class LanceDBConnection(DBConnection):
    """
@@ -713,9 +620,6 @@ class LanceDBConnection(DBConnection):
        self._namespace_client_properties = namespace_client_properties
        if _inner is not None:
            self._conn = _inner
            # Native-derived wrappers resolve this in their async reconstruction
            # path so construction never synchronously re-enters LOOP.
            self._read_consistency_interval = read_consistency_interval
            self._cached_namespace_client = None
            return
@@ -765,14 +669,11 @@ class LanceDBConnection(DBConnection):
        # storage_options.  Also, this class really shouldn't be holding any state
        # beyond _conn.
        self._conn = AsyncConnection(LOOP.run(do_connect()))
        # Keep property access synchronous so debugger introspection cannot wait on
        # the background loop while that thread is suspended at a breakpoint.
        self._read_consistency_interval = read_consistency_interval
        self._cached_namespace_client: Optional[LanceNamespace] = None
    @property
    def read_consistency_interval(self) -> Optional[timedelta]:
-        return self._read_consistency_interval
+        return LOOP.run(self._conn.get_read_consistency_interval())
    @property
    def session(self) -> Optional[Session]:
@@ -783,19 +684,15 @@ class LanceDBConnection(DBConnection):
        return self._conn.uri
    @classmethod
-    def from_inner(
+    def from_inner(cls, inner: LanceDbConnection):
-        cls,
+        return cls(None, _inner=inner)
        inner: LanceDbConnection,
        read_consistency_interval: Optional[timedelta],
    ):
        return cls(
            None,
            read_consistency_interval=read_consistency_interval,
            _inner=inner,
        )
    def __repr__(self) -> str:
-        return f"{self.__class__.__name__}(uri={self._conn.uri!r})"
+        val = f"{self.__class__.__name__}(uri={self._conn.uri!r}"
        if self.read_consistency_interval is not None:
            val += f", read_consistency_interval={repr(self.read_consistency_interval)}"
        val += ")"
        return val
    @override
    def serialize(self) -> str:
@@ -1192,20 +1089,6 @@ class LanceDBConnection(DBConnection):
            )
        )
    @override
    def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> Job:
        """Start dropping a table and return its cleanup job.
        The table may become unavailable before its data files are removed.
        Call :meth:`Job.wait` to wait for cleanup to finish.
        """
        if namespace_path is None:
            namespace_path = []
        job = LOOP.run(self._conn.drop_table_async(name, namespace_path=namespace_path))
        return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
    @override
    def drop_all_tables(self, namespace_path: Optional[List[str]] = None):
        if namespace_path is None:
@@ -1246,47 +1129,6 @@ class LanceDBConnection(DBConnection):
            )
        )
    @override
    def job(self, job_id: str) -> Job:
        """A [Job][lancedb.job.Job] 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.
        """
        return Job(self._conn.job(job_id))
    @override
    def list_jobs(self) -> List[JobInfo]:
        """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.
        Returns True if the server accepted the cancellation, False if no
        such job exists. Cancelling an already-terminal job is a no-op
        success.
        """
        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.
@@ -1983,23 +1825,6 @@ class AsyncConnection(object):
            if f"Table '{name}' was not found" not in str(e):
                raise e
    async def drop_table_async(
        self,
        name: str,
        *,
        namespace_path: Optional[List[str]] = None,
    ) -> AsyncJob:
        """Start dropping a table and return its cleanup job.
        The table may become unavailable before its data files are removed.
        Await :meth:`AsyncJob.wait` to wait for cleanup to finish.
        """
        if namespace_path is None:
            namespace_path = []
        return AsyncJob(
            await self._inner.drop_table_async(name, namespace_path=namespace_path)
        )
    async def drop_all_tables(self, namespace_path: Optional[List[str]] = None):
        """Drop all tables from the database.
@@ -2013,43 +1838,6 @@ class AsyncConnection(object):
            namespace_path = []
        await self._inner.drop_all_tables(namespace_path=namespace_path)
    def job(self, job_id: str) -> AsyncJob:
        """An [AsyncJob][lancedb.job.AsyncJob] 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.
        """
        return AsyncJob(self._inner.job(job_id))
    async def list_jobs(self) -> List[JobInfo]:
        """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.
        Returns True if the server accepted the cancellation, False if no
        such job exists. Cancelling an already-terminal job is a no-op
        success.
        """
        return await self._inner.cancel_job(job_id)
    async 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 await self._inner.job_history(job_id)
    async def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.
@@ -101,7 +101,8 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):
    @weak_lru(maxsize=1)
    def ndims(self):
-        return len(self.generate_embeddings([[self.source_instruction, "foo"]])[0])
+        model = self.get_model()
        return model.encode("foo").shape[0]
    def compute_query_embeddings(self, query: str, *args, **kwargs) -> List[np.array]:
        return self.generate_embeddings([[self.query_instruction, query]])
@@ -87,13 +87,12 @@ class JinaEmbeddings(EmbeddingFunction):
        if isinstance(image, bytes):
            image_dict = {"image": base64.b64encode(image).decode("utf-8")}
        elif isinstance(image, (str, Path)):
-            parsed = urlparse(str(image))
+            parsed = urlparse.urlparse(image)
            # TODO handle drive letter on windows.
            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
            if parsed.scheme == "file":
                pil_image = PIL_Image.open(parsed.path)
-            elif parsed.scheme == "" or (os.name == "nt" and len(parsed.scheme) == 1):
+            elif parsed.scheme == "":
                # A Windows drive letter parses as a one-character scheme
                # ("C:\\img.png" -> scheme="c"), so treat it as a local path.
                pil_image = PIL_Image.open(image if os.name == "nt" else parsed.path)
            elif parsed.scheme.startswith("http"):
                pil_image = PIL_Image.open(io.BytesIO(url_retrieve(image)))
@@ -23,15 +23,3 @@ class MissingColumnError(KeyError):
        return (
            f"Error: Column '{self.column_name}' does not exist in the DataFrame object"
        )
 class JobFailedError(RuntimeError):
    """Exception raised when an asynchronous job reaches the failed state."""
    pass
 class JobCancelledError(RuntimeError):
    """Exception raised when an asynchronous job was cancelled."""
    pass
@@ -1,105 +0,0 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 """Handles to operations a server may run asynchronously."""
 import asyncio
 from datetime import timedelta
 from typing import Optional
 from lancedb.background_loop import LOOP
 from . import _lancedb
 class AsyncJob:
    """A handle to an operation that may still be running.
    The operation may already be complete when the handle is created.
    """
    def __init__(self, inner: Optional["_lancedb.Job"]):
        self._inner = inner
    @property
    def id(self) -> Optional[str]:
        """Identifies the operation on the server that is running it.
        Returned for correlating with server logs or the jobs API. Operations
        that run in this process have no server id and return `None`. The value
        is opaque: parsing it or storing it to resume the job later is not
        supported.
        """
        return self._inner.id if self._inner is not None else None
    async def status(self) -> str:
        """The operation's current lifecycle state: "running", "finished",
        "failed", or "cancelled".
        A point snapshot; unlike `wait` it does not block or raise on a
        terminal failure state. States a newer server reports that this
        client version does not know pass through as-is.
        """
        if self._inner is None:
            return "finished"
        return await self._inner.status()
    async def wait(self, timeout: Optional[timedelta] = None):
        """Wait until the operation reaches a terminal state.
        Raises `JobFailedError` if the operation failed, `JobCancelledError`
        if it was cancelled, and `TimeoutError` if `timeout` elapses first.
        """
        if self._inner is None:
            return
        if timeout is None:
            await self._inner.wait()
        else:
            await asyncio.wait_for(self._inner.wait(), timeout.total_seconds())
    async def cancel(self):
        """Request cancellation. Cancelling a finished operation is a no-op."""
        if self._inner is None:
            return
        await self._inner.cancel()
 class Job:
    """Synchronous counterpart of `AsyncJob`."""
    def __init__(self, inner: Optional[AsyncJob]):
        self._inner = inner
    @property
    def id(self) -> Optional[str]:
        """Identifies the operation on the server that is running it.
        See :attr:`AsyncJob.id`.
        """
        return self._inner.id if self._inner is not None else None
    def status(self) -> str:
        """The operation's current lifecycle state: "running", "finished",
        "failed", or "cancelled".
        See :meth:`AsyncJob.status`.
        """
        if self._inner is None:
            return "finished"
        return LOOP.run(self._inner.status())
    def wait(self, timeout: Optional[timedelta] = None):
        """Block until the operation reaches a terminal state.
        Raises `JobFailedError` if the operation failed, `JobCancelledError`
        if it was cancelled, and `TimeoutError` if `timeout` elapses first.
        """
        if self._inner is None:
            return
        LOOP.run(self._inner.wait(timeout))
    def cancel(self):
        """Request cancellation. Cancelling a finished operation is a no-op."""
        if self._inner is None:
            return
        LOOP.run(self._inner.cancel())
@@ -92,10 +92,8 @@ class LanceMergeInsertBuilder(object):
        self._when_not_matched_by_source_delete = True
        if isinstance(condition, Expr):
            self._when_not_matched_by_source_condition_expr = condition._inner
-            self._when_not_matched_by_source_condition = None
+        elif condition is not None:
        else:
            self._when_not_matched_by_source_condition = condition
            self._when_not_matched_by_source_condition_expr = None
        return self
    def use_index(self, use_index: bool) -> LanceMergeInsertBuilder:
@@ -38,18 +38,13 @@ from lance_namespace_urllib3_client.models.query_table_request_vector import (
    QueryTableRequestVector,
 )
 from lance_namespace_urllib3_client.models.string_fts_query import StringFtsQuery
-from lance_namespace.errors import (
+from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError
    NamespaceNotEmptyError,
    NamespaceNotFoundError,
    TableNotFoundError,
 )
 from lancedb._lancedb import (
    connect_namespace as _connect_namespace,
    connect_namespace_client as _connect_namespace_client,
 )
 from lancedb.background_loop import LOOP
 from lancedb.db import AsyncConnection, DBConnection
 from lancedb.job import AsyncJob, Job
 from lance_namespace import (
    LanceNamespace,
    connect as namespace_connect,
@@ -58,8 +53,6 @@ from lance_namespace import (
    DropNamespaceResponse,
    ListNamespacesResponse,
    ListTablesResponse,
    NamespaceExistsRequest,
    TableExistsRequest,
 )
 from lancedb.table import AsyncTable, LanceTable, Table
 from lancedb.util import validate_table_name
@@ -625,18 +618,6 @@ class LanceNamespaceDBConnection(DBConnection):
            namespace_path = []
        LOOP.run(self._inner.drop_table(name, namespace_path=namespace_path))
    @override
    def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> Job:
        """Start dropping a table and return its cleanup job."""
        if namespace_path is None:
            namespace_path = []
        job = LOOP.run(
            self._inner.drop_table_async(name, namespace_path=namespace_path)
        )
        return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
    @override
    def rename_table(
        self,
@@ -799,51 +780,6 @@ class LanceNamespaceDBConnection(DBConnection):
        """
        return LOOP.run(self._inner.describe_namespace(namespace_path))
    @override
    def namespace_exists(self, namespace_id: List[str]) -> bool:
        """
        Check if a namespace exists.
        Parameters
        ----------
        namespace_id : List[str]
            The namespace identifier to check.
        Returns
        -------
        bool
            True if the namespace exists, False otherwise.
        """
        request = NamespaceExistsRequest(id=namespace_id)
        try:
            self._namespace_client.namespace_exists(request)
            return True
        except NamespaceNotFoundError:
            return False
    @override
    def table_exists(self, table_id: List[str]) -> bool:
        """
        Check if a table exists.
        Parameters
        ----------
        table_id : List[str]
            The table identifier to check (full path including namespace
            segments and table name).
        Returns
        -------
        bool
            True if the table exists, False otherwise.
        """
        request = TableExistsRequest(id=table_id)
        try:
            self._namespace_client.table_exists(request)
            return True
        except TableNotFoundError:
            return False
    @override
    def list_tables(
        self,
@@ -1147,14 +1083,6 @@ class AsyncLanceNamespaceDBConnection:
            namespace_path = []
        await self._inner.drop_table(name, namespace_path=namespace_path)
    async def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> AsyncJob:
        """Start dropping a table and return its cleanup job."""
        if namespace_path is None:
            namespace_path = []
        return await self._inner.drop_table_async(name, namespace_path=namespace_path)
    async def rename_table(
        self,
        cur_name: str,
@@ -1305,49 +1233,6 @@ class AsyncLanceNamespaceDBConnection:
        """
        return await self._inner.describe_namespace(namespace_path)
    async def namespace_exists(self, namespace_id: List[str]) -> bool:
        """
        Check if a namespace exists.
        Parameters
        ----------
        namespace_id : List[str]
            The namespace identifier to check.
        Returns
        -------
        bool
            True if the namespace exists, False otherwise.
        """
        request = NamespaceExistsRequest(id=namespace_id)
        try:
            self._namespace_client.namespace_exists(request)
            return True
        except NamespaceNotFoundError:
            return False
    async def table_exists(self, table_id: List[str]) -> bool:
        """
        Check if a table exists.
        Parameters
        ----------
        table_id : List[str]
            The table identifier to check (full path including namespace
            segments and table name).
        Returns
        -------
        bool
            True if the table exists, False otherwise.
        """
        request = TableExistsRequest(id=table_id)
        try:
            self._namespace_client.table_exists(request)
            return True
        except TableNotFoundError:
            return False
    async def list_tables(
        self,
        namespace_path: Optional[List[str]] = None,
@@ -226,7 +226,7 @@ class PermutationBuilder:
        async def do_execute():
            inner_tbl = await self._async.execute()
-            return await LanceTable.from_inner(inner_tbl)
+            return LanceTable.from_inner(inner_tbl)
        return LOOP.run(do_execute())
@@ -1 +0,0 @@
@@ -153,16 +153,6 @@ def Vector(
    return FixedSizeList
 def _raise_bare_vector_error(*_args):
    raise TypeError("Vector must be parameterized with a dimension, e.g. Vector(128).")
 # Pydantic v1 and v2 otherwise treat the bare Vector factory as a field validator
 # and inspect its signature, which produces misleading errors about internal types.
 setattr(Vector, "__get_validators__", _raise_bare_vector_error)
 setattr(Vector, "__get_pydantic_core_schema__", _raise_bare_vector_error)
 def MultiVector(
    dim: int, value_type: pa.DataType = pa.float32(), nullable: bool = True
 ) -> Type:
@@ -52,6 +52,7 @@ from ._blob import (
    finalize_blob_query_table,
    replace_v2_blob_columns_with_bytes,
    replace_v2_blob_columns_with_bytes_sync,
    supports_blob_auto_row_id,
    validate_blob_mode,
 )
 from .types import BlobMode, QueryProjection
@@ -1279,7 +1280,10 @@ class LanceQueryBuilder(ABC):
        return self._with_row_id is True
    def _blob_auto_row_id_enabled(self) -> bool:
        if not supports_blob_auto_row_id(self._table):
            return False
        return blob_auto_row_id_for_scan(
            self._table,
            self._table.schema,
            self._columns,
            with_row_id=self._with_row_id,
@@ -2235,7 +2239,6 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
            reranker=self._reranker,
            limit=self._limit,
            with_row_ids=True,
            offset=self._offset,
        )
        return self._finish_hybrid_results(results)
@@ -2257,7 +2260,6 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
        reranker,
        limit: int,
        with_row_ids: bool,
        offset: Optional[int] = None,
    ) -> pa.Table:
        if norm == "rank":
            vector_results = LanceHybridQueryBuilder._rank(vector_results, "_distance")
@@ -2334,7 +2336,7 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
            score_i = results.column_names.index("_score")
            results = results.set_column(score_i, "_score", original_scores)
-        results = results.slice(offset=offset or 0, length=limit)
+        results = results.slice(length=limit)
        if not with_row_ids:
            results = results.drop(["_rowid"])
@@ -2681,12 +2683,8 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
        # Apply common configurations
        if self._limit:
-            # The final offset/limit window is sliced out of the combined,
+            self._vector_query.limit(self._limit)
-            # reranked results, so each sub-query must fetch enough rows to
+            self._fts_query.limit(self._limit)
            # cover the skipped prefix as well as the window itself.
            sub_query_limit = self._limit + (self._offset or 0)
            self._vector_query.limit(sub_query_limit)
            self._fts_query.limit(sub_query_limit)
        if self._columns:
            self._vector_query.select(self._columns)
            self._fts_query.select(self._columns)
@@ -2703,7 +2701,7 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
            self._fts_query.phrase_query(True)
        if self._distance_type:
            self._vector_query.metric(self._distance_type)
-        if self._minimum_nprobes is not None:
+        if self._minimum_nprobes:
            self._vector_query.minimum_nprobes(self._minimum_nprobes)
        if self._maximum_nprobes is not None:
            self._vector_query.maximum_nprobes(self._maximum_nprobes)
@@ -2776,7 +2774,7 @@ class AsyncQueryBase(object):
        )
    async def _maybe_add_blob_row_id(self) -> None:
-        if self._table is None:
+        if self._table is None or not supports_blob_auto_row_id(self._table):
            self._blob_auto_row_id = False
            self._blob_paths = ()
            return
@@ -2784,6 +2782,7 @@ class AsyncQueryBase(object):
        req = self._inner.to_query_request()
        schema = await self._table.schema()
        self._blob_auto_row_id = blob_auto_row_id_for_scan(
            self._table,
            schema,
            req.select,
            with_row_id=self._with_row_id,
@@ -3035,6 +3034,7 @@ class AsyncQueryBase(object):
        schema = await self._table.schema()
        blob_auto_row_id = blob_auto_row_id_for_scan(
            self._table,
            schema,
            query.columns,
            with_row_id=self._with_row_id,
@@ -3880,9 +3880,10 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        req = fts_query._inner.to_query_request()
        blob_auto_row_id = False
        blob_paths: tuple[str, ...] = ()
-        if self._table is not None:
+        if self._table is not None and supports_blob_auto_row_id(self._table):
            schema = await self._table.schema()
            blob_auto_row_id = blob_auto_row_id_for_scan(
                self._table,
                schema,
                req.select,
                with_row_id=self._with_row_id,
@@ -7,7 +7,7 @@ import json
 import logging
 from concurrent.futures import ThreadPoolExecutor
 import sys
-from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
+from typing import Any, Dict, Iterable, List, Optional, Union
 from urllib.parse import urlparse
 import warnings
@@ -23,10 +23,6 @@ import pyarrow as pa
 from ..common import DATA
 from ..db import DBConnection, LOOP
 from ..job import AsyncJob, Job
 if TYPE_CHECKING:
    from .._lancedb import JobDescription, JobInfo
 from ..embeddings import EmbeddingFunctionConfig
 from lance_namespace import (
    LanceNamespace,
@@ -419,11 +415,6 @@ class RemoteDBConnection(DBConnection):
        if namespace_path is None:
            namespace_path = []
        if storage_options is not None:
            logging.info(
                "storage_options is ignored in LanceDb Cloud"
                " (storage is managed; set storage_options on connect() instead)"
            )
        if index_cache_size is not None:
            logging.info(
                "index_cache_size is ignored in LanceDb Cloud"
@@ -663,16 +654,6 @@ class RemoteDBConnection(DBConnection):
            namespace_path = []
        LOOP.run(self._conn.drop_table(name, namespace_path=namespace_path))
    @override
    def drop_table_async(
        self, name: str, namespace_path: Optional[List[str]] = None
    ) -> Job:
        """Start dropping a table and return its cleanup job."""
        if namespace_path is None:
            namespace_path = []
        job = LOOP.run(self._conn.drop_table_async(name, namespace_path=namespace_path))
        return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
    @override
    def rename_table(
        self,
@@ -703,47 +684,6 @@ class RemoteDBConnection(DBConnection):
            )
        )
    @override
    def job(self, job_id: str) -> Job:
        """A [Job][lancedb.job.Job] 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.
        """
        return Job(self._conn.job(job_id))
    @override
    def list_jobs(self) -> List["JobInfo"]:
        """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.
        Returns True if the server accepted the cancellation, False if no
        such job exists. Cancelling an already-terminal job is a no-op
        success.
        """
        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.
@@ -20,7 +20,6 @@ from typing import (
 import warnings
 from lancedb import __version__
 from lancedb._blob import BlobFile
 from lancedb._lancedb import (
    AddColumnsResult,
@@ -48,7 +47,6 @@ from lancedb.index import (
    IvfSq,
    LabelList,
 )
 from lancedb.job import Job
 from lancedb.remote.db import LOOP
 from lancedb.table import IndexConfigType, KNOWN_METRICS
 import pyarrow as pa
@@ -542,34 +540,6 @@ class RemoteTable(Table):
            )
        )
    def create_index_async(
        self,
        column: str,
        *,
        config: IndexConfigType,
        replace: Optional[bool] = None,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
    ) -> Job:
        """Create an index, returning a handle to the indexing job.
        The job may already be complete when returned; callers must not assume
        the index exists until :meth:`Job.wait` returns.
        """
        return Job(
            LOOP.run(
                self._table.create_index_async(
                    column,
                    replace=replace,
                    config=config,
                    wait_timeout=wait_timeout,
                    name=name,
                    train=train,
                )
            )
        )
    def _is_legacy_create_index_call(
        self,
        first_arg: str,
@@ -958,19 +928,8 @@ class RemoteTable(Table):
    def count_rows(self, filter: Optional[str] = None) -> int:
        return LOOP.run(self._table.count_rows(filter))
-    def add_columns(
+    def add_columns(self, transforms: Dict[str, str]) -> AddColumnsResult:
-        self,
+        return LOOP.run(self._table.add_columns(transforms))
        transforms: Dict[str, str] | None = None,
        *,
        computed: Dict[str, str] | None = None,
    ) -> AddColumnsResult:
        return LOOP.run(self._table.add_columns(transforms, computed=computed))
    def refresh_column(self, column: str):
        return LOOP.run(self._table.refresh_column(column))
    def refresh_column_async(self, column: str) -> Job:
        return Job(LOOP.run(self._table.refresh_column_async(column)))
    def alter_columns(
        self, *alterations: Iterable[Dict[str, str]]
@@ -990,39 +949,17 @@ class RemoteTable(Table):
        return LOOP.run(self._table.set_unenforced_primary_key(columns))
    def set_lsm_write_spec(self, spec: "LsmWriteSpec") -> None:
-        """Install an LsmWriteSpec."""
+        """Not supported on LanceDB Cloud."""
        return LOOP.run(self._table.set_lsm_write_spec(spec))
    def unset_lsm_write_spec(self) -> None:
-        """Remove the LsmWriteSpec."""
+        """Not supported on LanceDB Cloud."""
        return LOOP.run(self._table.unset_lsm_write_spec())
    def get_lsm_write_spec(self) -> Optional["LsmWriteSpec"]:
        """Read the installed LsmWriteSpec, or ``None``."""
        return LOOP.run(self._table.get_lsm_write_spec())
    def checkpoint_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.checkpoint_lsm`][lancedb.AsyncTable.checkpoint_lsm]."""
        return LOOP.run(self._table.checkpoint_lsm())
    def flush_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.flush_lsm`][lancedb.AsyncTable.flush_lsm]."""
        return LOOP.run(self._table.flush_lsm())
    def compact_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.compact_lsm`][lancedb.AsyncTable.compact_lsm]."""
        return LOOP.run(self._table.compact_lsm())
    def get_lsm_stats(self, *, include_generation_rows: bool = False) -> Optional[dict]:
        """Synchronous version of
        [`AsyncTable.get_lsm_stats`][lancedb.AsyncTable.get_lsm_stats]."""
        return LOOP.run(
            self._table.get_lsm_stats(include_generation_rows=include_generation_rows)
        )
    def close_lsm_writers(self) -> None:
        """No-op on LanceDB Cloud (no local shard writers)."""
        return LOOP.run(self._table.close_lsm_writers())
@@ -1102,22 +1039,22 @@ class RemoteTable(Table):
        )
    def blob_columns(self) -> list[str]:
-        return LOOP.run(self._table.blob_columns())
+        raise NotImplementedError(
            "blob_columns() is not yet supported on the LanceDB Cloud"
        )
-    def fetch_blobs(
+    def fetch_blobs(self, column: str, row_ids) -> pa.LargeBinaryArray:
-        self, column: str, row_ids: Union[list[int], pa.Table]
+        raise NotImplementedError("fetch_blobs() is not supported on LanceDB Cloud")
    ) -> pa.LargeBinaryArray:
        return LOOP.run(self._table.fetch_blobs(column, row_ids))
    def fetch_blob_ranges(self, column: str, requests) -> pa.LargeBinaryArray:
        raise NotImplementedError(
            "fetch_blob_ranges() is not supported on LanceDB Cloud"
        )
-    def fetch_blob_files(
+    def fetch_blob_files(self, column: str, row_ids):
-        self, column: str, row_ids: Union[list[int], pa.Table]
+        raise NotImplementedError(
-    ) -> "list[Optional[BlobFile]]":
+            "fetch_blob_files() is not supported on LanceDB Cloud"
-        return LOOP.run(self._table.fetch_blob_files(column, row_ids))
+        )
    def head(self, n=5) -> pa.Table:
        """
@@ -11,11 +11,6 @@ Provides StreamingDataset, a PyTorch IterableDataset that guarantees:
 - **Resumability**: state_dict / load_state_dict capture per-split consumption
  counts so training can resume from an exact mid-epoch position even when the
  distributed topology changes between runs.
 Transform failures on bad rows (e.g. nulls or NaNs from incomplete data) can
 be tolerated with ``on_transform_error="skip"``; see the parameter
 documentation on StreamingDataset for how this interacts with the guarantees
 above.
 """
 import ctypes
@@ -27,7 +22,7 @@ import time
 from collections import deque
 from concurrent.futures import ThreadPoolExecutor
 from multiprocessing import RawArray
-from typing import Any, Callable, Iterator, Optional, Union
+from typing import Any, Callable, Iterator, Optional
 from torch.utils.data import IterableDataset, get_worker_info
@@ -132,49 +127,6 @@ class StreamingDataset(IterableDataset):
        Maximum number of transforms to run concurrently.  Must be greater
        than zero.  When ``None`` (the default), uses ``os.cpu_count()`` or 1
        when the CPU count is unavailable.
    on_transform_error:
        What to do when the transform raises an exception:
        - ``"raise"`` (the default): the exception propagates and iteration
          aborts.
        - ``"skip"``: the failing rows are dropped and iteration continues.
        - ``"warn"``: like ``"skip"``, but a warning is logged for each
          failing batch.
        - a callable ``handler(exc) -> bool``: called with the exception;
          return ``True`` to skip the failing rows or ``False`` to re-raise.
          Useful to skip only expected error types (compatible with
          ``webdataset.handlers`` style handlers).
        When a batch fails, the transform is re-invoked on each single-row
        slice of the batch so that only the rows that actually fail are
        dropped.  Transforms should therefore be deterministic and accept
        batches of any size (including one row).  Skipped rows are counted in
        ``rows_skipped``.
        Skipping weakens the elastic-determinism guarantee at the end of the
        epoch: splits that lose more rows than others run dry earlier, and
        each rank's iterator ends at the last cycle where every split *it
        owns* still has a row.  Because bad rows are not distributed evenly
        across splits, this means one rank's iterator can yield noticeably
        fewer or more steps than another rank's *in the same run* — there is
        no cross-rank coordination that stops every rank at the same global
        step.  This is generally safe for asynchronous or single-rank use,
        but synchronous distributed training (e.g. ranks that call
        ``all_reduce`` every step) can hang or deadlock if one rank's
        iterator is exhausted while others are still stepping; callers doing
        synchronous multi-rank training with ``on_transform_error != "raise"``
        are responsible for their own cross-rank stopping mechanism (e.g.
        broadcasting a stop signal on ``StopIteration``).  The final few
        global steps can also differ across topologies (bounded by the skew
        in bad-row counts across splits).  The sequence of samples yielded
        from each split remains deterministic.  Mid-epoch
        checkpoints remain exact provided the transform fails
        deterministically; in multi-rank training each rank must save its
        own ``state_dict`` and the states must be combined with
        ``merge_state_dicts`` before resuming on a different topology.
        Prefer the ``filter`` parameter when bad rows can be expressed as a
        SQL predicate (e.g. ``"col IS NOT NULL"``) — filtering happens before
        splits are built, so every guarantee is fully preserved.
    worker_info_override:
        If set, used in place of ``torch.utils.data.get_worker_info()`` to
        determine the DataLoader worker assignment.  Intended for unit tests
@@ -200,7 +152,6 @@ class StreamingDataset(IterableDataset):
        filter: Optional[str] = None,
        transform: Optional[Callable] = None,
        transform_parallelism: Optional[int] = None,
        on_transform_error: Union[str, Callable[[Exception], bool]] = "raise",
        connection_factory: Optional[Callable[[str], Any]] = None,
        worker_info_override=None,
    ):
@@ -216,13 +167,6 @@ class StreamingDataset(IterableDataset):
            )
        if transform_parallelism is not None and transform_parallelism <= 0:
            raise ValueError("transform_parallelism must be greater than 0")
        if on_transform_error not in ("raise", "skip", "warn") and not callable(
            on_transform_error
        ):
            raise ValueError(
                "on_transform_error must be 'raise', 'skip', 'warn', or a "
                f"callable, got {on_transform_error!r}"
            )
        self._table = table
        self._num_splits = num_splits
@@ -238,7 +182,6 @@ class StreamingDataset(IterableDataset):
        self._filter = filter
        self._transform = transform
        self._transform_parallelism = transform_parallelism
        self._on_transform_error = on_transform_error
        self._connection_factory = connection_factory
        self._worker_info_override = worker_info_override
@@ -256,28 +199,19 @@ class StreamingDataset(IterableDataset):
        # in the main process.  RawArray is picklable via the forkserver
        # reduction protocol so it survives the dataset pickle round-trip.
        # Layout: [unscanned_rows, raw_rows, cooked_rows, consumed_rows,
-        #          bytes_loaded, fetch_time_us, transform_time_us,
+        #          bytes_loaded, fetch_time_us, transform_time_us]
-        #          rows_skipped]
+        self._worker_stats: RawArray = RawArray(ctypes.c_int64, 7)
        self._worker_stats: RawArray = RawArray(ctypes.c_int64, 8)
        # Cumulative bytes of Arrow buffer data fetched across all iterations.
        self._bytes_loaded: int = 0
        # Cumulative seconds spent in LanceDB I/O and in transform functions.
        self._fetch_time: float = 0.0
        self._transform_time: float = 0.0
        # Cumulative rows dropped by on_transform_error across all iterations.
        self._rows_skipped: int = 0
        # Number of samples each split has already been consumed.  At global
        # step boundaries all splits have consumed this many samples, so a
        # single scalar captures the topology-independent checkpoint state.
        self._resume_offset: int = 0
        # Permutation position each split has consumed through, keyed by
        # global split index.  Equal to _resume_offset for every split unless
        # on_transform_error skipped rows, in which case skipped positions
        # push the watermark of the affected splits further ahead.  Splits
        # this instance has never iterated have no entry.
        self._resume_positions: dict[int, int] = {}
        # Build the permutation table once, deterministically.
        builder = permutation_builder(table)
@@ -341,7 +275,6 @@ class StreamingDataset(IterableDataset):
        # Set identity transform on each Permutation so __getitems__ returns
        # the raw RecordBatch.  Stage 2 applies the real transform.
        permutations: list[Permutation] = []
        initial_positions: list[int] = []
        for split_idx in my_splits:
            perm = Permutation.from_tables(
                self._table, self._perm_table, split=split_idx
@@ -349,20 +282,14 @@ class StreamingDataset(IterableDataset):
            if self._columns is not None:
                perm = perm.select_columns(self._columns)
            perm = perm.with_transform(lambda batch: batch)
-            start_pos = self._resume_positions.get(split_idx, self._resume_offset)
+            if self._resume_offset > 0:
-            if start_pos > 0:
+                perm = perm.with_skip(self._resume_offset)
                perm = perm.with_skip(start_pos)
            initial_positions.append(start_pos)
            permutations.append(perm)
        n = len(permutations)
        split_sizes = [perm.num_rows for perm in permutations]
        initial_offset = self._resume_offset
        local_consumed = [0] * n
        # Permutation position each split has consumed through (absolute,
        # i.e. counted from the start of the unskipped split).  Runs ahead of
        # initial + local_consumed when rows are skipped.
        pos_consumed = list(initial_positions)
        batch_size = self._read_batch_size
        max_prefetch = self._prefetch_batches
@@ -375,14 +302,12 @@ class StreamingDataset(IterableDataset):
            self._transform if self._transform is not None else Transforms.arrow2python
        )
-        # Per-split pipeline state.  Batches are paired with the absolute
+        # Per-split pipeline state.
        # permutation position of their first row so that skipped rows can be
        # accounted for in pos_consumed.
        fetch_head = [0] * n
-        io_pending = [deque() for _ in range(n)]  # (abs_start, Future[RecordBatch])
+        io_pending = [deque() for _ in range(n)]  # Future[RecordBatch]
-        raw_batches = [deque() for _ in range(n)]  # (abs_start, RecordBatch)
+        raw_batches = [deque() for _ in range(n)]  # RecordBatch — fetched, awaiting tx
-        tx_pending = [deque() for _ in range(n)]  # Future[list[(abs_pos, row)]]
+        tx_pending = [deque() for _ in range(n)]  # Future[list[Any]]
-        cooked = [deque() for _ in range(n)]  # (abs_pos, row) ready to yield
+        cooked = [deque() for _ in range(n)]  # rows ready to yield
        # Limit simultaneous transforms to transform_workers across all splits.
        tx_semaphore = threading.Semaphore(transform_workers)
@@ -405,8 +330,7 @@ class StreamingDataset(IterableDataset):
            fetch_head[i] += fetch
            perm_i = permutations[i]
            indices = list(range(start, start + fetch))
-            abs_start = initial_positions[i] + start
+            io_pending[i].append(io_pool.submit(_io_call, perm_i, indices))
            io_pending[i].append((abs_start, io_pool.submit(_io_call, perm_i, indices)))
        def _fill_io(i: int) -> None:
            while len(io_pending[i]) < max_prefetch and fetch_head[i] < split_sizes[i]:
@@ -414,72 +338,15 @@ class StreamingDataset(IterableDataset):
        def _drain_io(i: int) -> None:
            """Move completed I/O futures into raw_batches non-blockingly."""
-            while io_pending[i] and io_pending[i][0][1].done():
+            while io_pending[i] and io_pending[i][0].done():
-                abs_start, fut = io_pending[i].popleft()
+                raw_batches[i].append(io_pending[i].popleft().result())
                raw_batches[i].append((abs_start, fut.result()))
        # ── Stage 2 helpers ───────────────────────────────────────────────────
-        on_error = self._on_transform_error
+        def _tx_call_guarded(batch):
        def _should_skip(exc: Exception) -> bool:
            if on_error == "raise":
                return False
            if callable(on_error):
                return bool(on_error(exc))
            return True  # "skip" or "warn"
        def _check_row_count(rows: list, num_rows: int) -> None:
            if len(rows) != num_rows:
                raise ValueError(
                    f"transform returned {len(rows)} rows for a batch of "
                    f"{num_rows}; transforms must return exactly one output "
                    "row per input row.  To drop bad rows, raise inside the "
                    "transform and pass on_transform_error='skip'."
                )
        def _transform_isolated(abs_start, batch, batch_exc):
            """Re-run the transform on single-row slices, dropping failures."""
            out = []
            skipped = 0
            first_exc = None
            for j in range(batch.num_rows):
                try:
                    rows = list(final_transform(batch.slice(j, 1)))
                except Exception as exc:
                    if not _should_skip(exc):
                        raise
                    skipped += 1
                    if first_exc is None:
                        first_exc = exc
                    continue
                _check_row_count(rows, 1)
                out.append((abs_start + j, rows[0]))
            self._rows_skipped += skipped
            if skipped and on_error == "warn":
                logger.warning(
                    "Skipped %d of %d rows whose transform failed (first error: %r)",
                    skipped,
                    batch.num_rows,
                    first_exc if first_exc is not None else batch_exc,
                )
            return out
        def _transform_batch(abs_start, batch):
            """Apply the transform, returning [(abs_pos, row), ...]."""
            try:
                rows = list(final_transform(batch))
            except Exception as exc:
                if not _should_skip(exc):
                    raise
                return _transform_isolated(abs_start, batch, exc)
            _check_row_count(rows, batch.num_rows)
            return [(abs_start + j, row) for j, row in enumerate(rows)]
        def _tx_call_guarded(abs_start, batch):
            try:
                t0 = time.perf_counter()
-                result = _transform_batch(abs_start, batch)
+                result = final_transform(batch)
                self._transform_time += time.perf_counter() - t0
                return result
            finally:
@@ -488,8 +355,8 @@ class StreamingDataset(IterableDataset):
        def _try_submit_tx(i: int) -> None:
            """Submit transforms for raw_batches[i] up to available capacity."""
            while raw_batches[i] and tx_semaphore.acquire(blocking=False):
-                abs_start, batch = raw_batches[i].popleft()
+                batch = raw_batches[i].popleft()
-                tx_pending[i].append(tx_pool.submit(_tx_call_guarded, abs_start, batch))
+                tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
        def _drain_tx(i: int) -> None:
            """Move completed transform futures into cooked non-blockingly."""
@@ -517,14 +384,11 @@ class StreamingDataset(IterableDataset):
                    # Acquire a transform slot (may block briefly if all
                    # transform_workers are busy with other splits).
                    tx_semaphore.acquire()
-                    abs_start, batch = raw_batches[i].popleft()
+                    batch = raw_batches[i].popleft()
-                    tx_pending[i].append(
+                    tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
                        tx_pool.submit(_tx_call_guarded, abs_start, batch)
                    )
                elif io_pending[i]:
                    # Block on the oldest in-flight I/O fetch.
-                    abs_start, fut = io_pending[i].popleft()
+                    raw_batches[i].append(io_pending[i].popleft().result())
                    raw_batches[i].append((abs_start, fut.result()))
                    _advance(i)
                else:
                    break  # split exhausted
@@ -543,28 +407,15 @@ class StreamingDataset(IterableDataset):
                        _fill_io(i)
                    while True:
-                        # A cycle only runs if every split can still produce a
+                        # Stop when any split is exhausted (all exhaust
-                        # row.  Without skips all splits exhaust simultaneously
+                        # simultaneously: equal split sizes + round-robin).
-                        # (equal split sizes + round-robin); when
+                        if any(local_consumed[i] >= split_sizes[i] for i in range(n)):
                        # on_transform_error drops rows a split can run dry
                        # early, ending the epoch at the last complete cycle.
                        # This check only sees splits owned by this rank/worker
                        # (my_splits) — there is no cross-rank coordination, so
                        # a different rank with fewer skipped rows keeps going;
                        # see the on_transform_error docstring.
                        exhausted = False
                        for i in range(n):
                            _ensure_cooked(i)
                            if not cooked[i]:
                                exhausted = True
                                break
                        if exhausted:
                            break
                        for i in range(n):
-                            pos, row = cooked[i].popleft()
+                            _ensure_cooked(i)
                            row = cooked[i].popleft()
                            local_consumed[i] += 1
                            pos_consumed[i] = pos + 1
                            _advance(i)
                            # After the last split in each cycle: update the
@@ -573,39 +424,21 @@ class StreamingDataset(IterableDataset):
                            # even when __iter__ runs in a worker process.
                            if i == n - 1:
                                self._resume_offset = initial_offset + local_consumed[i]
                                for j, split_idx in enumerate(my_splits):
                                    self._resume_positions[split_idx] = pos_consumed[j]
                                ws = self._worker_stats
                                ws[0] = sum(
                                    split_sizes[j] - fetch_head[j] for j in range(n)
                                )
                                ws[1] = sum(
-                                    batch.num_rows
+                                    batch.num_rows for q in raw_batches for batch in q
                                    for q in raw_batches
                                    for _, batch in q
                                )
                                ws[2] = sum(len(q) for q in cooked)
                                ws[3] = sum(local_consumed)
                                ws[4] = self._bytes_loaded
                                ws[5] = int(self._fetch_time * 1_000_000)
                                ws[6] = int(self._transform_time * 1_000_000)
                                ws[7] = self._rows_skipped
                            yield row
                finally:
                    # Final stats flush: the per-cycle write above never runs
                    # when iteration ends mid-cycle (e.g. a split whose rows
                    # were all skipped before completing a single cycle), so
                    # counters like rows_skipped would otherwise be stale.
                    ws = self._worker_stats
                    ws[0] = sum(split_sizes[j] - fetch_head[j] for j in range(n))
                    ws[1] = 0  # queue-depth properties document 0 when idle
                    ws[2] = 0
                    ws[3] = sum(local_consumed)
                    ws[4] = self._bytes_loaded
                    ws[5] = int(self._fetch_time * 1_000_000)
                    ws[6] = int(self._transform_time * 1_000_000)
                    ws[7] = self._rows_skipped
                    self._raw_batches_ref = None
                    self._cooked_ref = None
                    self._fetch_head_ref = None
@@ -659,7 +492,7 @@ class StreamingDataset(IterableDataset):
        batches.  Returns 0 when not iterating.
        """
        if self._raw_batches_ref is not None:
-            return sum(batch.num_rows for q in self._raw_batches_ref for _, batch in q)
+            return sum(batch.num_rows for q in self._raw_batches_ref for batch in q)
        return int(self._worker_stats[1])
    @property
@@ -689,19 +522,6 @@ class StreamingDataset(IterableDataset):
            )
        return int(self._worker_stats[0])
    @property
    def rows_skipped(self) -> int:
        """Number of rows dropped because their transform raised an exception.
        Only ever non-zero when ``on_transform_error`` is set to ``"skip"``,
        ``"warn"``, or a callable that returned ``True``.  Accumulates across
        multiple iterations of the same dataset instance and is never reset
        automatically.
        """
        if self._raw_batches_ref is not None:
            return self._rows_skipped
        return int(self._worker_stats[7])
    @property
    def consumed_rows(self) -> int:
        """Number of rows already yielded to the caller across all splits.
@@ -767,27 +587,12 @@ class StreamingDataset(IterableDataset):
        every split has been consumed the same number of times (by the
        round-robin design), so the per-split count is a single uniform value
        that is identical across all ranks and DataLoader workers.
        ``positions_consumed_per_split`` records how far into each split's
        permutation iteration has advanced.  It only differs from
        ``samples_consumed_per_split`` when ``on_transform_error`` skipped
        rows, in which case entries are exact for the splits this instance
        iterated and a lower bound (the sample count) for splits owned by
        other ranks or workers.  Combine the state dicts from all ranks with
        [merge_state_dicts][lancedb.streaming.StreamingDataset.merge_state_dicts]
        to recover the exact value for every split before resuming on a
        different topology.
        """
        positions = [
            self._resume_positions.get(split, self._resume_offset)
            for split in range(self._num_splits)
        ]
        return {
            "shuffle_seed": self._shuffle_seed,
            "num_splits": self._num_splits,
            "epoch": self._epoch,
            "samples_consumed_per_split": [self._resume_offset] * self._num_splits,
            "positions_consumed_per_split": positions,
        }
    def load_state_dict(self, state: dict) -> None:
@@ -813,96 +618,3 @@ class StreamingDataset(IterableDataset):
            self._resume_offset = consumed[0] if consumed else 0
        else:
            self._resume_offset = int(consumed)
        # Older checkpoints predate positions_consumed_per_split; without
        # skipped rows positions equal sample counts, so falling back to
        # _resume_offset (the .get default in __iter__) is exact.
        positions = state.get("positions_consumed_per_split")
        if positions is None:
            self._resume_positions = {}
        else:
            self._resume_positions = {
                split: int(pos) for split, pos in enumerate(positions)
            }
    @staticmethod
    def merge_state_dicts(states: list[dict]) -> dict:
        """Merge state dicts saved by different ranks into one exact state.
        Only needed when ``on_transform_error`` skips rows in multi-rank
        training: each rank then knows the exact permutation position only for
        its own splits, and records a lower bound for the rest.  Because
        exactly one rank owns each split, the elementwise maximum across all
        ranks' ``positions_consumed_per_split`` recovers the exact position of
        every split.  Without skipped rows every rank's state is already
        identical and merging is a no-op.
        Raises ``ValueError`` if the states are empty or were not produced by
        the same run (mismatched seed, split count, epoch, or sample counts).
        The merge is always all-to-all and topology-agnostic: collect the
        ``state_dict()`` from every rank of the *previous* run into one list,
        merge that whole list, and hand the identical merged result to every
        rank of the *next* run — regardless of whether the rank count grew,
        shrank, or stayed the same. There is no pairwise or subset merging
        step, because each split's exact position is only known to whichever
        rank owned that split, and the elementwise maximum needs every rank's
        contribution to be correct.
        For example, checkpointing 8 ranks and resuming on 4 (the same
        pattern applies when growing, e.g. 4 ranks resuming on 8)::
            states = [ds.state_dict() for ds in previous_run_datasets]  # 8
            merged = StreamingDataset.merge_state_dicts(states)
            for ds in resumed_datasets:  # now only 4 ranks
                ds.load_state_dict(merged)  # same dict on every rank
        The rank count on either side never affects the merge itself, since
        ``merge_state_dicts`` only cares about the list of states it is
        given.  Each split's position is recovered by elementwise maximum;
        here rank 0 owned split 0 (and skipped two rows there) while rank 1
        owned split 1 (and skipped one row):
        >>> rank0 = {
        ...     "shuffle_seed": 0, "num_splits": 2, "epoch": 0,
        ...     "samples_consumed_per_split": [3, 3],
        ...     "positions_consumed_per_split": [5, 3],
        ... }
        >>> rank1 = {
        ...     "shuffle_seed": 0, "num_splits": 2, "epoch": 0,
        ...     "samples_consumed_per_split": [3, 3],
        ...     "positions_consumed_per_split": [3, 4],
        ... }
        >>> merged = StreamingDataset.merge_state_dicts([rank0, rank1])
        >>> merged["positions_consumed_per_split"]
        [5, 4]
        """
        if not states:
            raise ValueError("merge_state_dicts requires at least one state dict")
        first = states[0]
        for state in states[1:]:
            for key in ("shuffle_seed", "num_splits", "epoch"):
                if state[key] != first[key]:
                    raise ValueError(
                        f"{key} mismatch across state dicts: "
                        f"{state[key]} != {first[key]}"
                    )
            if (
                state["samples_consumed_per_split"]
                != first["samples_consumed_per_split"]
            ):
                raise ValueError(
                    "samples_consumed_per_split mismatch across state dicts; "
                    "state_dict() must be called at the same global step "
                    "boundary on every rank"
                )
        merged = dict(first)
        all_positions = [
            state.get(
                "positions_consumed_per_split", state["samples_consumed_per_split"]
            )
            for state in states
        ]
        merged["positions_consumed_per_split"] = [
            max(per_split) for per_split in zip(*all_positions)
        ]
        return merged
@@ -40,7 +40,6 @@ from ._blob import (
 from .types import BlobMode
 from lancedb.arrow import peek_reader
 from lancedb.background_loop import LOOP, embedding_executor
 from lancedb.job import AsyncJob, Job
 from .dependencies import (
    _check_for_hugging_face,
    _check_for_lance,
@@ -108,11 +107,6 @@ def _should_push_down_query_table(
    return namespace_client is not None and "QueryTable" in pushdown_operations
 def _polars_predicate_pushdown_barrier(frame: Any) -> Any:
    """Return a Polars frame unchanged while blocking predicate pushdown."""
    return frame
 _MODEL_BACKED_TOKENIZER_PREFIXES = ("jieba", "lindera")
 _MODEL_BACKED_TOKENIZER_ERRORS = (
    "unknown base tokenizer",
@@ -176,7 +170,6 @@ if TYPE_CHECKING:
        CompactionStats,
        Tag,
        AddColumnsResult,
        RefreshColumnResult,
        AddResult,
        AlterColumnsResult,
        UpdateFieldMetadataResult,
@@ -870,18 +863,12 @@ class Table(ABC):
        """
        raise NotImplementedError
-    def to_polars(self, **kwargs) -> "pl.LazyFrame":
+    def to_polars(self, **kwargs) -> "pl.DataFrame":
-        """Return the table as a Polars LazyFrame.
+        """Return the table as a polars.DataFrame.
        Note
        ----
        The Polars streaming engine is not supported because it does not currently
        implement Python PyArrow dataset scans. Use the default engine when collecting
        this LazyFrame.
        Returns
        -------
-        polars.LazyFrame
+        polars.DataFrame
        """
        raise NotImplementedError
@@ -990,24 +977,6 @@ class Table(ABC):
        """
        raise NotImplementedError
    def create_index_async(
        self,
        column: str,
        *,
        config: IndexConfigType,
        replace: Optional[bool] = None,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
    ) -> Job:
        """Create an index, returning a handle to the indexing job.
        Takes the same arguments as :meth:`create_index`. The job may already
        be complete when returned; callers must not assume the index exists
        until :meth:`Job.wait` returns.
        """
        raise NotImplementedError
    def drop_index(self, name: str) -> None:
        """
        Drop an index from the table.
@@ -1605,10 +1574,8 @@ class Table(ABC):
        """Open lazy, seekable :class:`~lancedb._blob.BlobFile` handles.
        Prefer this over :meth:`fetch_blobs` for large payloads. ``row_ids`` is
-        a ``list[int]`` or a query ``pyarrow.Table`` carrying row identity via
+        a ``list[int]`` or query ``pyarrow.Table`` with ``_rowid`` (or stashed
-        ``_rowid`` or a ``_lance_row_id`` field on the blob descriptor. Null
+        row-id metadata). Null rows are ``None``. Local tables only.
        rows are ``None``. Remote tables require LanceDB Cloud server 0.5.0 or
        newer.
        """
    @abstractmethod
@@ -1917,14 +1884,7 @@ class Table(ABC):
    @abstractmethod
    def add_columns(
-        self,
+        self, transforms: Dict[str, str] | pa.Field | List[pa.Field] | pa.Schema
        transforms: Dict[str, str]
        | pa.Field
        | List[pa.Field]
        | pa.Schema
        | None = None,
        *,
        computed: Dict[str, str] | None = None,
    ):
        """
        Add new columns with defined values.
@@ -1938,95 +1898,11 @@ class Table(ABC):
            Alternatively, a pyarrow Field or Schema can be provided to add
            new columns with the specified data types. The new columns will
            be initialized with null values.
        computed: Dict[str, str], optional
            A map of column name to a SQL expression defining the column. The
            column's type and inputs are derived from the expression, so no
            data type is supplied.
            Unlike ``transforms``, the expression is stored rather than
            evaluated now: the column is committed with no values, and rows get
            them from [`refresh_column`][lancedb.table.Table.refresh_column].
            Declaring one therefore costs the same on a large table as on an
            empty one.
            A refresh does not revisit rows it has already filled, so mutating
            an input leaves the value computed at fill time; recomputing means
            dropping the column and declaring it again. While a declaration
            reads a column, that column cannot be renamed, retyped or dropped.
            On LanceDB Cloud and Enterprise the expression is planned by the
            server, and the refresh runs as a server job -- see
            [`refresh_column_async`][lancedb.table.Table.refresh_column_async].
            Cannot be combined with ``transforms``.
        Returns
        -------
        AddColumnsResult
            version: the new version number of the table after adding columns.
        Examples
        --------
        >>> import lancedb
        >>> db = lancedb.connect("./.lancedb")
        >>> table = db.create_table("computed_demo", [{"x": 1}, {"x": 2}])
        >>> table.add_columns(computed={"doubled": "x * 2"})
        AddColumnsResult(version=2)
        >>> table.refresh_column("doubled")
        RefreshColumnResult(rows_filled=2, version=3)
        >>> table.to_arrow().sort_by("x").to_pandas()
           x  doubled
        0  1        2
        1  2        4
        """
    @abstractmethod
    def refresh_column(self, column: str) -> "RefreshColumnResult":
        """
        Fill the rows of a computed column that hold no value yet.
        Declared with ``add_columns(computed=...)``, a column starts empty and
        gets its values here. Rows appended since the last refresh are filled
        by the next one; rows already filled are left as they are, so the call
        is idempotent and does not observe a mutated input.
        Local tables only: a remote refresh runs as a server job, through
        [`refresh_column_async`][lancedb.table.Table.refresh_column_async].
        Parameters
        ----------
        column: str
            The name of the computed column to fill.
        Returns
        -------
        RefreshColumnResult
            rows_filled: the number of rows given a value.
            version: the new version number of the table.
        """
    @abstractmethod
    def refresh_column_async(self, column: str) -> Job:
        """
        Like :meth:`refresh_column`, but returns a handle to the refresh job
        instead of blocking until it completes.
        The job may already be complete when returned; callers must not assume
        the column is filled until :meth:`Job.wait` returns. Invalid input --
        an unknown column, or one that is not computed -- raises here rather
        than failing the job. On local tables the job runs in-process; on
        LanceDB Cloud and Enterprise it is the server's backfill job.
        Examples
        --------
        >>> import lancedb
        >>> db = lancedb.connect("./.lancedb")
        >>> table = db.create_table("computed_job_demo", [{"x": 1}, {"x": 2}])
        >>> table.add_columns(computed={"doubled": "x * 2"})
        AddColumnsResult(version=2)
        >>> job = table.refresh_column_async("doubled")
        >>> job.wait()
        >>> job.status()
        'finished'
        """
    @abstractmethod
@@ -2285,15 +2161,11 @@ class LanceTable(Table):
        return self.name
    @classmethod
-    async def from_inner(cls, tbl: LanceDBTable):
+    def from_inner(cls, tbl: LanceDBTable):
-        from .db import AsyncConnection, LanceDBConnection
+        from .db import LanceDBConnection
        async_tbl = AsyncTable(tbl)
-        inner_conn = tbl.database()
+        conn = LanceDBConnection.from_inner(tbl.database())
        read_consistency_interval = await AsyncConnection(
            inner_conn
        ).get_read_consistency_interval()
        conn = LanceDBConnection.from_inner(inner_conn, read_consistency_interval)
        return cls(
            conn,
            async_tbl.name,
@@ -2597,7 +2469,13 @@ class LanceTable(Table):
        return LOOP.run(self._table.count_rows(filter))
    def __repr__(self) -> str:
-        return f"{self.__class__.__name__}(name={self.name!r}, _conn={self._conn!r})"
+        val = f"{self.__class__.__name__}(name={self.name!r}"
        if self._conn.read_consistency_interval is not None:
            val += ", read_consistency_interval={!r}".format(
                self._conn.read_consistency_interval
            )
        val += f", _conn={self._conn!r})"
        return val
    def __str__(self) -> str:
        return self.__repr__()
@@ -2672,9 +2550,6 @@ class LanceTable(Table):
        2. Currently we've disabled push-down of the filters from polars
           because polars pushdown into pyarrow uses pyarrow compute
           expressions rather than SQl strings (which LanceDB supports)
        3. The Polars streaming engine is not supported because it does not
           currently implement Python PyArrow dataset scans. Use the default
           engine when collecting this LazyFrame.
        Returns
        -------
@@ -2683,12 +2558,8 @@ class LanceTable(Table):
        from lancedb.integrations.pyarrow import PyarrowDatasetAdapter
        dataset = PyarrowDatasetAdapter(self)
-        # Polars 1.32's non-PyArrow callback path passes batch_size twice.  Keep
+        return pl.scan_pyarrow_dataset(
-        # the compatible PyArrow path, but block predicates because this adapter
+            dataset, allow_pyarrow_filter=False, batch_size=batch_size
        # cannot translate PyArrow expressions into LanceDB filters.
        return pl.scan_pyarrow_dataset(dataset, batch_size=batch_size).map_batches(
            _polars_predicate_pushdown_barrier,
            predicate_pushdown=False,
        )
    # New unified API overload
@@ -2913,34 +2784,6 @@ class LanceTable(Table):
            )
        )
    def create_index_async(
        self,
        column: str,
        *,
        config: IndexConfigType,
        replace: Optional[bool] = None,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
    ) -> Job:
        """Create an index, returning a handle to the indexing job.
        The job may already be complete when returned; callers must not assume
        the index exists until :meth:`Job.wait` returns.
        """
        return Job(
            LOOP.run(
                self._table.create_index_async(
                    column,
                    replace=replace,
                    config=config,
                    wait_timeout=wait_timeout,
                    name=name,
                    train=train,
                )
            )
        )
    def _is_legacy_create_index_call(
        self,
        first_arg: str,
@@ -4031,28 +3874,9 @@ class LanceTable(Table):
        return LOOP.run(self._table.index_stats(index_name))
    def add_columns(
-        self,
+        self, transforms: Dict[str, str] | pa.field | List[pa.field] | pa.Schema
        transforms: Dict[str, str]
        | pa.field
        | List[pa.field]
        | pa.Schema
        | None = None,
        *,
        computed: Dict[str, str] | None = None,
    ) -> AddColumnsResult:
-        return LOOP.run(self._table.add_columns(transforms, computed=computed))
+        return LOOP.run(self._table.add_columns(transforms))
    def refresh_column(self, column: str) -> "RefreshColumnResult":
        """Fill a computed column's unfilled rows. See
        [`AsyncTable.refresh_column`][lancedb.AsyncTable.refresh_column]."""
        return LOOP.run(self._table.refresh_column(column))
    def refresh_column_async(self, column: str) -> Job:
        """Fill a computed column's unfilled rows, returning a handle to the
        refresh job. See
        [`Table.refresh_column_async`][lancedb.table.Table.refresh_column_async].
        """
        return Job(LOOP.run(self._table.refresh_column_async(column)))
    def alter_columns(
        self, *alterations: Iterable[Dict[str, str]]
@@ -4087,28 +3911,6 @@ class LanceTable(Table):
        [`AsyncTable.get_lsm_write_spec`][lancedb.AsyncTable.get_lsm_write_spec]."""
        return LOOP.run(self._table.get_lsm_write_spec())
    def checkpoint_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.checkpoint_lsm`][lancedb.AsyncTable.checkpoint_lsm]."""
        return LOOP.run(self._table.checkpoint_lsm())
    def flush_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.flush_lsm`][lancedb.AsyncTable.flush_lsm]."""
        return LOOP.run(self._table.flush_lsm())
    def compact_lsm(self) -> None:
        """Synchronous version of
        [`AsyncTable.compact_lsm`][lancedb.AsyncTable.compact_lsm]."""
        return LOOP.run(self._table.compact_lsm())
    def get_lsm_stats(self, *, include_generation_rows: bool = False) -> Optional[dict]:
        """Synchronous version of
        [`AsyncTable.get_lsm_stats`][lancedb.AsyncTable.get_lsm_stats]."""
        return LOOP.run(
            self._table.get_lsm_stats(include_generation_rows=include_generation_rows)
        )
    def close_lsm_writers(self) -> None:
        """Close cached MemWAL shard writers. See
        [`AsyncTable.close_lsm_writers`][lancedb.AsyncTable.close_lsm_writers]."""
@@ -4787,13 +4589,6 @@ class AsyncTable:
        via [`set_unenforced_primary_key`]; bucket sharding additionally
        requires it to be the single column being bucketed.
        By default the MemWAL maintains every index on the table, resolved
        here — a snapshot, so an index created afterwards needs the spec unset
        and set again. This fails if one cannot be maintained; name the set
        with ``with_maintained_indexes`` to install anyway. That pins an exact
        set (a still-building index is rejected, not omitted); ``[]`` maintains
        none.
        Parameters
        ----------
        spec : LsmWriteSpec
@@ -4801,7 +4596,7 @@ class AsyncTable:
        Examples
        --------
-        >>> from lancedb import LsmWriteSpec
+        >>> from lancedb._lancedb import LsmWriteSpec
        >>> # table.set_unenforced_primary_key("id")
        >>> # table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 16))
        """
@@ -4820,73 +4615,12 @@ class AsyncTable:
        Returns ``None`` when the MemWAL LSM write path is not enabled (no
        spec has been set, or it was removed with `unset_lsm_write_spec`).
-        The returned spec mirrors what was passed to `set_lsm_write_spec`,
+        The returned spec — including its ``maintained_indexes`` and
-        except that ``maintained_indexes`` always reports the concrete list
+        ``writer_config_defaults`` — mirrors what was passed to
-        resolved when the spec was set — ``None`` never round-trips.
+        `set_lsm_write_spec`.
        """
        return await self._inner.get_lsm_write_spec()
    async def checkpoint_lsm(self) -> None:
        """Converge this table's LSM write path into its base table.
        One flush, sealing every memtable into L0, then compaction triggers
        until every generation that existed at that moment has reached base.
        The loop runs client-side, reading progress from ``get_lsm_stats``.
        Best-effort: generations created *while* it runs are deliberately not
        waited on, which is what lets it terminate on a table taking writes.
        Idempotent and safe on a cadence.
        There is no deadline, and the caller owns that. It returns when the
        target generations are gone, raises on a terminal server fault, and
        otherwise waits however long the server takes. A slow table and a
        stuck one are the same picture from the client: the compactor pool is
        shared across every table on the node, so a checkpoint queued behind
        unrelated work looks exactly like one that is merging. Wrap this in
        ``asyncio.wait_for`` for a wall-clock bound; abandoning it partway
        costs nothing.
        """
        await self._inner.checkpoint_lsm()
    async def flush_lsm(self) -> None:
        """Seal every bucket's active memtable into L0.
        Does not touch the base table — moving L0 into base is
        `compact_lsm`. On a node that has not claimed this table, this claims
        it and replays its WAL log first.
        """
        await self._inner.flush_lsm()
    async def compact_lsm(self) -> None:
        """Trigger a background L0 to base compaction pass per bucket.
        Returns once the passes are dispatched, not once they finish: watch
        ``get_lsm_stats`` for progress, or use ``checkpoint_lsm`` to loop
        until the current L0 has reached base.
        """
        await self._inner.compact_lsm()
    async def get_lsm_stats(
        self, *, include_generation_rows: bool = False
    ) -> Optional[dict]:
        """Read live per-bucket LSM state.
        Answers "how far behind is my fresh tier", "which bucket is hot", and
        "why is my fresh-tier vector search brute-force". Mutates no table
        state, though on a node that has not claimed this table it claims it,
        exactly as a read would.
        Returns ``None`` only when the LSM write path is not enabled.
        Parameters
        ----------
        include_generation_rows
            Report a row count per L0 generation. Off by default: each count
            opens an uncached Lance dataset, and ``checkpoint_lsm`` polls this
            needing only generation numbers.
        """
        return await self._inner.get_lsm_stats(include_generation_rows)
    async def close_lsm_writers(self) -> None:
        """Drain and close any cached MemWAL shard writers for this table.
@@ -5137,46 +4871,6 @@ class AsyncTable:
                )
            raise e
    async def create_index_async(
        self,
        column: str,
        *,
        replace: Optional[bool] = None,
        config: Optional[
            Union[
                IvfFlat,
                IvfPq,
                IvfRq,
                HnswPq,
                HnswSq,
                HnswFlat,
                BTree,
                Bitmap,
                LabelList,
                Fm,
                FTS,
            ]
        ] = None,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
        train: bool = True,
    ) -> AsyncJob:
        """Create an index, returning a handle to the indexing job.
        Takes the same arguments as :meth:`create_index`. The job may already
        be complete when returned; callers must not assume the index exists
        until :meth:`AsyncJob.wait` resolves.
        """
        job = await self._inner.create_index_async(
            column,
            index=config,
            replace=replace,
            wait_timeout=wait_timeout,
            name=name,
            train=train,
        )
        return AsyncJob(job)
    async def drop_index(self, name: str) -> None:
        """
        Drop an index from the table.
@@ -5967,14 +5661,7 @@ class AsyncTable:
        return await self._inner.update(updates_sql, where)
    async def add_columns(
-        self,
+        self, transforms: dict[str, str] | pa.field | List[pa.field] | pa.Schema
        transforms: dict[str, str]
        | pa.field
        | List[pa.field]
        | pa.Schema
        | None = None,
        *,
        computed: dict[str, str] | None = None,
    ) -> AddColumnsResult:
        """
        Add new columns with defined values.
@@ -5987,22 +5674,6 @@ class AsyncTable:
            each row in the table, and can reference existing columns.
            Alternatively, you can pass a pyarrow field or schema to add
            new columns with NULLs.
        computed: Dict[str, str], optional
            A map of column name to a SQL expression defining the column. The
            column's type and inputs are derived from the expression.
            Unlike ``transforms``, the expression is stored rather than
            evaluated now: the column is committed with no values, and rows get
            them from
            [`refresh_column`][lancedb.table.AsyncTable.refresh_column].
            A refresh does not revisit rows it has already filled, so mutating
            an input leaves the value computed at fill time. While a
            declaration reads a column, that column cannot be renamed, retyped
            or dropped.
            On LanceDB Cloud and Enterprise the expression is planned by
            the server. Cannot be combined with ``transforms``.
        Returns
        -------
@@ -6016,71 +5687,11 @@ class AsyncTable:
            {isinstance(f, pa.Field) for f in transforms}
        ):
            transforms = pa.schema(transforms)
        if computed:
            if transforms:
                raise ValueError(
                    "add_columns cannot take both transforms and computed columns"
                )
            return await self._inner.add_computed_columns(list(computed.items()))
        if transforms is None:
            raise ValueError("add_columns requires transforms or computed columns")
        if isinstance(transforms, pa.Schema):
            return await self._inner.add_columns_with_schema(transforms)
        else:
            return await self._inner.add_columns(list(transforms.items()))
    async def refresh_column(self, column: str) -> RefreshColumnResult:
        """
        Fill the rows of a computed column that hold no value yet.
        Declared with ``add_columns(computed=...)``, a column starts empty and
        gets its values here. Rows appended since the last refresh are filled
        by the next one; rows already filled are left as they are, so the call
        is idempotent and does not observe a mutated input.
        Local tables only: a remote refresh runs as a server job, through
        [`refresh_column_async`][lancedb.table.Table.refresh_column_async].
        Parameters
        ----------
        column: str
            The name of the computed column to fill.
        Returns
        -------
        RefreshColumnResult
            The number of rows filled and the new version of the table.
        """
        return await self._inner.refresh_column(column)
    async def refresh_column_async(self, column: str) -> AsyncJob:
        """
        Like :meth:`refresh_column`, but returns a handle to the refresh job
        instead of blocking until it completes.
        The job may already be complete when returned; callers must not assume
        the column is filled until :meth:`AsyncJob.wait` resolves. Invalid
        input -- an unknown column, or one that is not computed -- raises here
        rather than failing the job. On local tables the job runs
        in-process; on LanceDB Cloud and Enterprise it is the server's
        backfill job.
        Examples
        --------
        >>> import asyncio
        >>> import lancedb
        >>> async def refresh_in_background():
        ...     db = await lancedb.connect_async("./.lancedb")
        ...     table = await db.create_table("computed_job_async_demo", [{"x": 1}])
        ...     await table.add_columns(computed={"doubled": "x * 2"})
        ...     job = await table.refresh_column_async("doubled")
        ...     await job.wait()
        ...     return await job.status()
        >>> asyncio.run(refresh_in_background())
        'finished'
        """
        return AsyncJob(await self._inner.refresh_column_async(column))
    async def alter_columns(
        self, *alterations: Iterable[dict[str, Any]]
    ) -> AlterColumnsResult:
@@ -6535,9 +6146,7 @@ class TableStatistics:
    Attributes
    ----------
    total_bytes: int
-        The total size, in bytes, of the table's data files, index files, and
+        The total number of bytes in the table.
        overlay files. Read from the manifest, so this excludes deletion files
        and manifests.
    num_rows: int
        The total number of rows in the table.
    num_indices: int
@@ -395,11 +395,6 @@ def _(value: dict):
    )
@value_to_sql.register(pa.Scalar)
 def _(value: pa.Scalar):
    return value_to_sql(value.as_py())
@value_to_sql.register(np.ndarray)
 def _(value: np.ndarray):
    return value_to_sql(value.tolist())
@@ -226,13 +226,13 @@ def test_fetch_blob_ranges_validates_requests():
    table = _blob_table("range_validation", [{"id": 1, "image": b"abc"}])
    row_id = _row_ids_by_id(table)[1]
-    with pytest.raises(ValueError, match="exceeds blob size"):
+    with pytest.raises(RuntimeError, match="exceeds blob size"):
        table.fetch_blob_ranges("image", [(row_id, 2, 2)])
-    with pytest.raises(ValueError, match="offset \\+ length overflowed"):
+    with pytest.raises(RuntimeError, match="offset \\+ length overflowed"):
        table.fetch_blob_ranges("image", [(row_id, 2**64 - 1, 1)])
-    with pytest.raises(ValueError, match="row IDs"):
+    with pytest.raises(ValueError, match="row ids"):
        table.fetch_blob_ranges("image", [(2**64 - 1, 0, 1)])
@@ -2,11 +2,9 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import inspect
 import re
 import sys
 from datetime import timedelta
 from importlib import resources
 import os
 from types import SimpleNamespace
@@ -19,10 +17,6 @@ from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError
 from lancedb.pydantic import LanceModel, Vector
 def test_package_includes_pep_561_marker():
    assert resources.files(lancedb).joinpath("py.typed").is_file()
 def test_basic(tmp_path):
    db = lancedb.connect(tmp_path)
@@ -68,44 +62,6 @@ def test_basic(tmp_path):
    assert db.open_table("test").name == db["test"].name
 def test_sync_debugger_inspection_does_not_use_background_loop(tmp_path, monkeypatch):
    from lancedb.background_loop import LOOP
    db = lancedb.connect(tmp_path)
    table = db.create_table("test", data=[{"id": 1}])
    def fail_run(*args, **kwargs):
        raise AssertionError("debugger inspection should not use the background loop")
    monkeypatch.setattr(LOOP, "run", fail_run)
    # Debuggers enumerate and evaluate every exposed attribute when expanding a
    # variable. This must remain safe while their breakpoint suspends LOOP's thread.
    members = dict(inspect.getmembers(db))
    assert members["uri"] == str(tmp_path)
    assert members["read_consistency_interval"] is None
    assert repr(db) == f"LanceDBConnection(uri={str(tmp_path)!r})"
    assert repr(table) == f"LanceTable(name='test', _conn={db!r})"
 def test_read_consistency_interval_does_not_use_background_loop(tmp_path, monkeypatch):
    from lancedb.background_loop import LOOP
    from lancedb.db import LanceDBConnection
    consistency_interval = timedelta(seconds=5)
    db = lancedb.connect(tmp_path, read_consistency_interval=consistency_interval)
    db_from_inner = LanceDBConnection.from_inner(db._inner, consistency_interval)
    def fail_run(*args, **kwargs):
        raise AssertionError("properties should not use the Python background loop")
    monkeypatch.setattr(LOOP, "run", fail_run)
    assert db.read_consistency_interval == consistency_interval
    assert db_from_inner.read_consistency_interval == consistency_interval
 def test_ingest_pd(tmp_path):
    db = lancedb.connect(tmp_path)
@@ -755,7 +711,8 @@ def test_delete_table(tmp_db: lancedb.DBConnection):
    assert tmp_db.table_names() == []
-def test_drop_table_async(tmp_db: lancedb.DBConnection):
+@pytest.mark.asyncio
 async def test_delete_table_async(tmp_db: lancedb.DBConnection):
    data = pd.DataFrame(
        {
            "vector": [[3.1, 4.1], [5.9, 26.5]],
@@ -771,10 +728,7 @@ def test_drop_table_async(tmp_db: lancedb.DBConnection):
    assert tmp_db.table_names() == ["test"]
-    job = tmp_db.drop_table_async("test")
+    tmp_db.drop_table("test")
    assert job.id is None
    assert job.status() == "finished"
    job.wait()
    assert tmp_db.table_names() == []
    tmp_db.create_table("test", data=data)
@@ -783,17 +737,6 @@ def test_drop_table_async(tmp_db: lancedb.DBConnection):
    tmp_db.drop_table("does_not_exist", ignore_missing=True)
@pytest.mark.asyncio
 async def test_drop_table_async_connection(tmp_db_async: lancedb.AsyncConnection):
    await tmp_db_async.create_table("test", data=pa.table({"id": [1, 2]}))
    job = await tmp_db_async.drop_table_async("test")
    assert job.id is None
    assert await job.status() == "finished"
    await job.wait()
    assert await tmp_db_async.table_names() == []
 def test_drop_database(tmp_db: lancedb.DBConnection):
    data = pd.DataFrame(
        {
@@ -1456,408 +1456,6 @@ def test_shuffle_clump_size_yields_all_rows(lance_table):
    )
 # ---------------------------------------------------------------------------
 # on_transform_error tests
 # ---------------------------------------------------------------------------
 class BadRowError(ValueError):
    """Raised by the failing transforms below when a batch contains a bad id."""
 def _failing_transform(bad_ids: set):
    """A transform that raises BadRowError whenever the batch has a bad id.
    Raises on the full batch and on any single-row slice containing a bad id,
    so per-row isolation drops exactly the bad rows.
    """
    def transform(batch: pa.RecordBatch) -> list:
        ids = batch.column("id").to_pylist()
        bad = sorted(set(ids) & bad_ids)
        if bad:
            raise BadRowError(f"bad ids in batch: {bad}")
        return [{"id": i} for i in ids]
    return transform
 def _sequential_split_members(table) -> list[list[int]]:
    """Return each split's ids in yield order for shuffle=False.
    With a single rank and no workers the round-robin yields one row per split
    per cycle, so item k of a clean run belongs to split k % NUM_SPLITS.
    """
    ds = StreamingDataset(table, num_splits=NUM_SPLITS, shuffle=False)
    members: list[list[int]] = [[] for _ in range(NUM_SPLITS)]
    for k, row in enumerate(ds):
        members[k % NUM_SPLITS].append(row["id"])
    return members
 def test_on_transform_error_default_raises(lance_table):
    """By default a transform exception propagates and aborts iteration."""
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle_seed=SHUFFLE_SEED,
        transform=_failing_transform({7}),
    )
    with pytest.raises(BadRowError):
        list(ds)
 def test_on_transform_error_invalid_value(lance_table):
    with pytest.raises(ValueError, match="on_transform_error"):
        StreamingDataset(lance_table, num_splits=NUM_SPLITS, on_transform_error="bogus")
 def test_on_transform_error_skip_drops_bad_rows(lance_table):
    """With one bad row per split, 'skip' yields every good row exactly once
    and counts the dropped rows in rows_skipped."""
    members = _sequential_split_members(lance_table)
    bad_ids = {members[i][4] for i in range(NUM_SPLITS)}
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="skip",
    )
    assert ds.rows_skipped == 0
    ids = [row["id"] for row in ds]
    assert sorted(ids) == sorted(set(range(NUM_ROWS)) - bad_ids)
    assert ds.rows_skipped == NUM_SPLITS
 def test_on_transform_error_skip_uneven_ends_at_last_complete_cycle(lance_table):
    """When one split loses more rows than the others, the epoch ends at the
    last cycle where every split still has a row — no crash, no bad rows, and
    every step remains one sample per split."""
    members = _sequential_split_members(lance_table)
    bad_ids = set(members[0][:3])  # all 3 bad rows in split 0
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="skip",
    )
    items = [row["id"] for row in ds]
    rows_per_split = NUM_ROWS // NUM_SPLITS
    expected_cycles = rows_per_split - len(bad_ids)
    assert len(items) == expected_cycles * NUM_SPLITS
    assert len(set(items)) == len(items), "duplicate samples yielded"
    assert not set(items) & bad_ids, "a bad row was yielded"
    # Split 0 contributed exactly its surviving rows, in order, one per cycle.
    survivors = [i for i in members[0] if i not in bad_ids]
    assert items[0::NUM_SPLITS] == survivors[:expected_cycles]
 def test_on_transform_error_warn_logs(lance_table, caplog):
    """'warn' skips like 'skip' but logs a warning for the failing batch."""
    members = _sequential_split_members(lance_table)
    bad_ids = {members[i][3] for i in range(NUM_SPLITS)}
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="warn",
    )
    with caplog.at_level(logging.WARNING, logger="lancedb.streaming"):
        items = list(ds)
    assert len(items) == NUM_ROWS - NUM_SPLITS
    assert ds.rows_skipped == NUM_SPLITS
    assert "Skipped" in caplog.text
    assert "BadRowError" in caplog.text
 def test_on_transform_error_callable_selective(lance_table):
    """A callable handler can skip expected errors and re-raise the rest."""
    members = _sequential_split_members(lance_table)
    bad_ids = {members[i][0] for i in range(NUM_SPLITS)}
    handled: list[Exception] = []
    def handler(exc: Exception) -> bool:
        handled.append(exc)
        return isinstance(exc, BadRowError)
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error=handler,
    )
    items = list(ds)
    assert len(items) == NUM_ROWS - NUM_SPLITS
    assert handled and all(isinstance(exc, BadRowError) for exc in handled)
    def broken_transform(batch: pa.RecordBatch) -> list:
        raise TypeError("boom")
    ds2 = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=broken_transform,
        on_transform_error=handler,
    )
    with pytest.raises(TypeError, match="boom"):
        list(ds2)
 def test_transform_wrong_row_count_raises(lance_table):
    """A transform that returns the wrong number of rows is an error even with
    on_transform_error='skip' — silent shrinkage would corrupt accounting."""
    def drops_rows(batch: pa.RecordBatch) -> list:
        return batch.column("id").to_pylist()[:-1]
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle_seed=SHUFFLE_SEED,
        transform=drops_rows,
        on_transform_error="skip",
    )
    with pytest.raises(ValueError, match="one output row per input row"):
        list(ds)
 def test_skip_deterministic_across_runs(lance_table):
    """With a fixed seed, skipping produces the identical sample sequence on
    every run — skips are data-dependent, not run-dependent."""
    bad_ids = {5, 17, 46}
    def run() -> tuple[list[int], int]:
        ds = StreamingDataset(
            lance_table,
            num_splits=NUM_SPLITS,
            shuffle_seed=SHUFFLE_SEED,
            transform=_failing_transform(bad_ids),
            on_transform_error="skip",
        )
        return [row["id"] for row in ds], ds.rows_skipped
    ids_a, skipped_a = run()
    ids_b, skipped_b = run()
    assert ids_a == ids_b
    assert skipped_a == skipped_b
    assert not set(ids_a) & bad_ids
 def test_skip_elastic_det_across_world_sizes(lance_table):
    """With equal bad-row counts per split, skipping preserves the full
    elastic-determinism guarantee: identical global batches at every step for
    every compatible world_size."""
    members = _sequential_split_members(lance_table)
    bad_ids = {members[i][6] for i in range(NUM_SPLITS)}
    def collect(world_size: int) -> list[frozenset[int]]:
        micro = GLOBAL_BATCH_SIZE // world_size
        iters = [
            iter(
                StreamingDataset(
                    lance_table,
                    num_splits=NUM_SPLITS,
                    shuffle=False,
                    rank=rank,
                    world_size=world_size,
                    transform=_failing_transform(bad_ids),
                    on_transform_error="skip",
                )
            )
            for rank in range(world_size)
        ]
        _STOP = object()
        batches: list[frozenset[int]] = []
        while True:
            step_samples: set[int] = set()
            exhausted = 0
            for it in iters:
                for _ in range(micro):
                    val = next(it, _STOP)
                    if val is _STOP:
                        exhausted += 1
                        break
                    step_samples.add(val["id"])
            if exhausted == len(iters):
                break
            assert exhausted == 0, (
                "Rank iterators exhausted at different steps despite equal "
                "bad-row counts per split"
            )
            batches.append(frozenset(step_samples))
        return batches
    reference = collect(1)
    assert len(reference) == NUM_ROWS // NUM_SPLITS - 1
    for ws in (2, 3, 4):
        assert collect(ws) == reference, f"world_size={ws} diverged"
 def test_resumability_with_skips_same_topology(lance_table):
    """Checkpointing mid-epoch with skipped rows resumes exactly: no sample
    repeated, no sample lost, skipped rows stay skipped."""
    members = _sequential_split_members(lance_table)
    # Uneven skips: positions diverge across splits (2 bad in split 0, 1 in
    # split 5), which only a position-based checkpoint can resume exactly.
    bad_ids = {members[0][2], members[0][3], members[5][7]}
    kwargs = dict(
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="skip",
    )
    reference = [row["id"] for row in StreamingDataset(lance_table, **kwargs)]
    rows_per_split = NUM_ROWS // NUM_SPLITS
    assert len(reference) == (rows_per_split - 2) * NUM_SPLITS
    steps = 3
    ds = StreamingDataset(lance_table, **kwargs)
    it = iter(ds)
    consumed = [next(it)["id"] for _ in range(steps * NUM_SPLITS)]
    checkpoint = ds.state_dict()
    it.close()
    # Split 0 skipped positions 2 and 3 within its first 3 yields; split 5's
    # bad row is beyond the checkpoint.  Everything else is at 3 = the sample
    # count.
    positions = checkpoint["positions_consumed_per_split"]
    assert positions[0] == 5
    assert positions[1:] == [3] * (NUM_SPLITS - 1)
    assert checkpoint["samples_consumed_per_split"] == [3] * NUM_SPLITS
    ds2 = StreamingDataset(lance_table, **kwargs)
    ds2.load_state_dict(checkpoint)
    resumed = [row["id"] for row in ds2]
    assert consumed == reference[: steps * NUM_SPLITS]
    assert resumed == reference[steps * NUM_SPLITS :]
 def test_resumability_with_skips_elastic_merge(lance_table):
    """Elastic resume with skips: each rank's checkpoint knows exact positions
    only for its own splits; merge_state_dicts recovers the global state, and
    a run on a different world_size continues exactly."""
    members = _sequential_split_members(lance_table)
    # Bad rows early in split 0 (rank 0) and split 6 (rank 1 of a ws=2 run) so
    # both ranks' position vectors diverge before the checkpoint.
    bad_ids = {members[0][0], members[0][2], members[6][1]}
    kwargs = dict(
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="skip",
    )
    reference = [row["id"] for row in StreamingDataset(lance_table, **kwargs)]
    steps = 3
    world_size = 2
    micro = GLOBAL_BATCH_SIZE // world_size
    datasets = [
        StreamingDataset(lance_table, rank=rank, world_size=world_size, **kwargs)
        for rank in range(world_size)
    ]
    iters = [iter(ds) for ds in datasets]
    seen: list[frozenset[int]] = []
    for _ in range(steps):
        step_samples = set()
        for it in iters:
            for _ in range(micro):
                step_samples.add(next(it)["id"])
        seen.append(frozenset(step_samples))
    states = [ds.state_dict() for ds in datasets]
    for it in iters:
        it.close()
    merged = StreamingDataset.merge_state_dicts(states)
    expected_positions = [3] * NUM_SPLITS
    expected_positions[0] = 5  # skipped positions 0 and 2
    expected_positions[6] = 4  # skipped position 1
    assert merged["positions_consumed_per_split"] == expected_positions
    # The first 3 global batches match the world_size=1 reference.
    ref_batches = [
        frozenset(reference[s * NUM_SPLITS : (s + 1) * NUM_SPLITS])
        for s in range(len(reference) // NUM_SPLITS)
    ]
    assert seen == ref_batches[:steps]
    # Resume on world_size=1 from the merged state.
    ds_resume = StreamingDataset(lance_table, **kwargs)
    ds_resume.load_state_dict(merged)
    resumed = [row["id"] for row in ds_resume]
    assert resumed == reference[steps * NUM_SPLITS :]
 def test_rows_skipped_flushed_when_split_entirely_bad(lance_table):
    """A split whose rows all fail never completes a cycle, so the epoch ends
    immediately — but rows_skipped must still report the drops after the
    iterator exits (the shared-memory counter is flushed on exhaustion)."""
    members = _sequential_split_members(lance_table)
    bad_ids = set(members[0])  # every row of split 0 is bad
    ds = StreamingDataset(
        lance_table,
        num_splits=NUM_SPLITS,
        shuffle=False,
        transform=_failing_transform(bad_ids),
        on_transform_error="skip",
    )
    assert list(ds) == []
    assert ds.rows_skipped == len(bad_ids)
 def test_merge_state_dicts_validates_consistency(lance_table):
    ds = StreamingDataset(lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED)
    state = ds.state_dict()
    other = dict(state, shuffle_seed=SHUFFLE_SEED + 1)
    with pytest.raises(ValueError, match="shuffle_seed mismatch"):
        StreamingDataset.merge_state_dicts([state, other])
    with pytest.raises(ValueError, match="at least one"):
        StreamingDataset.merge_state_dicts([])
 def test_load_state_dict_without_positions_key(lance_table):
    """Checkpoints from before positions_consumed_per_split existed still
    resume exactly (positions equal sample counts when nothing is skipped)."""
    reference = [
        row["id"]
        for row in StreamingDataset(
            lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED
        )
    ]
    steps = 4
    ds = StreamingDataset(lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED)
    it = iter(ds)
    for _ in range(steps * NUM_SPLITS):
        next(it)
    checkpoint = ds.state_dict()
    it.close()
    del checkpoint["positions_consumed_per_split"]
    ds2 = StreamingDataset(
        lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED
    )
    ds2.load_state_dict(checkpoint)
    resumed = [row["id"] for row in ds2]
    assert resumed == reference[steps * NUM_SPLITS :]
 def test_num_splits_defaults_to_world_size(lance_table):
    """Omitting num_splits gives world_size splits (one per rank)."""
    ds = StreamingDataset(
@@ -64,23 +64,6 @@ def test_embedding_function(tmp_path):
    assert np.allclose(actual, expected)
 def test_instructor_ndims_uses_instruction():
    instructor = get_registry().get("instructor").create()
    model = MagicMock()
    model.encode.return_value = np.zeros((1, 384))
    with patch.object(type(instructor), "get_model", return_value=model):
        assert instructor.ndims() == 384
    model.encode.assert_called_once_with(
        [[instructor.source_instruction, "foo"]],
        batch_size=instructor.batch_size,
        show_progress_bar=instructor.show_progress_bar,
        normalize_embeddings=instructor.normalize_embeddings,
        device=instructor.device,
    )
 def test_embedding_function_variables():
    @register("variable-testing")
    class VariableTestingFunction(TextEmbeddingFunction):
@@ -132,16 +115,34 @@ def test_embedding_function_variables():
    assert func.safe_model_dump()["secret_key"] == "$var:secret"
-def test_openai_variables_survive_metadata_round_trip():
+def test_parse_functions_with_variables():
    @register("variable-parsing-test")
    class VariableParsingFunction(TextEmbeddingFunction):
        api_key: str
        base_url: Optional[str] = None
        @staticmethod
        def sensitive_keys():
            return ["api_key"]
        def ndims(self):
            return 10
        def generate_embeddings(self, texts):
            # Mock implementation that just returns random embeddings
            # In real usage, this would use the api_key to call an API
            return [np.random.rand(self.ndims()).tolist() for _ in texts]
    registry = EmbeddingFunctionRegistry.get_instance()
    registry.set_var("test_api_key", "sk-test-key-12345")
    registry.set_var("test_base_url", "https://api.example.com")
    conf = EmbeddingFunctionConfig(
        source_column="text",
        vector_column="vector",
-        function=registry.get("openai").create(
+        function=registry.get("variable-parsing-test").create(
-            api_key="$var:test_api_key", base_url="https://api.example.com"
+            api_key="$var:test_api_key", base_url="$var:test_base_url"
        ),
    )
@@ -149,10 +150,7 @@ def test_openai_variables_survive_metadata_round_trip():
    # Create a mock arrow table with the metadata
    schema = pa.schema(
-        [
+        [pa.field("text", pa.string()), pa.field("vector", pa.list_(pa.float32(), 10))]
            pa.field("text", pa.string()),
            pa.field("vector", pa.list_(pa.float32(), 1536)),
        ]
    )
    table = pa.table({"text": [], "vector": []}, schema=schema)
    table = table.replace_schema_metadata(metadata)
@@ -166,15 +164,13 @@ def test_openai_variables_survive_metadata_round_trip():
    assert parsed_func.api_key == "sk-test-key-12345"
    assert parsed_func.base_url == "https://api.example.com"
    embeddings = parsed_func.generate_embeddings(["test text"])
    assert len(embeddings) == 1
    assert len(embeddings[0]) == 10
    assert parsed_func.safe_model_dump()["api_key"] == "$var:test_api_key"
    with patch("lancedb.embeddings.openai.attempt_import_or_raise") as import_openai:
        parsed_func._openai_client
    import_openai.return_value.OpenAI.assert_called_once_with(
        api_key="sk-test-key-12345", base_url="https://api.example.com"
    )
 def test_embedding_with_bad_results(tmp_path):
    @register("null-embedding")
@@ -631,23 +627,3 @@ def test_url_retrieve_downloads_image():
    image_bytes = url_retrieve(image_url)
    img = Image.open(io.BytesIO(image_bytes))
    assert img.size[0] > 0 and img.size[1] > 0
 def test_jina_generate_image_input_dict_local_path(tmp_path):
    """
    JinaEmbeddings._generate_image_input_dict must accept a local image path
    (str or Path), not just bytes. Previously it crashed with
    `AttributeError: 'function' object has no attribute 'urlparse'` on any
    str/Path input because it called `urlparse.urlparse(image)` instead of
    `urlparse(image)` (urlparse was imported as a function, not a module).
    """
    Image = pytest.importorskip("PIL.Image")
    from lancedb.embeddings.jinaai import JinaEmbeddings
    image_path = tmp_path / "test.png"
    Image.new("RGB", (4, 4), color="red").save(image_path, format="PNG")
    for image in (str(image_path), image_path):
        image_dict = JinaEmbeddings._generate_image_input_dict(image)
        assert "image" in image_dict
        assert isinstance(image_dict["image"], str) and len(image_dict["image"]) > 0
@@ -632,101 +632,3 @@ class TestExprBytesIntegration:
            .to_arrow()
        )
        assert result.num_rows == 2
 # ── datetime / timezone integration for lit() (issue #3262) ──────────────────
 class TestExprDatetimeTimezoneIntegration:
    """Integration coverage for lit(datetime) against table timestamp columns.
    PyArrow stores naive timestamps as UTC wall-clock microseconds. Python's
    datetime.timestamp() treats naive values as *local* time, which used to
    shift lit(naive) by the host UTC offset and break equality filters on
    non-UTC machines. These cases lock the expected semantics.
    """
    def test_both_naive_match(self, tmp_path):
        """Table naive + lit naive with the same wall clock must match."""
        db = lancedb.connect(str(tmp_path / "naive"))
        ts = datetime(2024, 7, 1, 10, 0, 0)
        table = db.create_table(
            "t", [{"id": 1, "ts": ts}, {"id": 2, "ts": datetime(2024, 7, 2, 10, 0, 0)}]
        )
        result = table.search().where(col("ts") == lit(ts)).to_list()
        assert len(result) == 1
        assert result[0]["id"] == 1
    def test_both_same_timezone_match(self, tmp_path):
        """Table UTC + lit UTC for the same instant must match."""
        db = lancedb.connect(str(tmp_path / "utc"))
        ts = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
        table = db.create_table(
            "t",
            pa.table(
                {
                    "id": [1, 2],
                    "ts": pa.array(
                        [ts, datetime(2024, 7, 2, 10, 0, 0, tzinfo=timezone.utc)],
                        type=pa.timestamp("us", tz="UTC"),
                    ),
                }
            ),
        )
        result = table.search().where(col("ts") == lit(ts)).to_list()
        assert len(result) == 1
        assert result[0]["id"] == 1
    def test_different_timezones_same_instant(self, tmp_path):
        """UTC table row equals lit of the same instant in a different zone."""
        db = lancedb.connect(str(tmp_path / "diff_tz"))
        ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
        # Same instant as 06:00 in UTC-4
        ts_est = datetime(2024, 7, 1, 6, 0, 0, tzinfo=timezone(timedelta(hours=-4)))
        table = db.create_table(
            "t",
            pa.table(
                {
                    "id": [1],
                    "ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
                }
            ),
        )
        result = table.search().where(col("ts") == lit(ts_est)).to_list()
        assert len(result) == 1
        assert result[0]["id"] == 1
    def test_table_tz_literal_naive(self, tmp_path):
        """UTC table + naive lit uses wall-clock equality (10:00 == 10:00 UTC)."""
        db = lancedb.connect(str(tmp_path / "tz_naive"))
        ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
        ts_naive = datetime(2024, 7, 1, 10, 0, 0)
        table = db.create_table(
            "t",
            pa.table(
                {
                    "id": [1],
                    "ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
                }
            ),
        )
        result = table.search().where(col("ts") == lit(ts_naive)).to_list()
        assert len(result) == 1
        assert result[0]["id"] == 1
    def test_table_naive_literal_aware(self, tmp_path):
        """Naive table + UTC lit with the same wall clock must match."""
        db = lancedb.connect(str(tmp_path / "naive_aware"))
        ts_naive = datetime(2024, 7, 1, 10, 0, 0)
        ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
        table = db.create_table("t", [{"id": 1, "ts": ts_naive}])
        result = table.search().where(col("ts") == lit(ts_utc)).to_list()
        assert len(result) == 1
        assert result[0]["id"] == 1
    def test_naive_lit_sql_is_wall_clock_not_local_shifted(self):
        """Regression: naive lit must not apply the host local UTC offset."""
        ts = datetime(2024, 7, 1, 10, 0, 0)
        sql = lit(ts).to_sql()
        # Must encode 10:00 wall clock, not 10:00+local_offset.
        assert "2024-07-01 10:00:00" in sql
@@ -12,7 +12,7 @@ import pyarrow.compute as pc
 import pytest
 import pytest_asyncio
-from lancedb.index import BTree, FTS, IvfPq
+from lancedb.index import FTS
 from lancedb.table import AsyncTable, Table
@@ -99,86 +99,6 @@ async def test_async_hybrid_query_filters(table: AsyncTable):
    assert result["text"].to_pylist() == ["cat", "b"]
@pytest.mark.asyncio
 async def test_hybrid_query_with_stale_fixed_size_binary_prefilter(
    tmpdir_factory,
 ):
    tmp_path = str(tmpdir_factory.mktemp("stale_scalar_prefilter"))
    db = await lancedb.connect_async(tmp_path)
    def fixed_size_binary(value: int) -> bytes:
        return value.to_bytes(16, byteorder="big")
    num_rows = 1000
    data = pa.table(
        {
            "space_id": pa.array(
                [fixed_size_binary(i) for i in range(num_rows)],
                type=pa.binary(16),
            ),
            "text": ["book"] * num_rows,
            "vector": pa.array(
                [[float(i), float(i)] for i in range(num_rows)],
                type=pa.list_(pa.float32(), 2),
            ),
        }
    )
    table = await db.create_table("test", data)
    await table.create_index(
        "vector", config=IvfPq(num_partitions=4, num_sub_vectors=2)
    )
    await table.create_index("space_id", config=BTree())
    await table.create_index("text", config=FTS(with_position=False))
    # Advance the search indices without advancing the scalar index. This is the
    # state that previously let hybrid search use an incomplete scalar prefilter.
    await table.add(data)
    lance_dataset = await table.to_lance()
    lance_dataset.optimize.optimize_indices(index_names=["vector_idx", "text_idx"])
    await table.checkout_latest()
    scalar_stats = await table.index_stats("space_id_idx")
    assert scalar_stats is not None
    assert scalar_stats.num_indexed_rows == num_rows
    assert scalar_stats.num_unindexed_rows == num_rows
    for index_name in ["vector_idx", "text_idx"]:
        search_stats = await table.index_stats(index_name)
        assert search_stats is not None
        assert search_stats.num_indexed_rows == num_rows * 2
        assert search_stats.num_unindexed_rows == 0
    matching_ids = [5, 10, 15, 20, 25, 30]
    literals = [
        f"arrow_cast(0x{fixed_size_binary(i).hex()}, 'FixedSizeBinary(16)')"
        for i in matching_ids
    ]
    predicate = f"space_id IN ({', '.join(literals)})"
    expected_ids = sorted(fixed_size_binary(i) for i in matching_ids for _ in range(2))
    vector_query = (
        table.query().where(predicate).nearest_to([5.0, 5.0]).limit(num_rows * 2)
    )
    vector_results = await vector_query.to_arrow()
    assert sorted(vector_results["space_id"].to_pylist()) == expected_ids
    fts_query = (
        table.query().where(predicate).nearest_to_text("book").limit(num_rows * 2)
    )
    fts_results = await fts_query.to_arrow()
    assert sorted(fts_results["space_id"].to_pylist()) == expected_ids
    hybrid_results = await (
        table.query()
        .where(predicate)
        .nearest_to([5.0, 5.0])
        .nearest_to_text("book")
        .limit(num_rows * 2)
        .to_arrow()
    )
    assert sorted(hybrid_results["space_id"].to_pylist()) == expected_ids
@pytest.mark.asyncio
 async def test_async_hybrid_query_default_limit(table: AsyncTable):
    # add 10 new rows
@@ -203,44 +123,6 @@ async def test_async_hybrid_query_default_limit(table: AsyncTable):
    assert texts.count("a") == 1
 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.
    full = (
        sync_table.search(query_type="hybrid")
        .vector([0.0, 0.4])
        .text("dog")
        .limit(4)
        .with_row_id(True)
        .to_arrow()
    )
    assert len(full) == 4
    offset_result = (
        sync_table.search(query_type="hybrid")
        .vector([0.0, 0.4])
        .text("dog")
        .offset(2)
        .limit(2)
        .with_row_id(True)
        .to_arrow()
    )
    assert offset_result["_rowid"].to_pylist() == full["_rowid"].to_pylist()[2:]
 def test_hybrid_query_minimum_nprobes_zero_raises(sync_table: Table):
    # minimum_nprobes(0) must raise the same validation error a plain vector
    # query raises, not silently no-op because 0 is falsy.
    with pytest.raises(ValueError, match="minimum_nprobes must be greater than 0"):
        (
            sync_table.search(query_type="hybrid")
            .vector([0.0, 0.4])
            .text("dog")
            .minimum_nprobes(0)
            .to_arrow()
        )
 def test_hybrid_query_distance_range(sync_table: Table):
    reranker = RRFReranker(return_score="all")
    result = (
@@ -1,33 +0,0 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import re
 import shutil
 import subprocess
 import sys
 import lancedb._lancedb as _lancedb
 import pytest
@pytest.mark.skipif(sys.platform != "linux", reason="ldd is Linux-specific")
 def test_native_extension_does_not_link_openssl():
    """OpenSSL-linked wheels abort when imported on RHEL hosts in FIPS mode."""
    ldd = shutil.which("ldd")
    if ldd is None:
        pytest.skip("ldd is not installed")
    result = subprocess.run(
        [ldd, _lancedb.__file__],
        check=True,
        capture_output=True,
        text=True,
    )
    openssl_libraries = re.findall(
        r"^\s*(lib(?:crypto|ssl)\S*)\s+=>", result.stdout, flags=re.MULTILINE
    )
    assert not openssl_libraries, (
        "the LanceDB native extension must use rustls instead of linking OpenSSL: "
        f"{openssl_libraries}"
    )
@@ -84,15 +84,6 @@ async def binary_table(db_async):
    )
@pytest.mark.asyncio
 async def test_create_index_async_returns_done_job(some_table: AsyncTable):
    job = await some_table.create_index_async("id", config=BTree())
    assert job.id is None
    await job.wait()
    assert len(await some_table.list_indices()) == 1
    await job.cancel()
@pytest.mark.asyncio
 async def test_create_scalar_index(some_table: AsyncTable):
    # Can create
@@ -372,31 +363,6 @@ async def test_create_vector_index(some_table: AsyncTable):
    assert stats.num_indices == 1
@pytest.mark.asyncio
 async def test_create_ivf_index_reports_unsplittable_partitions(db_async):
    dim = 8
    num_partitions = 300  # More than 256 selects hierarchical k-means.
    base_vectors = [[float(row == column) for column in range(dim)] for row in range(5)]
    vectors = pa.array(base_vectors * 200, pa.list_(pa.float32(), dim))
    table = await db_async.create_table(
        "unsplittable_partitions",
        pa.table({"vector": vectors}),
    )
    error_pattern = (
        rf"Cannot create {num_partitions} IVF partitions: k-means could only form"
    )
    with pytest.raises(RuntimeError, match=error_pattern):
        await table.create_index(
            "vector",
            config=IvfFlat(
                distance_type="dot",
                num_partitions=num_partitions,
                max_iterations=10,
            ),
        )
@pytest.mark.asyncio
 async def test_create_4bit_ivfpq_index(some_table: AsyncTable):
    # Can create
@@ -83,9 +83,7 @@ def test_lsm_write_spec_repr():
    assert s.spec_type == "bucket"
    assert s.column == "id"
    assert s.num_buckets == 4
-    # A fresh spec defers its maintained set to install time.
+    assert s.maintained_indexes == []
    assert s.maintained_indexes is None
    assert s.with_maintained_indexes([]).maintained_indexes == []
    assert "bucket" in repr(s)
    assert "id" in repr(s)
    assert "4" in repr(s)
@@ -171,23 +169,18 @@ def test_get_lsm_write_spec(tmp_path):
    table.unset_lsm_write_spec()
    assert table.get_lsm_write_spec() is None
-    # Identity round-trips (column recovered from the schema). Leaving the
+    # Identity round-trips (column recovered from the schema).
    # maintained set to be inferred picks up the index on the table, so the
    # spec reads back naming it rather than as "infer".
    table.set_lsm_write_spec(LsmWriteSpec.identity("id"))
    spec = table.get_lsm_write_spec()
    assert spec.spec_type == "identity"
    assert spec.column == "id"
    assert spec.maintained_indexes == [idx_name]
    table.unset_lsm_write_spec()
-    # Unsharded round-trips (no routing column). Opting out is distinct from
+    # Unsharded round-trips (no routing column).
-    # the inferred default.
+    table.set_lsm_write_spec(LsmWriteSpec.unsharded())
    table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
    spec = table.get_lsm_write_spec()
    assert spec.spec_type == "unsharded"
    assert spec.column is None
    assert spec.maintained_indexes == []
@pytest.mark.asyncio
@@ -544,7 +544,7 @@ def test_lsm_read_fts_unmaintained_index_errors(tmp_path):
    table.create_index("text", config=FTS())
    # No maintained indexes: the active memtable FTS arm cannot serve un-compacted
    # docs, so the search would silently omit them — reject instead.
-    table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
+    table.set_lsm_write_spec(LsmWriteSpec.unsharded())
    with pytest.raises(Exception, match="maintained"):
        table.search("fox", query_type="fts", fts_columns="text").to_arrow()
@@ -631,7 +631,7 @@ def test_lsm_read_vector_unmaintained_index_errors(tmp_path):
    )
    # Spec with NO maintained indexes: the base vector index's catch-up is untracked,
    # so the scanner rejects rather than risk dropping compacted-but-unindexed rows.
-    table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
+    table.set_lsm_write_spec(LsmWriteSpec.unsharded())
    with pytest.raises(Exception, match="maintained"):
        table.search([1.0] * VECTOR_DIM).to_arrow()
@@ -18,7 +18,6 @@ Tests verify:
 """
 import copy
 import os
 import shutil
 import sys
 import tempfile
@@ -240,7 +239,7 @@ def create_tracking_namespace(
    dir_props = {f"storage.{k}": v for k, v in storage_options_with_refresh.items()}
-    if os.path.isabs(bucket_name) or bucket_name.startswith("file://"):
+    if bucket_name.startswith("/") or bucket_name.startswith("file://"):
        dir_props["root"] = f"{bucket_name}/namespace_root"
    else:
        dir_props["root"] = f"s3://{bucket_name}/namespace_root"
@@ -768,70 +767,3 @@ def test_namespace_with_schema_only(s3_bucket: str, use_custom: bool):
    # Verify data was added
    assert table.count_rows() == 2
@pytest.mark.parametrize("use_custom", [False, True], ids=["DirectoryNS", "CustomNS"])
 def test_namespace_exists(use_custom: bool):
    """
    Test namespace_exists returns True for existing and False for non-existent.
    """
    temp_dir = tempfile.mkdtemp()
    try:
        ns_client, _ = create_tracking_namespace(
            bucket_name=temp_dir,
            storage_options={},
            credential_expires_in_seconds=3600,
            use_custom=use_custom,
        )
        db = LanceNamespaceDBConnection(ns_client)
        namespace_name = f"test_ns_{uuid.uuid4().hex[:8]}"
        db.create_namespace([namespace_name])
        # Existing namespace should return True
        assert db.namespace_exists(namespace_id=[namespace_name]) is True
        # Non-existent namespace should return False
        assert db.namespace_exists(namespace_id=["nonexistent_ns"]) is False
    finally:
        shutil.rmtree(temp_dir, ignore_errors=True)
@pytest.mark.parametrize("use_custom", [False, True], ids=["DirectoryNS", "CustomNS"])
 def test_table_exists(use_custom: bool):
    """
    Test table_exists returns True for existing table and False for non-existent.
    """
    temp_dir = tempfile.mkdtemp()
    try:
        ns_client, _ = create_tracking_namespace(
            bucket_name=temp_dir,
            storage_options={},
            credential_expires_in_seconds=3600,
            use_custom=use_custom,
        )
        db = LanceNamespaceDBConnection(ns_client)
        namespace_name = f"test_ns_{uuid.uuid4().hex[:8]}"
        db.create_namespace([namespace_name])
        table_name = f"test_table_{uuid.uuid4().hex}"
        namespace_path = [namespace_name]
        schema = pa.schema(
            [
                pa.field("id", pa.int64()),
                pa.field("vector", pa.list_(pa.float32(), 2)),
                pa.field("text", pa.string()),
            ]
        )
        db.create_table(table_name, schema=schema, namespace_path=namespace_path)
        # Existing table should return True
        table_id = namespace_path + [table_name]
        assert db.table_exists(table_id=table_id) is True
        # Non-existent table should return False
        assert db.table_exists(table_id=namespace_path + ["nonexistent_table"]) is False
    finally:
        shutil.rmtree(temp_dir, ignore_errors=True)
@@ -1,42 +0,0 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import importlib
 import re
 import sys
 from pathlib import Path
 import pytest
 def test_pyo3_abi_matches_minimum_supported_python():
    project_dir = Path(__file__).parents[2]
    pyproject = (project_dir / "pyproject.toml").read_text()
    cargo_manifest = (project_dir / "Cargo.toml").read_text()
    minimum_python = re.search(
        r'^requires-python\s*=\s*">=(\d+)\.(\d+)"$', pyproject, re.MULTILINE
    )
    assert minimum_python is not None
    major, minor = minimum_python.groups()
    expected_abi = f"abi3-py{major}{minor}"
    configured_abis = re.findall(r'"(abi3-py\d+)"', cargo_manifest)
    assert configured_abis == [expected_abi, expected_abi], (
        "the pyo3 runtime and build ABI features must both match requires-python"
    )
@pytest.mark.skipif(sys.platform != "win32", reason="Windows wheel regression test")
 def test_windows_wheel_tag_and_native_import():
    project_dir = Path(__file__).parents[2]
    wheels = list((project_dir.parent / "target" / "wheels").glob("lancedb-*.whl"))
    if not wheels:
        pytest.skip("no wheel artifact is available in this development environment")
    assert len(wheels) == 1
    assert wheels[0].name.endswith("-cp310-abi3-win_amd64.whl")
    native_module = importlib.import_module("lancedb._lancedb")
    assert Path(native_module.__file__).suffix == ".pyd"
@@ -6,7 +6,6 @@ import math
 import pytest
 from lancedb import DBConnection, Table, connect
 from lancedb.background_loop import LOOP
 from lancedb.permutation import Permutation, Permutations, permutation_builder
@@ -32,25 +31,6 @@ def test_split_random_ratios(mem_db):
    assert 65 <= split_1_count <= 75  # ~70% ± tolerance
 def test_execute_does_not_reenter_background_loop(tmp_path, monkeypatch):
    import threading
    db = connect(tmp_path)
    tbl = db.create_table("test_table", pa.table({"x": range(10)}))
    original_run = LOOP.run
    def fail_on_reentry(future):
        assert threading.current_thread() is not LOOP.thread
        return original_run(future)
    monkeypatch.setattr(LOOP, "run", fail_on_reentry)
    permutation_tbl = permutation_builder(tbl).execute()
    assert permutation_tbl.count_rows() == 10
    assert permutation_tbl._conn.read_consistency_interval is None
 def test_split_random_counts(mem_db):
    """Test random splitting with absolute counts."""
    tbl = mem_db.create_table(
@@ -415,17 +415,6 @@ def test_nullable_vector():
    assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), True)])
 def test_bare_vector_raises_clear_error():
    namespace = {
        "__name__": "test_model_without_pyarrow",
        "LanceModel": LanceModel,
        "Vector": Vector,
    }
    with pytest.raises(TypeError, match=r"Vector must be parameterized.*Vector\(128\)"):
        exec("class TestModel(LanceModel):\n    vector: Vector", namespace)
 def test_fixed_size_list_field():
    class TestModel(pydantic.BaseModel):
        vec: Vector(16)
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Will Jones	011def461c	docs(python): fix cross-references that resolved to the wrong page `mkdocs build --strict` only catches references it cannot resolve. A bare anchor such as `[limit][]` or `[vector search][search]` is matched by autorefs against any heading on the site, so six of them silently linked into the JavaScript reference instead. The relative links in `permutation.py` and `remote/errors.py` pointed at in-page anchors and paths that do not exist. Targets that still exist here or in an imported inventory now use mkdocstrings references; the guide pages deleted in #2770 use their lancedb.com URLs. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-30 16:19:38 -07:00
Will Jones	ed6be12ad6	docs: clear the mkdocs warning backlog so --strict passes `mkdocs build` emitted 61 warnings on main, and rendering the previously undocumented classes in this PR pushed that to 158. That backlog is what blocks turning on strict mode (#3707), so clear it here rather than leave it worse than we found it. Most of it was one systematic false positive: griffe cannot see the generated `__init__` of a pydantic dataclass, so every documented parameter looked unknown. `warn_unknown_params` turns that check off. The rest were real docstring bugs, in 15 docstrings: * Prose trailing a `Parameters` section is read as parameter names, which invented parameters called `The`, `you` and `To`. Moved into `Notes` or the summary. * numpydoc only reads a type when the colon has spaces around it. Where the documented name is a pydantic attribute rather than a signature parameter, griffe has no signature to fall back on and the type was dropped. Affects nine embedding classes. * `num_partitions, default sqrt(num_rows)` and friends parse as a list of names, rendering a bogus `default` parameter. * One parameter indented five spaces instead of four. `nodejs/CONTRIBUTING.md` links to the repo-root CONTRIBUTING.md, which does not resolve once typedoc copies the file into `docs/src/js/_media/`; an absolute URL works from both places. `mkdocs build --strict` now exits 0. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-29 14:15:20 -07:00
Will Jones	ac2b689cdb	docs(python): render index/embeddings/remote/rerankers from __all__ Four packages are now rendered by a single mkdocstrings directive each, driven by the module's `__all__`, instead of a hand-maintained list of symbols. These were where most of the drift was: 7 of 12 rerankers and 14 of 17 embedding functions had never been listed. `lancedb.embeddings` had no `__all__`; without one mkdocstrings renders no members at all for a re-export package, so one is added. AGENTS.md gains a section describing how the reference page is wired up and how to check a docs build locally, plus a step in the "adding a new method on Table" checklist. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-29 13:59:23 -07:00
Will Jones	4fc8114871	docs(python): add missing public APIs to the Python reference The Python API reference page had drifted from the public API. Branch management (`Branches` / `AsyncBranches`, which own `diff` and `merge`), structured full-text query classes, take queries, blob helpers, namespace connections, most rerankers and embedding functions, the PyTorch dataloader, and several other public symbols were never listed, so they did not appear in the rendered docs. Also fixes docstring cross-references that pointed at guide pages which have since moved off this site, and at unresolvable relative targets (`[Table](Table)`, `[PyArrow Table](pyarrow.Table)`). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-07-29 13:46:45 -07:00