fix(node): reject non-ascii cfg keys

fix(node): reject commented cfg arguments
fix(node): reject target feature cfg overrides
2026-08-27 16:38:31 +00:00 · 2026-08-06 09:24:53 +00:00 · 2026-08-06 09:07:59 +00:00 · 2026-08-06 08:35:42 +00:00 · 2026-08-06 08:08:07 +00:00 · 2026-08-06 07:25:21 +00:00
118 changed files with 1386 additions and 10660 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.38.0-beta.0"
+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
-          # 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-checksums --precise 0.63.9
          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-eventstream --precise 0.60.14
+          cargo update -p aws-smithy-http --precise 0.62.4
+          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-async --precise 1.2.7
-          cargo update -p aws-smithy-types --precise 1.3.6
+          cargo update -p aws-smithy-runtime-api --precise 1.9.1
+          cargo update -p aws-smithy-async --precise 1.2.6
+          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
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"

 [workspace.dependencies]
-lance = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=10.1.0-beta.1", default-features = false, "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=10.1.0-beta.1", default-features = false, "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=10.1.0-beta.1", default-features = false, "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=10.1.0-beta.1", "tag" = "v10.1.0-beta.1", "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 }
@@ -52,7 +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"
@@ -101,13 +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" },
 ]

 # ---------------------------------------------------------------------------
@@ -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.0</version>
+    <version>0.37.1-beta.0</version>
 </dependency>
 ```

@@ -386,29 +386,6 @@ 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
@@ -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**:
-    \| `Field`&lt;`any`&gt;
-    \| `Field`&lt;`any`&gt;[]
-    \| `Schema`&lt;`any`&gt;
-    \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
-    \| `object`
+* **newColumnTransforms**: `Field`&lt;`any`&gt; \| `Field`&lt;`any`&gt;[] \| `Schema`&lt;`any`&gt; \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
    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()
@@ -458,10 +431,9 @@ 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
-[Table#setLsmWriteSpec](Table.md#setlsmwritespec), except that `maintainedIndexes` always
-reports the concrete list resolved when the spec was set — `undefined`
-never round-trips.
+The returned spec — including its `maintainedIndexes` and
+`writerConfigDefaults` — mirrors what was passed to
+[Table#setLsmWriteSpec](Table.md#setlsmwritespec).

 #### Returns

@@ -745,67 +717,6 @@ 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
@@ -895,11 +806,6 @@ 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)
@@ -105,7 +105,6 @@
 - [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)
@@ -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
-index, resolved on install — a snapshot, so indexes created later are not
-maintained. Pass `[]` for none.
+Names of indexes the MemWAL should keep up to date during writes.

 ***

@@ -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;
-```
@@ -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
-overlay files
-
-Read from the manifest, so this excludes deletion files and manifests.
+The total number of bytes in the table
@@ -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
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.38.0-beta.0</version>
+      <version>0.37.1-beta.0</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

@@ -6,7 +6,7 @@

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.38.0-beta.0</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.13</lance-core.version>
+        <lance-core.version>10.1.0-beta.1</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>
@@ -0,0 +1,21 @@
+# Keep Node's Linux x64 addons compatible with pre-Haswell CPUs.
+# lance-linalg dispatches hot vector kernels to newer SIMD tiers at runtime.
+[env]
+LANCEDB_NODE_ENFORCE_X86_64_V2 = "1"
+
+[target.x86_64-unknown-linux-gnu]
+rustflags = [
+    "-C",
+    "target-cpu=x86-64-v2",
+    "-C",
+    "target-feature=-avx,-avx2,-fma,-f16c",
+]
+
+# Preserve the workspace's dynamic C runtime configuration for musl.
+[target.x86_64-unknown-linux-musl]
+rustflags = [
+    "-C",
+    "target-cpu=x86-64-v2",
+    "-C",
+    "target-feature=-crt-static,-avx,-avx2,-fma,-f16c",
+]
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.38.0-beta.0"
+version = "0.37.1-beta.0"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -12,6 +12,10 @@ categories.workspace = true
 [lib]
 crate-type = ["cdylib"]

+[[test]]
+name = "x86_64_v2_build_flags"
+path = "build_support/x86_64_v2.rs"
+
 [dependencies]
 async-trait.workspace = true
 arrow-ipc.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()),
@@ -89,16 +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);
@@ -0,0 +1,50 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import * as tmp from "tmp";
+
+import { connect } from "../lancedb";
+import {
+  Field,
+  FixedSizeList,
+  Float32,
+  Int32,
+  Schema,
+  makeArrowTable,
+} from "../lancedb/arrow";
+
+test("cosine vector search runs on the pre-Haswell build baseline", async () => {
+  const tmpDir = tmp.dirSync({ unsafeCleanup: true });
+
+  try {
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int32(), false),
+      new Field(
+        "vector",
+        new FixedSizeList(3, new Field("item", new Float32(), false)),
+        false,
+      ),
+    ]);
+    const data = makeArrowTable(
+      [
+        { id: 1, vector: [1, 0, 0] },
+        { id: 2, vector: [0, 1, 0] },
+      ],
+      { schema },
+    );
+    const table = await db.createTable("vectors", data);
+
+    const results = await table
+      .vectorSearch([1, 0, 0])
+      .distanceType("cosine")
+      .limit(1)
+      .toArray();
+
+    expect(results).toHaveLength(1);
+    expect(results[0].id).toBe(1);
+    expect(results[0]._distance).toBeCloseTo(0);
+  } finally {
+    tmpDir.removeCallback();
+  }
+}, 60_000);
@@ -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) => {
@@ -1001,49 +969,4 @@ describe("remote connection jobs surface", () => {
      },
    );
  });
-
-  it("addBases posts the bases array", async () => {
-    const postedBodies: unknown[] = [];
-    await withMockDatabase(
-      (req, res) => {
-        const path = req.url ?? "";
-        if (path.endsWith("/describe/")) {
-          res.writeHead(200, { "Content-Type": "application/json" }).end(
-            JSON.stringify({
-              name: "photos",
-              version: 1,
-              schema: { fields: [] },
-            }),
-          );
-          return;
-        }
-        if (path.endsWith("/bases/")) {
-          const chunks: Buffer[] = [];
-          req.on("data", (chunk) => chunks.push(chunk));
-          req.on("end", () => {
-            postedBodies.push(JSON.parse(Buffer.concat(chunks).toString()));
-            res
-              .writeHead(200, { "Content-Type": "application/json" })
-              .end(JSON.stringify({ version: 2 }));
-          });
-          return;
-        }
-        res.writeHead(404).end();
-      },
-      async (db) => {
-        const table = await db.openTable("photos");
-        await table.addBases({ path: "s3://bucket/media/" });
-      },
-    );
-    expect(postedBodies).toEqual([
-      {
-        bases: [
-          {
-            path: "s3://bucket/media/",
-            isDatasetRoot: false,
-          },
-        ],
-      },
-    ]);
-  });
 });
@@ -4,7 +4,6 @@
 import * as fs from "fs";
 import * as path from "path";
 import * as tmp from "tmp";
-import { pathToFileURL } from "url";

 import * as arrow15 from "apache-arrow-15";
 import * as arrow16 from "apache-arrow-16";
@@ -87,44 +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);
@@ -278,16 +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: 684,
+        totalBytes: 44,
      });
-
-      // 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 () => {
@@ -3341,86 +3294,3 @@ describe("LSM merge insert", () => {
    await expect(table.query().useLsm(true).toArray()).rejects.toThrow();
  });
 });
-
-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]);
-  });
-});
-
-describe("table bases", () => {
-  let tmpDir: tmp.DirResult;
-  beforeEach(() => {
-    tmpDir = tmp.dirSync({ unsafeCleanup: true });
-  });
-  afterEach(() => tmpDir.removeCallback());
-
-  it("addBases accepts a file uri", async () => {
-    const conn = await connect(tmpDir.name);
-    const table = await conn.createEmptyTable(
-      "photos",
-      new arrow.Schema([new arrow.Field("id", new arrow.Int64(), false)]),
-    );
-    const media = path.join(tmpDir.name, "media");
-    fs.mkdirSync(media);
-    await table.addBases(pathToFileURL(media).toString());
-  });
-});
@@ -3,6 +3,29 @@

 extern crate napi_build;

+use std::env;
+
+#[path = "build_support/x86_64_v2.rs"]
+mod x86_64_v2;
+
+const ENFORCE_BASELINE: &str = "LANCEDB_NODE_ENFORCE_X86_64_V2";
+
 fn main() {
    napi_build::setup();
+    println!("cargo:rerun-if-env-changed={ENFORCE_BASELINE}");
+    println!("cargo:rerun-if-env-changed=CARGO_ENCODED_RUSTFLAGS");
+
+    let is_linux_x64 = env::var("CARGO_CFG_TARGET_ARCH").as_deref() == Ok("x86_64")
+        && env::var("CARGO_CFG_TARGET_OS").as_deref() == Ok("linux");
+    let is_release = env::var("PROFILE").as_deref() == Ok("release");
+    let is_node_build = env::var(ENFORCE_BASELINE).as_deref() == Ok("1");
+
+    if !is_linux_x64 || (!is_release && !is_node_build) {
+        return;
+    }
+
+    let encoded_rustflags = env::var("CARGO_ENCODED_RUSTFLAGS").unwrap_or_default();
+    x86_64_v2::validate_encoded_rustflags(&encoded_rustflags).unwrap_or_else(|error| {
+        panic!("Linux x64 Node addons must use the x86-64-v2 baseline; {error}")
+    });
 }
@@ -0,0 +1,430 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+use std::collections::{BTreeMap, BTreeSet};
+
+const SAFE_TARGET_CPUS: [&str; 2] = ["x86-64", "x86-64-v2"];
+const BASELINE_FEATURES: [&str; 9] = [
+    "cmpxchg16b",
+    "fxsr",
+    "popcnt",
+    "sse",
+    "sse2",
+    "sse3",
+    "sse4.1",
+    "sse4.2",
+    "ssse3",
+];
+
+pub(crate) fn validate_encoded_rustflags(encoded: &str) -> Result<(), String> {
+    let mut target_cpu = None;
+    let mut feature_states = BTreeMap::new();
+    let mut required_disables = BTreeSet::new();
+    let mut unsupported_features = BTreeSet::new();
+
+    for option in codegen_options(encoded)? {
+        let Some((name, value)) = option.split_once('=') else {
+            continue;
+        };
+
+        let name = name.replace('_', "-");
+        match name.as_str() {
+            "target-cpu" => target_cpu = Some(value),
+            "target-feature" => {
+                for toggle in value.split(',').filter(|toggle| !toggle.is_empty()) {
+                    let (enabled, feature) = match toggle.as_bytes()[0] {
+                        b'+' => (true, &toggle[1..]),
+                        b'-' => (false, &toggle[1..]),
+                        _ => return Err(format!("invalid target feature flag: {toggle}")),
+                    };
+
+                    feature_states.insert(feature, enabled);
+                    if enabled && !BASELINE_FEATURES.contains(&feature) {
+                        match feature {
+                            // These are inherited from the workspace configuration and
+                            // explicitly canceled by the Node configuration. Account for
+                            // their implied AVX prerequisite as well as the named feature.
+                            "avx" => {
+                                required_disables.insert("avx");
+                            }
+                            "avx2" => {
+                                required_disables.extend(["avx", "avx2"]);
+                            }
+                            "f16c" => {
+                                required_disables.extend(["avx", "f16c"]);
+                            }
+                            "fma" => {
+                                required_disables.extend(["avx", "fma"]);
+                            }
+                            _ => {
+                                unsupported_features.insert(feature);
+                            }
+                        }
+                    }
+                }
+            }
+            // LLVM arguments can independently alter the target feature set and
+            // cannot be proven safe by inspecting rustc's target options.
+            "llvm-args" => return Err("LLVM arguments can override the CPU baseline".to_owned()),
+            _ => {}
+        }
+    }
+
+    if let Some(cpu) = target_cpu.filter(|cpu| !SAFE_TARGET_CPUS.contains(cpu)) {
+        return Err(format!(
+            "effective target CPU is {}, expected x86-64-v2 or lower",
+            cpu
+        ));
+    }
+
+    if !unsupported_features.is_empty() {
+        return Err(format!(
+            "features above v2: {}",
+            unsupported_features
+                .into_iter()
+                .collect::<Vec<_>>()
+                .join(", ")
+        ));
+    }
+
+    let not_disabled = required_disables
+        .into_iter()
+        .filter(|feature| feature_states.get(feature) != Some(&false))
+        .collect::<Vec<_>>();
+    if !not_disabled.is_empty() {
+        return Err(format!(
+            "inherited features not fully disabled: {}",
+            not_disabled.join(", ")
+        ));
+    }
+
+    Ok(())
+}
+
+fn codegen_options(encoded: &str) -> Result<Vec<&str>, String> {
+    let arguments = encoded.split('\u{1f}').collect::<Vec<_>>();
+    if arguments.iter().any(|argument| argument.starts_with('@')) {
+        return Err("rustc response-file arguments cannot be validated".to_owned());
+    }
+
+    let mut options = Vec::new();
+    let mut index = 0;
+
+    while index < arguments.len() {
+        let argument = arguments[index];
+        if argument == "--cfg" {
+            index += 1;
+            let cfg = arguments
+                .get(index)
+                .copied()
+                .ok_or_else(|| "missing value after --cfg".to_owned())?;
+            reject_builtin_target_feature_cfg(cfg)?;
+        } else if let Some(cfg) = argument.strip_prefix("--cfg=") {
+            reject_builtin_target_feature_cfg(cfg)?;
+        } else if argument == "-C" || argument == "--codegen" {
+            index += 1;
+            let option = arguments
+                .get(index)
+                .copied()
+                .ok_or_else(|| format!("missing value after {argument}"))?;
+            options.push(option.trim_start_matches('='));
+        } else if let Some(option) = argument.strip_prefix("-C") {
+            if !option.is_empty() {
+                options.push(option.trim_start_matches('='));
+            }
+        } else if let Some(option) = argument.strip_prefix("--codegen=") {
+            options.push(option);
+        }
+        index += 1;
+    }
+
+    Ok(options)
+}
+
+fn reject_builtin_target_feature_cfg(cfg: &str) -> Result<(), String> {
+    let key = cfg.split_once('=').map_or(cfg, |(key, _)| key);
+    if key.contains("/*") || key.contains("//") {
+        return Err("comment-bearing cfgs cannot be validated".to_owned());
+    }
+    if !key.is_ascii() {
+        return Err("non-ASCII cfg keys cannot be validated".to_owned());
+    }
+
+    let name = key.trim();
+    let name = name.strip_prefix("r#").unwrap_or(name);
+    if name == "target_feature" {
+        return Err("built-in target_feature cfgs can override runtime CPU detection".to_owned());
+    }
+    Ok(())
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn encoded(arguments: &[&str]) -> String {
+        arguments.join("\u{1f}")
+    }
+
+    #[test]
+    fn accepts_merged_workspace_and_node_flags() {
+        let flags = encoded(&[
+            "-C",
+            "target-cpu=haswell",
+            "-C",
+            "target-feature=+avx2,+fma,+f16c",
+            "-C",
+            "target-cpu=x86-64-v2",
+            "-C",
+            "target-feature=-avx,-avx2,-fma,-f16c",
+        ]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_non_merging_v2_boundary() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64-v2"]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_default_cpu_with_non_codegen_flags() {
+        let flags = encoded(&["-D", "warnings"]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_unrelated_custom_cfg() {
+        let flags = encoded(&["--cfg=tokio_unstable"]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_comment_like_syntax_in_cfg_value() {
+        let flags = encoded(&[r#"--cfg=endpoint="https://example.com/*""#]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_explicit_x86_64_v1_cpu() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64"]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn accepts_musl_dynamic_crt_configuration() {
+        let flags = encoded(&[
+            "-C",
+            "target-cpu=haswell",
+            "-C",
+            "target-feature=-crt-static,+avx2,+fma,+f16c",
+            "-C",
+            "target-cpu=x86-64-v2",
+            "-C",
+            "target-feature=-crt-static,-avx,-avx2,-fma,-f16c",
+        ]);
+
+        assert_eq!(validate_encoded_rustflags(&flags), Ok(()));
+    }
+
+    #[test]
+    fn rejects_feature_omitted_from_target_cfg() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64-v2", "-Ctarget-feature=+apxf"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("features above v2: apxf".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_underscore_spelling_above_baseline_feature() {
+        let flags = encoded(&["-Ctarget_cpu=x86-64-v2", "-Ctarget_feature=+apxf"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("features above v2: apxf".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_unexpected_above_baseline_feature() {
+        let flags = encoded(&[
+            "--codegen=target-cpu=x86-64-v2",
+            "--codegen",
+            "target-feature=+bmi2",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("features above v2: bmi2".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_cpu_above_v2() {
+        let flags = encoded(&["-Ctarget-cpu=haswell"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("effective target CPU is haswell, expected x86-64-v2 or lower".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_incompletely_disabled_feature_implications() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64-v2", "-Ctarget-feature=+avx2,-avx2"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("inherited features not fully disabled: avx".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_llvm_feature_overrides() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64-v2", "-Cllvm-args=-mattr=+apxf"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("LLVM arguments can override the CPU baseline".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_underscore_spelling_llvm_feature_overrides() {
+        let flags = encoded(&["-Ctarget_cpu=x86-64-v2", "-Cllvm_args=-mattr=+apxf"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("LLVM arguments can override the CPU baseline".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_response_file_arguments() {
+        let flags = encoded(&["-Ctarget-cpu=x86-64-v2", "@flags.rsp"]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("rustc response-file arguments cannot be validated".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_split_builtin_target_feature_cfg() {
+        let flags = encoded(&[
+            "-Ctarget-cpu=x86-64-v2",
+            "--cfg",
+            r#"target_feature="avx2""#,
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("built-in target_feature cfgs can override runtime CPU detection".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_equals_builtin_target_feature_cfg() {
+        let flags = encoded(&[
+            "-Ctarget-cpu=x86-64-v2",
+            r#"--cfg=target_feature="avx2""#,
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("built-in target_feature cfgs can override runtime CPU detection".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_raw_identifier_builtin_target_feature_cfg() {
+        let flags = encoded(&[
+            "-Ctarget-cpu=x86-64-v2",
+            r#"--cfg=r#target_feature="avx2""#,
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("built-in target_feature cfgs can override runtime CPU detection".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_block_comment_after_cfg_name() {
+        let flags = encoded(&[
+            "--cfg",
+            r#"target_feature/*gate*/="avx2""#,
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("comment-bearing cfgs cannot be validated".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_block_comment_before_cfg_name() {
+        let flags = encoded(&[
+            r#"--cfg=/*gate*/target_feature="avx2""#,
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("comment-bearing cfgs cannot be validated".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_line_comment_cfg_trivia() {
+        let flags = encoded(&[
+            "--cfg",
+            "target_feature// gate\n=\"avx2\"",
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("comment-bearing cfgs cannot be validated".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_leading_bom_in_cfg_key() {
+        let flags = encoded(&[
+            "--cfg",
+            "\u{feff}target_feature=\"avx2\"",
+            "-Aexplicit_builtin_cfgs_in_flags",
+        ]);
+
+        assert_eq!(
+            validate_encoded_rustflags(&flags),
+            Err("non-ASCII cfg keys cannot be validated".to_owned())
+        );
+    }
+
+    #[test]
+    fn rejects_non_ascii_pattern_whitespace_in_cfg_key() {
+        for whitespace in ['\u{200e}', '\u{200f}'] {
+            let cfg = format!("{whitespace}target_feature=\"avx2\"");
+            let flags = encoded(&["--cfg", &cfg, "-Aexplicit_builtin_cfgs_in_flags"]);
+
+            assert_eq!(
+                validate_encoded_rustflags(&flags),
+                Err("non-ASCII cfg keys cannot be validated".to_owned())
+            );
+        }
+    }
+}
@@ -0,0 +1,37 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+const assert = require("node:assert/strict");
+const fs = require("node:fs");
+const os = require("node:os");
+const path = require("node:path");
+
+const { connect } = require("../dist");
+
+async function main() {
+  const tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), "lancedb-cpu-"));
+
+  try {
+    const db = await connect(tmpDir);
+    const table = await db.createTable("vectors", [
+      { id: 1, vector: [1, 0, 0] },
+      { id: 2, vector: [0, 1, 0] },
+    ]);
+    const results = await table
+      .vectorSearch([1, 0, 0])
+      .distanceType("cosine")
+      .limit(1)
+      .toArray();
+
+    assert.equal(results.length, 1);
+    assert.equal(results[0].id, 1);
+    assert.ok(Math.abs(results[0]._distance) < 1e-6);
+  } finally {
+    fs.rmSync(tmpDir, { force: true, recursive: true });
+  }
+}
+
+main().catch((error) => {
+  console.error(error);
+  process.exitCode = 1;
+});
@@ -327,14 +327,6 @@ 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).
@@ -713,10 +705,6 @@ 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 ?? []);
  }
@@ -50,7 +50,6 @@ export {
  MergeResult,
  AddResult,
  AddColumnsResult,
-  RefreshColumnResult,
  AlterColumnsResult,
  UpdateFieldMetadataResult,
  DeleteResult,
@@ -130,7 +129,6 @@ export {

 export {
  Table,
-  TableBase,
  Branches,
  BranchColumnSummary,
  BranchColumnChange,
@@ -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(
-    typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
-  );
+  return new Struct(typeLike.children.map((child) => sanitizeField(child)));
 }

 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_(
-    sanitizeFieldWithContext(typeLike.children[0], context),
-    typeLike.keysSorted,
-  );
+  return new Map_(sanitizeField(typeLike.children[0]), 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),
-    sanitizeTypeWithContext(typeLike.indices, context) as TKeys,
+    sanitizeType(typeLike.dictionary),
+    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 = sanitizeSchemaWithContext(tableLike.schema, context);
-  const batches = tableLike.batches.map((batch) =>
-    sanitizeRecordBatch(batch, context),
-  );
+  const schema = sanitizeSchema(tableLike.schema);
+
+  const batches = tableLike.batches.map(sanitizeRecordBatch);
  return new Table(schema, batches);
 }

-function sanitizeRecordBatch(
-  batchLike: RecordBatchLike,
-  context: SanitizationContext,
-): RecordBatch {
+function sanitizeRecordBatch(batchLike: RecordBatchLike): 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 data = sanitizeData(batchLike.data, context) as Data<Struct>;
+  const schema = sanitizeSchema(batchLike.schema);
+  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,
-): Data<DataType> {
+  // biome-ignore lint/suspicious/noExplicitAny: <explanation>
+): import("apache-arrow").Data<Struct<any>> {
  if (dataLike instanceof Data) {
    return dataLike;
  }
-  const cachedData = context.data.get(dataLike);
-  if (cachedData !== undefined) {
-    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),
+  return new Data(
+    dataLike.type,
    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 = {
@@ -33,7 +33,6 @@ import {
  Job,
  Branches as NativeBranches,
  OptimizeStats,
-  RefreshColumnResult,
  TableStatistics,
  Tags,
  UpdateFieldMetadataResult,
@@ -78,25 +77,6 @@ export interface WriteProgress {
  done: boolean;
 }

-/**
- * An extra storage prefix registered on a table.
- *
- * `path` is an object-store URI. `name` is an optional alias. `isDatasetRoot`
- * is true when `path` points to a Lance dataset root. When false, `path`
- * points directly to the directory containing the referenced files.
- */
-export interface TableBase {
-  /** Object store URI such as `s3://bucket/media/`. */
-  path: string;
-  /** Optional alias. */
-  name?: string;
-  /**
-   * True when `path` is a Lance dataset root. When false, `path` is the
-   * directory containing the referenced files.
-   */
-  isDatasetRoot?: boolean;
-}
-
 /**
 * Options for adding data to a table.
 */
@@ -217,11 +197,7 @@ export interface LsmWriteSpec {
  column?: string;
  /** Bucket variant: the number of buckets, in `[1, 1024]`. */
  numBuckets?: number;
-  /**
-   * 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.
-   */
+  /** Names of indexes the MemWAL should keep up to date during writes. */
  maintainedIndexes?: string[];
  /** Default `ShardWriter` configuration recorded in the MemWAL index. */
  writerConfigDefaults?: Record<string, string>;
@@ -545,84 +521,18 @@ 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:
-      | AddColumnsSql[]
-      | Field
-      | Field[]
-      | Schema
-      | { computed: AddColumnsSql[] },
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
  ): Promise<AddColumnsResult>;

-  /**
-   * Register additional storage bases for this table.
-   *
-   * A URI string is a non-root base with no alias.
-   */
-  abstract addBases(
-    bases: string | TableBase | Array<string | TableBase>,
-  ): Promise<void>;
-
-  /**
-   * 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
@@ -685,11 +595,6 @@ 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
@@ -717,10 +622,9 @@ 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
-   * {@link Table#setLsmWriteSpec}, except that `maintainedIndexes` always
-   * reports the concrete list resolved when the spec was set — `undefined`
-   * never round-trips.
+   * The returned spec — including its `maintainedIndexes` and
+   * `writerConfigDefaults` — mirrors what was passed to
+   * {@link Table#setLsmWriteSpec}.
   * @returns {Promise<LsmWriteSpec | undefined>}
   */
  abstract getLsmWriteSpec(): Promise<LsmWriteSpec | undefined>;
@@ -1174,22 +1078,8 @@ export class LocalTable extends Table {
  // TODO: Support BatchUDF

  async addColumns(
-    newColumnTransforms:
-      | AddColumnsSql[]
-      | Field
-      | Field[]
-      | Schema
-      | { computed: AddColumnsSql[] },
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
  ): 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];
@@ -1224,20 +1114,6 @@ export class LocalTable extends Table {
    throw new Error("Invalid input type for addColumns");
  }

-  async addBases(
-    bases: string | TableBase | Array<string | TableBase>,
-  ): Promise<void> {
-    await this.inner.addBases(normalizeBases(bases));
-  }
-
-  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> {
@@ -1430,21 +1306,6 @@ export class LocalTable extends Table {
  }
 }

-function normalizeBases(
-  bases: string | TableBase | Array<string | TableBase>,
-): TableBase[] {
-  const baseInputs = Array.isArray(bases) ? bases : [bases];
-  return baseInputs.map((base) =>
-    typeof base === "string"
-      ? { path: base, isDatasetRoot: false }
-      : {
-          path: base.path,
-          name: base.name,
-          isDatasetRoot: base.isDatasetRoot ?? false,
-        },
-  );
-}
-
 /**
 *  A definition of a column alteration. The alteration changes the column at
 * `path` to have the new name `name`, to be nullable if `nullable` is true,
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.38.0-beta.0",
+	"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.0",
+	"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.0",
+	"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.0",
+	"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.0",
+	"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.0",
+  "version": "0.37.1-beta.0",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.38.0-beta.0",
+	"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.0",
+  "version": "0.37.1-beta.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.38.0-beta.0",
+      "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.0",
+  "version": "0.37.1-beta.0",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -88,6 +88,7 @@
    "lint-fix": "biome check --write . && biome format --write .",
    "prepublishOnly": "napi prepublish -t npm",
    "test": "jest --verbose",
+    "test:pre-haswell": "node ci/pre_haswell_smoke.js",
    "integration": "S3_TEST=1 pnpm test",
    "universal": "napi universalize",
    "version": "napi version"
@@ -101,12 +102,6 @@
    "openai": "4.29.2"
  },
  "peerDependencies": {
-    "@types/node": ">=18",
    "apache-arrow": ">=15.0.0 <=18.1.0"
-  },
-  "peerDependenciesMeta": {
-    "@types/node": {
-      "optional": true
-    }
  }
 }
@@ -334,22 +334,6 @@ 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();
@@ -10,7 +10,6 @@ use lancedb::table::{
    AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration,
    FieldMetadataUpdate as LanceFieldMetadataUpdate, FtsToken as LanceDbFtsToken,
    NewColumnTransform, OptimizeAction, OptimizeOptions, Ref, Table as LanceDbTable,
-    TableBase as LanceTableBase,
 };
 use napi::bindgen_prelude::*;
 use napi::threadsafe_function::{ThreadsafeFunction, ThreadsafeFunctionCallMode};
@@ -348,40 +347,6 @@ impl Table {
        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,
@@ -447,18 +412,6 @@ impl Table {
        Ok(res.into())
    }

-    #[napi(catch_unwind)]
-    pub async fn add_bases(&self, bases: Vec<TableBase>) -> napi::Result<()> {
-        self.inner_ref()?
-            .add_bases(bases.into_iter().map(|base| LanceTableBase {
-                path: base.path,
-                name: base.name,
-                is_dataset_root: base.is_dataset_root,
-            }))
-            .await
-            .default_error()
-    }
-
    #[napi(catch_unwind)]
    pub async fn drop_columns(&self, columns: Vec<String>) -> napi::Result<DropColumnsResult> {
        let col_refs = columns.iter().map(String::as_str).collect::<Vec<_>>();
@@ -713,18 +666,6 @@ impl Table {
    }
 }

-#[napi(object)]
-/// An extra storage prefix registered on a table.
-pub struct TableBase {
-    /// Object store URI such as `s3://bucket/media/`.
-    pub path: String,
-    /// Optional alias.
-    pub name: Option<String>,
-    /// True when `path` is a Lance dataset root. When false, `path` is the
-    /// directory containing the referenced files.
-    pub is_dataset_root: bool,
-}
-
 #[napi(object)]
 /// A description of an index currently configured on a column
 pub struct IndexConfig {
@@ -831,8 +772,7 @@ 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
-    /// maintainable index on install; an empty array means none.
+    /// Names of indexes the MemWAL should keep up to date during writes.
    pub maintained_indexes: Option<Vec<String>>,
    /// Default `ShardWriter` configuration recorded in the MemWAL index.
    pub writer_config_defaults: Option<HashMap<String, String>>,
@@ -842,6 +782,7 @@ 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" => {
@@ -868,7 +809,7 @@ 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))
    }
 }
@@ -886,7 +827,7 @@ 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 {
@@ -897,7 +838,7 @@ 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 {
@@ -907,7 +848,7 @@ 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),
            },
        }
@@ -1102,10 +1043,7 @@ 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
-    /// overlay files
-    ///
-    /// Read from the manifest, so this excludes deletion files and manifests.
+    /// The total number of bytes in the table
    pub total_bytes: i64,

    /// The number of rows in the table
@@ -1255,21 +1193,6 @@ 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.0"
+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"
@@ -21,7 +21,7 @@ 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, TableBase
+from .table import AsyncTable, Table
 from .types import BaseTokenizerType
 from ._lancedb import Session
 from .namespace import (
@@ -521,6 +521,5 @@ __all__ = [
    "RemoteDBConnection",
    "Session",
    "Table",
-    "TableBase",
    "__version__",
 ]
@@ -198,9 +198,6 @@ 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: ...
@@ -338,11 +335,6 @@ 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 +355,6 @@ 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: ...
@@ -377,7 +365,6 @@ class Table:
    def take_offsets(self, offsets: list[int]) -> TakeQuery: ...
    def take_row_ids(self, row_ids: list[int]) -> TakeQuery: ...
    async def blob_columns(self) -> list[str]: ...
-    async def add_bases(self, bases: list[Any]) -> None: ...
    async def fetch_blobs(
        self, column: str, row_ids: list[int]
    ) -> pa.LargeBinaryArray: ...
@@ -662,10 +649,9 @@ class LsmWriteSpec:
    def identity(column: str) -> "LsmWriteSpec": ...
    @staticmethod
    def unsharded() -> "LsmWriteSpec": ...
-    def with_maintained_indexes(self, indexes: Optional[List[str]]) -> "LsmWriteSpec":
-        """Set which indexes the MemWAL keeps up to date. None resolves every
-        index on the table at install, failing if one cannot be maintained;
-        a list is verbatim, empty means none."""
+    def with_maintained_indexes(self, indexes: List[str]) -> "LsmWriteSpec":
+        """Return a copy of this spec asking the MemWAL to keep the named
+        indexes up to date as rows are appended."""
        ...
    def with_writer_config_defaults(self, defaults: Dict[str, str]) -> "LsmWriteSpec":
        """Return a copy of this spec recording the given default
@@ -680,19 +666,13 @@ class LsmWriteSpec:
    @property
    def num_buckets(self) -> Optional[int]: ...
    @property
-    def maintained_indexes(self) -> Optional[List[str]]:
-        """Indexes the MemWAL keeps up to date, or None for every supported one."""
-        ...
+    def maintained_indexes(self) -> List[str]: ...
    @property
    def writer_config_defaults(self) -> Dict[str, str]: ...

 class AddColumnsResult:
    version: int

-class RefreshColumnResult:
-    rows_filled: int
-    version: int
-
 class AlterColumnsResult:
    version: int

@@ -524,12 +524,6 @@ 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,
@@ -1192,20 +1186,6 @@ 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:
@@ -1983,23 +1963,6 @@ 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.

@@ -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):
-                # A Windows drive letter parses as a one-character scheme
-                # ("C:\\img.png" -> scheme="c"), so treat it as a local path.
+            elif parsed.scheme == "":
                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)))
@@ -49,7 +49,6 @@ from lancedb._lancedb import (
 )
 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,
@@ -625,18 +624,6 @@ 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,
@@ -1147,14 +1134,6 @@ 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,
@@ -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:
@@ -23,7 +23,7 @@ import pyarrow as pa

 from ..common import DATA
 from ..db import DBConnection, LOOP
-from ..job import AsyncJob, Job
+from ..job import Job

 if TYPE_CHECKING:
    from .._lancedb import JobDescription, JobInfo
@@ -663,16 +663,6 @@ 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,
@@ -50,7 +50,7 @@ from lancedb.index import (
 )
 from lancedb.job import Job
 from lancedb.remote.db import LOOP
-from lancedb.table import IndexConfigType, KNOWN_METRICS, TableBase
+from lancedb.table import IndexConfigType, KNOWN_METRICS
 import pyarrow as pa

 from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
@@ -958,19 +958,8 @@ class RemoteTable(Table):
    def count_rows(self, filter: Optional[str] = None) -> int:
        return LOOP.run(self._table.count_rows(filter))

-    def add_columns(
-        self,
-        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 add_columns(self, transforms: Dict[str, str]) -> AddColumnsResult:
+        return LOOP.run(self._table.add_columns(transforms))

    def alter_columns(
        self, *alterations: Iterable[Dict[str, str]]
@@ -1082,13 +1071,6 @@ class RemoteTable(Table):
    def blob_columns(self) -> list[str]:
        return LOOP.run(self._table.blob_columns())

-    def add_bases(
-        self,
-        bases: Union[str, TableBase, Iterable[Union[str, TableBase]]],
-    ) -> None:
-        """Register additional storage bases for this table."""
-        LOOP.run(self._table.add_bases(bases))
-
    def fetch_blobs(
        self, column: str, row_ids: Union[list[int], pa.Table]
    ) -> pa.LargeBinaryArray:
@@ -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,
-        #          rows_skipped]
-        self._worker_stats: RawArray = RawArray(ctypes.c_int64, 8)
+        #          bytes_loaded, fetch_time_us, transform_time_us]
+        self._worker_stats: RawArray = RawArray(ctypes.c_int64, 7)

        # 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 start_pos > 0:
-                perm = perm.with_skip(start_pos)
-            initial_positions.append(start_pos)
+            if self._resume_offset > 0:
+                perm = perm.with_skip(self._resume_offset)
            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
-        # permutation position of their first row so that skipped rows can be
-        # accounted for in pos_consumed.
+        # Per-split pipeline state.
        fetch_head = [0] * n
-        io_pending = [deque() for _ in range(n)]  # (abs_start, Future[RecordBatch])
-        raw_batches = [deque() for _ in range(n)]  # (abs_start, RecordBatch)
-        tx_pending = [deque() for _ in range(n)]  # Future[list[(abs_pos, row)]]
-        cooked = [deque() for _ in range(n)]  # (abs_pos, row) ready to yield
+        io_pending = [deque() for _ in range(n)]  # Future[RecordBatch]
+        raw_batches = [deque() for _ in range(n)]  # RecordBatch — fetched, awaiting tx
+        tx_pending = [deque() for _ in range(n)]  # Future[list[Any]]
+        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((abs_start, io_pool.submit(_io_call, perm_i, indices)))
+            io_pending[i].append(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():
-                abs_start, fut = io_pending[i].popleft()
-                raw_batches[i].append((abs_start, fut.result()))
+            while io_pending[i] and io_pending[i][0].done():
+                raw_batches[i].append(io_pending[i].popleft().result())

        # ── Stage 2 helpers ───────────────────────────────────────────────────

-        on_error = self._on_transform_error
-
-        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):
+        def _tx_call_guarded(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()
-                tx_pending[i].append(tx_pool.submit(_tx_call_guarded, abs_start, batch))
+                batch = raw_batches[i].popleft()
+                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()
-                    tx_pending[i].append(
-                        tx_pool.submit(_tx_call_guarded, abs_start, batch)
-                    )
+                    batch = raw_batches[i].popleft()
+                    tx_pending[i].append(tx_pool.submit(_tx_call_guarded, 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((abs_start, fut.result()))
+                    raw_batches[i].append(io_pending[i].popleft().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
-                        # row.  Without skips all splits exhaust simultaneously
-                        # (equal split sizes + round-robin); when
-                        # 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:
+                        # Stop when any split is exhausted (all exhaust
+                        # simultaneously: equal split sizes + round-robin).
+                        if any(local_consumed[i] >= split_sizes[i] for i in range(n)):
                            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
-                                    for q in raw_batches
-                                    for _, batch in q
+                                    batch.num_rows 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
@@ -19,7 +19,6 @@ from typing import (
    Iterable,
    List,
    Literal,
-    Mapping,
    Optional,
    Sequence,
    Tuple,
@@ -109,11 +108,6 @@ 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",
@@ -177,7 +171,6 @@ if TYPE_CHECKING:
        CompactionStats,
        Tag,
        AddColumnsResult,
-        RefreshColumnResult,
        AddResult,
        AlterColumnsResult,
        UpdateFieldMetadataResult,
@@ -711,21 +704,6 @@ def _normalize_progress(progress):
    return progress, False


-@dataclass
-class TableBase:
-    """An extra storage prefix registered on a table.
-
-    ``path`` is an object-store URI. ``name`` is an optional alias.
-    ``is_dataset_root`` is true when ``path`` points to a Lance dataset
-    root. When false, ``path`` points directly to the directory containing
-    the referenced files.
-    """
-
-    path: str
-    name: Optional[str] = None
-    is_dataset_root: bool = False
-
-
 class Table(ABC):
    """
    A Table is a collection of Records in a LanceDB Database.
@@ -886,18 +864,12 @@ class Table(ABC):
        """
        raise NotImplementedError

-    def to_polars(self, **kwargs) -> "pl.LazyFrame":
-        """Return the table as a Polars LazyFrame.
-
-        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.
+    def to_polars(self, **kwargs) -> "pl.DataFrame":
+        """Return the table as a polars.DataFrame.

        Returns
        -------
-        polars.LazyFrame
+        polars.DataFrame
        """
        raise NotImplementedError

@@ -1584,18 +1556,6 @@ class Table(ABC):
    def blob_columns(self) -> list[str]:
        """Names of the blob v2 columns declared on this table."""

-    def add_bases(
-        self,
-        bases: Union[str, TableBase, Iterable[Union[str, TableBase]]],
-    ) -> None:
-        """Register additional storage bases for this table.
-
-        A URI string is a non-root base with no alias::
-
-            table.add_bases("s3://bucket/media/")
-        """
-        raise NotImplementedError
-
    @abstractmethod
    def fetch_blobs(
        self, column: str, row_ids: Union[list[int], pa.Table]
@@ -1945,14 +1905,7 @@ class Table(ABC):

    @abstractmethod
    def add_columns(
-        self,
-        transforms: Dict[str, str]
-        | pa.Field
-        | List[pa.Field]
-        | pa.Schema
-        | None = None,
-        *,
-        computed: Dict[str, str] | None = None,
+        self, transforms: Dict[str, str] | pa.Field | List[pa.Field] | pa.Schema
    ):
        """
        Add new columns with defined values.
@@ -1966,95 +1919,11 @@ 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
@@ -2442,12 +2311,6 @@ class LanceTable(Table):
    def blob_columns(self) -> list[str]:
        return LOOP.run(self._table.blob_columns())

-    def add_bases(
-        self,
-        bases: Union[str, TableBase, Iterable[Union[str, TableBase]]],
-    ) -> None:
-        LOOP.run(self._table.add_bases(bases))
-
    def fetch_blobs(
        self, column: str, row_ids: Union[list[int], pa.Table]
    ) -> pa.LargeBinaryArray:
@@ -2706,9 +2569,6 @@ 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
        -------
@@ -2717,12 +2577,8 @@ 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
-        # the compatible PyArrow path, but block predicates because this adapter
-        # 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,
+        return pl.scan_pyarrow_dataset(
+            dataset, allow_pyarrow_filter=False, batch_size=batch_size
        )

    # New unified API overload
@@ -4065,28 +3921,9 @@ class LanceTable(Table):
        return LOOP.run(self._table.index_stats(index_name))

    def add_columns(
-        self,
-        transforms: Dict[str, str]
-        | pa.field
-        | List[pa.field]
-        | pa.Schema
-        | None = None,
-        *,
-        computed: Dict[str, str] | None = None,
+        self, transforms: Dict[str, str] | pa.field | List[pa.field] | pa.Schema
    ) -> AddColumnsResult:
-        return LOOP.run(self._table.add_columns(transforms, computed=computed))
-
-    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)))
+        return LOOP.run(self._table.add_columns(transforms))

    def alter_columns(
        self, *alterations: Iterable[Dict[str, str]]
@@ -4121,28 +3958,6 @@ 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]."""
@@ -4821,13 +4636,6 @@ 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
@@ -4854,73 +4662,12 @@ 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`,
-        except that ``maintained_indexes`` always reports the concrete list
-        resolved when the spec was set — ``None`` never round-trips.
+        The returned spec — including its ``maintained_indexes`` and
+        ``writer_config_defaults`` — mirrors what was passed to
+        `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.
-        """
-        return 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.
-        """
-        return 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.
-        """
-        return 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.

@@ -6001,14 +5748,7 @@ class AsyncTable:
        return await self._inner.update(updates_sql, where)

    async def add_columns(
-        self,
-        transforms: dict[str, str]
-        | pa.field
-        | List[pa.field]
-        | pa.Schema
-        | None = None,
-        *,
-        computed: dict[str, str] | None = None,
+        self, transforms: dict[str, str] | pa.field | List[pa.field] | pa.Schema
    ) -> AddColumnsResult:
        """
        Add new columns with defined values.
@@ -6021,22 +5761,6 @@ 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
        -------
@@ -6050,71 +5774,11 @@ 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:
@@ -6300,18 +5964,6 @@ class AsyncTable:
    async def blob_columns(self) -> list[str]:
        return await self._inner.blob_columns()

-    async def add_bases(
-        self,
-        bases: Union[str, TableBase, Iterable[Union[str, TableBase]]],
-    ) -> None:
-        """Register additional storage bases for this table.
-
-        A URI string is a non-root base with no alias::
-
-            await table.add_bases("s3://bucket/media/")
-        """
-        await self._inner.add_bases(_normalize_bases(bases))
-
    async def fetch_blobs(
        self, column: str, row_ids: Union[list[int], pa.Table]
    ) -> pa.LargeBinaryArray:
@@ -6530,30 +6182,6 @@ class AsyncTable:
        await self._inner.replace_field_metadata(field_name, new_metadata)


-def _normalize_bases(
-    base_inputs: Union[str, TableBase, Iterable[Union[str, TableBase]]],
-) -> list[TableBase]:
-    if isinstance(base_inputs, (str, TableBase)):
-        items: Iterable[Union[str, TableBase]] = [base_inputs]
-    elif isinstance(base_inputs, Mapping):
-        raise TypeError(
-            "Expected a URI string, TableBase, or an iterable of those values"
-        )
-    else:
-        items = base_inputs
-    normalized_bases: list[TableBase] = []
-    for base in items:
-        if isinstance(base, str):
-            normalized_bases.append(TableBase(path=base))
-        elif isinstance(base, TableBase):
-            normalized_bases.append(base)
-        else:
-            raise TypeError(
-                f"Expected a URI string or TableBase, got {type(base).__name__}"
-            )
-    return normalized_bases
-
-
@dataclass
 class IndexStatistics:
    """
@@ -6605,9 +6233,7 @@ class TableStatistics:
    Attributes
    ----------
    total_bytes: int
-        The total size, in bytes, of the table's data files, index files, and
-        overlay files. Read from the manifest, so this excludes deletion files
-        and manifests.
+        The total number of bytes in the table.
    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())
@@ -1,72 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-import pyarrow as pa
-import pytest
-
-import lancedb
-
-
-def test_add_bases_accepts_named_and_dataset_root(tmp_path):
-    media = tmp_path / "media"
-    parent = tmp_path / "parent"
-    media.mkdir()
-    parent.mkdir()
-    db = lancedb.connect(tmp_path / "db")
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = db.create_table("photos", schema=schema)
-    table.add_bases(
-        [
-            lancedb.TableBase(path=media.as_uri(), name="media", is_dataset_root=False),
-            lancedb.TableBase(
-                path=parent.as_uri(), name="parent", is_dataset_root=True
-            ),
-        ]
-    )
-
-
-def test_add_bases_accepts_two_unnamed_paths(tmp_path):
-    media = tmp_path / "media"
-    other = tmp_path / "other"
-    media.mkdir()
-    other.mkdir()
-    db = lancedb.connect(tmp_path / "db")
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = db.create_table("photos", schema=schema)
-    table.add_bases([media.as_uri(), other.as_uri()])
-
-
-def test_add_bases_rejects_dict_input(tmp_path):
-    db = lancedb.connect(tmp_path / "db")
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = db.create_table("photos", schema=schema)
-    with pytest.raises(TypeError, match="TableBase"):
-        table.add_bases({"path": "s3://bucket/media/"})
-
-
-@pytest.mark.asyncio
-async def test_async_add_bases_accepts_file_uri(tmp_path):
-    media = tmp_path / "media"
-    media.mkdir()
-    db = await lancedb.connect_async(tmp_path / "db")
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = await db.create_table("photos", schema=schema)
-    await table.add_bases(media.as_uri())
-
-
-def test_memory_add_bases_accepts_file_uri(tmp_path):
-    media = tmp_path / "media"
-    media.mkdir()
-    db = lancedb.connect("memory:///")
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = db.create_table("photos", schema=schema)
-    table.add_bases(media.as_uri())
-
-
-def test_namespace_add_bases_accepts_file_uri(tmp_path):
-    media = tmp_path / "media"
-    media.mkdir()
-    db = lancedb.connect_namespace("dir", {"root": str(tmp_path / "ns")})
-    schema = pa.schema([pa.field("id", pa.int64())])
-    table = db.create_table("photos", schema=schema)
-    table.add_bases(media.as_uri())
@@ -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)

@@ -68,23 +62,17 @@ 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):
+def test_sync_repr_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")
+        raise AssertionError("repr should not use the Python 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})"

@@ -755,7 +743,8 @@ 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 +760,7 @@ def test_drop_table_async(tmp_db: lancedb.DBConnection):

    assert tmp_db.table_names() == ["test"]

-    job = tmp_db.drop_table_async("test")
-    assert job.id is None
-    assert job.status() == "finished"
-    job.wait()
+    tmp_db.drop_table("test")
    assert tmp_db.table_names() == []

    tmp_db.create_table("test", data=data)
@@ -783,17 +769,6 @@ 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(
-            api_key="$var:test_api_key", base_url="https://api.example.com"
+        function=registry.get("variable-parsing-test").create(
+            api_key="$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(), 1536)),
-        ]
+        [pa.field("text", pa.string()), pa.field("vector", pa.list_(pa.float32(), 10))]
    )
    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
@@ -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
@@ -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}"
-    )
@@ -372,31 +372,6 @@ 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 is None
-    assert s.with_maintained_indexes([]).maintained_indexes == []
+    assert s.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
-    # maintained set to be inferred picks up the index on the table, so the
-    # spec reads back naming it rather than as "infer".
+    # Identity round-trips (column recovered from the schema).
    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
-    # the inferred default.
-    table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
+    # Unsharded round-trips (no routing column).
+    table.set_lsm_write_spec(LsmWriteSpec.unsharded())
    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()

@@ -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"
@@ -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)
@@ -570,15 +570,6 @@ def test_query_builder(table):
    assert all(np.array(rs[0]["vector"]) == [1, 2])


-def test_query_multiple_vectors(table):
-    results = table.search([np.array([1, 2]), np.array([4, 5])]).limit(1).to_list()
-
-    assert len(results) == 2
-    results_by_query = {result["query_index"]: result for result in results}
-    assert results_by_query[0]["id"] == 1
-    assert results_by_query[1]["id"] == 2
-
-
 def test_with_row_id(table: lancedb.table.Table):
    rs = table.search().with_row_id(True).to_arrow()
    assert "_rowid" in rs.column_names
@@ -35,12 +35,6 @@ def make_mock_http_handler(handler):
    return MockLanceDBHandler


-@pytest.mark.parametrize("db_name", ["a" * 64, "invalid..database"])
-def test_connect_rejects_invalid_cloud_dns_hostname(db_name):
-    with pytest.raises(ValueError, match="DNS labels must contain 1 to 63 bytes"):
-        lancedb.connect(f"db://{db_name}", api_key="fake")
-
-
@contextlib.contextmanager
 def mock_lancedb_connection(handler):
    with http.server.HTTPServer(
@@ -2306,36 +2300,3 @@ def test_remote_connection_jobs_surface():
        assert job.status() == "failed"
        with pytest.raises(JobFailedError, match="worker died"):
            job.wait(timeout=timedelta(seconds=5))
-
-
-def test_remote_add_bases_posts_the_bases_array():
-    captured_body = {}
-
-    def handler(request):
-        if request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(json.dumps(BLOB_DESCRIBE_RESPONSE).encode())
-        elif request.path == "/v1/table/test/bases/":
-            content_len = int(request.headers.get("Content-Length", 0))
-            captured_body.update(json.loads(request.rfile.read(content_len)))
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b'{"version": 2}')
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.open_table("test")
-        table.add_bases(lancedb.TableBase(path="s3://bucket/media/"))
-
-    assert captured_body["bases"] == [
-        {
-            "path": "s3://bucket/media/",
-            "isDatasetRoot": False,
-        }
-    ]
-
@@ -2,13 +2,10 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors


-import ctypes
-import gc
 import os
 import sys
 import threading
 import warnings
-import weakref
 from concurrent.futures import ThreadPoolExecutor
 from datetime import date, datetime, timedelta
 from time import sleep
@@ -102,30 +99,6 @@ def test_basic(mem_db: DBConnection):
    assert table.to_arrow() == expected_data


-def test_search_preserves_nulls_from_sliced_arrow_table(mem_db: DBConnection):
-    data = pa.table(
-        {
-            "id": [0, 1, 2, 3, 4],
-            "score_cn": [None, 22, None, 5, 8],
-            "score_mt": [None, 42, None, 5, 8],
-            "vector": [
-                [20, 19, -1, -1],
-                [41, 38, 22, 42],
-                [10, 10, -1, -1],
-                [5, 5, 5, 5],
-                [8, 8, 8, 8],
-            ],
-        }
-    ).slice(1)
-
-    table = mem_db.create_table("sliced_nullable", data=data)
-    result = table.search([41, 38, 22, 42]).limit(1).to_arrow()
-
-    assert result["id"].to_pylist() == [1]
-    assert result["score_cn"].to_pylist() == [22]
-    assert result["score_mt"].to_pylist() == [42]
-
-
 def test_table_to_pandas_default_matches_arrow(tmp_db: DBConnection):
    pd = pytest.importorskip("pandas")
    data = pa.table({"id": [1, 2], "text": ["one", "two"]})
@@ -462,38 +435,6 @@ def test_add(mem_db: DBConnection):
    _add(table, schema)


-def test_add_releases_arrow_buffers_without_gc(mem_db: DBConnection):
-    """Regression test for https://github.com/lancedb/lancedb/issues/2512."""
-    schema = pa.schema([pa.field("x", pa.int64())])
-    table = mem_db.create_table("test_add_releases_arrow_buffers", schema=schema)
-
-    class BufferOwner:
-        def __init__(self, size: int):
-            self.memory = ctypes.create_string_buffer(size)
-
-    owner_refs = []
-    gc_was_enabled = gc.isenabled()
-    gc.disable()
-    try:
-        for _ in range(3):
-            size = 8 * 1024
-            owner = BufferOwner(size)
-            arrow_buffer = pa.foreign_buffer(
-                ctypes.addressof(owner.memory), size, owner
-            )
-            array = pa.Array.from_buffers(pa.int64(), 1024, [None, arrow_buffer])
-            batch = pa.RecordBatch.from_arrays([array], schema=schema)
-            owner_refs.append(weakref.ref(owner))
-
-            table.add(batch)
-            del batch, array, arrow_buffer, owner
-
-        assert all(owner_ref() is None for owner_ref in owner_refs)
-    finally:
-        if gc_was_enabled:
-            gc.enable()
-
-
 def test_add_write_parallelism(mem_db: DBConnection):
    schema = pa.schema([pa.field("id", pa.int64())])
    table = mem_db.create_table("test", schema=schema)
@@ -929,7 +870,6 @@ def test_polars(mem_db: DBConnection):

    # enter table to polars dataframe
    result = table.to_polars()
-    assert isinstance(result, pl.LazyFrame)
    assert np.allclose(result.collect()["vector"].to_list(), data["vector"])

    # make sure filtering isn't broken
@@ -1846,27 +1786,6 @@ def test_add_with_empty_fixed_size_list_drops_bad_rows(mem_db: DBConnection):
    assert np.allclose(data["embedding"].to_pylist()[0], np.array([0.1] * 16))


-def test_add_nullable_fixed_size_list_with_none(mem_db: DBConnection):
-    """Regression test for issue #2340."""
-    table = mem_db.create_table(
-        "test_nullable_fixed_size_list",
-        schema=pa.schema(
-            [
-                pa.field("id", pa.string()),
-                pa.field("feature", pa.list_(pa.float32(), 256)),
-                pa.field("tags", pa.list_(pa.string())),
-            ]
-        ),
-    )
-
-    table.add([{"id": "1", "feature": None, "tags": ["tag1", "tag2"]}])
-
-    result = table.to_arrow()
-    assert result.to_pylist() == [
-        {"id": "1", "feature": None, "tags": ["tag1", "tag2"]}
-    ]
-
-
 def test_add_nullable_struct_with_none(mem_db: DBConnection):
    """Regression test for issue #2654: a nullable struct column whose
    first batch contains only None values must not crash in
@@ -1906,33 +1825,6 @@ def test_add_nullable_struct_with_none(mem_db: DBConnection):
    assert result.column("data").to_pylist() == [{"x": 1.0}, None]


-def test_read_mostly_null_list_v2_2_page_boundary(tmp_path):
-    # Regression test for #3194. This row/value count crosses a v2.2 structural
-    # encoding page boundary where Lance 3.0.0 sliced repetition/definition
-    # levels by row offset and decoded child arrays at different lengths.
-    num_rows = 64_885
-    num_values = 217
-    list_type = pa.list_(pa.float32())
-    source = pa.table(
-        {
-            "id": np.arange(num_rows, dtype=np.int64),
-            "coords": pa.array(
-                [[1.0, 2.0, 3.0, 4.0]] * num_values + [None] * (num_rows - num_values),
-                type=list_type,
-            ),
-        }
-    )
-    db = lancedb.connect(
-        tmp_path,
-        storage_options={"new_table_data_storage_version": "2.2"},
-    )
-    table = db.create_table("test_sparse_nullable_list", data=source)
-
-    result = table.search().select(["id", "coords"]).limit(num_rows).to_arrow()
-
-    assert result.equals(source)
-
-
 def test_add_with_integer_embeddings_preserves_casting(mem_db: DBConnection):
    class Schema(LanceModel):
        text: str
@@ -2218,45 +2110,6 @@ def test_merge(tmp_db: DBConnection, tmp_path):
    table.merge(other_dataset, left_on="id")


-@pytest.mark.parametrize("storage_version", ["legacy", "stable"])
-def test_search_after_merge(tmp_path, storage_version):
-    pytest.importorskip("lance")
-    pd = pytest.importorskip("pandas")
-
-    db = lancedb.connect(
-        tmp_path,
-        storage_options={"new_table_data_storage_version": storage_version},
-    )
-    rng = np.random.default_rng(42)
-    row_count = 512
-    vectors = rng.standard_normal((row_count, 8)).astype(np.float32)
-    table = db.create_table(
-        "search_after_merge",
-        data=pd.DataFrame(
-            {
-                "id": [str(i) for i in range(row_count)],
-                "vector": list(vectors),
-            }
-        ),
-    )
-    table.create_index("vector", config=IvfPq(num_partitions=1, num_sub_vectors=2))
-
-    links = pd.DataFrame(
-        {
-            "id": [str(i) for i in range(row_count // 2)],
-            "link": [f"https://example.com/{i}" for i in range(row_count // 2)],
-        }
-    )
-    table.merge(links, left_on="id")
-
-    query = table.search(vectors[-1]).refine_factor(50).limit(10)
-    assert "ANN" in query.explain_plan(verbose=True)
-
-    result = query.to_arrow()
-    links_by_id = dict(zip(result["id"].to_pylist(), result["link"].to_pylist()))
-    assert links_by_id[str(row_count - 1)] is None
-
-
 def test_delete(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2343,20 +2196,6 @@ def test_update(mem_db: DBConnection):
    assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))


-def test_update_with_arrow_scalar(mem_db: DBConnection):
-    schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
-    table = mem_db.create_table("my_table", schema=schema)
-    table.add([{"id": 1, "vector": [1.0, 2.0, 3.0, 4.0]}])
-
-    value = table.search().select(["vector"]).limit(1).to_arrow()["vector"][0]
-    assert isinstance(value, pa.FixedSizeListScalar)
-
-    result = table.update(where="id == 1", values={"vector": value})
-
-    assert result.rows_updated == 1
-    assert table.to_arrow()["vector"].to_pylist() == [[1.0, 2.0, 3.0, 4.0]]
-
-
 def test_update_types(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2524,55 +2363,6 @@ def test_merge_insert(mem_db: DBConnection):
        )


-def test_merge_insert_nullable_pandas_into_pydantic_schema(mem_db: DBConnection):
-    # Regression test for https://github.com/lancedb/lancedb/issues/2366
-    pd = pytest.importorskip("pandas")
-
-    class Document(LanceModel):
-        id: int
-        title: str
-        content: str
-
-    table = mem_db.create_table("documents", schema=Document)
-    table.add(
-        pd.DataFrame(
-            {
-                "title": ["Old title", "Unchanged"],
-                "id": [2, 3],
-                "content": ["Old content", "Keep this"],
-            }
-        )
-    )
-
-    # Pandas produces nullable Arrow fields, in an order that differs from the
-    # non-nullable Pydantic schema. This is valid as long as the data has no nulls.
-    new_data = pd.DataFrame(
-        {
-            "title": ["Inserted", "Updated"],
-            "id": [1, 2],
-            "content": ["New row", "New content"],
-        }
-    )
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .execute(new_data)
-    )
-
-    assert result.num_inserted_rows == 1
-    assert result.num_updated_rows == 1
-    expected = pa.Table.from_pylist(
-        [
-            {"id": 1, "title": "Inserted", "content": "New row"},
-            {"id": 2, "title": "Updated", "content": "New content"},
-            {"id": 3, "title": "Unchanged", "content": "Keep this"},
-        ],
-        schema=Document.to_arrow_schema(),
-    )
-    assert table.to_arrow().sort_by("id") == expected
-
-
 def test_merge_insert_by_source_delete_expr(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2673,36 +2463,6 @@ def test_merge_insert_subschema(mem_db: DBConnection, data_format):
    assert table.to_arrow().sort_by("id") == expected


-def test_repeated_partial_merge_insert_with_scalar_index(mem_db: DBConnection):
-    def make_batch(start: int) -> pa.Table:
-        return pa.table(
-            {
-                "id": [f"id-{i:04}" for i in range(start, start + 100)],
-                "category": ["A"] * 100,
-                "value_a": [float(i) for i in range(start, start + 100)],
-                "value_b": [float(i) / 10 for i in range(100)],
-            }
-        )
-
-    table = mem_db.create_table("my_table", data=make_batch(0))
-    table.add(make_batch(100))
-    table.add(make_batch(200))
-    table.create_index("id", config=BTree())
-
-    ids = [f"id-{i:04}" for i in range(100, 200)]
-    for value in (999.0, 888.0):
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .execute(pa.table({"id": ids, "value_a": [value] * 100}))
-        )
-        assert result.num_updated_rows == 100
-
-    actual = table.to_arrow().sort_by("id")
-    assert actual.num_rows == 300
-    assert actual["value_a"].to_pylist()[100:200] == [888.0] * 100
-
-
@pytest.mark.asyncio
 async def test_merge_insert_async(mem_db_async: AsyncConnection):
    data = pa.table({"a": [1, 2, 3], "b": ["a", "b", "c"]})
@@ -2799,40 +2559,15 @@ def test_create_with_embedding_function(mem_db: DBConnection):
    assert actual == expected


-def test_create_f16_table_from_arrow_data(mem_db: DBConnection):
-    dimension = 32
-    num_rows = 512
-    values = pa.array(
-        np.random.default_rng(42)
-        .standard_normal(num_rows * dimension)
-        .astype(np.float16)
-    )
-    df = pa.table(
-        {
-            "text": [f"s-{i}" for i in range(num_rows)],
-            "vector": pa.FixedSizeListArray.from_arrays(values, dimension),
-        }
-    )
-    table = mem_db.create_table("f16_tbl", data=df)
-    assert table.schema.field("vector").type == pa.list_(pa.float16(), dimension)
-    table.create_index(num_partitions=2, num_sub_vectors=2)
-
-    query = df["vector"][2].as_py()
-    expected = table.search(query).limit(2).to_arrow()
-
-    assert "s-2" in expected["text"].to_pylist()
-
-
 def test_create_f16_table(mem_db: DBConnection):
    class MyTable(LanceModel):
        text: str
        vector: Vector(32, value_type=pa.float16())

-    rng = np.random.default_rng(42)
    df = pa.table(
        {
            "text": [f"s-{i}" for i in range(512)],
-            "vector": [rng.standard_normal(32).astype(np.float16) for _ in range(512)],
+            "vector": [np.random.randn(32).astype(np.float16) for _ in range(512)],
        }
    )
    table = mem_db.create_table(
@@ -3713,8 +3448,7 @@ def test_stats(mem_db: DBConnection):
    stats = table.stats()
    print(f"{stats=}")
    assert stats == {
-        # Full on-disk size of the data file, footer and metadata included.
-        "total_bytes": 633,
+        "total_bytes": 60,
        "num_rows": 2,
        "num_indices": 0,
        "fragment_stats": {
@@ -3732,13 +3466,6 @@ def test_stats(mem_db: DBConnection):
        },
    }

-    # Index files count toward total_bytes too (only deletion files and
-    # manifests are excluded).
-    table.create_index("id", config=BTree())
-    stats_with_index = table.stats()
-    assert stats_with_index["num_indices"] == 1
-    assert stats_with_index["total_bytes"] > stats["total_bytes"]
-

 def test_create_table_empty_list_with_schema(mem_db: DBConnection):
    """Test creating table with empty list data and schema
@@ -3762,8 +3489,8 @@ def test_create_table_empty_list_no_schema_error(mem_db: DBConnection):
        mem_db.create_table("test_empty_no_schema", data=[])


-def test_create_table_without_data_with_vector_schema(tmp_path):
-    """Test exact scenario from issue #1968.
+def test_add_table_with_empty_embeddings(tmp_path):
+    """Test exact scenario from issue #1968

    Regression test for issue #1968:
    https://github.com/lancedb/lancedb/issues/1968
@@ -3775,9 +3502,6 @@ def test_create_table_without_data_with_vector_schema(tmp_path):
        embedding: Vector(16)

    table = db.create_table("test", schema=MySchema)
-    assert table.count_rows() == 0
-    assert table.schema == MySchema.to_arrow_schema()
-
    table.add(
        [{"text": "bar", "embedding": [0.1] * 16}],
        on_bad_vectors="drop",
@@ -3854,65 +3578,3 @@ async def test_async_search_runs_embedding_on_dedicated_executor(
    assert all(name.startswith("lancedb-embedding") for name in captured_threads), (
        f"embedding ran off the dedicated executor: {captured_threads}"
    )
-
-
-def test_computed_column_declare_and_refresh(tmp_path):
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("computed", [{"x": 1}, {"x": 2}])
-
-    table.add_columns(computed={"doubled": "x * 2"})
-    assert table.to_arrow()["doubled"].to_pylist() == [None, None]
-
-    result = table.refresh_column("doubled")
-    assert result.rows_filled == 2
-    assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4]
-
-    table.add([{"x": 5}])
-    assert table.refresh_column("doubled").rows_filled == 1
-    assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4, 10]
-
-
-def test_computed_column_rejects_transforms_and_computed_together(tmp_path):
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("computed_mixed", [{"x": 1}])
-    with pytest.raises(ValueError):
-        table.add_columns({"a": "x + 1"}, computed={"b": "x * 2"})
-
-
-@pytest.mark.asyncio
-async def test_computed_column_async(tmp_path):
-    db = await lancedb.connect_async(tmp_path)
-    table = await db.create_table("computed_async", [{"x": 3}])
-
-    await table.add_columns(computed={"tripled": "x * 3"})
-    await table.refresh_column("tripled")
-
-    assert (await table.to_arrow())["tripled"].to_pylist() == [9]
-
-
-def test_refresh_column_async_returns_job(tmp_path):
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("computed_job", [{"x": 1}, {"x": 2}])
-    table.add_columns(computed={"doubled": "x * 2"})
-
-    job = table.refresh_column_async("doubled")
-    assert job.id is None  # in-process jobs have no server id
-    job.wait()
-    assert job.status() == "finished"
-    assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4]
-
-    # Bad input raises at the call, not through the job.
-    with pytest.raises(Exception, match="not a computed column"):
-        table.refresh_column_async("x")
-
-
-@pytest.mark.asyncio
-async def test_refresh_column_async_job_async_table(tmp_path):
-    db = await lancedb.connect_async(tmp_path)
-    table = await db.create_table("computed_job_async", [{"x": 3}])
-    await table.add_columns(computed={"tripled": "x * 3"})
-
-    job = await table.refresh_column_async("tripled")
-    await job.wait()
-    assert await job.status() == "finished"
-    assert (await table.to_arrow())["tripled"].to_pylist() == [9]
@@ -75,22 +75,6 @@ class TestVoyageAIModelRegistration:
        with pytest.raises(ValueError, match="not supported"):
            func.ndims()

-    def test_voyage3_source_embeddings_use_text_api(self, mock_voyageai_client):
-        """Regression test for text table data being sent to the multimodal API."""
-        mock_voyageai_client.tokenize.return_value = [["hello", "world"]]
-        mock_voyageai_client.embed.return_value.embeddings = [[0.1] * 1024]
-
-        registry = get_registry()
-        func = registry.get("voyageai").create(name="voyage-3")
-
-        embeddings = func.compute_source_embeddings("hello world")
-
-        assert embeddings == [[0.1] * 1024]
-        mock_voyageai_client.embed.assert_called_once_with(
-            texts=["hello world"], model="voyage-3", input_type="document"
-        )
-        mock_voyageai_client.multimodal_embed.assert_not_called()
-
    @pytest.mark.parametrize(
        "model_name",
        [
@@ -1,15 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-from typing import assert_type
-
-import lancedb
-from lancedb import AsyncConnection, DBConnection
-
-
-def check_connect_type() -> None:
-    assert_type(lancedb.connect("memory://"), DBConnection)
-
-
-async def check_connect_async_type() -> None:
-    assert_type(await lancedb.connect_async("memory://"), AsyncConnection)
@@ -346,23 +346,6 @@ impl Connection {
        })
    }

-    #[pyo3(signature = (name, namespace_path=None))]
-    pub fn drop_table_async(
-        self_: PyRef<'_, Self>,
-        name: String,
-        namespace_path: Option<Vec<String>>,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        let ns_path = namespace_path.unwrap_or_default();
-        future_into_py(self_.py(), async move {
-            inner
-                .drop_table_async(name, &ns_path)
-                .await
-                .infer_error()
-                .map(crate::job::Job::new)
-        })
-    }
-
    #[pyo3(signature = (namespace_path=None,))]
    pub fn drop_all_tables(
        self_: PyRef<'_, Self>,
@@ -289,7 +289,7 @@ struct IvfHnswFlatParams {
    target_partition_size: Option<u32>,
 }

-#[pyclass(module = "lancedb._lancedb", get_all)]
+#[pyclass(get_all)]
 /// A description of an index currently configured on a column
 pub struct IndexConfig {
    /// The type of the index
@@ -16,8 +16,7 @@ use query::{FTSQuery, HybridQuery, Query, VectorQuery};
 use session::Session;
 use table::{
    AddColumnsResult, AddResult, AlterColumnsResult, DeleteResult, DropColumnsResult, FtsToken,
-    LsmWriteSpec, MergeResult, PyBlobFile, RefreshColumnResult, Table, UpdateFieldMetadataResult,
-    UpdateResult,
+    LsmWriteSpec, MergeResult, PyBlobFile, Table, UpdateFieldMetadataResult, UpdateResult,
 };

 pub mod arrow;
@@ -58,7 +57,6 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<VectorQuery>()?;
    m.add_class::<RecordBatchStream>()?;
    m.add_class::<AddColumnsResult>()?;
-    m.add_class::<RefreshColumnResult>()?;
    m.add_class::<AlterColumnsResult>()?;
    m.add_class::<UpdateFieldMetadataResult>()?;
    m.add_class::<AddResult>()?;
@@ -11,7 +11,7 @@ use pyo3::{PyResult, pyclass, pymethods};
 /// Sessions allow you to configure cache sizes for index and metadata caches,
 /// which can significantly impact memory use and performance. They can
 /// also be re-used across multiple connections to share the same cache state.
-#[pyclass(module = "lancedb._lancedb", from_py_object)]
+#[pyclass(from_py_object)]
 #[derive(Clone)]
 pub struct Session {
    pub(crate) inner: Arc<LanceSession>,
@@ -22,86 +22,17 @@ use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::table::{
    AddDataMode, ColumnAlteration, Duration, FieldMetadataUpdate, FtsToken as LanceDbFtsToken,
    NewColumnTransform, OptimizeAction, OptimizeOptions, Ref, Table as LanceDbTable,
-    TableBase as LanceTableBase,
 };
 use lancedb::tokenize as lancedb_tokenize;
 use pyo3::{
    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
    exceptions::{PyRuntimeError, PyValueError},
    pyclass, pyfunction, pymethods,
-    types::{IntoPyDict, PyAnyMethods, PyBytes, PyDict, PyDictMethods, PyList, PyListMethods},
+    types::{IntoPyDict, PyAnyMethods, PyBytes, PyDict, PyDictMethods},
 };

 mod scannable;

-/// Convert `LsmStats` to a Python dict, preserving the per-bucket list.
-///
-/// Deliberately not flattened to a table-level summary: a table is N
-/// buckets on one node, and the per-bucket detail is the reason the
-/// endpoint exists — flattening hides the single hot bucket someone opened
-/// it to find.
-fn lsm_stats_to_py(py: Python<'_>, stats: &lancedb::table::LsmStats) -> PyResult<Py<PyDict>> {
-    let out = PyDict::new(py);
-    let buckets = PyList::empty(py);
-    for b in &stats.buckets {
-        let e = PyDict::new(py);
-        e.set_item("shard_id", &b.shard_id)?;
-        e.set_item("status", &b.status)?;
-        e.set_item("writer_epoch", b.writer_epoch)?;
-        e.set_item("manifest_version", b.manifest_version)?;
-        e.set_item("current_generation", b.current_generation)?;
-        e.set_item(
-            "replay_after_wal_entry_position",
-            b.replay_after_wal_entry_position,
-        )?;
-        e.set_item(
-            "wal_entry_position_last_seen",
-            b.wal_entry_position_last_seen,
-        )?;
-
-        let generations = PyList::empty(py);
-        for g in &b.generations {
-            let ge = PyDict::new(py);
-            ge.set_item("generation", g.generation)?;
-            ge.set_item("bytes", g.bytes)?;
-            ge.set_item("rows", g.rows)?;
-            generations.append(ge)?;
-        }
-        e.set_item("generations", generations)?;
-        e.set_item("compacting", b.compacting)?;
-
-        e.set_item(
-            "memtables",
-            b.memtables
-                .as_ref()
-                .map(|ms| {
-                    let l = PyList::empty(py);
-                    for m in ms {
-                        let d = PyDict::new(py);
-                        d.set_item("generation", m.generation)?;
-                        d.set_item("rows", m.rows)?;
-                        d.set_item("bytes", m.bytes)?;
-                        d.set_item("batches", m.batches)?;
-                        d.set_item("indexes", m.indexes.clone())?;
-                        l.append(d)?;
-                    }
-                    PyResult::Ok(l.unbind())
-                })
-                .transpose()?,
-        )?;
-        buckets.append(e)?;
-    }
-    out.set_item("buckets", buckets)?;
-    Ok(out.unbind())
-}
-
-#[derive(FromPyObject)]
-pub(crate) struct PyTableBase {
-    path: String,
-    name: Option<String>,
-    is_dataset_root: bool,
-}
-
 #[derive(FromPyObject)]
 enum PredicateArg {
    Expr(PyExpr),
@@ -254,22 +185,12 @@ impl From<lancedb::table::MergeResult> for MergeResult {
    }
 }

-/// Render for `__repr__`, so the default reads as Python's `None` rather than
-/// Rust's `Some([..])`.
-fn fmt_maintained(maintained: &Option<Vec<String>>) -> String {
-    match maintained {
-        Some(names) => format!("{:?}", names),
-        None => "None".to_string(),
-    }
-}
-
 /// Specification selecting Lance's MemWAL LSM-style write path for
 /// `merge_insert`.
 ///
 /// Constructed via the `bucket(...)`, `identity(...)`, or `unsharded()`
 /// classmethods, then optionally chain `with_maintained_indexes(...)` and
-/// `with_writer_config_defaults(...)`. A fresh spec maintains every index the
-/// MemWAL supports, resolved on install.
+/// `with_writer_config_defaults(...)`.
 #[pyclass(from_py_object)]
 #[derive(Clone, Debug)]
 pub struct LsmWriteSpec {
@@ -309,11 +230,11 @@ impl LsmWriteSpec {
        }
    }

-    /// Set which indexes the MemWAL maintains. `None` (the default)
-    /// resolves every supported index on install; a list is verbatim,
-    /// and an empty list maintains nothing.
-    #[pyo3(signature = (indexes))]
-    pub fn with_maintained_indexes(&self, indexes: Option<Vec<String>>) -> Self {
+    /// Replace the list of indexes the MemWAL should keep up to date as
+    /// rows are appended. Each name must reference an index that
+    /// already exists on the table at the time `set_lsm_write_spec`
+    /// is called.
+    pub fn with_maintained_indexes(&self, indexes: Vec<String>) -> Self {
        Self {
            inner: self.inner.clone().with_maintained_indexes(indexes),
        }
@@ -335,29 +256,23 @@ impl LsmWriteSpec {
                maintained_indexes,
                writer_config_defaults,
            } => format!(
-                "LsmWriteSpec.bucket(column={:?}, num_buckets={}, maintained_indexes={}, writer_config_defaults={:?})",
-                column,
-                num_buckets,
-                fmt_maintained(maintained_indexes),
-                writer_config_defaults,
+                "LsmWriteSpec.bucket(column={:?}, num_buckets={}, maintained_indexes={:?}, writer_config_defaults={:?})",
+                column, num_buckets, maintained_indexes, writer_config_defaults,
            ),
            lancedb::table::LsmWriteSpec::Identity {
                column,
                maintained_indexes,
                writer_config_defaults,
            } => format!(
-                "LsmWriteSpec.identity(column={:?}, maintained_indexes={}, writer_config_defaults={:?})",
-                column,
-                fmt_maintained(maintained_indexes),
-                writer_config_defaults,
+                "LsmWriteSpec.identity(column={:?}, maintained_indexes={:?}, writer_config_defaults={:?})",
+                column, maintained_indexes, writer_config_defaults,
            ),
            lancedb::table::LsmWriteSpec::Unsharded {
                maintained_indexes,
                writer_config_defaults,
            } => format!(
-                "LsmWriteSpec.unsharded(maintained_indexes={}, writer_config_defaults={:?})",
-                fmt_maintained(maintained_indexes),
-                writer_config_defaults,
+                "LsmWriteSpec.unsharded(maintained_indexes={:?}, writer_config_defaults={:?})",
+                maintained_indexes, writer_config_defaults,
            ),
        }
    }
@@ -392,10 +307,10 @@ impl LsmWriteSpec {
        }
    }

-    /// Indexes the MemWAL keeps up to date, or `None` for every supported one.
+    /// Names of indexes the MemWAL should keep up to date during writes.
    #[getter]
-    pub fn maintained_indexes(&self) -> Option<Vec<String>> {
-        self.inner.maintained_indexes().map(<[String]>::to_vec)
+    pub fn maintained_indexes(&self) -> Vec<String> {
+        self.inner.maintained_indexes().to_vec()
    }

    /// Default `ShardWriter` configuration recorded by this spec.
@@ -423,32 +338,6 @@ pub struct AddColumnsResult {
    pub version: u64,
 }

-#[pyclass(get_all, from_py_object)]
-#[derive(Clone, Debug)]
-pub struct RefreshColumnResult {
-    pub rows_filled: u64,
-    pub version: u64,
-}
-
-#[pymethods]
-impl RefreshColumnResult {
-    pub fn __repr__(&self) -> String {
-        format!(
-            "RefreshColumnResult(rows_filled={}, version={})",
-            self.rows_filled, self.version
-        )
-    }
-}
-
-impl From<lancedb::table::RefreshColumnResult> for RefreshColumnResult {
-    fn from(result: lancedb::table::RefreshColumnResult) -> Self {
-        Self {
-            rows_filled: result.rows_filled,
-            version: result.version,
-        }
-    }
-}
-
 #[pymethods]
 impl AddColumnsResult {
    pub fn __repr__(&self) -> String {
@@ -613,7 +502,7 @@ impl PyBlobFile {
    }
 }

-#[pyclass(module = "lancedb._lancedb", get_all, from_py_object)]
+#[pyclass(get_all, from_py_object)]
 #[derive(Clone, Debug)]
 pub struct FtsToken {
    pub text: String,
@@ -1246,25 +1135,6 @@ impl Table {
        })
    }

-    #[pyo3(signature = (bases))]
-    pub fn add_bases(
-        self_: PyRef<'_, Self>,
-        bases: Vec<PyTableBase>,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        let bases: Vec<LanceTableBase> = bases
-            .into_iter()
-            .map(|base| LanceTableBase {
-                path: base.path,
-                name: base.name,
-                is_dataset_root: base.is_dataset_root,
-            })
-            .collect();
-        future_into_py(self_.py(), async move {
-            inner.add_bases(bases).await.infer_error()
-        })
-    }
-
    /// Read blob bytes for `row_ids` from blob v2 column `column`.
    #[pyo3(signature = (column, row_ids))]
    pub fn fetch_blobs(
@@ -1469,51 +1339,6 @@ impl Table {
        })
    }

-    /// Converge the table's LSM write path into its base table.
-    ///
-    /// Best-effort: with writes flowing, new rows may land after the last
-    /// pass. Errors if the table stops making progress.
-    pub fn checkpoint_lsm(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            inner.checkpoint_lsm().await.infer_error()
-        })
-    }
-
-    /// Seal every bucket's active memtable into L0.
-    pub fn flush_lsm(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(
-            self_.py(),
-            async move { inner.flush_lsm().await.infer_error() },
-        )
-    }
-
-    /// Trigger a background L0 → base pass per bucket. Returns once the
-    /// passes are dispatched, not once they finish — watch `get_lsm_stats`.
-    pub fn compact_lsm(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            inner.compact_lsm().await.infer_error()
-        })
-    }
-
-    /// Live LSM state, or `None` when the LSM write path is not enabled.
-    #[pyo3(signature = (include_generation_rows=false))]
-    pub fn get_lsm_stats(
-        self_: PyRef<'_, Self>,
-        include_generation_rows: bool,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            let stats = inner
-                .get_lsm_stats(include_generation_rows)
-                .await
-                .infer_error()?;
-            Python::attach(|py| stats.map(|s| lsm_stats_to_py(py, &s)).transpose())
-        })
-    }
-
    pub fn close_lsm_writers(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
@@ -1563,40 +1388,6 @@ impl Table {
        })
    }

-    pub fn add_computed_columns(
-        self_: PyRef<'_, Self>,
-        columns: Vec<(String, String)>,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            let mut builder = inner.add_columns();
-            for (name, expression) in columns {
-                builder = builder.computed(name, expression);
-            }
-            let result = builder.execute().await.infer_error()?;
-            Ok(AddColumnsResult::from(result))
-        })
-    }
-
-    pub fn refresh_column(self_: PyRef<'_, Self>, column: String) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            let result = inner.refresh_column(column).await.infer_error()?;
-            Ok(RefreshColumnResult::from(result))
-        })
-    }
-
-    pub fn refresh_column_async(
-        self_: PyRef<'_, Self>,
-        column: String,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move {
-            let job = inner.refresh_column_async(column).await.infer_error()?;
-            Ok(crate::job::Job::new(job))
-        })
-    }
-
    pub fn add_columns_with_schema(
        self_: PyRef<'_, Self>,
        schema: PyArrowType<Schema>,
@@ -1998,7 +1998,7 @@ requires-dist = [
    { name = "pillow", marker = "extra == 'clip'", specifier = ">=12.1.1" },
    { name = "pillow", marker = "extra == 'embeddings'", specifier = ">=12.1.1" },
    { name = "pillow", marker = "extra == 'siglip'", specifier = ">=12.1.1" },
-    { name = "polars", marker = "extra == 'tests'", specifier = ">=0.19,<=1.32.3" },
+    { name = "polars", marker = "extra == 'tests'", specifier = ">=0.19,<=1.3.0" },
    { name = "pre-commit", marker = "extra == 'dev'", specifier = ">=3.5.0" },
    { name = "pyarrow", specifier = ">=16" },
    { name = "pyarrow", marker = "extra == 'tests'", specifier = "<25" },
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.38.0-beta.0"
+version = "0.37.1-beta.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -49,6 +49,8 @@ lance-namespace = { workspace = true }
 lance-namespace-impls = { workspace = true }
 metrics = { workspace = true, optional = true }
 metrics-util = { workspace = true, optional = true }
+# Pin the transitive GooseFS SDK until the 0.1.6 compile break is fixed upstream.
+goosefs-sdk = { version = "=0.1.5", optional = true }
 moka = { workspace = true }
 pin-project = { workspace = true }
 tokio = { version = "1.23", features = ["rt-multi-thread", "sync"] }
@@ -73,8 +75,6 @@ reqwest = { version = "0.12.0", default-features = false, features = [
    "http2",
    "json",
    "macos-system-configuration",
-    # Avoid linking OpenSSL into Python wheels, which breaks on FIPS hosts.
-    "rustls-tls-native-roots",
    "stream",
 ], optional = true }
 http = { version = "1", optional = true } # Matching what is in reqwest
@@ -98,8 +98,7 @@ anyhow = "1"
 lance-testing = { workspace = true }
 tempfile = "3.5.0"
 random_word = { version = "0.4.3", features = ["en"] }
-roaring = "0.11.4"
-tokio = { version = "1.23", features = ["io-util", "macros", "net", "rt-multi-thread", "sync", "test-util"] }
+tokio = { version = "1.23", features = ["io-util", "macros", "net", "rt-multi-thread", "sync"] }
 uuid = { version = "1.7.0", features = ["v4"] }
 walkdir = "2"
 aws-sdk-dynamodb = { version = "1.55.0" }
@@ -134,6 +133,7 @@ azure = [
 ]
 cos = ["lance/tencent", "lance-io/tencent"]
 goosefs = [
+    "dep:goosefs-sdk",
    "lance/goosefs",
    "lance-io/goosefs",
    "lance-namespace-impls/dir-goosefs",
@@ -188,9 +188,6 @@ required-features = ["bedrock"]
 [[example]]
 name = "bench_streaming_dataloader"

-[[example]]
-name = "bench_open_missing_table"
-
 [[example]]
 name = "simple"

@@ -1,150 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-// Release benchmark for opening a missing table as sibling-table cardinality grows.
-//
-// The fixture uses real `.lance` directories and marker files. Fixture creation is
-// outside the timed section. Defaults intentionally cover 1k, 10k, and 100k siblings
-// with 10 warmups and 100 distinct missing-table opens per scale:
-//
-// ```text
-// cargo run --release -p lancedb --example bench_open_missing_table
-// ```
-//
-// `BENCH_SIBLINGS`, `BENCH_WARMUPS`, and `BENCH_TRIALS` override those defaults.
-// Reduced settings are useful only as a smoke test. Performance comparisons require
-// the same machine, filesystem, fixture sizes, settings, lockfile, and alternating
-// baseline/candidate execution order.
-
-use std::time::{Duration, Instant};
-
-use anyhow::{Context, Result, bail};
-use lancedb::connection::Connection;
-use lancedb::{Error, connect};
-use object_store::ObjectStoreExt as _;
-use object_store::path::Path;
-
-const MAX_SIBLINGS: usize = 1_000_000;
-const MAX_WARMUPS: usize = 10_000;
-const MAX_TRIALS: usize = 100_000;
-
-fn env_usize(key: &str, default: usize, max: usize) -> Result<usize> {
-    let value = match std::env::var(key) {
-        Ok(value) => value
-            .parse()
-            .with_context(|| format!("invalid {key} value: {value}"))?,
-        Err(std::env::VarError::NotPresent) => default,
-        Err(error) => return Err(error).with_context(|| format!("reading {key}")),
-    };
-    if value == 0 || value > max {
-        bail!("{key} must be between 1 and {max}");
-    }
-    Ok(value)
-}
-
-fn sibling_counts() -> Result<Vec<usize>> {
-    let raw = std::env::var("BENCH_SIBLINGS").unwrap_or_else(|_| "1000,10000,100000".into());
-    let mut counts = raw
-        .split(',')
-        .map(|value| {
-            value
-                .trim()
-                .parse::<usize>()
-                .with_context(|| format!("invalid BENCH_SIBLINGS value: {value}"))
-        })
-        .collect::<Result<Vec<_>>>()?;
-    counts.sort_unstable();
-    counts.dedup();
-    if counts.is_empty() || counts[0] == 0 || counts[counts.len() - 1] > MAX_SIBLINGS {
-        bail!("BENCH_SIBLINGS values must be between 1 and {MAX_SIBLINGS}");
-    }
-    Ok(counts)
-}
-
-async fn add_siblings(
-    store: &object_store::local::LocalFileSystem,
-    start: usize,
-    end: usize,
-) -> Result<()> {
-    for index in start..end {
-        let marker = Path::from(format!("sibling_{index:06}.lance/_marker"));
-        store
-            .put(&marker, bytes::Bytes::new().into())
-            .await
-            .with_context(|| format!("creating benchmark marker {marker}"))?;
-    }
-    Ok(())
-}
-
-async fn time_missing_open(db: &Connection, name: &str) -> Result<Duration> {
-    let started = Instant::now();
-    let result = db.open_table(name).execute().await;
-    let elapsed = started.elapsed();
-    match result {
-        Err(Error::TableNotFound { .. }) => Ok(elapsed),
-        Err(error) => bail!("expected TableNotFound for {name}, got {error:?}"),
-        Ok(_) => bail!("benchmark missing-table name unexpectedly exists: {name}"),
-    }
-}
-
-fn percentile(sorted: &[Duration], percentile: usize) -> Duration {
-    let rank = (sorted.len() * percentile).div_ceil(100).saturating_sub(1);
-    sorted[rank]
-}
-
-#[tokio::main]
-async fn main() -> Result<()> {
-    let counts = sibling_counts()?;
-    let warmups = env_usize("BENCH_WARMUPS", 10, MAX_WARMUPS)?;
-    let trials = env_usize("BENCH_TRIALS", 100, MAX_TRIALS)?;
-
-    let fixture = tempfile::tempdir().context("creating benchmark fixture")?;
-    let database_path = fixture.path();
-    let fixture_store = object_store::local::LocalFileSystem::new_with_prefix(database_path)
-        .context("creating benchmark object store")?;
-    let db = connect(database_path.to_str().context("non-UTF-8 fixture path")?)
-        .execute()
-        .await?;
-
-    println!(
-        "config: siblings={counts:?} warmups={warmups} trials={trials} profile={} os={} arch={}",
-        if cfg!(debug_assertions) {
-            "debug"
-        } else {
-            "release"
-        },
-        std::env::consts::OS,
-        std::env::consts::ARCH,
-    );
-    println!("lower is better; fixture setup and teardown are excluded");
-    println!("| siblings | samples | p50 | p95 | max |");
-    println!("| ---: | ---: | ---: | ---: | ---: |");
-
-    let mut created = 0;
-    for sibling_count in counts {
-        add_siblings(&fixture_store, created, sibling_count).await?;
-        created = sibling_count;
-
-        for index in 0..warmups {
-            let name = format!("__missing_warmup_{sibling_count}_{index}");
-            let _ = time_missing_open(&db, &name).await?;
-        }
-
-        let mut samples = Vec::with_capacity(trials);
-        for index in 0..trials {
-            let name = format!("__missing_trial_{sibling_count}_{index}");
-            samples.push(time_missing_open(&db, &name).await?);
-        }
-        samples.sort_unstable();
-
-        println!(
-            "| {sibling_count} | {} | {:?} | {:?} | {:?} |",
-            samples.len(),
-            percentile(&samples, 50),
-            percentile(&samples, 95),
-            samples[samples.len() - 1],
-        );
-    }
-
-    Ok(())
-}
@@ -17,7 +17,7 @@ use arrow_array::builder::LargeBinaryBuilder;
 use arrow_schema::{DataType, Field, Schema};
 use lance::dataset::{BlobRangeRequest as LanceBlobRangeRequest, Dataset, WriteParams};
 use lance_arrow::FieldExt;
-use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
+use lance_encoding::version::LanceFileVersion;
 use lance_io::object_store::ObjectStore;
 use object_store::path::Path;

@@ -333,10 +333,7 @@ pub(crate) fn ensure_blob_storage_version(schema: &Schema, params: &mut WritePar
        .data_storage_version
        .unwrap_or(LanceFileVersion::Stable)
        .resolve();
-    if matches!(
-        resolved,
-        ConcreteFileVersion::V1 | ConcreteFileVersion::V2_0 | ConcreteFileVersion::V2_1
-    ) {
+    if resolved < LanceFileVersion::V2_2 {
        params.data_storage_version = Some(LanceFileVersion::V2_2);
    }
 }
@@ -502,7 +499,7 @@ mod tests {
        ensure_blob_storage_version(&blob_schema(), &mut params);
        assert_eq!(
            params.data_storage_version.unwrap().resolve(),
-            ConcreteFileVersion::V2_2
+            LanceFileVersion::V2_2
        );
    }

@@ -515,7 +512,7 @@ mod tests {
        ensure_blob_storage_version(&blob_schema(), &mut params);
        assert_eq!(
            params.data_storage_version.unwrap().resolve(),
-            ConcreteFileVersion::V2_2
+            LanceFileVersion::V2_2
        );
    }

@@ -34,7 +34,7 @@ use crate::remote::{
    db::{OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION},
 };
 use lance::io::ObjectStoreParams;
-pub use lance_file::version::LanceFileVersion;
+pub use lance_encoding::version::LanceFileVersion;
 #[cfg(feature = "remote")]
 use lance_io::object_store::StorageOptions;
 use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
@@ -409,11 +409,6 @@ impl Connection {
    ///
    /// The names will be returned in lexicographical order (ascending)
    ///
-    /// Listing databases discover physical `*.lance` entries without opening every
-    /// dataset. The result is a point-in-time discovery snapshot: an entry may still be
-    /// under creation, may contain only uncommitted storage, or may be concurrently
-    /// dropped before it is opened.
-    ///
    /// The parameters `page_token` and `limit` can be used to paginate the results
    pub fn table_names(&self) -> TableNamesBuilder {
        TableNamesBuilder::new(self.internal.clone())
@@ -461,9 +456,10 @@ impl Connection {
    ///
    /// # Returns
    /// Created [`TableRef`], or [`Error::TableNotFound`] if the table does not exist.
-    /// On listing databases, a committed Lance manifest is authoritative for table
-    /// existence. Uncommitted files or a physical `<name>.lance` directory alone do not
-    /// make a table openable.
+    /// If the table's storage is present but holds no readable dataset (for example a
+    /// `<name>.lance` directory left behind by an interrupted drop and re-create, which
+    /// [`Self::table_names`] still lists) this returns [`Error::TableCorrupted`]
+    /// instead.
    pub fn open_table(&self, name: impl Into<String>) -> OpenTableBuilder {
        OpenTableBuilder::new(
            self.internal.clone(),
@@ -565,21 +561,6 @@ impl Connection {
            .await
    }

-    /// Start dropping a table and return a handle to the cleanup job.
-    ///
-    /// The table may become unavailable before its physical data is removed.
-    /// Call [`crate::job::Job::wait`] to wait for cleanup to finish. Local
-    /// backends may complete the drop before returning the handle.
-    pub async fn drop_table_async(
-        &self,
-        name: impl AsRef<str>,
-        namespace_path: &[String],
-    ) -> Result<crate::job::Job> {
-        self.internal
-            .drop_table_async(name.as_ref(), namespace_path)
-            .await
-    }
-
    /// Drop the database
    ///
    /// This is the same as dropping all of the tables
@@ -202,17 +202,6 @@ mod tests {
        assert_eq!(table.count_rows(None).await.unwrap(), 0);
    }

-    #[tokio::test]
-    async fn create_table_in_named_memory_database() {
-        let db = connect("memory://foo").execute().await.unwrap();
-        let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
-
-        let table = db.create_table("my_table", batch).execute().await.unwrap();
-
-        assert_eq!(table.uri().await.unwrap(), "memory://foo/my_table.lance");
-        assert_eq!(table.count_rows(None).await.unwrap(), 3);
-    }
-
    async fn test_create_table_with_data<T>(data: T)
    where
        T: Scannable + 'static,
@@ -438,9 +427,10 @@ mod tests {
            .await
            .unwrap()
            .data_storage_format
-            .lance_file_format();
+            .lance_file_version()
+            .unwrap();
        // Compare resolved versions since Stable/Next are aliases that resolve at storage time
-        assert_eq!(storage_format, data_storage_version.resolve());
+        assert_eq!(storage_format.resolve(), data_storage_version.resolve());
    }

    #[tokio::test]
@@ -323,18 +323,6 @@ pub trait Database:
    ) -> Result<()>;
    /// Drop a table in the database
    async fn drop_table(&self, name: &str, namespace_path: &[String]) -> Result<()>;
-    /// Start dropping a table and return a handle to the cleanup job.
-    ///
-    /// Backends without asynchronous cleanup complete the drop before
-    /// returning an already-finished job.
-    async fn drop_table_async(
-        &self,
-        name: &str,
-        namespace_path: &[String],
-    ) -> Result<crate::job::Job> {
-        self.drop_table(name, namespace_path).await?;
-        Ok(crate::job::Job::new_done())
-    }
    /// Drop all tables in the database
    async fn drop_all_tables(&self, namespace_path: &[String]) -> Result<()>;
    fn as_any(&self) -> &dyn std::any::Any;
@@ -12,7 +12,7 @@ use lance::dataset::refs::Ref;
 use lance::dataset::{ReadParams, WriteMode, builder::DatasetBuilder};
 use lance::io::{ObjectStore, ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
-use lance_file::version::LanceFileVersion;
+use lance_encoding::version::LanceFileVersion;
 use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
 use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
@@ -1032,7 +1032,6 @@ impl Database for ListingDatabase {
        };

        Ok(ListTablesResponse {
-            context: None,
            tables: f,
            page_token: next_page_token,
        })
@@ -1292,21 +1291,14 @@ impl Database for ListingDatabase {
 mod tests {
    use super::*;
    use crate::Table;
-    use crate::arrow::{SendableRecordBatchStream, SimpleRecordBatchStream};
    use crate::connection::ConnectRequest;
    use crate::data::scannable::Scannable;
    use crate::database::{CreateTableMode, CreateTableRequest};
-    use crate::query::QueryRequest;
-    use crate::table::{AnyQuery, WriteOptions};
+    use crate::table::WriteOptions;
    use arrow_array::{Int32Array, RecordBatch, StringArray};
-    use arrow_schema::{DataType, Field, Schema, SchemaRef};
-    use futures::{TryStreamExt, stream::once};
+    use arrow_schema::{DataType, Field, Schema};
    use std::path::PathBuf;
-    use std::sync::Arc;
-    use std::time::Duration;
    use tempfile::tempdir;
-    use tokio::sync::Barrier;
-    use tokio::time::timeout;

    async fn setup_database() -> (tempfile::TempDir, ListingDatabase) {
        let tempdir = tempdir().unwrap();
@@ -1330,114 +1322,6 @@ mod tests {
        (tempdir, db)
    }

-    struct BarrierScannable {
-        batch: RecordBatch,
-        barrier: Arc<Barrier>,
-    }
-
-    impl Scannable for BarrierScannable {
-        fn schema(&self) -> SchemaRef {
-            self.batch.schema()
-        }
-
-        fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
-            let batch = self.batch.clone();
-            let schema = batch.schema();
-            let barrier = self.barrier.clone();
-            Box::pin(SimpleRecordBatchStream {
-                schema,
-                stream: once(async move {
-                    barrier.wait().await;
-                    Ok(batch)
-                }),
-            })
-        }
-    }
-
-    fn create_request(name: &str, data: Box<dyn Scannable>) -> CreateTableRequest {
-        CreateTableRequest {
-            name: name.to_string(),
-            namespace_path: vec![],
-            data,
-            mode: CreateTableMode::Create,
-            write_options: Default::default(),
-            location: None,
-            namespace_client: None,
-        }
-    }
-
-    #[tokio::test]
-    async fn test_create_ignores_uncommitted_storage_without_manifest() {
-        let (tmp_dir, db) = setup_database().await;
-        let data_dir = tmp_dir.path().join("test.lance/data");
-        std::fs::create_dir_all(&data_dir).unwrap();
-        std::fs::write(data_dir.join("orphan.lance"), b"uncommitted").unwrap();
-
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        let batch =
-            RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1]))]).unwrap();
-
-        let table = db
-            .create_table(create_request("test", Box::new(batch)))
-            .await
-            .unwrap();
-        assert_eq!(table.count_rows(None).await.unwrap(), 1);
-    }
-
-    #[tokio::test]
-    async fn test_concurrent_create_is_arbitrated_by_manifest_commit() {
-        let uri = format!("memory:///concurrent-create-{}", uuid::Uuid::new_v4());
-        let db = crate::connect(&uri).execute().await.unwrap();
-        let store: Arc<dyn object_store::ObjectStore> =
-            Arc::new(object_store::memory::InMemory::new());
-        let table_url = url::Url::parse("memory:///database/test.lance").unwrap();
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        let batch =
-            RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1]))]).unwrap();
-        let barrier = Arc::new(Barrier::new(2));
-
-        #[allow(deprecated)]
-        let request = |batch, barrier| {
-            let mut request = create_request("test", Box::new(BarrierScannable { batch, barrier }));
-            request.write_options = WriteOptions {
-                lance_write_params: Some(lance::dataset::WriteParams {
-                    store_params: Some(ObjectStoreParams {
-                        object_store: Some((store.clone(), table_url.clone())),
-                        ..Default::default()
-                    }),
-                    commit_handler: Some(Arc::new(
-                        lance_table::io::commit::ConditionalPutCommitHandler,
-                    )),
-                    ..Default::default()
-                }),
-            };
-            request
-        };
-
-        let left = db
-            .database()
-            .create_table(request(batch.clone(), barrier.clone()));
-        let right = db.database().create_table(request(batch, barrier));
-        let (left, right) = timeout(Duration::from_secs(30), async { tokio::join!(left, right) })
-            .await
-            .expect("concurrent creates deadlocked");
-
-        let results = [left, right];
-        assert_eq!(
-            results.iter().filter(|result| result.is_ok()).count(),
-            1,
-            "expected one successful create, got {results:?}"
-        );
-        assert_eq!(
-            results
-                .iter()
-                .filter(|result| matches!(result, Err(Error::TableAlreadyExists { .. })))
-                .count(),
-            1,
-            "expected one manifest conflict, got {results:?}"
-        );
-    }
-
    #[tokio::test]
    async fn test_listing_database_root_ops_do_not_create_manifest() {
        let tempdir = tempdir().unwrap();
@@ -1492,156 +1376,6 @@ mod tests {
        assert!(!tempdir.path().join("__manifest").exists());
    }

-    /// Regression test for https://github.com/lancedb/lancedb/issues/1600.
-    ///
-    /// Opening a table used to create a separate object-store client instead of
-    /// reusing the one that successfully connected to the database.  Repeating
-    /// credential discovery made S3 table opens intermittent, especially in AWS
-    /// Lambda, and the failed open was reported as `TableNotFound`.
-    #[tokio::test]
-    async fn test_open_table_reuses_connection_object_store() {
-        let tempdir = tempdir().unwrap();
-        let uri = tempdir.path().to_str().unwrap();
-        let registry = Arc::new(lance_io::object_store::ObjectStoreRegistry::default());
-        let session = Arc::new(lance::session::Session::new(16, 16, registry.clone()));
-
-        let request = ConnectRequest {
-            uri: uri.to_string(),
-            #[cfg(feature = "remote")]
-            client_config: Default::default(),
-            options: Default::default(),
-            namespace_client_properties: Default::default(),
-            manifest_enabled: false,
-            read_consistency_interval: None,
-            session: Some(session),
-        };
-        let db = ListingDatabase::connect_with_options(&request)
-            .await
-            .unwrap();
-
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        db.create_table(CreateTableRequest {
-            name: "test".to_string(),
-            namespace_path: vec![],
-            data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
-            mode: CreateTableMode::Create,
-            write_options: Default::default(),
-            location: None,
-            namespace_client: None,
-        })
-        .await
-        .unwrap();
-
-        let before_open = registry.stats();
-        for _ in 0..3 {
-            let table = db
-                .open_table(OpenTableRequest {
-                    name: "test".to_string(),
-                    namespace_path: vec![],
-                    index_cache_size: None,
-                    lance_read_params: None,
-                    location: None,
-                    namespace_client: None,
-                    managed_versioning: None,
-                })
-                .await
-                .unwrap();
-            assert_eq!(table.count_rows(None).await.unwrap(), 0);
-        }
-
-        let after_open = registry.stats();
-        assert_eq!(after_open.misses, before_open.misses);
-        assert!(after_open.hits >= before_open.hits + 3);
-    }
-
-    /// Regression test for https://github.com/lancedb/lancedb/issues/3197.
-    #[cfg(unix)]
-    #[tokio::test]
-    async fn test_open_table_follows_hugging_face_symlinks() {
-        let (tempdir, db) = setup_database().await;
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        db.create_table(CreateTableRequest {
-            name: "test".to_string(),
-            namespace_path: vec![],
-            data: Box::new(
-                RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1, 2, 3]))])
-                    .unwrap(),
-            ) as Box<dyn Scannable>,
-            mode: CreateTableMode::Create,
-            write_options: Default::default(),
-            location: None,
-            namespace_client: None,
-        })
-        .await
-        .unwrap();
-
-        let table_dir = tempdir.path().join("test.lance");
-        let versions_dir = table_dir.join("_versions");
-        let manifest_path = std::fs::read_dir(&versions_dir)
-            .unwrap()
-            .map(|entry| entry.unwrap().path())
-            .find(|path| path.extension().is_some_and(|ext| ext == "manifest"))
-            .unwrap();
-        let data_path = std::fs::read_dir(table_dir.join("data"))
-            .unwrap()
-            .map(|entry| entry.unwrap().path())
-            .find(|path| path.extension().is_some_and(|ext| ext == "lance"))
-            .unwrap();
-
-        // Hugging Face snapshots keep dataset objects in a separate blob directory and
-        // expose them through relative symlinks.
-        let blobs_dir = tempdir.path().join("blobs");
-        std::fs::create_dir(&blobs_dir).unwrap();
-        let manifest_blob = "9b603c63d0e692e05d58be25605f2f2064cc781e5ff94fe983a405059547b816";
-        let data_blob = "be64f20e5723bd0a27cfdbdb41cf7d6fad94cd572a71973b717fb8340f4310c5";
-        std::fs::rename(&manifest_path, blobs_dir.join(manifest_blob)).unwrap();
-        std::fs::rename(&data_path, blobs_dir.join(data_blob)).unwrap();
-        std::os::unix::fs::symlink(Path::new("../../blobs").join(manifest_blob), &manifest_path)
-            .unwrap();
-        std::os::unix::fs::symlink(Path::new("../../blobs").join(data_blob), &data_path).unwrap();
-        let symlink_len = std::fs::symlink_metadata(&manifest_path).unwrap().len();
-        let target_len = std::fs::metadata(&manifest_path).unwrap().len();
-        assert_ne!(symlink_len, target_len);
-
-        drop(db);
-        let db = ListingDatabase::connect_with_options(&ConnectRequest {
-            uri: tempdir.path().to_str().unwrap().to_string(),
-            #[cfg(feature = "remote")]
-            client_config: Default::default(),
-            options: Default::default(),
-            namespace_client_properties: Default::default(),
-            manifest_enabled: false,
-            read_consistency_interval: None,
-            session: None,
-        })
-        .await
-        .unwrap();
-
-        let table = db
-            .open_table(OpenTableRequest {
-                name: "test".to_string(),
-                namespace_path: vec![],
-                index_cache_size: None,
-                lance_read_params: None,
-                location: None,
-                namespace_client: None,
-                managed_versioning: None,
-            })
-            .await
-            .unwrap();
-        let batches = table
-            .query(
-                &AnyQuery::Query(QueryRequest::default()),
-                Default::default(),
-            )
-            .await
-            .unwrap()
-            .try_collect::<Vec<_>>()
-            .await
-            .unwrap();
-        assert_eq!(batches.iter().map(RecordBatch::num_rows).sum::<usize>(), 3);
-    }
-
    #[tokio::test]
    async fn test_clone_table_basic() {
        let (_tempdir, db) = setup_database().await;
@@ -2546,7 +2280,7 @@ mod tests {

    #[tokio::test]
    async fn test_table_uri() {
-        let (_tempdir, mut db) = setup_database().await;
+        let (_tempdir, db) = setup_database().await;

        let mut pb = PathBuf::new();
        pb.push(db.uri.clone());
@@ -2555,18 +2289,6 @@ mod tests {
        let expected = pb.to_str().unwrap();
        let uri = db.table_uri("test").ok().unwrap();
        assert_eq!(uri, expected);
-
-        // URI paths always use forward slashes, even on Windows. Using
-        // `Path::join` here used to produce `az://container/prefix\\test.lance`,
-        // which Azure treated as a different object from the table returned by
-        // `table_names` (https://github.com/lancedb/lancedb/issues/1072).
-        for base_uri in ["az://container/prefix", "az://container/prefix/"] {
-            db.uri = base_uri.to_string();
-            assert_eq!(
-                db.table_uri("test").unwrap(),
-                "az://container/prefix/test.lance"
-            );
-        }
    }

    /// Regression: connecting via a URL-style URI (which goes through
@@ -201,7 +201,7 @@ impl LanceNamespaceDatabase {
        &self,
        request: &DbCreateTableRequest,
    ) -> Result<(
-        Option<lance_file::version::LanceFileVersion>,
+        Option<lance_encoding::version::LanceFileVersion>,
        Option<bool>,
        Option<bool>,
    )> {
@@ -214,7 +214,7 @@ impl LanceNamespaceDatabase {

        let storage_version_override = storage_options
            .and_then(|opts| opts.get(OPT_NEW_TABLE_STORAGE_VERSION))
-            .map(|s| s.parse::<lance_file::version::LanceFileVersion>())
+            .map(|s| s.parse::<lance_encoding::version::LanceFileVersion>())
            .transpose()?;

        let v2_manifest_override = storage_options
@@ -71,14 +71,6 @@ pub enum Error {
    IndexNotFound { name: String },
    #[snafu(display("Embedding function '{name}' was not found. : {reason}"))]
    EmbeddingFunctionNotFound { name: String, reason: String },
-    #[snafu(display("Column '{name}' was not found"))]
-    ColumnNotFound { name: String },
-    #[snafu(display("Column '{name}' already exists"))]
-    ColumnAlreadyExists { name: String },
-    #[snafu(display("Column '{name}' is not a computed column"))]
-    NotAComputedColumn { name: String },
-    #[snafu(display("Invalid expression for column '{column}': {message}"))]
-    InvalidExpression { column: String, message: String },

    #[snafu(display("Table '{name}' already exists"))]
    TableAlreadyExists { name: String },
@@ -177,12 +169,6 @@ impl From<DataFusionError> for Error {

 impl From<lance::Error> for Error {
    fn from(source: lance::Error) -> Self {
-        if has_unsupported_local_filesystem_source(&source) {
-            return Self::NotSupported {
-                message: "the filesystem does not support an operation required for safe Lance commits (such as atomic rename). Object-storage mounts such as Mountpoint for Amazon S3 are not supported; use the native object-store URI (for example, s3://bucket/path) instead".to_string(),
-            };
-        }
-
        // Try to unwrap external errors that were wrapped by lance
        match source {
            lance::Error::Wrapped { error, .. } => Self::from_box_error(error),
@@ -195,27 +181,6 @@ impl From<lance::Error> for Error {
    }
 }

-fn has_unsupported_local_filesystem_source(error: &(dyn std::error::Error + 'static)) -> bool {
-    let mut current = Some(error);
-    let mut is_local_filesystem = false;
-    let mut is_unsupported = false;
-    while let Some(error) = current {
-        is_local_filesystem |= error
-            .downcast_ref::<object_store::Error>()
-            .is_some_and(|error| {
-                matches!(error, object_store::Error::Generic { store, .. } if *store == "LocalFileSystem")
-            });
-        is_unsupported |= error
-            .downcast_ref::<std::io::Error>()
-            .is_some_and(|error| error.kind() == std::io::ErrorKind::Unsupported);
-        if is_local_filesystem && is_unsupported {
-            return true;
-        }
-        current = error.source();
-    }
-    false
-}
-
 impl Error {
    fn from_box_error(mut source: Box<dyn std::error::Error + Send + Sync>) -> Self {
        source = match source.downcast::<Self>() {
@@ -305,46 +270,3 @@ impl From<candle_core::Error> for Error {
        }
    }
 }
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn unsupported_filesystem_operations_have_actionable_error() {
-        let object_store_error = object_store::Error::Generic {
-            store: "LocalFileSystem",
-            source: Box::new(std::io::Error::from(std::io::ErrorKind::Unsupported)),
-        };
-        let lance_error = lance::Error::io_source(Box::new(object_store_error));
-
-        let error = Error::from(lance_error);
-
-        assert!(matches!(
-            error,
-            Error::NotSupported { message }
-                if message.contains("Mountpoint for Amazon S3")
-                    && message.contains("s3://bucket/path")
-        ));
-    }
-
-    #[test]
-    fn other_io_errors_remain_lance_errors() {
-        let object_store_error = object_store::Error::Generic {
-            store: "LocalFileSystem",
-            source: Box::new(std::io::Error::from(std::io::ErrorKind::PermissionDenied)),
-        };
-        let lance_error = lance::Error::io_source(Box::new(object_store_error));
-
-        assert!(matches!(Error::from(lance_error), Error::Lance { .. }));
-    }
-
-    #[test]
-    fn unsupported_non_filesystem_errors_remain_lance_errors() {
-        let lance_error = lance::Error::io_source(Box::new(std::io::Error::from(
-            std::io::ErrorKind::Unsupported,
-        )));
-
-        assert!(matches!(Error::from(lance_error), Error::Lance { .. }));
-    }
-}
@@ -132,14 +132,9 @@ impl ObjectStore for MirroringObjectStore {
        if to.primary_only() {
            self.primary.copy_opts(from, to, options).await
        } else {
-            // The secondary store can be process-local and less durable than the
-            // primary, so a source written by another process may not exist here
-            // or may be evicted before the copy begins.
-            match self.secondary.copy_opts(from, to, options.clone()).await {
-                Ok(()) | Err(Error::NotFound { .. }) => {}
-                Err(err) => return Err(err),
-            }
-            self.primary.copy_opts(from, to, options).await
+            self.secondary.copy_opts(from, to, options.clone()).await?;
+            self.primary.copy_opts(from, to, options).await?;
+            Ok(())
        }
    }
 }
@@ -197,8 +192,7 @@ mod test {
    use futures::TryStreamExt;
    use lance::{dataset::WriteParams, io::ObjectStoreParams};
    use lance_testing::datagen::{BatchGenerator, IncrementingInt32, RandomVector};
-    use object_store::{local::LocalFileSystem, memory::InMemory};
-    use std::time::Duration;
+    use object_store::local::LocalFileSystem;
    use tempfile;

    use crate::{
@@ -207,139 +201,6 @@ mod test {
        table::WriteOptions,
    };

-    #[derive(Debug)]
-    struct EvictBeforeCopyStore {
-        inner: Arc<dyn ObjectStore>,
-    }
-
-    impl std::fmt::Display for EvictBeforeCopyStore {
-        fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
-            write!(f, "EvictBeforeCopyStore")
-        }
-    }
-
-    #[async_trait]
-    impl ObjectStore for EvictBeforeCopyStore {
-        async fn put_opts(
-            &self,
-            location: &Path,
-            payload: PutPayload,
-            options: PutOptions,
-        ) -> Result<PutResult> {
-            self.inner.put_opts(location, payload, options).await
-        }
-
-        async fn put_multipart_opts(
-            &self,
-            location: &Path,
-            options: PutMultipartOptions,
-        ) -> Result<Box<dyn MultipartUpload>> {
-            self.inner.put_multipart_opts(location, options).await
-        }
-
-        async fn get_opts(&self, location: &Path, options: GetOptions) -> Result<GetResult> {
-            self.inner.get_opts(location, options).await
-        }
-
-        fn delete_stream(
-            &self,
-            locations: BoxStream<'static, Result<Path>>,
-        ) -> BoxStream<'static, Result<Path>> {
-            self.inner.delete_stream(locations)
-        }
-
-        fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, Result<ObjectMeta>> {
-            self.inner.list(prefix)
-        }
-
-        async fn list_with_delimiter(&self, prefix: Option<&Path>) -> Result<ListResult> {
-            self.inner.list_with_delimiter(prefix).await
-        }
-
-        async fn copy_opts(&self, from: &Path, to: &Path, options: CopyOptions) -> Result<()> {
-            self.inner.delete(from).await?;
-            self.inner.copy_opts(from, to, options).await
-        }
-    }
-
-    #[tokio::test]
-    async fn test_copy_when_source_is_missing_from_secondary() {
-        let primary_dir = tempfile::tempdir().unwrap();
-        let secondary_dir = tempfile::tempdir().unwrap();
-        let primary: Arc<dyn ObjectStore> =
-            Arc::new(LocalFileSystem::new_with_prefix(primary_dir.path()).unwrap());
-        let secondary: Arc<dyn ObjectStore> =
-            Arc::new(LocalFileSystem::new_with_prefix(secondary_dir.path()).unwrap());
-        let store = MirroringObjectStore {
-            primary: primary.clone(),
-            secondary: secondary.clone(),
-        };
-        let staging = Path::from("_versions/1.manifest-staging");
-        let finalized = Path::from("_versions/1.manifest");
-
-        primary
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-
-        tokio::time::timeout(Duration::from_secs(5), store.copy(&staging, &finalized))
-            .await
-            .expect("copy should not hang when the secondary source is missing")
-            .unwrap();
-
-        let copied = primary
-            .get(&finalized)
-            .await
-            .unwrap()
-            .bytes()
-            .await
-            .unwrap();
-        assert_eq!(copied, "manifest contents");
-        assert!(matches!(
-            secondary.head(&finalized).await,
-            Err(Error::NotFound { .. })
-        ));
-    }
-
-    #[tokio::test]
-    async fn test_copy_when_secondary_source_disappears_after_head() {
-        let primary: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
-        let secondary_inner: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
-        let secondary: Arc<dyn ObjectStore> = Arc::new(EvictBeforeCopyStore {
-            inner: secondary_inner.clone(),
-        });
-        let store = MirroringObjectStore {
-            primary: primary.clone(),
-            secondary,
-        };
-        let staging = Path::from("_versions/1.manifest-staging");
-        let finalized = Path::from("_versions/1.manifest");
-
-        primary
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-        secondary_inner
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-
-        store.copy(&staging, &finalized).await.unwrap();
-
-        let copied = primary
-            .get(&finalized)
-            .await
-            .unwrap()
-            .bytes()
-            .await
-            .unwrap();
-        assert_eq!(copied, "manifest contents");
-        assert!(matches!(
-            secondary_inner.head(&finalized).await,
-            Err(Error::NotFound { .. })
-        ));
-    }
-
    // This test is ignored because lance 3.0 introduced LocalWriter optimization
    // that bypasses the object store wrapper for local writes. The mirroring feature
    // still works for remote/cloud storage, but can't be tested with local storage.
@@ -141,7 +141,7 @@ impl SpawnedJob {
                Ok(Err(err)) => Outcome::Failed(Arc::new(err)),
                Err(err) if err.is_cancelled() => Outcome::Cancelled,
                Err(err) => Outcome::Failed(Arc::new(Error::Runtime {
-                    message: format!("job task failed: {err}"),
+                    message: format!("index job task failed: {err}"),
                })),
            };
            let _ = tx.send(Some(outcome));
@@ -214,7 +214,7 @@ use lance_linalg::distance::DistanceType as LanceDistanceType;
 /// a built-in pull-based adapter.
 #[cfg(feature = "metrics")]
 pub use metrics;
-pub use table::{FtsToken, Table, TableBase};
+pub use table::{FtsToken, Table};

 /// Tokenize a full-text search query using an explicit FTS tokenizer configuration.
 ///
@@ -1661,8 +1661,14 @@ mod tests {

    #[tokio::test]
    async fn test_setters_getters() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_test_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1757,8 +1763,14 @@ mod tests {

    #[tokio::test]
    async fn test_execute() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1877,8 +1889,14 @@ mod tests {

    #[tokio::test]
    async fn test_select_with_transform() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1975,9 +1993,15 @@ mod tests {

    #[tokio::test]
    async fn test_execute_no_vector() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        // test that it's ok to not specify a query vector (just filter / limit)
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -19,15 +19,6 @@ const ARROW_FILE_CONTENT_TYPE: &str = "application/vnd.apache.arrow.file";
 #[cfg(test)]
 const JSON_CONTENT_TYPE: &str = "application/json";

-fn extract_job_id(body: &str) -> Option<String> {
-    serde_json::from_str::<serde_json::Value>(body)
-        .ok()?
-        .get("job_id")?
-        .as_str()
-        .filter(|job_id| !job_id.is_empty())
-        .map(str::to_string)
-}
-
 pub use client::{ClientConfig, HeaderProvider, RetryConfig, TimeoutConfig, TlsConfig};
 pub use db::{RemoteDatabaseOptions, RemoteDatabaseOptionsBuilder};
 pub use oauth::{OAuthConfig, OAuthFlow, OAuthHeaderProvider};
@@ -373,37 +373,6 @@ pub fn parse_db_url(db_url: &str) -> Result<ParsedDbUrl> {
    Ok(ParsedDbUrl { db_name, db_prefix })
 }

-fn validate_dns_hostname(hostname: &str) -> Result<()> {
-    let ascii_hostname = match url::Host::parse(hostname) {
-        Ok(url::Host::Domain(hostname)) => hostname,
-        Ok(_) => {
-            return Err(Error::InvalidInput {
-                message: "LanceDB Cloud database URI or region produced a non-DNS hostname"
-                    .to_string(),
-            });
-        }
-        Err(err) => {
-            return Err(Error::InvalidInput {
-                message: format!(
-                    "LanceDB Cloud database URI or region produced an invalid hostname: {err}"
-                ),
-            });
-        }
-    };
-
-    if ascii_hostname.len() > 253
-        || ascii_hostname
-            .split('.')
-            .any(|label| label.is_empty() || label.len() > 63)
-    {
-        return Err(Error::InvalidInput {
-            message: "LanceDB Cloud database URI or region produced an invalid hostname: DNS labels must contain 1 to 63 bytes and the full hostname must not exceed 253 bytes".to_string(),
-        });
-    }
-
-    Ok(())
-}
-
 impl RestfulLanceDbClient<Sender> {
    fn get_timeout(passed: Option<Duration>, env_var: &str) -> Result<Option<Duration>> {
        if let Some(passed) = passed {
@@ -511,11 +480,7 @@ impl RestfulLanceDbClient<Sender> {

        let host = match host_override {
            Some(host_override) => host_override,
-            None => {
-                let hostname = format!("{}.{}.api.lancedb.com", parsed_url.db_name, region);
-                validate_dns_hostname(&hostname)?;
-                format!("https://{hostname}")
-            }
+            None => format!("https://{}.{}.api.lancedb.com", parsed_url.db_name, region),
        };
        debug!("Created client for host: {}", host);
        let retry_config = client_config.retry_config.clone().try_into()?;
@@ -1192,29 +1157,6 @@ mod tests {
        assert_eq!(headers.get("x-api-key").unwrap(), "api-key");
    }

-    #[test]
-    fn test_rejects_invalid_cloud_dns_hostname() {
-        let invalid_database_names = ["a".repeat(64), "invalid..database".to_string()];
-
-        for db_name in invalid_database_names {
-            let parsed_url = parse_db_url(&format!("db://{db_name}")).unwrap();
-            let error = RestfulLanceDbClient::<Sender>::try_new(
-                &parsed_url,
-                "us-east-1",
-                None,
-                HeaderMap::new(),
-                ClientConfig::default(),
-                None,
-            )
-            .unwrap_err();
-
-            assert!(
-                matches!(error, Error::InvalidInput { ref message } if message.contains("DNS labels must contain 1 to 63 bytes")),
-                "unexpected error: {error}"
-            );
-        }
-    }
-
    // Test implementation of HeaderProvider
    #[derive(Debug, Clone)]
    struct TestHeaderProvider {
@@ -9,7 +9,6 @@ use http::StatusCode;
 use lance_io::object_store::StorageOptions;
 use lance_namespace_impls::{DynamicContextProvider, OperationInfo};
 use moka::future::Cache;
-use reqwest::Response;
 use reqwest::header::CONTENT_TYPE;

 use lance_namespace::models::{
@@ -24,17 +23,15 @@ use crate::database::{
    JobDescription, JobInfo, OpenTableRequest, ReadConsistency, TableNamesRequest,
 };
 use crate::error::Result;
-use crate::job::Job;
-use crate::remote::job::RemoteJob;
 use crate::remote::util::stream_as_body;
 use crate::table::BaseTable;

+use super::ARROW_STREAM_CONTENT_TYPE;
 use super::client::{
    ClientConfig, HeaderProvider, HttpSend, RequestResultExt, RestfulLanceDbClient, Sender,
 };
 use super::table::RemoteTable;
 use super::util::parse_server_version;
-use super::{ARROW_STREAM_CONTENT_TYPE, extract_job_id};

 // Request structure for the remote clone table API
 #[derive(serde::Serialize)]
@@ -329,22 +326,6 @@ impl RemoteDatabase {
    }
 }

-impl<S: HttpSend> RemoteDatabase<S> {
-    async fn submit_drop_table(
-        &self,
-        name: &str,
-        namespace_path: &[String],
-    ) -> Result<(String, Response)> {
-        let identifier = build_table_identifier(name, namespace_path, &self.client.id_delimiter);
-        let cache_key = build_cache_key(name, namespace_path);
-        let req = self.client.post(&format!("/v1/table/{}/drop/", identifier));
-        let (request_id, resp) = self.client.send(req).await?;
-        let resp = self.client.check_response(&request_id, resp).await?;
-        self.table_cache.remove(&cache_key).await;
-        Ok((request_id, resp))
-    }
-}
-
 #[cfg(all(test, feature = "remote"))]
 mod test_utils {
    use super::*;
@@ -913,28 +894,13 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
    }

    async fn drop_table(&self, name: &str, namespace_path: &[String]) -> Result<()> {
-        self.submit_drop_table(name, namespace_path)
-            .await
-            .map(|_| ())
-    }
-
-    async fn drop_table_async(&self, name: &str, namespace_path: &[String]) -> Result<Job> {
-        let (request_id, response) = self.submit_drop_table(name, namespace_path).await?;
-        let status = response.status();
-        let body = response.text().await.err_to_http(request_id.clone())?;
-        let job_id = extract_job_id(&body);
-        Ok(match job_id {
-            Some(job_id) => Job::new(Box::new(RemoteJob::new(self.client.clone(), job_id))),
-            None if status == StatusCode::ACCEPTED => {
-                return Err(Error::Http {
-                    source: "asynchronous drop-table response did not contain a valid job_id"
-                        .into(),
-                    request_id,
-                    status_code: Some(status),
-                });
-            }
-            None => Job::new_done(),
-        })
+        let identifier = build_table_identifier(name, namespace_path, &self.client.id_delimiter);
+        let cache_key = build_cache_key(name, namespace_path);
+        let req = self.client.post(&format!("/v1/table/{}/drop/", identifier));
+        let (request_id, resp) = self.client.send(req).await?;
+        self.client.check_response(&request_id, resp).await?;
+        self.table_cache.remove(&cache_key).await;
+        Ok(())
    }

    async fn drop_all_tables(&self, namespace_path: &[String]) -> Result<()> {
@@ -1526,67 +1492,6 @@ mod tests {
        // NOTE: the API will return 200 even if the table does not exist. So we shouldn't expect 404.
    }

-    #[tokio::test]
-    async fn test_drop_table_does_not_read_response_body() {
-        let conn = Connection::new_with_handler(|_| {
-            http::Response::builder()
-                .status(200)
-                .body(vec![0xff])
-                .unwrap()
-        });
-
-        conn.drop_table("table1", &[]).await.unwrap();
-    }
-
-    #[tokio::test]
-    async fn test_drop_table_async_returns_job() {
-        let conn = Connection::new_with_handler(|request| {
-            assert_eq!(request.method(), &reqwest::Method::POST);
-            assert_eq!(request.url().path(), "/v1/table/table1/drop/");
-            http::Response::builder()
-                .status(202)
-                .body(r#"{"job_id":"drop-job-123"}"#)
-                .unwrap()
-        });
-
-        let job = conn.drop_table_async("table1", &[]).await.unwrap();
-        assert_eq!(job.id(), Some("drop-job-123"));
-    }
-
-    #[tokio::test]
-    async fn test_drop_table_async_old_server_returns_done_job() {
-        let conn = Connection::new_with_handler(|_| {
-            http::Response::builder().status(200).body("").unwrap()
-        });
-
-        let job = conn.drop_table_async("table1", &[]).await.unwrap();
-        assert_eq!(job.id(), None);
-        assert_eq!(job.status().await.unwrap(), "finished");
-    }
-
-    #[tokio::test]
-    async fn test_drop_table_async_rejects_accepted_response_without_job_id() {
-        let conn = Connection::new_with_handler(|_| {
-            http::Response::builder().status(202).body("{}").unwrap()
-        });
-
-        let error = conn.drop_table_async("table1", &[]).await.err().unwrap();
-        assert!(error.to_string().contains("valid job_id"));
-    }
-
-    #[tokio::test]
-    async fn test_drop_table_async_rejects_empty_job_id() {
-        let conn = Connection::new_with_handler(|_| {
-            http::Response::builder()
-                .status(202)
-                .body(r#"{"job_id":""}"#)
-                .unwrap()
-        });
-
-        let error = conn.drop_table_async("table1", &[]).await.err().unwrap();
-        assert!(error.to_string().contains("valid job_id"));
-    }
-
    #[tokio::test]
    async fn test_rename_table() {
        let conn = Connection::new_with_handler(|request| {
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Gatefixer	8d3185dec6	fix(node): reject non-ascii cfg keys	2026-08-06 09:24:53 +00:00
Gatefixer	bb14667c81	fix(node): reject commented cfg arguments	2026-08-06 09:07:59 +00:00
Gatefixer	983ad2c011	fix(node): reject target feature cfg overrides	2026-08-06 08:35:42 +00:00
Gatefixer	bcff95b109	fix(node): reject rustc response files	2026-08-06 08:08:07 +00:00
Gatefixer	dfbb5f5ade	fix(node): validate underscore rustc options	2026-08-06 07:25:21 +00:00
Gatefixer	12ee5ca626	fix(node): allow default CPU in lint builds	2026-08-06 06:46:48 +00:00
Gatefixer	fcef32bfd3	fix(node): validate encoded CPU build flags	2026-08-06 06:35:58 +00:00
Gatefixer	3863189b16	fix(node): validate complete x86-64-v2 feature set	2026-08-06 05:26:53 +00:00
Gatefixer	c858e25494	fix(node): enforce x86-64-v2 artifact baseline	2026-08-06 04:48:31 +00:00
Gatefixer	cf9a8bf91d	fix(node): support pre-Haswell x86_64 CPUs	2026-08-06 04:09:09 +00:00