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Jack Ye
ddb318567a
## Summary - Complete the SQL reference: `ATTACH DATABASE`, the `CHANGES` clause, and `dedupe()`/`duplicate_pairs()` (verified against current sophon source; these were recently renamed from `vector_dedup`/`vector_duplicate_pairs`). Fix the blob-column default-projection claim and add the previously undocumented `blob_descriptor()`. - Enrich the gated Functions draft (still `.mintignore`'d, pre-release): chained Functions over blob outputs, GPU-produced blobs, Secrets, multi-input/output binding, `code=[module]` packaging. - Upgrade the materialized-view and computed-column auto-refresh drafts with precise, verified catch-up semantics, and add the missing `ALTER MATERIALIZED VIEW` / `CREATE ... WITH(...)` sections (also gated — the automatic-refresh scheduler is still dev/staging-only). - Thread one running example (video frames → GPU extract/caption → dedup → auto-refreshing materialized view) through Functions, materialized views, and the LeRobotDataset integration guide instead of a separate tutorial. - Rename "LanceDB OSS"/"OSS" to "LanceDB Embedded"/"Embedded" throughout (52 files); activate the existing availability-comparison mechanism on `basics/offerings.mdx` for a full feature-by-feature comparison table.
98 lines
3.8 KiB
Plaintext
98 lines
3.8 KiB
Plaintext
---
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title: "DUPLICATE_PAIRS"
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sidebarTitle: "DUPLICATE_PAIRS"
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description: "The duplicate_pairs() table function: every close pair in a vector column, scanned over the index."
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icon: clone
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keywords: ["duplicate_pairs", "vector_duplicate_pairs", "sql", "deduplication", "near-duplicate", "table function"]
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availability:
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embedded: unavailable
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enterprise: available
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---
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`duplicate_pairs` scans a vector column's [index](/indexing/vector-index)
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partitions for every pair of rows closer than a distance threshold, without a
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full pairwise scan or a shuffle. It returns one row per close pair, not one
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row per source row -- use it to inspect what would be collapsed before
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committing to [`dedupe`](/sql/dql/dedupe), which resolves these same pairs
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into groups.
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```sql
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SELECT * FROM duplicate_pairs(<table>, <vector_column>,
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distance_threshold => <float>
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[, id_column => <column>]
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[, selection => 'all' | 'first' | 'random', count => <int>, seed => <int>]
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)
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```
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```sql
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SELECT * FROM duplicate_pairs('frames', 'vec', distance_threshold => 0.02)
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```
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<Note>
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Earlier releases spelled this `vector_duplicate_pairs`; that name is rejected
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on current deployments.
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</Note>
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## Input {#input}
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| Argument | Type | Required | Meaning |
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| --- | --- | --- | --- |
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| table name | string literal | yes | the table to scan |
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| vector column | string literal | yes | the indexed vector column to compare |
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| `distance_threshold` | float | yes | maximum distance for a pair to count as close |
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| `id_column` | column name | no | project this column's value instead of the internal row ID -- see [Application-level identifiers](#id-column) |
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| `selection` | `'all'` (default) \| `'first'` \| `'random'` | no | which index partitions to scan |
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| `count` | int | no | number of partitions to sample when `selection => 'random'` |
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| `seed` | int | no | random seed when `selection => 'random'` |
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`resolution` is refused on `duplicate_pairs`: a pair has no notion of a group,
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only [`dedupe`](/sql/dql/dedupe#input) accepts it.
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## Output {#output}
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One row per close pair found, in a fixed schema independent of the source
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table:
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| Column | Type | Meaning |
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| --- | --- | --- |
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| `row_id_a` | uint64 | internal row ID of the first row in the pair, the same identifier as the [`_rowid`](/sql/data-types#pseudo-columns) pseudo-column |
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| `row_id_b` | uint64 | internal row ID of the second row in the pair |
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| `distance` | float32 | distance between the pair's vectors, at or below `distance_threshold` |
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| `segment_id` | int64 | which index segment the pair was found in |
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| `partition_id` | int64 | which index partition the pair was found in |
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| `dataset_version` | int64 | the dataset version the scan ran against |
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### Application-level identifiers {#id-column}
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A row ID is internal and not stable across compaction. Pass `id_column`, a
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top-level scalar column such as a primary key, to project its value instead:
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`row_id_a`/`row_id_b` are replaced by `id_a`/`id_b`, typed like `id_column`.
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```sql
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SELECT * FROM duplicate_pairs('frames', 'vec', distance_threshold => 0.02, id_column => 'frame_id')
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```
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## Sampling partitions {#sampling}
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`selection` scopes the scan to a sample of partitions instead of all of them,
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the same `all` (default) / `first` / `random` choice as
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[`ivf_partition`](/sql/scalar-functions#ivf-partition). Use it to estimate a
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distance threshold or duplicate rate on a large table before scanning it in
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full:
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```sql
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SELECT * FROM duplicate_pairs('frames', 'vec',
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distance_threshold => 0.02, selection => 'random', count => 100, seed => 42)
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```
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## What to read next {#next}
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<CardGroup cols={2}>
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<Card title="DEDUPE" icon="layer-group" href="/sql/dql/dedupe">
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Resolve these same pairs into one representative row per group.
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</Card>
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<Card title="Deduplicate near-duplicates" icon="copy" href="/curation/dedupe">
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When to reach for this instead of exact-key deduplication.
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</Card>
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</CardGroup>
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