lancedb/docs/web/sql/dql/dedupe.mdx

---
title: "DEDUPE"
sidebarTitle: "DEDUPE"
description: "The dedupe() table function: one representative row per near-duplicate group, scanned over the index."
icon: layer-group
keywords: ["dedupe", "vector_dedup", "sql", "deduplication", "near-duplicate", "table function"]
availability:
  embedded: unavailable
  enterprise: available
---

`dedupe` scans a vector column's [index](/indexing/vector-index) partitions
for rows closer than a distance threshold, resolves the overlapping pairs it
finds into duplicate groups, and returns one representative row per group --
without a full pairwise scan or a shuffle. See
[`duplicate_pairs`](/sql/dql/duplicate-pairs) to inspect the pairs themselves
before committing to this resolution.

```sql
SELECT * FROM dedupe(<table>, <vector_column>,
  distance_threshold => <float>
  [, resolution => 'connected_components' | 'direct_representative']
  [, selection => 'all' | 'first' | 'random', count => <int>, seed => <int>]
)
```

```sql
SELECT * FROM dedupe('frames', 'vec', distance_threshold => 0.02)
```

<Note>
Earlier releases spelled this `vector_dedup`; that name is rejected on
current deployments.
</Note>

## Input {#input}

| Argument | Type | Required | Meaning |
| --- | --- | --- | --- |
| table name | string literal | yes | the table to scan |
| vector column | string literal | yes | the indexed vector column to compare |
| `distance_threshold` | float | yes | maximum distance for a pair to count as close |
| `resolution` | `'connected_components'` (default) \| `'direct_representative'` | no | how overlapping pairs group together -- see [Resolution](#resolution) |
| `selection` | `'all'` (default) \| `'first'` \| `'random'` | no | which index partitions to scan |
| `count` | int | no | number of partitions to sample when `selection => 'random'` |
| `seed` | int | no | random seed when `selection => 'random'` |

`id_column` is refused on `dedupe`: it has no separate pair-identifier output
to project onto, only [`duplicate_pairs`](/sql/dql/duplicate-pairs#input)
accepts it.

## Output {#output}

One row per duplicate group, **in the table's own schema** -- every column of
`<table>`, including a BlobV2 column, comes through unchanged on the
representative row Lance selected for that group. Unlike
[`duplicate_pairs`](/sql/dql/duplicate-pairs#output), there is no fixed
`dedupe`-specific schema to document: the output schema is the source
table's schema.

Because the result is already shaped like the table, it composes directly
into a new table or a materialized view:

```sql
CREATE MATERIALIZED VIEW frames_deduped AS
SELECT * FROM dedupe('frames', 'vec', distance_threshold => 0.02)
```

## Resolution {#resolution}

`resolution` chooses how overlapping pairs group together:

| `resolution` value | How pairs group |
| --- | --- |
| `connected_components` (default) | groups transitively: if a~b and b~c are both close, all three resolve together |
| `direct_representative` | only pairs within the threshold of each other resolve together |

## Sampling partitions {#sampling}

`selection` scopes the scan to a sample of partitions instead of all of them,
the same `all` (default) / `first` / `random` choice as
[`ivf_partition`](/sql/scalar-functions#ivf-partition). Use it to estimate a
duplicate rate on a large table before scanning it in full:

```sql
SELECT * FROM dedupe('frames', 'vec',
  distance_threshold => 0.02, selection => 'random', count => 100, seed => 42)
```

## What to read next {#next}

<CardGroup cols={2}>
  <Card title="DUPLICATE_PAIRS" icon="clone" href="/sql/dql/duplicate-pairs">
    Inspect the close pairs themselves instead of the resolved groups.
  </Card>
  <Card title="Deduplicate near-duplicates" icon="copy" href="/curation/dedupe">
    When to reach for this instead of exact-key deduplication.
  </Card>
</CardGroup>