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IVF_PARTITION

The ivf_partition() scalar function: assign each row to its trained IVF index partition.

Applies to: Embedded ❌, Enterprise ✅

SELECT
    ivf_partition(embedding, selection => 'random', count => 100, seed => 42) AS partition,
    array_agg(id) AS ids
FROM documents
GROUP BY partition

ivf_partition reads an existing IVF-family vector index's trained partitions and assigns each row to the one its vector falls into. The column needs an up-to-date, single-segment index before the function runs -- the same requirement dedupe has.

Grouping by its result buckets rows by vector proximity without a full pairwise scan -- useful for blocking a large table into comparable chunks, such as before a pairwise similarity pass.

Input

ivf_partition takes exactly 1, 3, or 4 arguments -- the vector column alone (scans every partition), or the vector column plus selection and count, plus seed only when selection is 'random':

Argument	Type	Required	Meaning
vector column	column reference	yes	the indexed vector column to assign
selection	'first' | 'random'	required with count	which partitions to sample -- there is no explicit 'all'; omit selection and count entirely to scan every partition
count	int, > 0	required with selection	number of partitions to sample
seed	int, >= 0	required for 'random', refused for 'first'	random seed

Arguments can be passed positionally, ivf_partition(embedding, 'random', 100, 42), or named as shown above. count and seed are the same scan-scoping arguments duplicate_pairs accepts, so a sampled partition estimate carries over -- but not dedupe, which always scans every partition and refuses sampling arguments entirely.

What to read next

Cluster records by index partitionUse this function to group and sample records by an existing index's partitions.DEDUPEThe packaged table function for the deduplication use case, over the same index.