block_fuzzy_lookup: Fuzzy-match query keys against a materialized block

In vectra: Columnar Query Engine for Larger-than-RAM Data

Fuzzy-match query keys against a materialized block

Description

Computes string distances between query keys and a string column in a materialized block. Optionally uses exact-match blocking on a second column (e.g., genus) to reduce the search space.

Usage

block_fuzzy_lookup(
  block,
  column,
  keys,
  method = "dl",
  max_dist = 0.2,
  block_col = NULL,
  block_keys = NULL,
  n_threads = 4L
)

Arguments

block	A vectra_block from materialize().
column	Character scalar. Name of the string column to fuzzy-match against.
keys	Character vector. Query strings to match.
method	Character. Distance method: "dl" (Damerau-Levenshtein, default), "levenshtein", or "jw" (Jaro-Winkler).
max_dist	Numeric. Maximum normalized distance (default 0.2).
block_col	Optional character scalar. Column name for exact-match blocking (e.g., genus). When provided, only rows where block_col matches the corresponding block_keys value are compared.
block_keys	Optional character vector (same length as keys). Exact-match values for blocking. Required when block_col is provided.
n_threads	Integer. Number of OpenMP threads (default 4L).

Value

A data.frame with columns query_idx (1-based position in keys), fuzzy_dist (normalized distance), plus all columns from the block.

vectra documentation built on May 8, 2026, 9:06 a.m.