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bigKNN: Exact Search and Graph Construction for 'bigmemory' Matrices

Exact nearest-neighbour and radius-search routines that operate directly on 'bigmemory::big.matrix' objects. The package streams row blocks through 'BLAS' kernels, supports self-search and external-query search, exposes prepared references for repeated queries, and can build exact k-nearest-neighbour, radius, mutual k-nearest-neighbour, and shared-nearest-neighbour graphs. Version 0.3.0 adds execution plans, serializable prepared caches, resumable streamed graph jobs, coercion helpers, exact candidate reranking, and recall summaries for evaluating approximate neighbours.

Version: 0.3.0
Depends: R (≥ 3.5.0)
Imports: Matrix, Rcpp (≥ 1.0.12), methods
LinkingTo: Rcpp, bigmemory, BH
Suggests: bigmemory, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-04-01
DOI: 10.32614/CRAN.package.bigKNN (may not be active yet)
Author: Frederic Bertrand [aut, cre]
Maintainer: Frederic Bertrand <frederic.bertrand at lecnam.net>
BugReports: https://github.com/fbertran/bigKNN/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://fbertran.github.io/bigKNN/, https://github.com/fbertran/bigKNN
NeedsCompilation: yes
Citation: bigKNN citation info
Materials: NEWS
CRAN checks: bigKNN results

Documentation:

Reference manual: bigKNN.html , bigKNN.pdf
Vignettes: Benchmarking bigKNN Against Other Exact Implementations (source)
Using bigKNN as Exact Ground Truth (source, R code)
Exact Graph Construction from big.matrix Data (source, R code)
Prepared References for Repeated Exact Search (source, R code)
Quick Start with bigKNN (source, R code)
Resumable Streaming Jobs (source, R code)
Execution Plans and Streaming Workflows (source, R code)

Downloads:

Package source: bigKNN_0.3.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): bigKNN_0.3.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): bigKNN_0.3.0.tgz, r-oldrel (x86_64): bigKNN_0.3.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bigKNN to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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