vectra: Columnar Query Engine for Larger-than-RAM Data
A minimal columnar query engine with lazy execution on datasets
larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(),
group_by(), summarise(), joins, window functions) and common aggregations
(n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a
pure C11 pull-based execution engine and a custom on-disk format ('.vtr').
Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a
tiled raster format ('.vec') with overview pyramids and time cubes for
larger-than-RAM raster data. Streams vector operations (spatial transforms,
point-in-polygon and nearest-feature joins including a two-sided
grid-partitioned join, select-by-location, clip, erase, dissolve,
'rasterization', 'polygonization', and contouring) through 'sf', and runs
raster operations (zonal statistics, focal windows, terrain derivatives,
resample or 'reproject' warp, polygon masking, map algebra, and 'mosaicking')
in native C or over the tiled '.vec' format, one batch or tile at a time for
data larger than RAM.
| Version: |
0.9.7 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
tidyselect, rlang, libgeos, parallel |
| LinkingTo: |
libgeos |
| Suggests: |
biglm, bit64, igraph, knitr, openxlsx2, rmarkdown, sf, terra, testthat (≥ 3.0.0) |
| Published: |
2026-06-29 |
| DOI: |
10.32614/CRAN.package.vectra |
| Author: |
Gilles Colling 
[aut, cre, cph] |
| Maintainer: |
Gilles Colling <gilles.colling051 at gmail.com> |
| BugReports: |
https://github.com/gcol33/vectra/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://gillescolling.com/vectra/,
https://github.com/gcol33/vectra |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
README, NEWS |
| CRAN checks: |
vectra results |
Documentation:
| Reference manual: |
vectra.html , vectra.pdf
|
| Vignettes: |
Coverage and topology (source, R code)
vectra Engine Reference (source, R code)
Format Backends (source, R code)
Geometry functions in expressions (source, R code)
Indexing and Query Optimization (source, R code)
Joins (source, R code)
Working with Large Data (source, R code)
Network analysis (source, R code)
Offloading: streaming, monoids, and out-of-core fits (source, R code)
Getting Started with vectra (source, R code)
Star Schemas and Lookup (source, R code)
Species Distribution Models (source, R code)
Out-of-core GIS with vectra (source, R code)
Streaming spatial operations (source, R code)
String Operations and Fuzzy Matching (source, R code)
|
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