h2oplyr

Tidy-style data manipulation with H2O as the only data backend. The only non-base runtime dependency is h2o. knitr and rmarkdown are optional vignette-building dependencies. No dplyr, tidytable or data.table is used.

# Install h2o first, then this package from its source archive.
install.packages("h2oplyr_0.2.6.tar.gz", repos = NULL, type = "source")
h2o::h2o.init(nthreads = 2, max_mem_size = "2G")
library(h2oplyr)
p <- h_penguins()
h_summarize(p, n = n(), mass = mean(body_mass_g, na.rm = TRUE), .by = species)
vignette("h2oplyr-penguins")

The matching H2O server and Java runtime are external system requirements. This package never starts or shuts down a cluster automatically.

See the vignette for the supported expression language, examples and limits. Help pages have independently executable examples for all 73 exports. Additional asserted examples and regression tests are installed under system.file("examples", package = "h2oplyr").

Migration from the standalone prototype

Tests

Start a matching H2O cluster explicitly on a local port, then set H2OPLYR_TEST_PORT when running R CMD check. Without that variable, static tests run and integration tests state that they were skipped. Live integration tests verify that H2O namespace function bindings remain unchanged. Rebuilding vignettes against a live server can be requested with H2OPLYR_VIGNETTE_PORT.

Copyright 2026 Carlos Ortega. Code: MIT. Included Palmer penguin data: CC0; see inst/extdata/PROVENANCE.md.