sdf_rgeom

Generate random samples from a geometric distribution

Description

Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a geometric distribution.

Usage

sdf_rgeom(sc, n, prob, num_partitions = NULL, seed = NULL, output_col = "x")

Arguments

Argument	Description
sc	A Spark connection.
n	Sample Size (default: 1000).
prob	Probability of success in each trial.
num_partitions	Number of partitions in the resulting Spark dataframe

(default: default parallelism of the Spark cluster). seed | Random seed (default: a random long integer). output_col | Name of the output column containing sample values (default: “x”).

See Also

Other Spark statistical routines: sdf_rbeta(), sdf_rbinom(), sdf_rcauchy(), sdf_rchisq(), sdf_rexp(), sdf_rgamma(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()