sdf_runif

Generate random samples from the uniform distribution U(0, 1).

Description

Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from the uniform distribution U(0, 1).

Usage

sdf_runif(
  sc,
  n,
  min = 0,
  max = 1,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)

Arguments

Argument Description
sc A Spark connection.
n Sample Size (default: 1000).
min The lower limit of the distribution.
max The upper limit of the distribution.
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_rgeom(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_rweibull()