Generate random samples from the standard normal distribution — sdf_rnorm • sparklyr

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

Usage

sdf_rnorm(
  sc,
  n,
  mean = 0,
  sd = 1,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)

Arguments

sc: A Spark connection.
n: Sample Size (default: 1000).
mean: The mean value of the normal distribution.
sd: The standard deviation of the normal 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_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()