Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from the uniform distribution U(0, 1).
sdf_runif(
  sc,
  n,
  min = 0,
  max = 1,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)A Spark connection.
Sample Size (default: 1000).
The lower limit of the distribution.
The upper limit of the distribution.
Number of partitions in the resulting Spark dataframe (default: default parallelism of the Spark cluster).
Random seed (default: a random long integer).
Name of the output column containing sample values (default: "x").
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()