Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a binomial distribution.
sdf_rbinom(
sc,
n,
size,
prob,
num_partitions = NULL,
seed = NULL,
output_col = "x"
)
A Spark connection.
Sample Size (default: 1000).
Number of trials (zero or more).
Probability of success on each trial.
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_rcauchy()
,
sdf_rchisq()
,
sdf_rexp()
,
sdf_rgamma()
,
sdf_rgeom()
,
sdf_rhyper()
,
sdf_rlnorm()
,
sdf_rnorm()
,
sdf_rpois()
,
sdf_rt()
,
sdf_runif()
,
sdf_rweibull()