Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from an exponential distribution.
sdf_rexp(sc, n, rate = 1, num_partitions = NULL, seed = NULL, output_col = "x")
A Spark connection.
Sample Size (default: 1000).
Rate of the exponential distribution (default: 1). The exponential distribution with rate lambda has mean 1 / lambda and density f(x) = lambda e ^ - lambda x.
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_rgamma()
,
sdf_rgeom()
,
sdf_rhyper()
,
sdf_rlnorm()
,
sdf_rnorm()
,
sdf_rpois()
,
sdf_rt()
,
sdf_runif()
,
sdf_rweibull()