sdf_runif | R Documentation |
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"
)
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"). |
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()
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