Draw a random sample of rows (with or without replacement) from a Spark DataFrame If the sampling is done without replacement, then it will be conceptually equivalent to an iterative process such that in each step the probability of adding a row to the sample set is equal to its weight divided by summation of weights of all rows that are not in the sample set yet in that step.
sdf_weighted_sample(x, weight_col, k, replacement = TRUE, seed = NULL)An object coercable to a Spark DataFrame.
Name of the weight column
Sample set size
Whether to sample with replacement
An (optional) integer seed
Other Spark data frames:
sdf_copy_to(),
sdf_distinct(),
sdf_random_split(),
sdf_register(),
sdf_sample(),
sdf_sort()