Randomly Sample Rows from a Spark DataFrame
R/sdf_interface.R
sdf_sample
Description
Draw a random sample of rows (with or without replacement) from a Spark DataFrame.
Usage
sdf_sample(x, fraction = 1, replacement = TRUE, seed = NULL) Arguments
| Arguments | Description |
|---|---|
| x | An object coercable to a Spark DataFrame. |
| fraction | The fraction to sample. |
| replacement | Boolean; sample with replacement? |
| seed | An (optional) integer seed. |
Section
Transforming Spark DataFrames
The family of functions prefixed with sdf_ generally access the Scala Spark DataFrame API directly, as opposed to the dplyr interface which uses Spark SQL. These functions will ‘force’ any pending SQL in a dplyr pipeline, such that the resulting tbl_spark object returned will no longer have the attached ‘lazy’ SQL operations. Note that the underlying Spark DataFrame does execute its operations lazily, so that even though the pending set of operations (currently) are not exposed at the R level, these operations will only be executed when you explicitly collect() the table.
See Also
Other Spark data frames: sdf_copy_to(), sdf_distinct(), sdf_random_split(), sdf_register(), sdf_sort(), sdf_weighted_sample()