sdf_distinct: Invoke distinct on a Spark DataFrame

Description Usage Arguments Transforming Spark DataFrames See Also

View source: R/sdf_distinct.R

Description

Invoke distinct on a Spark DataFrame

Usage

1

Arguments

x

A Spark DataFrame.

...

Optional variables to use when determining uniqueness. If there are multiple rows for a given combination of inputs, only the first row will be preserved. If omitted, will use all variables.

name

A name to assign this table. Passed to [sdf_register()].

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_random_split(), sdf_register(), sdf_sample(), sdf_sort(), sdf_weighted_sample()


sparklyr documentation built on June 17, 2021, 5:06 p.m.