sdf_project

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Project features onto principal components

Project features onto principal components

Usage
sdf_project(object, newdata, features = dimnames(object$pc)[[1]],
  feature_prefix = NULL, ...)
Arguments
object

A Spark PCA model object

newdata

An object coercible to a Spark DataFrame

features

A vector of names of columns to be projected

feature_prefix

The prefix used in naming the output features

...

Optional arguments; currently unused.

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.

Aliases
  • sdf_project
Documentation reproduced from package sparklyr, version 0.9.1, License: Apache License 2.0 | file LICENSE

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