analysisPipelines (version 1.0.2)

assessEngineSetUp: Assesses engine (R, Spark, Python, Spark Structured Streaming) set up

Description

Assesses engine (R, Spark, Python, Spark Structured Streaming) set up

Usage

assessEngineSetUp(object)
# S4 method for BaseAnalysisPipeline
assessEngineSetUp(object)

Arguments

object

A Pipeline object

Value

Tibble containing the details of available engines, whether they are required for a pipeline, a logical value reporting whether the engine has been set up, and comments.

Details

Assesses whether engines required for executing functions in an AnalysisPipeline or StreamingAnalysisPipeline object have been set up

This method is implemented on the base class as it is a shared functionality across Pipeline objects

See Also

Other Package core functions: BaseAnalysisPipeline-class, MetaAnalysisPipeline-class, checkSchemaMatch, createPipelineInstance, exportAsMetaPipeline, generateOutput, genericPipelineException, getInput, getLoggerDetails, getOutputById, getPipelinePrototype, getPipeline, getRegistry, initDfBasedOnType, initialize,BaseAnalysisPipeline-method, loadMetaPipeline, loadPipeline, loadPredefinedFunctionRegistry, loadRegistry, prepExecution, registerFunction, savePipeline, saveRegistry, setInput, setLoggerDetails, updateObject, visualizePipeline

Examples

# NOT RUN {
library(analysisPipelines)
pipelineObj <- AnalysisPipeline(input = iris)
pipelineObj %>>% univarCatDistPlots(uniCol = "Species", priColor = "blue",
 optionalPlots = 0) %>>% assessEngineSetUp
# }