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Assesses engine (R, Spark, Python, Spark Structured Streaming) set up
assessEngineSetUp(object)# S4 method for BaseAnalysisPipeline
assessEngineSetUp(object)
A Pipeline object
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.
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
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
# NOT RUN {
library(analysisPipelines)
pipelineObj <- AnalysisPipeline(input = iris)
pipelineObj %>>% univarCatDistPlots(uniCol = "Species", priColor = "blue",
optionalPlots = 0) %>>% assessEngineSetUp
# }
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