public abstract class UnaryTransformer<IN,OUT,T extends UnaryTransformer<IN,OUT,T>> extends Transformer implements HasInputCol, HasOutputCol, org.apache.spark.internal.Logging
| Constructor and Description |
|---|
UnaryTransformer(scala.reflect.api.TypeTags.TypeTag<IN> evidence$1,
scala.reflect.api.TypeTags.TypeTag<OUT> evidence$2) |
| Modifier and Type | Method and Description |
|---|---|
T |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<String> |
inputCol()
Param for input column name.
|
Param<String> |
outputCol()
Param for output column name.
|
T |
setInputCol(String value) |
T |
setOutputCol(String value) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
transform, transform, transformparamsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetInputColgetOutputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoString, uid$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic T copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Transformerextra - (undocumented)public final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic T setInputCol(String value)
public T setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformertransform in class Transformerdataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
We check validity for interactions between parameters during transformSchema and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate().
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema in class PipelineStageschema - (undocumented)