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, transform
params
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getInputCol
getOutputCol
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString, 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_, uninitialize
public T copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Transformer
extra
- (undocumented)public final Param<String> inputCol()
HasInputCol
inputCol
in interface HasInputCol
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public T setInputCol(String value)
public T setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (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 PipelineStage
schema
- (undocumented)